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Sample records for biomarkers predicting clinical

  1. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  2. Strategies to design clinical studies to identify predictive biomarkers in cancer research.

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    Perez-Gracia, Jose Luis; Sanmamed, Miguel F; Bosch, Ana; Patiño-Garcia, Ana; Schalper, Kurt A; Segura, Victor; Bellmunt, Joaquim; Tabernero, Josep; Sweeney, Christopher J; Choueiri, Toni K; Martín, Miguel; Fusco, Juan Pablo; Rodriguez-Ruiz, Maria Esperanza; Calvo, Alfonso; Prior, Celia; Paz-Ares, Luis; Pio, Ruben; Gonzalez-Billalabeitia, Enrique; Gonzalez Hernandez, Alvaro; Páez, David; Piulats, Jose María; Gurpide, Alfonso; Andueza, Mapi; de Velasco, Guillermo; Pazo, Roberto; Grande, Enrique; Nicolas, Pilar; Abad-Santos, Francisco; Garcia-Donas, Jesus; Castellano, Daniel; Pajares, María J; Suarez, Cristina; Colomer, Ramon; Montuenga, Luis M; Melero, Ignacio

    2017-02-01

    The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  3. Predictive Biomarkers for Asthma Therapy.

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    Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

    2017-09-19

    Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

  4. Blood DNA methylation biomarkers predict clinical reactivity in food-sensitized infants.

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    Martino, David; Dang, Thanh; Sexton-Oates, Alexandra; Prescott, Susan; Tang, Mimi L K; Dharmage, Shyamali; Gurrin, Lyle; Koplin, Jennifer; Ponsonby, Anne-Louise; Allen, Katrina J; Saffery, Richard

    2015-05-01

    The diagnosis of food allergy (FA) can be challenging because approximately half of food-sensitized patients are asymptomatic. Current diagnostic tests are excellent makers of sensitization but poor predictors of clinical reactivity. Thus oral food challenges (OFCs) are required to determine a patient's risk of reactivity. We sought to discover genomic biomarkers of clinical FA with utility for predicting food challenge outcomes. Genome-wide DNA methylation (DNAm) profiling was performed on blood mononuclear cells from volunteers who had undergone objective OFCs, concurrent skin prick tests, and specific IgE tests. Fifty-eight food-sensitized patients (aged 11-15 months) were assessed, half of whom were clinically reactive. Thirteen nonallergic control subjects were also assessed. Reproducibility was assessed in an additional 48 samples by using methylation data from an independent population of patients with clinical FA. Using a supervised learning approach, we discovered a DNAm signature of 96 CpG sites that predict clinical outcomes. Diagnostic scores were derived from these 96 methylation sites, and cutoffs were determined in a sensitivity analysis. Methylation biomarkers outperformed allergen-specific IgE and skin prick tests for predicting OFC outcomes. FA status was correctly predicted in the replication cohort with an accuracy of 79.2%. DNAm biomarkers with clinical utility for predicting food challenge outcomes are readily detectable in blood. The development of this technology in detailed follow-up studies will yield highly innovative diagnostic assays. Copyright © 2015 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

  5. Sputum biomarkers and the prediction of clinical outcomes in patients with cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

    Full Text Available Lung function, acute pulmonary exacerbations (APE, and weight are the best clinical predictors of survival in cystic fibrosis (CF; however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6 years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD] =1.75 predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005, number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression and time-to-lung transplantation or death (HR=1.59, p=0.02. At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26 was significantly associated with APE-associated declines in lung function (-10.8 FEV(1% points per log-unit GM-CSF, p<0.001 by linear regression. Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM

  6. Clinical Relevance and Predictive Value of Damage Biomarkers of Drug-Induced Kidney Injury.

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    Kane-Gill, Sandra L; Smithburger, Pamela L; Kashani, Kianoush; Kellum, John A; Frazee, Erin

    2017-11-01

    Nephrotoxin exposure accounts for up to one-fourth of acute kidney injury episodes in hospitalized patients, and the associated consequences are as severe as acute kidney injury due to other etiologies. As the use of nephrotoxic agents represents one of the few modifiable risk factors for acute kidney injury, clinicians must be able to identify patients at high risk for drug-induced kidney injury rapidly. Recently, significant advancements have been made in the field of biomarker utilization for the prediction and detection of acute kidney injury. Such biomarkers may have a role both for detection of drug-induced kidney disease and implementation of preventative and therapeutic strategies designed to mitigate injury. In this article, basic principles of renal biomarker use in practice are summarized, and the existing evidence for six markers specifically used to detect drug-induced kidney injury are outlined, including liver-type fatty acid binding protein, neutrophil gelatinase-associated lipocalin, tissue inhibitor of metalloproteinase-2 times insulin-like growth factor-binding protein 7 ([TIMP-2]·[IGFBP7]), kidney injury molecule-1 and N-acetyl-β-D-glucosaminidase. The results of the literature search for these six kidney damage biomarkers identified 29 unique articles with none detected for liver-type fatty acid binding protein and [TIMP-2]·[IGFBP7]. For three biomarkers, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin and N-acetyl-β-D-glucosaminidase, the majority of the studies suggest utility in clinical practice. While many questions need to be answered to clearly articulate the use of biomarkers to predict drug-induced kidney disease, current data are promising.

  7. Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

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    Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

    2016-06-01

    Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We

  8. Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

    DEFF Research Database (Denmark)

    Swanton, C.; Larkin, J.M.; Gerlinger, M.

    2010-01-01

    -cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway...

  9. Bayesian Nonparametric Estimation of Targeted Agent Effects on Biomarker Change to Predict Clinical Outcome

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    Graziani, Rebecca; Guindani, Michele; Thall, Peter F.

    2015-01-01

    Summary The effect of a targeted agent on a cancer patient's clinical outcome putatively is mediated through the agent's effect on one or more early biological events. This is motivated by pre-clinical experiments with cells or animals that identify such events, represented by binary or quantitative biomarkers. When evaluating targeted agents in humans, central questions are whether the distribution of a targeted biomarker changes following treatment, the nature and magnitude of this change, and whether it is associated with clinical outcome. Major difficulties in estimating these effects are that a biomarker's distribution may be complex, vary substantially between patients, and have complicated relationships with clinical outcomes. We present a probabilistically coherent framework for modeling and estimation in this setting, including a hierarchical Bayesian nonparametric mixture model for biomarkers that we use to define a functional profile of pre-versus-post treatment biomarker distribution change. The functional is similar to the receiver operating characteristic used in diagnostic testing. The hierarchical model yields clusters of individual patient biomarker profile functionals, and we use the profile as a covariate in a regression model for clinical outcome. The methodology is illustrated by analysis of a dataset from a clinical trial in prostate cancer using imatinib to target platelet-derived growth factor, with the clinical aim to improve progression-free survival time. PMID:25319212

  10. External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

    Science.gov (United States)

    Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

    2017-08-01

    Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

  11. Predicting the disease of Alzheimer with SNP biomarkers and clinical data using data mining classification approach: decision tree.

    Science.gov (United States)

    Erdoğan, Onur; Aydin Son, Yeşim

    2014-01-01

    Single Nucleotide Polymorphisms (SNPs) are the most common genomic variations where only a single nucleotide differs between individuals. Individual SNPs and SNP profiles associated with diseases can be utilized as biological markers. But there is a need to determine the SNP subsets and patients' clinical data which is informative for the diagnosis. Data mining approaches have the highest potential for extracting the knowledge from genomic datasets and selecting the representative SNPs as well as most effective and informative clinical features for the clinical diagnosis of the diseases. In this study, we have applied one of the widely used data mining classification methodology: "decision tree" for associating the SNP biomarkers and significant clinical data with the Alzheimer's disease (AD), which is the most common form of "dementia". Different tree construction parameters have been compared for the optimization, and the most accurate tree for predicting the AD is presented.

  12. Microparticles provide a novel biomarker to predict severe clinical outcomes of dengue virus infection.

    Science.gov (United States)

    Punyadee, Nuntaya; Mairiang, Dumrong; Thiemmeca, Somchai; Komoltri, Chulaluk; Pan-Ngum, Wirichada; Chomanee, Nusara; Charngkaew, Komgrid; Tangthawornchaikul, Nattaya; Limpitikul, Wannee; Vasanawathana, Sirijitt; Malasit, Prida; Avirutnan, Panisadee

    2015-02-01

    Shedding of microparticles (MPs) is a consequence of apoptotic cell death and cellular activation. Low levels of circulating MPs in blood help maintain homeostasis, whereas increased MP generation is linked to many pathological conditions. Herein, we investigated the role of MPs in dengue virus (DENV) infection. Infection of various susceptible cells by DENV led to apoptotic death and MP release. These MPs harbored a viral envelope protein and a nonstructural protein 1 (NS1) on their surfaces. Ex vivo analysis of clinical specimens from patients with infections of different degrees of severity at multiple time points revealed that MPs generated from erythrocytes and platelets are two major MP populations in the circulation of DENV-infected patients. Elevated levels of red blood cell-derived MPs (RMPs) directly correlated with DENV disease severity, whereas a significant decrease in platelet-derived MPs was associated with a bleeding tendency. Removal by mononuclear cells of complement-opsonized NS1-anti-NS1 immune complexes bound to erythrocytes via complement receptor type 1 triggered MP shedding in vitro, a process that could explain the increased levels of RMPs in severe dengue. These findings point to the multiple roles of MPs in dengue pathogenesis. They offer a potential novel biomarker candidate capable of differentiating dengue fever from the more serious dengue hemorrhagic fever. Dengue is the most important mosquito-transmitted viral disease in the world. No vaccines or specific treatments are available. Rapid diagnosis and immediate treatment are the keys to achieve a positive outcome. Dengue virus (DENV) infection, like some other medical conditions, changes the level and composition of microparticles (MPs), tiny bag-like structures which are normally present at low levels in the blood of healthy individuals. This study investigated how MPs in culture and patients' blood are changed in response to DENV infection. Infection of cells led to programmed

  13. Clinical risk stratification optimizes value of biomarkers to predict new-onset heart failure in a community-based cohort.

    Science.gov (United States)

    Brouwers, Frank P; van Gilst, Wiek H; Damman, Kevin; van den Berg, Maarten P; Gansevoort, Ron T; Bakker, Stephan J L; Hillege, Hans L; van Veldhuisen, Dirk J; van der Harst, Pim; de Boer, Rudolf A

    2014-09-01

    We aim to identify and quantify the value of biomarkers for incident new-onset heart failure (HF) in a community-based cohort and subgroups based on cardiovascular risk and evaluate the prognostic value of 13 biomarkers for HF with reduced and preserved ejection fraction. Thirteen biomarkers reflecting diverse pathophysiologic domains were examined in 8569 HF-free participants in Prevention of Vascular and Renal Endstage Disease (mean age, 49 years; 50% men). Subjects were categorized in 2 risk groups based on cardiovascular history. Incremental value per biomarker was assessed using Harrell C-indices. One hundred sixty-eight subjects (2.4%) were diagnosed with new-onset HF in the low-risk group (n=6915; Framingham Risk Score, 5.9%) and 206 (12.2%) subjects in the high-risk group (n=1654; Framingham Risk Score, 18.6%). The association of natriuretic peptides, adrenomedullin, endothelin, and galectin-3 with new-onset HF was stronger in the high-risk group (all Prisk for new-onset HF between both risk groups. The best model for new-onset HF included the combination of N-terminal pro-B-type natriuretic peptide, troponin-T, and urinary albumin excretion, increasing model accuracy to 0.81 (9.5%, Prisk group. Except for a modest effect of cystatin-C, no biomarker was associated with increased risk for HF with preserved ejection fraction. Risk stratification increases the incremental value per biomarker to predict new-onset HF, especially HF with reduced ejection fraction. We suggest that routine biomarker testing should be limited to the use of natriuretic peptides and troponin-T in patients with increased cardiovascular risk. © 2014 American Heart Association, Inc.

  14. Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers.

    Directory of Open Access Journals (Sweden)

    Lesley M E McCowan

    Full Text Available Most small for gestational age pregnancies are unrecognised before birth, resulting in substantial avoidable perinatal mortality and morbidity. Our objective was to develop multivariable prediction models for small for gestational age combining clinical risk factors and biomarkers at 15±1 weeks' with ultrasound parameters at 20±1 weeks' gestation.Data from 5606 participants in the Screening for Pregnancy Endpoints (SCOPE cohort study were divided into Training (n = 3735 and Validation datasets (n = 1871. The primary outcomes were All-SGA (small for gestational age with birthweight <10th customised centile, Normotensive-SGA (small for gestational age with a normotensive mother and Hypertensive-SGA (small for gestational age with an hypertensive mother. The comparison group comprised women without the respective small for gestational age phenotype. Multivariable analysis was performed using stepwise logistic regression beginning with clinical variables, and subsequent additions of biomarker and then ultrasound (biometry and Doppler variables. Model performance was assessed in Training and Validation datasets by calculating area under the curve.633 (11.2% infants were All-SGA, 465(8.2% Normotensive-SGA and 168 (3% Hypertensive-SGA. Area under the curve (95% Confidence Intervals for All-SGA using 15±1 weeks' clinical variables, 15±1 weeks' clinical+ biomarker variables and clinical + biomarkers + biometry /Doppler at 20±1 weeks' were: 0.63 (0.59-0.67, 0.64 (0.60-0.68 and 0.69 (0.66-0.73 respectively in the Validation dataset; Normotensive-SGA results were similar: 0.61 (0.57-0.66, 0.61 (0.56-0.66 and 0.68 (0.64-0.73 with small increases in performance in the Training datasets. Area under the curve (95% Confidence Intervals for Hypertensive-SGA were: 0.76 (0.70-0.82, 0.80 (0.75-0.86 and 0.84 (0.78-0.89 with minimal change in the Training datasets.Models for prediction of small for gestational age, which combine biomarkers, clinical and

  15. The prognostic blood biomarker proadrenomedullin for outcome prediction in patients with chronic obstructive pulmonary disease (COPD): a qualitative clinical review.

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    Schuetz, Philipp; Marlowe, Robert J; Mueller, Beat

    2015-03-01

    Plasma proadrenomedullin (ProADM) is a blood biomarker that may aid in multidimensional risk assessment of patients with chronic obstructive pulmonary disease (COPD). Co-secreted 1:1 with adrenomedullin (ADM), ProADM is a less biologically active, more chemically stable surrogate for this pluripotent regulatory peptide, which due to biological and ex vivo physical characteristics is difficult to reliably directly quantify. Upregulated by hypoxia, inflammatory cytokines, bacterial products, and shear stress and expressed widely in pulmonary cells and ubiquitously throughout the body, ADM exerts or mediates vasodilatory, natriuretic, diuretic, antioxidative, anti-inflammatory, antimicrobial, and metabolic effects. Observational data from four separate studies totaling 1366 patients suggest that as a single factor, ProADM is a significant independent, and accurate, long-term all-cause mortality predictor in COPD. This body of work also suggests that combined with different groups of demographic/clinical variables, ProADM provides significant incremental long-term mortality prediction power relative to the groups of variables alone. Additionally, the literature contains indications that ProADM may be a global cardiopulmonary stress marker, potentially supplying prognostic information when cardiopulmonary exercise testing results such as 6-min walk distance are unavailable due to time or other resource constraints or to a patient's advanced disease. Prospective, randomized, controlled interventional studies are needed to demonstrate whether ProADM use in risk-based guidance of site-of-care, monitoring, and treatment decisions improves clinical, quality-of-life, or pharmacoeconomic outcomes in patients with COPD.

  16. Predictive values of semi-quantitative procalcitonin test and common biomarkers for the clinical outcomes of community-acquired pneumonia.

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    Ugajin, Motoi; Yamaki, Kenichi; Hirasawa, Natsuko; Yagi, Takeo

    2014-04-01

    The semi-quantitative serum procalcitonin test (Brahms PCT-Q) is available conveniently in clinical practice. However, there are few data on the relationship between results for this semi-quantitative procalcitonin test and clinical outcomes of community-acquired pneumonia (CAP). We investigated the usefulness of this procalcitonin test for predicting the clinical outcomes of CAP in comparison with severity scoring systems and the blood urea nitrogen/serum albumin (B/A) ratio, which has been reported to be a simple but reliable prognostic indicator in our prior CAP study. This retrospective study included data from subjects who were hospitalized for CAP from August 2010 through October 2012 and who were administered the semi-quantitative serum procalcitonin test on admission. The demographic characteristics; laboratory biomarkers; microbiological test results; Pneumonia Severity Index scores; confusion, urea nitrogen, breathing frequency, blood pressure, ≥ 65 years of age (CURB-65) scale scores; and age, dehydration, respiratory failure, orientation disturbance, pressure (A-DROP) scale scores on hospital admission were retrieved from their medical charts. The outcomes were mortality within 28 days of hospital admission and the need for intensive care. Of the 213 subjects with CAP who were enrolled in the study, 20 died within 28 days of hospital admission, and 32 required intensive care. Mortality did not differ significantly among subjects with different semi-quantitative serum procalcitonin levels; however, subjects with serum procalcitonin levels ≥ 10.0 ng/mL were more likely to require intensive care than those with lower levels (P pneumonia. Using the receiver operating characteristic curves for mortality, the area under the curve was 0.86 for Pneumonia Severity Index class, 0.81 for B/A ratio, 0.81 for A-DROP, 0.80 for CURB-65, and 0.57 for semi-quantitative procalcitonin test. The semi-quantitative serum procalcitonin level on hospital admission was less

  17. Biomarkers of fibrosis and impaired liver function in chronic hepatitis C: how well do they predict clinical outcomes?

    DEFF Research Database (Denmark)

    Peters, L.; Rockstroh, J.K.

    2010-01-01

    PURPOSE OF REVIEW: To review the recent literature on the prognostic value of biomarkers of liver fibrosis and impaired liver function in patients with chronic hepatitis C with or without HIV coinfection. RECENT FINDINGS: A combination of standard blood tests seems to be useful in identifying...... levels of the fibrosis marker hyaluronic acid are a strong predictor of clinical complications. A smaller study found hyaluronic acid and two other fibrosis tests, aspartate aminotransferase-to-platelet ratio index (APRI) and Fib-4, to be independent predictors of mortality when included in models...

  18. Phase II cancer clinical trials for biomarker-guided treatments.

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    Jung, Sin-Ho

    2018-01-01

    The design and analysis of cancer clinical trials with biomarker depend on various factors, such as the phase of trials, the type of biomarker, whether the used biomarker is validated or not, and the study objectives. In this article, we demonstrate the design and analysis of two Phase II cancer clinical trials, one with a predictive biomarker and the other with an imaging prognostic biomarker. Statistical testing methods and their sample size calculation methods are presented for each trial. We assume that the primary endpoint of these trials is a time to event variable, but this concept can be used for any type of endpoint.

  19. Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study.

    Directory of Open Access Journals (Sweden)

    Laura K Erdman

    Full Text Available Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance.We studied children with WHO-defined clinical pneumonia (n = 155 within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30, other infiltrates (n = 31, or normal chest x-ray (n = 94. Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis.Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5-98.8, 80.8% specificity (72.6-87.1, positive likelihood ratio 4.9 (3.4-7.1, negative likelihood ratio 0

  20. Biomarkers of Host Response Predict Primary End-Point Radiological Pneumonia in Tanzanian Children with Clinical Pneumonia: A Prospective Cohort Study

    Science.gov (United States)

    Erdman, Laura K.; D’Acremont, Valérie; Hayford, Kyla; Kilowoko, Mary; Kyungu, Esther; Hongoa, Philipina; Alamo, Leonor; Streiner, David L.; Genton, Blaise; Kain, Kevin C.

    2015-01-01

    Background Diagnosing pediatric pneumonia is challenging in low-resource settings. The World Health Organization (WHO) has defined primary end-point radiological pneumonia for use in epidemiological and vaccine studies. However, radiography requires expertise and is often inaccessible. We hypothesized that plasma biomarkers of inflammation and endothelial activation may be useful surrogates for end-point pneumonia, and may provide insight into its biological significance. Methods We studied children with WHO-defined clinical pneumonia (n = 155) within a prospective cohort of 1,005 consecutive febrile children presenting to Tanzanian outpatient clinics. Based on x-ray findings, participants were categorized as primary end-point pneumonia (n = 30), other infiltrates (n = 31), or normal chest x-ray (n = 94). Plasma levels of 7 host response biomarkers at presentation were measured by ELISA. Associations between biomarker levels and radiological findings were assessed by Kruskal-Wallis test and multivariable logistic regression. Biomarker ability to predict radiological findings was evaluated using receiver operating characteristic curve analysis and Classification and Regression Tree analysis. Results Compared to children with normal x-ray, children with end-point pneumonia had significantly higher C-reactive protein, procalcitonin and Chitinase 3-like-1, while those with other infiltrates had elevated procalcitonin and von Willebrand Factor and decreased soluble Tie-2 and endoglin. Clinical variables were not predictive of radiological findings. Classification and Regression Tree analysis generated multi-marker models with improved performance over single markers for discriminating between groups. A model based on C-reactive protein and Chitinase 3-like-1 discriminated between end-point pneumonia and non-end-point pneumonia with 93.3% sensitivity (95% confidence interval 76.5–98.8), 80.8% specificity (72.6–87.1), positive likelihood ratio 4.9 (3.4–7

  1. CSF biomarkers of Alzheimer's disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts.

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    Hansson, Oskar; Seibyl, John; Stomrud, Erik; Zetterberg, Henrik; Trojanowski, John Q; Bittner, Tobias; Lifke, Valeria; Corradini, Veronika; Eichenlaub, Udo; Batrla, Richard; Buck, Katharina; Zink, Katharina; Rabe, Christina; Blennow, Kaj; Shaw, Leslie M

    2018-03-01

    We studied whether fully automated Elecsys cerebrospinal fluid (CSF) immunoassay results were concordant with positron emission tomography (PET) and predicted clinical progression, even with cutoffs established in an independent cohort. Cutoffs for Elecsys amyloid-β 1-42 (Aβ), total tau/Aβ(1-42), and phosphorylated tau/Aβ(1-42) were defined against [ 18 F]flutemetamol PET in Swedish BioFINDER (n = 277) and validated against [ 18 F]florbetapir PET in Alzheimer's Disease Neuroimaging Initiative (n = 646). Clinical progression in patients with mild cognitive impairment (n = 619) was studied. CSF total tau/Aβ(1-42) and phosphorylated tau/Aβ(1-42) ratios were highly concordant with PET classification in BioFINDER (overall percent agreement: 90%; area under the curve: 94%). The CSF biomarker statuses established by predefined cutoffs were highly concordant with PET classification in Alzheimer's Disease Neuroimaging Initiative (overall percent agreement: 89%-90%; area under the curves: 96%) and predicted greater 2-year clinical decline in patients with mild cognitive impairment. Strikingly, tau/Aβ ratios were as accurate as semiquantitative PET image assessment in predicting visual read-based outcomes. Elecsys CSF biomarker assays may provide reliable alternatives to PET in Alzheimer's disease diagnosis. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

  2. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

    Science.gov (United States)

    Korolev, Igor O.; Symonds, Laura L.; Bozoki, Andrea C.

    2016-01-01

    Background Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer's disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level. Methods Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework. Results Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions. Conclusions We developed an accurate prognostic model for predicting

  3. Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical, MRI, and Plasma Biomarkers via Probabilistic Pattern Classification.

    Directory of Open Access Journals (Sweden)

    Igor O Korolev

    Full Text Available Individuals with mild cognitive impairment (MCI have a substantially increased risk of developing dementia due to Alzheimer's disease (AD. In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139 and those who did not (n = 120 during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87. Predictors of progression included scores on the Alzheimer's Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex. Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.We developed an accurate prognostic model for predicting MCI-to-dementia progression

  4. Clinical Risk Stratification Optimizes Value of Biomarkers to Predict New-Onset Heart Failure in a Community-Based Cohort

    NARCIS (Netherlands)

    Brouwers, Frank P.; van Gilst, Wiek H.; Damman, Kevin; van den Berg, Maarten P.; Gansevoort, Ron T.; Bakker, Stephan J. L.; Hillege, Hans L.; van Veldhuisen, Dirk J.; van der Harst, Pim; de Boer, Rudolf A.

    Background-We aim to identify and quantify the value of biomarkers for incident new-onset heart failure (HF) in a community-based cohort and subgroups based on cardiovascular risk and evaluate the prognostic value of 13 biomarkers for HF with reduced and preserved ejection fraction. Methods and

  5. Use of biomarkers in ALS drug development and clinical trials.

    Science.gov (United States)

    Bakkar, Nadine; Boehringer, Ashley; Bowser, Robert

    2015-05-14

    The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis. Copyright © 2014 Elsevier B.V. All rights reserved.

  6. Epidemiological and Clinical Baseline Characteristics as Predictive Biomarkers of Response to Anti-VEGF Treatment in Patients with Neovascular AMD

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    Miltiadis K. Tsilimbaris

    2016-01-01

    Full Text Available Purpose. To review the current literature investigating patient response to antivascular endothelial growth factor-A (VEGF therapy in the treatment of neovascular age-related macular degeneration (nAMD and to identify baseline characteristics that might predict response. Method. A literature search of the PubMed database was performed, using the keywords: AMD, anti-VEGF, biomarker, optical coherence tomography, treatment outcome, and predictor. The search was limited to articles published from 2006 to date. Exclusion criteria included phase 1 trials, case reports, studies focusing on indications other than nAMD, and oncology. Results. A total of 1467 articles were identified, of which 845 were excluded. Of the 622 remaining references, 47 met all the search criteria and were included in this review. Conclusion. Several baseline characteristics correlated with anti-VEGF treatment response, including best-corrected visual acuity, age, lesion size, and retinal thickness. The majority of factors were associated with disease duration, suggesting that longer disease duration before treatment results in worse treatment outcomes. This highlights the need for early treatment for patients with nAMD to gain optimal treatment outcomes. Many of the identified baseline characteristics are interconnected and cannot be evaluated in isolation; therefore multivariate analyses will be required to determine any specific relationship with treatment response.

  7. Distinguishing prognostic and predictive biomarkers: An information theoretic approach.

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    Sechidis, Konstantinos; Papangelou, Konstantinos; Metcalfe, Paul D; Svensson, David; Weatherall, James; Brown, Gavin

    2018-05-02

    The identification of biomarkers to support decision-making is central to personalised medicine, in both clinical and research scenarios. The challenge can be seen in two halves: identifying predictive markers, which guide the development/use of tailored therapies; and identifying prognostic markers, which guide other aspects of care and clinical trial planning, i.e. prognostic markers can be considered as covariates for stratification. Mistakenly assuming a biomarker to be predictive, when it is in fact largely prognostic (and vice-versa) is highly undesirable, and can result in financial, ethical and personal consequences. We present a framework for data-driven ranking of biomarkers on their prognostic/predictive strength, using a novel information theoretic method. This approach provides a natural algebra to discuss and quantify the individual predictive and prognostic strength, in a self-consistent mathematical framework. Our contribution is a novel procedure, INFO+, which naturally distinguishes the prognostic vs predictive role of each biomarker and handles higher order interactions. In a comprehensive empirical evaluation INFO+ outperforms more complex methods, most notably when noise factors dominate, and biomarkers are likely to be falsely identified as predictive, when in fact they are just strongly prognostic. Furthermore, we show that our methods can be 1-3 orders of magnitude faster than competitors, making it useful for biomarker discovery in 'big data' scenarios. Finally, we apply our methods to identify predictive biomarkers on two real clinical trials, and introduce a new graphical representation that provides greater insight into the prognostic and predictive strength of each biomarker. R implementations of the suggested methods are available at https://github.com/sechidis. konstantinos.sechidis@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

  8. Clinical and biomarker changes in premanifest Huntington disease show trial feasibility: a decade of the PREDICT-HD study

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    Jane S Paulsen

    2014-04-01

    Full Text Available There is growing consensus that intervention and treatment of Huntington disease (HD should occur at the earliest stage possible. Various early-intervention methods for this fatal neurodegenerative disease have been identified, but preventive clinical trials for HD are limited by a lack of knowledge of the natural history of the disease and a dearth of appropriate outcome measures. Objectives of the current study are to document the natural history of premanifest HD progression in the largest cohort ever studied and to develop a battery of imaging and clinical markers of premanifest HD progression that can be used as outcome measures in preventive clinical trials. PREDICT-HD is a 32-site, international, observational study of premanifest HD, with annual examination of 1013 participants with premanifest HD and 301 gene-expansion negative controls between 2001 and 2012. Findings document 39 variables representing imaging, motor, cognitive, functional, and psychiatric domains, showing different rates of decline between premanifest Huntington disease and controls. Required sample size and models of premanifest HD are presented to inform future design of clinical and preclinical research. Preventive clinical trials in premanifest HD with participants who have a medium or high probability of motor onset are calculated to be as resource-effective as those conducted in diagnosed HD and could interrupt disease seven to twelve years earlier. Methods and measures for preventive clinical trials in premanifest HD more than a dozen years from motor onset are also feasible. These findings represent the most thorough documentation of a clinical battery for experimental therapeutics in stages of premanifest HD, the time period for which effective intervention may provide the most positive possible outcome for patients and their families affected by this devastating disease.

  9. Biomarkers of Renal Function : Towards Clinical Actionability

    NARCIS (Netherlands)

    Binnenmars, S Heleen; Hijmans, R S; Navis, G; de Borst, M H

    This review provides an overview of the clinical value of themost relevant renal biomarkers, focusing on two main clinical conditions: acute kidney injury and chronic kidney disease. We categorize biomarkers according to their actionability, in terms of a documented response to treatment in relation

  10. The potential role of biomarkers in predicting gestational diabetes

    Directory of Open Access Journals (Sweden)

    Huguette S Brink

    2016-08-01

    Full Text Available Gestational diabetes (GD is a frequent complication during pregnancy and is associated with maternal and neonatal complications. It is suggested that a disturbing environment for the foetus, such as impaired glucose metabolism during intrauterine life, may result in enduring epigenetic changes leading to increased disease risk in adult life. Hence, early prediction of GD is vital. Current risk prediction models are based on maternal and clinical parameters, lacking a strong predictive value. Adipokines are mainly produced by adipocytes and suggested to be a link between obesity and its cardiovascular complications. Various adipokines, including adiponectin, leptin and TNFα, have shown to be dysregulated in GD. This review aims to outline biomarkers potentially associated with the pathophysiology of GD and discuss the role of integrating predictive biomarkers in current clinical risk prediction models, in order to enhance the identification of those at risk.

  11. Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy.

    Science.gov (United States)

    Forker, L J; Choudhury, A; Kiltie, A E

    2015-10-01

    Radiotherapy is an essential component of treatment for more than half of newly diagnosed cancer patients. The response to radiotherapy varies widely between individuals and although advances in technology have allowed the adaptation of radiotherapy fields to tumour anatomy, it is still not possible to tailor radiotherapy based on tumour biology. A biomarker of intrinsic radiosensitivity would be extremely valuable for individual dosing, aiding decision making between radical treatment options and avoiding toxicity of neoadjuvant or adjuvant radiotherapy in those unlikely to benefit. This systematic review summarises the current evidence for biomarkers under investigation as predictors of radiotherapy benefit. Only 10 biomarkers were identified as having been evaluated for their radiotherapy-specific predictive value in over 100 patients in a clinical setting, highlighting that despite a rich literature there were few high-quality studies for inclusion. The most extensively studied radiotherapy predictive biomarkers were the radiosensitivity index and MRE11; however, neither has been evaluated in a randomised controlled trial. Although these biomarkers show promise, there is not enough evidence to justify their use in routine practice. Further validation is needed before biomarkers can fulfil their potential and predict treatment outcomes for large numbers of patients. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

  12. Human cervicovaginal fluid biomarkers to predict term and preterm labor

    Science.gov (United States)

    Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

    2015-01-01

    Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

  13. Regulatory T cell frequency, but not plasma IL-33 levels, represents potential immunological biomarker to predict clinical response to intravenous immunoglobulin therapy.

    Science.gov (United States)

    Maddur, Mohan S; Stephen-Victor, Emmanuel; Das, Mrinmoy; Prakhar, Praveen; Sharma, Varun K; Singh, Vikas; Rabin, Magalie; Trinath, Jamma; Balaji, Kithiganahalli N; Bolgert, Francis; Vallat, Jean-Michel; Magy, Laurent; Kaveri, Srini V; Bayry, Jagadeesh

    2017-03-20

    Intravenous immunoglobulin (IVIG) is a polyspecific pooled immunoglobulin G preparation and one of the commonly used therapeutics for autoimmune diseases including those of neurological origin. A recent report in murine model proposed that IVIG expands regulatory T (T reg ) cells via induction of interleukin 33 (IL-33). However, translational insight on these observations is lacking. Ten newly diagnosed Guillain-Barré syndrome (GBS) patients were treated with IVIG at the rate of 0.4 g/kg for three to five consecutive days. Clinical evaluation for muscular weakness was performed by Medical Research Council (MRC) and modified Rankin scoring (MRS) system. Heparinized blood samples were collected before and 1, 2, and 4-5 weeks post-IVIG therapy. Peripheral blood mononuclear cells were stained for surface CD4 and intracellular Foxp3, IFN-γ, and tumor necrosis factor alpha (TNF-α) and were analyzed by flow cytometry. IL-33 and prostaglandin E2 in the plasma were measured by ELISA. The fold changes in plasma IL-33 at week 1 showed no correlation with the MRC and MRS scores at weeks 1, 2, and ≥4 post-IVIG therapy. Clinical recovery following IVIG therapy appears to be associated with T reg cell response. Contrary to murine study, there was no association between the fold changes in IL-33 at week 1 and T reg cell frequency at weeks 1, 2, and ≥4 post-IVIG therapy. T reg cell-mediated clinical response to IVIG therapy in GBS patients was associated with reciprocal regulation of effector T cells-expressing TNF-α. T reg cell expansion by IVIG in patients with autoimmune diseases lack correlation with IL-33. T reg cell frequency, but not plasma IL-33 levels, represents potential immunological biomarker to predict clinical response to IVIG therapy.

  14. Biomarkers in T cell therapy clinical trials

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    Kalos Michael

    2011-08-01

    Full Text Available Abstract T cell therapy represents an emerging and promising modality for the treatment of both infectious disease and cancer. Data from recent clinical trials have highlighted the potential for this therapeutic modality to effect potent anti-tumor activity. Biomarkers, operationally defined as biological parameters measured from patients that provide information about treatment impact, play a central role in the development of novel therapeutic agents. In the absence of information about primary clinical endpoints, biomarkers can provide critical insights that allow investigators to guide the clinical development of the candidate product. In the context of cell therapy trials, the definition of biomarkers can be extended to include a description of parameters of the cell product that are important for product bioactivity. This review will focus on biomarker studies as they relate to T cell therapy trials, and more specifically: i. An overview and description of categories and classes of biomarkers that are specifically relevant to T cell therapy trials, and ii. Insights into future directions and challenges for the appropriate development of biomarkers to evaluate both product bioactivity and treatment efficacy of T cell therapy trials.

  15. The utility of P300 as a schizophrenia endophenotype and predictive biomarker: clinical and socio-demographic modulators in COGS-2.

    Science.gov (United States)

    Turetsky, Bruce I; Dress, Erich M; Braff, David L; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Sprock, Joyce; Stone, William S; Sugar, Catherine A; Swerdlow, Neal R; Tsuang, Debby W; Tsuang, Ming T; Light, Gregory

    2015-04-01

    Reduced auditory P300 amplitude is a robust schizophrenia deficit exhibiting the qualities of a viable genetic endophenotype. These include heritability, test-retest reliability, and trait-like stability. Recent evidence suggests that P300 may also serve as a predictive biomarker for transition to psychosis during the schizophrenia prodrome. Historically, the utility of the P300 has been limited by its clinical nonspecificity, cross-site measurement variability, and required EEG expertise. The Consortium on the Genetics of Schizophrenia (COGS-2) study provided an opportunity to examine the consistency of the measure across multiple sites with varying degrees of EEG experience, and to identify important modulating factors that contribute to measurement variability. Auditory P300 was acquired from 649 controls and 587 patients at 5 sites. An overall patient deficit was observed with effect size 0.62. Each site independently observed a significant patient deficit, but site differences also existed. In patients, site differences reflected clinical differences in positive symptomatology and functional capacity. In controls, site differences reflected differences in racial stratification, smoking and substance use history. These factors differentially suppressed the P300 response, but only in control subjects. This led to an attenuated patient-control difference among smokers and among African Americans with history of substance use. These findings indicate that the P300 can be adequately assessed quantitatively, across sites, without substantial EEG expertise. Measurements are suitable for both genetic endophenotype analyses and studies of psychosis risk and conversion. However, careful attention must be given to selection of appropriate comparison samples to avoid misleading false negative results. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

    Science.gov (United States)

    Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

    2017-10-11

    Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

  17. Serum biomarkers predictive of depressive episodes in panic disorder.

    Science.gov (United States)

    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2016-02-01

    Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that can detect PD/PDA patients at increased risk of developing subsequent depressive disorders with good predictive performance in a naturalistic cohort design. After an independent validation our proposed biomarkers could prove useful in the detection of at-risk PD/PDA patients, allowing for early therapeutic interventions and improving clinical outcome. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Biomarkers in prostate cancer - Current clinical utility and future perspectives.

    Science.gov (United States)

    Kretschmer, Alexander; Tilki, Derya

    2017-12-01

    Current tendencies in the treatment course of prostate cancer patients increase the need for reliable biomarkers that help in decision-making in a challenging clinical setting. Within the last decade, several novel biomarkers have been introduced. In the following comprehensive review article, we focus on diagnostic (PHI ® , 4K score, SelectMDx ® , ConfirmMDx ® , PCA3, MiPS, ExoDX ® , mpMRI) and prognostic (OncotypeDX GPS ® , Prolaris ® , ProMark ® , DNA-ploidy, Decipher ® ) biomarkers that are in widespread clinical use and are supported by evidence. Hereby, we focus on multiple clinical situations in which innovative biomarkers may guide decision-making in prostate cancer therapy. In addition, we describe novel liquid biopsy approaches (circulating tumor cells, cell-free DNA) that have been described as predictive biomarkers in metastatic castration-resistant prostate cancer and might support an individual patient-centred oncological approach in the nearer future. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Potential biomarkers for the clinical prognosis of severe dengue

    Directory of Open Access Journals (Sweden)

    Mayara Marques Carneiro da Silva

    2013-09-01

    Full Text Available Currently, several assays can confirm acute dengue infection at the point-of-care. However, none of these assays can predict the severity of the disease symptoms. A prognosis test that predicts the likelihood of a dengue patient to develop a severe form of the disease could permit more efficient patient triage and treatment. We hypothesise that mRNA expression of apoptosis and innate immune response-related genes will be differentially regulated during the early stages of dengue and might predict the clinical outcome. Aiming to identify biomarkers for dengue prognosis, we extracted mRNA from the peripheral blood mononuclear cells of mild and severe dengue patients during the febrile stage of the disease to measure the expression levels of selected genes by quantitative polymerase chain reaction. The selected candidate biomarkers were previously identified by our group as differentially expressed in microarray studies. We verified that the mRNA coding for CFD, MAGED1, PSMB9, PRDX4 and FCGR3B were differentially expressed between patients who developed clinical symptoms associated with the mild type of dengue and patients who showed clinical symptoms associated with severe dengue. We suggest that this gene expression panel could putatively serve as biomarkers for the clinical prognosis of dengue haemorrhagic fever.

  20. Immunohistochemistry for predictive biomarkers in non-small cell lung cancer.

    Science.gov (United States)

    Mino-Kenudson, Mari

    2017-10-01

    In the era of targeted therapy, predictive biomarker testing has become increasingly important for non-small cell lung cancer. Of multiple predictive biomarker testing methods, immunohistochemistry (IHC) is widely available and technically less challenging, can provide clinically meaningful results with a rapid turn-around-time and is more cost efficient than molecular platforms. In fact, several IHC assays for predictive biomarkers have already been implemented in routine pathology practice. In this review, we will discuss: (I) the details of anaplastic lymphoma kinase (ALK) and proto-oncogene tyrosine-protein kinase ROS (ROS1) IHC assays including the performance of multiple antibody clones, pros and cons of IHC platforms and various scoring systems to design an optimal algorithm for predictive biomarker testing; (II) issues associated with programmed death-ligand 1 (PD-L1) IHC assays; (III) appropriate pre-analytical tissue handling and selection of optimal tissue samples for predictive biomarker IHC.

  1. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

    2015-01-01

    To improve the clinical course of diseases, more accurate diagnostic and assessment methods are required as early as possible. In order to achieve this, metabolomics offers new opportunities for biomarker discovery in complex diseases and may provide pathological understanding of diseases beyond traditional technologies. It is the systematic analysis of low-molecular-weight metabolites in biological samples and has become an important tool in clinical research and the diagnosis of human disease and has been applied to discovery and identification of the perturbed pathways. It provides a powerful approach to discover biomarkers in biological systems and offers a holistic approach with the promise to clinically enhance diagnostics. When carried out properly, it could provide insight into the understanding of the underlying mechanisms of diseases, help to identify patients at risk of disease, and predict the response to specific treatments. Currently, metabolomics has become an important tool in clinical research and the diagnosis of human disease and becomes a hot topic. This review will highlight the importance and benefit of metabolomics for identifying biomarkers that accurately screen potential biomarkers of diseases. PMID:26090402

  2. Angiogenesis-Related Biomarkers (sFlt-1/PLGF in the Prediction and Diagnosis of Placental Dysfunction: An Approach for Clinical Integration

    Directory of Open Access Journals (Sweden)

    Ignacio Herraiz

    2015-08-01

    Full Text Available Placental dysfunction is involved in a group of obstetrical conditions including preeclampsia, intrauterine growth restriction, and placental abruption. Their timely and accurate recognition is often a challenge since diagnostic criteria are still based on nonspecific signs and symptoms. The discovering of the role of angiogenic-related factors (sFlt-1/PlGF in the underlying pathophysiology of placental dysfunction, taking into account that angiogenesis-related biomarkers are not specific to any particular placental insufficiency-related disease, has marked an important step for improving their early diagnosis and prognosis assessment. However, sFlt-1/PlGF has not been yet established as a part of most guidelines. We will review the current evidence on the clinical utility of sFlt-1/PlGF and propose a new protocol for its clinical integration.

  3. Clinical Translation and Validation of a Predictive Biomarker for Patritumab, an Anti-human Epidermal Growth Factor Receptor 3 (HER3) Monoclonal Antibody, in Patients With Advanced Non-small Cell Lung Cancer.

    Science.gov (United States)

    Mendell, Jeanne; Freeman, Daniel J; Feng, Wenqin; Hettmann, Thore; Schneider, Matthias; Blum, Sabine; Ruhe, Jens; Bange, Johannes; Nakamaru, Kenji; Chen, Shuquan; Tsuchihashi, Zenta; von Pawel, Joachim; Copigneaux, Catherine; Beckman, Robert A

    2015-03-01

    During early clinical development, prospective identification of a predictive biomarker and validation of an assay method may not always be feasible. Dichotomizing a continuous biomarker measure to classify responders also leads to challenges. We present a case study of a prospective-retrospective approach for a continuous biomarker identified after patient enrollment but defined prospectively before the unblinding of data. An analysis of the strengths and weaknesses of this approach and the challenges encountered in its practical application are also provided. HERALD (NCT02134015) was a double-blind, phase 2 study in patients with non-small cell lung cancer (NSCLC) randomized to erlotinib with placebo or with high or low doses of patritumab, a monoclonal antibody targeted against human epidermal growth factor receptor 3 (HER3). While the primary objective was to assess safety and progression-free survival (PFS), a secondary objective was to determine a single predictive biomarker hypothesis to identify subjects most likely to benefit from the addition of patritumab. Although not identified as the primary biomarker in the study protocol, on the basis of preclinical results from 2 independent laboratories, expression levels of the HER3 ligand heregulin (HRG) were prospectively declared the predictive biomarker before data unblinding but after subject enrollment. An assay to measure HRG mRNA was developed and validated. Other biomarkers, such as epidermal growth factor receptor (EGFR) mutation status, were also evaluated in an exploratory fashion. The cutoff value for high vs. low HRG mRNA levels was set at the median delta threshold cycle. A maximum likelihood analysis was performed to evaluate the provisional cutoff. The relationship of HRG values to PFS hazard ratios (HRs) was assessed as a measure of internal validation. Additional NSCLC samples were analyzed to characterize HRG mRNA distribution. The subgroup of patients with high HRG mRNA levels ("HRG

  4. Phosphoproteomic biomarkers predicting histologic nonalcoholic steatohepatitis and fibrosis.

    Science.gov (United States)

    Younossi, Zobair M; Baranova, Ancha; Stepanova, Maria; Page, Sandra; Calvert, Valerie S; Afendy, Arian; Goodman, Zachary; Chandhoke, Vikas; Liotta, Lance; Petricoin, Emanuel

    2010-06-04

    The progression of nonalcoholic fatty liver disease (NAFLD) has been linked to deregulated exchange of the endocrine signaling between adipose and liver tissue. Proteomic assays for the phosphorylation events that characterize the activated or deactivated state of the kinase-driven signaling cascades in visceral adipose tissue (VAT) could shed light on the pathogenesis of nonalcoholic steatohepatitis (NASH) and related fibrosis. Reverse-phase protein microarrays (RPMA) were used to develop biomarkers for NASH and fibrosis using VAT collected from 167 NAFLD patients (training cohort, N = 117; testing cohort, N = 50). Three types of models were developed for NASH and advanced fibrosis: clinical models, proteomics models, and combination models. NASH was predicted by a model that included measurements of two components of the insulin signaling pathway: AKT kinase and insulin receptor substrate 1 (IRS1). The models for fibrosis were less reliable when predictions were based on phosphoproteomic, clinical, or the combination data. The best performing model relied on levels of the phosphorylation of GSK3 as well as on two subunits of cyclic AMP regulated protein kinase A (PKA). Phosphoproteomics technology could potentially be used to provide pathogenic information about NASH and NASH-related fibrosis. This information can lead to a clinically relevant diagnostic/prognostic biomarker for NASH.

  5. Adiponectin as a routine clinical biomarker.

    Science.gov (United States)

    Kishida, Ken; Funahashi, Tohru; Shimomura, Iichiro

    2014-01-01

    Adiponectin is a protein synthesized and secreted predominantly by adipocytes into the peripheral blood. However, circulating adiponectin level is inversely related with body weight, especially visceral fat accumulation. The mechanism of this paradoxical relation remains obscure. Low circulating adiponectin concentrations (hypoadiponectinemia; osteoporosis, and cancer (endometrial cancer, postmenopausal breast cancer, leukemia, colon cancer, gastric cancer, prostate cancer). On the other hand, hyperadiponectinemia is associated with cardiac, renal and pulmonary diseases. This review article focuses on the significance of adiponectin as a clinical biomarker of obesity-related diseases. Routine measurement of adiponectin in patients with lifestyle-related diseases is highly recommended. Copyright © 2013 Elsevier Ltd. All rights reserved.

  6. Plasma Biomarkers Discriminate Clinical Forms of Multiple Sclerosis

    Science.gov (United States)

    Tejera-Alhambra, Marta; Casrouge, Armanda; de Andrés, Clara; Seyfferth, Ansgar; Ramos-Medina, Rocío; Alonso, Bárbara; Vega, Janet; Fernández-Paredes, Lidia; Albert, Matthew L.; Sánchez-Ramón, Silvia

    2015-01-01

    Multiple sclerosis, the most common cause of neurological disability in young population after trauma, represents a significant public health burden. Current challenges associated with management of multiple sclerosis (MS) patients stem from the lack of biomarkers that might enable stratification of the different clinical forms of MS and thus prompt treatment for those patients with progressive MS, for whom there is currently no therapy available. In the present work we analyzed a set of thirty different plasma cytokines, chemokines and growth factors present in circulation of 129 MS patients with different clinical forms (relapsing remitting, secondary progressive and primary progressive MS) and 53 healthy controls, across two independent cohorts. The set of plasma analytes was quantified with Luminex xMAP technology and their predictive power regarding clinical outcome was evaluated both individually using ROC curves and in combination using logistic regression analysis. Our results from two independent cohorts of MS patients demonstrate that the divergent clinical and histology-based MS forms are associated with distinct profiles of circulating plasma protein biomarkers, with distinct signatures being composed of chemokines and growth/angiogenic factors. With this work, we propose that an evaluation of a set of 4 circulating biomarkers (HGF, Eotaxin/CCL11, EGF and MIP-1β/CCL4) in MS patients might serve as an effective tool in the diagnosis and more personalized therapeutic targeting of MS patients. PMID:26039252

  7. Predictive Biomarkers for Bevacizumab in Anti-tumor Therapy

    Directory of Open Access Journals (Sweden)

    Qingqing PAN

    2011-07-01

    Full Text Available Bevacizumab, the monoclonal antibody of vascular endothelial growth factor (VEGF has been applied to the therapy of several neoplasms, but an appropriate biomarker to predict the efficacy has not been found. Those markers can originate from peripheral circulation, tumor tissue and genes. Some researches have found that low level of vascular cell adhesion molecule-1 (VCAM-1, E-selectin, angiopoietin 2 (Ang-2 in circulation or carbonic anhydrase 9 (CA9, CD31-microvessel density (CD31-MVD in tumor tissue can predict better activity of bevacizumab. Moreover, high level of soluble VEGFR2 (sVEGFR2 in circulation or the ratio of phosphorylated-VEGFR2 (p-VEGFR2 and VEGFR2 in tumor tissue increasing has the same predictive function. As to the gene, VEGF-634 CC, VEGF-1498 TT and VEGFR2 H472Q are only related to the side effct. Thus more clinical tirals and basic researches should be performed to find out effective biomarkers in bevacizumab’s therapy.

  8. Integrative EEG biomarkers predict progression to Alzheimer's disease at the MCI stage

    Directory of Open Access Journals (Sweden)

    Simon-Shlomo ePoil

    2013-10-01

    Full Text Available Alzheimer's disease (AD is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a two-year period. We followed 86 patients initially diagnosed with MCI for two years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/. We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.

  9. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

    Fagö-Olsen, Carsten Lindberg; Ottesen, Bent; Christensen, Ib Jarle

    2014-01-01

    AIM: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients. PATIENTS AND METHODS: The study consisted of three parts: Part I: Biomarker data obtained from mass spectrometry, baseline data and, surgical outcome were...... used to construct predictive indices for complete tumour resection; Part II: sera from randomly selected patients from part I were analyzed using enzyme-linked immunosorbent assay (ELISA) to investigate the correlation to mass spectrometry; Part III: the indices from part I were validated in a new.......64. CONCLUSION: Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer....

  10. Prognostic clinical and molecular biomarkers of renal disease in type 2 diabetes

    DEFF Research Database (Denmark)

    Pena, Michelle J; de Zeeuw, Dick; Mischak, Harald

    2015-01-01

    biomarkers address the predictive performance of novel biomarker panels in addition to the classical panel in type 2 diabetes. However, the prospective studies conducted so far have small sample sizes, are insufficiently powered and lack external validation. Adequately sized validation studies of multiple......Diabetic kidney disease occurs in ∼ 25-40% of patients with type 2 diabetes. Given the high risk of progressive renal function loss and end-stage renal disease, early identification of patients with a renal risk is important. Novel biomarkers may aid in improving renal risk stratification...... and metabolomics biomarkers. We focus on multiple biomarker panels since the molecular processes of renal disease progression in type 2 diabetes are heterogeneous, rendering it unlikely that a single biomarker significantly adds to clinical risk prediction. A limited number of prospective studies of multiple...

  11. The role of novel biomarkers in predicting diabetic nephropathy: a review

    Directory of Open Access Journals (Sweden)

    Uwaezuoke SN

    2017-08-01

    Full Text Available Samuel N Uwaezuoke Pediatric Nephrology Firm, Department of Pediatrics, University of Nigeria Teaching Hospital, Ituku-Ozalla, Enugu, Nigeria Abstract: Diabetic nephropathy (DN is one of the microvascular complications of the kidney arising commonly from type 1 diabetes mellitus (T1DM, and occasionally from type 2 diabetes mellitus (T2DM. Microalbuminuria serves as an early indicator of DN risk and a predictor of its progression as well as cardiovascular disease risk in both T1DM and T2DM. Although microalbuminuria remains the gold standard for early detection of DN, it is not a sufficiently accurate predictor of DN risk due to some limitations. Thus, there is a paradigm shift to novel biomarkers which would help to predict DN risk early enough and possibly prevent the occurrence of end-stage kidney disease. These new biomarkers have been broadly classified into glomerular biomarkers, tubular biomarkers, biomarkers of inflammation, biomarkers of oxidative stress, and miscellaneous biomarkers which also include podocyte biomarkers, some of which are also considered as tubular and glomerular biomarkers. Although they are potentially useful for the evaluation of DN, current data still preclude the routine clinical use of majority of them. However, their validation using high-quality and large longitudinal studies is of paramount importance, as well as the subsequent development of a biomarker panel which can reliably predict and evaluate this renal microvascular disease. This paper aims to review the predictive role of these biomarkers in the evaluation of DN. Keywords: type 1 diabetes mellitus, renal microvascular complication, microalbuminuria, end-stage kidney disease, biomarker panel

  12. The current status of biomarkers for predicting toxicity

    Science.gov (United States)

    Campion, Sarah; Aubrecht, Jiri; Boekelheide, Kim; Brewster, David W; Vaidya, Vishal S; Anderson, Linnea; Burt, Deborah; Dere, Edward; Hwang, Kathleen; Pacheco, Sara; Saikumar, Janani; Schomaker, Shelli; Sigman, Mark; Goodsaid, Federico

    2013-01-01

    Introduction There are significant rates of attrition in drug development. A number of compounds fail to progress past preclinical development due to limited tools that accurately monitor toxicity in preclinical studies and in the clinic. Research has focused on improving tools for the detection of organ-specific toxicity through the identification and characterization of biomarkers of toxicity. Areas covered This article reviews what we know about emerging biomarkers in toxicology, with a focus on the 2012 Northeast Society of Toxicology meeting titled ‘Translational Biomarkers in Toxicology.’ The areas covered in this meeting are summarized and include biomarkers of testicular injury and dysfunction, emerging biomarkers of kidney injury and translation of emerging biomarkers from preclinical species to human populations. The authors also provide a discussion about the biomarker qualification process and possible improvements to this process. Expert opinion There is currently a gap between the scientific work in the development and qualification of novel biomarkers for nonclinical drug safety assessment and how these biomarkers are actually used in drug safety assessment. A clear and efficient path to regulatory acceptance is needed so that breakthroughs in the biomarker toolkit for nonclinical drug safety assessment can be utilized to aid in the drug development process. PMID:23961847

  13. [Mixed depressions: clinical and neurophysiological biomarkers].

    Science.gov (United States)

    Micoulaud Franchi, J-A; Geoffroy, P-A; Vion-Dury, J; Balzani, C; Belzeaux, R; Maurel, M; Cermolacce, M; Fakra, E; Azorin, J-M

    2013-12-01

    Epidemiological studies of major depressive episodes (MDE) highlighted the frequent association of symptoms or signs of mania or hypomania with depressive syndrome. Beyond the strict definition of DSM-IV, epidemiological recognition of a subset of MDE characterized by the presence of symptoms or signs of the opposite polarity is clinically important because it is associated with pejorative prognosis and therapeutic response compared to the subgroup of "typical MDE". The development of DSM-5 took into account the epidemiological data. DSM-5 opted for a more dimensional perspective in implementing the concept of "mixed features" from an "episode" to a "specification" of mood disorder. As outlined in the DSM-5: "Mixed features associated with a major depressive episode have been found to be a significant risk factor for the development of bipolar I and II disorder. As a result, it is clinically useful to note the presence of this specifier for treatment planning and monitoring of response to therapeutic". However, the mixed features are sometimes difficult to identify, and neurophysiological biomarkers would be useful to make a more specific diagnosis. Two neurophysiological models make it possible to better understand MDE with mixed features : i) the emotional regulation model that highlights a tendency to hyper-reactive and unstable emotion response, and ii) the vigilance regulation model that highlights, through EEG recording, a tendency to unstable vigilance. Further research is required to better understand relationships between these two models. These models provide the opportunity of a neurophysiological framework to better understand the mixed features associated with MDE and to identify potential neurophysiological biomarkers to guide therapeutic strategies. Copyright © 2013 L’Encéphale. Published by Elsevier Masson SAS.. All rights reserved.

  14. Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

    Science.gov (United States)

    Tut, Thein Ga

    repair (MMR) proteins, the insufficiency of which is characteristic of CRCs with microsatellite instability (MSI). MSI may enable unlimited replicative potential of malignant cell that leads to radiation injury resistance. Therefore, these proteins were characterized in both CRC cell lines (MMR proteins) and different (core and invasive front) rectal cancer tissues (Plk1, gammaH2AX and MMR proteins) exposed to radiation. Histopathological grading of tumour regression was performed following radiotherapy in rectal cancer as a marker of radiotherapy response and a surrogate indicator of patient prognosis. Though MMR protein expressions correlated with improved in vitro cell survival following radiation, these findings could only be partially replicated in patient tissue samples. This may not be entirely unexpected, given intratumoural heterogeneity in genetic profiles and oxygenation between individual cancer cells, their interaction with stromal environment and a multitude of other factors that cannot be adequately replicated in cell line experiments. In our rectal cancer patient cohort, histopathological regression following radiotherapy did appear to correlate with better clinical outcome, but certainly no replacement for the routine pTNM staging with which it was compared. Overexpression of Plk1 in the primary rectal cancer also correlates with poor tumour regression and reduced overall survival. High level of gammaH2AX correlates with higher tumour stage, perineural invasion and vascular invasion. However, interpretation of the results is limited by the small number of positivity amongst the cohort, with respect to gammaH2AX and MMR proteins. The combined analysis of all the proteins examined in this thesis revealed no interactions, possibly suggesting these biomarkers act individually within the DDR pathway, rather than in a demonstrably interdependent manner. Though our results are mixed, finding biomarkers predictive of radiation response is nonetheless critical

  15. Genomic Biomarkers for Personalized Medicine: Development and Validation in Clinical Studies

    Directory of Open Access Journals (Sweden)

    Shigeyuki Matsui

    2013-01-01

    Full Text Available The establishment of high-throughput technologies has brought substantial advances to our understanding of the biology of many diseases at the molecular level and increasing expectations on the development of innovative molecularly targeted treatments and molecular biomarkers or diagnostic tests in the context of clinical studies. In this review article, we position the two critical statistical analyses of high-dimensional genomic data, gene screening and prediction, in the framework of development and validation of genomic biomarkers or signatures, through taking into consideration the possible different strategies for developing genomic signatures. A wide variety of biomarker-based clinical trial designs to assess clinical utility of a biomarker or a new treatment with a companion biomarker are also discussed.

  16. Evaluating biomarkers for prognostic enrichment of clinical trials.

    Science.gov (United States)

    Kerr, Kathleen F; Roth, Jeremy; Zhu, Kehao; Thiessen-Philbrook, Heather; Meisner, Allison; Wilson, Francis Perry; Coca, Steven; Parikh, Chirag R

    2017-12-01

    A potential use of biomarkers is to assist in prognostic enrichment of clinical trials, where only patients at relatively higher risk for an outcome of interest are eligible for the trial. We investigated methods for evaluating biomarkers for prognostic enrichment. We identified five key considerations when considering a biomarker and a screening threshold for prognostic enrichment: (1) clinical trial sample size, (2) calendar time to enroll the trial, (3) total patient screening costs and the total per-patient trial costs, (4) generalizability of trial results, and (5) ethical evaluation of trial eligibility criteria. Items (1)-(3) are amenable to quantitative analysis. We developed the Biomarker Prognostic Enrichment Tool for evaluating biomarkers for prognostic enrichment at varying levels of screening stringency. We demonstrate that both modestly prognostic and strongly prognostic biomarkers can improve trial metrics using Biomarker Prognostic Enrichment Tool. Biomarker Prognostic Enrichment Tool is available as a webtool at http://prognosticenrichment.com and as a package for the R statistical computing platform. In some clinical settings, even biomarkers with modest prognostic performance can be useful for prognostic enrichment. In addition to the quantitative analysis provided by Biomarker Prognostic Enrichment Tool, investigators must consider the generalizability of trial results and evaluate the ethics of trial eligibility criteria.

  17. Some aspects of cancer biomarkers and their clinical application in solid tumors – revisited

    Directory of Open Access Journals (Sweden)

    Isaac D

    2017-07-01

    Full Text Available Cancer biomarkers can be used for a variety of purposes related to screening, prediction, stratification, detection, diagnosis, prognosis, treatment design, and monitoring of a therapeutic response. One of the most important characteristics of a given biomarker includes ease of collection allowing for a non-invasive approach and frequent sampling. Such samples may be obtained from serum or plasma, sputum, bronchoalveolar lavage, saliva, nipple discharge, pleural, or peritoneal effusions. Validation of different biomarkers is considered a mandatory method for useful evaluation. In this review, we highlight the clinical applicability of some cancer biomarkers, as well as future approaches for their development and collection, which may help guide clinicians and researchers. The role of liquid biopsies will also be summarized. Further studies using liquid biopsies are needed to elucidate the significance of various sources of biomarkers suitable for clinical application.

  18. Biomarkers for AAA: Encouraging steps but clinical relevance still to be delivered.

    Science.gov (United States)

    Htun, Nay Min; Peter, Karlheinz

    2014-10-01

    Potential biomarkers have been investigated using proteomic studies in a variety of diseases. Some biomarkers have central roles in both diagnosis and monitoring of various disorders in clinical medicine, such as troponins, brain natriuretic peptide, and C-reactive protein. Although several biomarkers have been suggested in human abdominal aortic aneurysm (AAA), reliable markers have been lacking. In this issue, Moxon et al. [Proteomics Clin Appl. 2014, 8, 762-772] undertook a broad and systematic proteomic approach toward identification of biomarkers in a commonly used AAA mouse model (AAA created by angiotensin-II infusion). In this mouse model, apolipoprotein C1 and matrix metalloproteinase-9 were identified as novel biomarkers of stable AAA. This finding represents an important step forward, toward a clinically relevant role of biomarkers in AAA. This also encourages for further studies toward the identification of biomarkers (or their combinations) that can predict AAA progression and rupture, which would represent a major progress in AAA management and would establish an AAA biomarker as a much anticipated clinical tool. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Biomarkers in the clinical development of asthma therapies.

    Science.gov (United States)

    Staton, Tracy L; Choy, David F; Arron, Joseph R

    2016-01-01

    Here we review how biomarkers have been used in the design, execution and interpretation of recent clinical studies of therapeutic candidates targeting cytokine-mediated inflammatory pathways in asthma. This review focuses on type 2 inflammation, as there are multiple therapeutics and/or clinical studies that can be compared within that specific pathway. Comparative analyses of data from these clinical studies illustrate the utility of biomarkers to quantify pharmacodynamic effects, clarify mechanism of action and stratify patients, which may facilitate the interpretation of outcomes in the development of molecularly targeted therapies. These case examples provide a basis for biomarker considerations in the design of future studies in the asthma setting.

  20. Perceived age as a biomarker of ageing: a clinical methodology

    DEFF Research Database (Denmark)

    Gunn, David A; Murray, Peter G; Tomlin, Cyrena C

    2008-01-01

    In a previous field-based study, how old one looks for one's age (perceived age) was found to be predictive of mortality in elderly individuals. In conjunction, perceived age is of relevance and interest to the layperson. Here, a clinical methodology for generating perceived age as a biomarker...... of facial ageing is detailed. The methodology utilises facial photographs of subjects to present images to large numbers of age assessors who are primarily nationals of the country of study origin. In five observational studies in five different countries involving 874 female subjects it was found...... that subject age and assessor gender, nationality, age and ageing expertise had little effect on the perceived age data generated. However, increasing the numbers of age assessors up to 50 substantially increased the reproducibility of the mean perceived age for an image and a minimum of 10 assessors were...

  1. Prognostic and predictive biomarkers in colorectal cancer. Towards precision medicine

    NARCIS (Netherlands)

    Reimers, Marlies Suzanne

    2015-01-01

    The aim of this thesis was to define prognostic and predictive biomarkers in colorectal cancer for improved risk stratification and treatment benefit in the individual patient, with the introduction of precision medicine in the near future as the ultimate goal. By definition, precision medicine is

  2. Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

    Science.gov (United States)

    Iasonos, Alexia; Chapman, Paul B; Satagopan, Jaya M

    2016-05-01

    An increased interest has been expressed in finding predictive biomarkers that can guide treatment options for both mutation carriers and noncarriers. The statistical assessment of variation in treatment benefit (TB) according to the biomarker carrier status plays an important role in evaluating predictive biomarkers. For time-to-event endpoints, the hazard ratio (HR) for interaction between treatment and a biomarker from a proportional hazards regression model is commonly used as a measure of variation in TB. Although this can be easily obtained using available statistical software packages, the interpretation of HR is not straightforward. In this article, we propose different summary measures of variation in TB on the scale of survival probabilities for evaluating a predictive biomarker. The proposed summary measures can be easily interpreted as quantifying differential in TB in terms of relative risk or excess absolute risk due to treatment in carriers versus noncarriers. We illustrate the use and interpretation of the proposed measures with data from completed clinical trials. We encourage clinical practitioners to interpret variation in TB in terms of measures based on survival probabilities, particularly in terms of excess absolute risk, as opposed to HR. Clin Cancer Res; 22(9); 2114-20. ©2016 AACR. ©2016 American Association for Cancer Research.

  3. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    DEFF Research Database (Denmark)

    Mayer, Gert; Heerspink, Hiddo J L; Aschauer, Constantin

    2017-01-01

    hormone 1, hepatocyte growth factor, matrix metalloproteinase (MMP) 2, MMP7, MMP8, MMP13, tyrosine kinase, and tumor necrosis factor receptor-1. These biomarkers were measured in baseline serum samples from 1,765 patients recruited into two large clinical trials. eGFR decline was predicted based...... on molecular markers, clinical risk factors (including baseline eGFR and albuminuria), and both combined, and these predictions were evaluated using mixed linear regression models for longitudinal data. RESULTS: The variability of annual eGFR loss explained by the biomarkers, indicated by the adjusted R2 value......, combined with clinical variables, enhances the prediction of renal function loss over a wide range of baseline eGFR values in patients with type 2 diabetes and CKD....

  4. Prediction of preeclampsia with angiogenic biomarkers

    DEFF Research Database (Denmark)

    Andersen, Louise Bjørkholt; Dechend, Ralf; Jørgensen, Jan Stener

    2016-01-01

    OBJECTIVE: We aimed to investigate how maternal serum soluble Fms-like kinase 1 (sFlt-1), placental growth factor (PlGF), and sFlt-1/PlGF ratio prospectively associate to preeclampsia (PE) and clinical subtypes. METHODS: In an unselected cohort of 1909 pregnant women, sFlt-1 and PlGF were measured...

  5. BRAIN NATRIURETIC PEPTIDE (BNP: BIOMARKER FOR RISK STRATIFICATION AND FUNCTIONAL RECOVERY PREDICTION IN ISCHEMIC STROKE

    Directory of Open Access Journals (Sweden)

    STANESCU Ioana

    2015-02-01

    Full Text Available Functional outcome after cardiovascular and cerebrovascular events is traditionally predicted using demographic and clinical variables like age, gender, blood pressure, cholesterol levels, diabetes status, smoking habits or pre-existing morbidity. Identification of new variables will improve the risk stratification of specific categories of patients. Numerous blood-based biomarkers associated with increased cardiovascular risk have been identified; some of them even predict cardiovascular events. Investigators have tried to produce prediction models by incorporating traditional risk factors and biomarkers. (1. Widely-available, rapidly processed and less expensive biomarkers could be used in the future to guide management of complex cerebrovascular patients in order to maximize their recovery (2 Recently, studies have demonstrated that biomarkers can predict not only the risk for a specific clinical event, but also the risk of death of vascular cause and the functional outcome after cardiovascular or cerebrovascular events. Early prediction of fatal outcome after stroke may improve therapeutic strategies (such as the use of more aggressive treatments or inclusion of patients in clinical trials and guide decision-making processes in order to maximize patient’s chances for survival and recovery. (3 Long term functional outcome after stroke is one of the most difficult variables to predict. Elevated serum levels of brain natriuretic peptide (BNP are powerful predictor of outcomes in patients with cardiovascular disease (heart failure, atrial fibrillation. Potential role of BNP in predicting atrial fibrillation occurrence, cardio-embolic stroke and post-stroke mortality have been proved in many studies. However, data concerning the potential role of BNP in predicting short term and long term functional outcomes after stroke remain controversial.

  6. MTR-18 Predictive Biomarkers Of Bevacizumab Response In Recurrent Glioblastoma Patients

    DEFF Research Database (Denmark)

    Urup, Thomas; Michaelsen, Signe Regner; Olsen, Lars Rønn

    2015-01-01

    Bevacizumab (BEV) plus chemotherapy has shown activity in recurrent glioblastoma (GBM). However, the prognosis varies and only one third of patients have a durable clinical response to BEV combination therapy. Recent findings from a randomized phase-3 study (AVAglio) indicate that patients...... with the proneural GBM subtype have a survival benefit when treated with BEV in combination with standard treatment. However, no validated biomarkers able to predict BEV response have been identified and the biology reflecting a clinical BEV response is poorly understood. The primary objective of this study...... was to evaluate the predictive and prognostic value of GBM subtypes in recurrent GBM patients treated with BEV therapy. The secondary objective was to identify biomarkers able to predict response to BEV therapy in recurrent GBM patients. METHODS: A total of 90 recurrent GBM patients treated with BEV combination...

  7. Time-dependent efficacy of longitudinal biomarker for clinical endpoint.

    Science.gov (United States)

    Kolamunnage-Dona, Ruwanthi; Williamson, Paula R

    2018-06-01

    Joint modelling of longitudinal biomarker and event-time processes has gained its popularity in recent years as they yield more accurate and precise estimates. Considering this modelling framework, a new methodology for evaluating the time-dependent efficacy of a longitudinal biomarker for clinical endpoint is proposed in this article. In particular, the proposed model assesses how well longitudinally repeated measurements of a biomarker over various time periods (0,t) distinguish between individuals who developed the disease by time t and individuals who remain disease-free beyond time t. The receiver operating characteristic curve is used to provide the corresponding efficacy summaries at various t based on the association between longitudinal biomarker trajectory and risk of clinical endpoint prior to each time point. The model also allows detecting the time period over which a biomarker should be monitored for its best discriminatory value. The proposed approach is evaluated through simulation and illustrated on the motivating dataset from a prospective observational study of biomarkers to diagnose the onset of sepsis.

  8. New and emerging prognostic and predictive genetic biomarkers in B-cell precursor acute lymphoblastic leukemia

    Science.gov (United States)

    Moorman, Anthony V.

    2016-01-01

    Acute lymphoblastic leukemia (ALL) is a heterogeneous disease at the genetic level. Chromosomal abnormalities are used as diagnostic, prognostic and predictive biomarkers to provide subtype, outcome and drug response information. t(12;21)/ETV6-RUNX1 and high hyper-diploidy are good-risk prognostic biomarkers whereas KMT2A (MLL) translocations, t(17;19)/TCF3-HLF, haploidy or low hypodiploidy are high-risk biomarkers. t(9;22)/BCR-ABL1 patients require targeted treatment (imatinib/dasatinib), whereas iAMP21 patients achieve better outcomes when treated intensively. High-risk genetic biomarkers are four times more prevalent in adults compared to children. The application of genomic technologies to cases without an established abnormality (B-other) reveals copy number alterations which can be used either individually or in combination as prognostic biomarkers. Transcriptome sequencing studies have identified a network of fusion genes involving kinase genes - ABL1, ABL2, PDGFRB, CSF1R, CRLF2, JAK2 and EPOR. In vitro and in vivo studies along with emerging clinical observations indicate that patients with a kinase-activating aberration may respond to treatment with small molecular inhibitors like imatinib/dasatinib and ruxolitinib. Further work is required to determine the true frequency of these abnormalities across the age spectrum and the optimal way to incorporate such inhibitors into protocols. In conclusion, genetic biomarkers are playing an increasingly important role in the management of patients with ALL. PMID:27033238

  9. Using gene co-expression network analysis to predict biomarkers for chronic lymphocytic leukemia

    Directory of Open Access Journals (Sweden)

    Borlawsky Tara B

    2010-10-01

    Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Immunoglobin heavy chain variable region (IgVH mutational status was found to be associated with patient survival outcome, and biomarkers linked to the IgVH status has been a focus in the CLL prognosis research field. However, biomarkers highly correlated with IgVH mutational status which can accurately predict the survival outcome are yet to be discovered. Results In this paper, we investigate the use of gene co-expression network analysis to identify potential biomarkers for CLL. Specifically we focused on the co-expression network involving ZAP70, a well characterized biomarker for CLL. We selected 23 microarray datasets corresponding to multiple types of cancer from the Gene Expression Omnibus (GEO and used the frequent network mining algorithm CODENSE to identify highly connected gene co-expression networks spanning the entire genome, then evaluated the genes in the co-expression network in which ZAP70 is involved. We then applied a set of feature selection methods to further select genes which are capable of predicting IgVH mutation status from the ZAP70 co-expression network. Conclusions We have identified a set of genes that are potential CLL prognostic biomarkers IL2RB, CD8A, CD247, LAG3 and KLRK1, which can predict CLL patient IgVH mutational status with high accuracies. Their prognostic capabilities were cross-validated by applying these biomarker candidates to classify patients into different outcome groups using a CLL microarray datasets with clinical information.

  10. MAGIC biomarkers predict long term outcomes for steroid-resistant acute GVHD.

    Science.gov (United States)

    Major-Monfried, Hannah; Renteria, Anne S; Pawarode, Attaphol; Reddy, Pavan; Ayuk, Francis; Holler, Ernst; Efebera, Yvonne A; Hogan, William J; Wölfl, Matthias; Qayed, Muna; Hexner, Elizabeth O; Wudhikarn, Kitsada; Ordemann, Rainer; Young, Rachel; Shah, Jay; Hartwell, Matthew J; Chaudhry, Mohammed; Aziz, Mina; Etra, Aaron; Yanik, Gregory A; Kröger, Nicolaus; Weber, Daniela; Chen, Yi-Bin; Nakamura, Ryotaro; Rösler, Wolf; Kitko, Carrie L; Harris, Andrew C; Pulsipher, Michael; Reshef, Ran; Kowalyk, Steven; Morales, George; Torres, Ivan; Özbek, Umut; Ferrara, James L M; Levine, John E

    2018-03-15

    Acute graft versus host disease (GVHD) is treated with systemic corticosteroid immunosuppression. Clinical response after one week of therapy often guides further treatment decisions, but long term outcomes vary widely between centers and more accurate predictive tests are urgently needed. We analyzed clinical data and blood samples taken after one week of systemic treatment for GVHD from 507 patients from 17 centers of the Mount Sinai Acute GVHD International Consortium (MAGIC), dividing them into test (n=236) and two validation cohorts separated in time (n = 142 and 129, respectively). Initial response to systemic steroids correlated with response at four weeks, one-year non-relapse mortality (NRM) and overall survival (OS). A previously validated algorithm of two MAGIC biomarkers (ST2 and REG3α) consistently separated steroid resistant patients into two groups with dramatically different NRM and OS (p<0.001 for all three cohorts). High biomarker probability, resistance to steroids and GVHD severity (Minnesota risk) were all significant predictors of NRM in multivariate analysis. A direct comparison of receiver operating curves showed the area under the curve for biomarker probability (0.82) was significantly greater than that for steroid response (0.68, p=0.004) and for Minnesota risk (0.72, p=0.005). In conclusion, MAGIC biomarker probabilities generated after one week of systemic treatment for GVHD predict long term outcomes in steroid resistant GVHD better than clinical criteria and should prove useful in developing better treatment strategies. Copyright © 2018 American Society of Hematology.

  11. Clinical Relevance of Biomarkers of Oxidative Stress

    DEFF Research Database (Denmark)

    Frijhoff, Jeroen; Winyard, Paul G; Zarkovic, Neven

    2015-01-01

    SIGNIFICANCE: Oxidative stress is considered to be an important component of various diseases. A vast number of methods have been developed and used in virtually all diseases to measure the extent and nature of oxidative stress, ranging from oxidation of DNA to proteins, lipids, and free amino ac....... The vast diversity in oxidative stress between diseases and conditions has to be taken into account when selecting the most appropriate biomarker.......SIGNIFICANCE: Oxidative stress is considered to be an important component of various diseases. A vast number of methods have been developed and used in virtually all diseases to measure the extent and nature of oxidative stress, ranging from oxidation of DNA to proteins, lipids, and free amino...... acids. RECENT ADVANCES: An increased understanding of the biology behind diseases and redox biology has led to more specific and sensitive tools to measure oxidative stress markers, which are very diverse and sometimes very low in abundance. CRITICAL ISSUES: The literature is very heterogeneous...

  12. OARSI Clinical Trials Recommendations: Soluble biomarker assessments in clinical trials in osteoarthritis.

    Science.gov (United States)

    Kraus, V B; Blanco, F J; Englund, M; Henrotin, Y; Lohmander, L S; Losina, E; Önnerfjord, P; Persiani, S

    2015-05-01

    The objective of this work was to describe requirements for inclusion of soluble biomarkers in osteoarthritis (OA) clinical trials and progress toward OA-related biomarker qualification. The Guidelines for Biomarkers Working Group, representing experts in the field of OA biomarker research from both academia and industry, convened to discuss issues related to soluble biomarkers and to make recommendations for their use in OA clinical trials based on current knowledge and anticipated benefits. This document summarizes current guidance on use of biomarkers in OA clinical trials and their utility at five stages, including preclinical development and phase I to phase IV trials. As demonstrated by this summary, biomarkers can provide value at all stages of therapeutics development. When resources permit, we recommend collection of biospecimens in all OA clinical trials for a wide variety of reasons but in particular, to determine whether biomarkers are useful in identifying those individuals most likely to receive clinically important benefits from an intervention; and to determine whether biomarkers are useful for identifying individuals at earlier stages of OA in order to institute treatment at a time more amenable to disease modification. Copyright © 2015 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

  13. Biomarkers in differentiating clinical dengue cases: A prospective cohort study

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    Gary Kim Kuan Low

    2015-12-01

    Full Text Available Objective: To evaluate five biomarkers (neopterin, vascular endothelial growth factor-A, thrombomodulin, soluble vascular cell adhesion molecule 1 and pentraxin 3 in differentiating clinical dengue cases. Methods: A prospective cohort study was conducted whereby the blood samples were obtained at day of presentation and the final diagnosis were obtained at the end of patients’ follow-up. All patients included in the study were 15 years old or older, not pregnant, not infected by dengue previously and did not have cancer, autoimmune or haematological disorder. Median test was performed to compare the biomarker levels. A subgroup Mann-Whitney U test was analysed between severe dengue and non-severe dengue cases. Monte Carlo method was used to estimate the 2-tailed probability (P value for independent variables with unequal number of patients. Results: All biomarkers except thrombomodulin has P value < 0.001 in differentiating among the healthy subjects, non-dengue fever, dengue without warning signs and dengue with warning signs/severe dengue. Subgroup analysis for all the biomarkers between severe dengue and non-severe dengue cases was not statistically significant except vascular endothelial growth factor-A (P < 0.05. Conclusions: Certain biomarkers were able to differentiate the clinical dengue cases. This could be potentially useful in classifying and determining the severity of dengue infected patients in the hospital.

  14. Elevation in inflammatory serum biomarkers predicts response to trastuzumab-containing therapy.

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    Ahmed A Alkhateeb

    Full Text Available Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml or CRP (>7.25 mg/l was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.

  15. Clinical utility of asthma biomarkers: from bench to bedside

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    Vijverberg SJH

    2013-08-01

    Full Text Available Susanne JH Vijverberg,1,2,* Bart Hilvering,2,* Jan AM Raaijmakers,1 Jan-Willem J Lammers,2 Anke-Hilse Maitland-van der Zee,1,* Leo Koenderman2,* 1Division of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Faculty of Science, Utrecht University, Utrecht, The Netherlands; 2Department of Respiratory Medicine, University Medical Centre Utrecht, Utrecht, The Netherlands *These authors contributed equally to this work Abstract: Asthma is a chronic disease characterized by airway inflammation, bronchial hyperresponsiveness, and recurrent episodes of reversible airway obstruction. The disease is very heterogeneous in onset, course, and response to treatment, and seems to encompass a broad collection of heterogeneous disease subtypes with different underlying pathophysiological mechanisms. There is a strong need for easily interpreted clinical biomarkers to assess the nature and severity of the disease. Currently available biomarkers for clinical practice – for example markers in bronchial lavage, bronchial biopsies, sputum, or fraction of exhaled nitric oxide (FeNO – are limited due to invasiveness or lack of specificity. The assessment of markers in peripheral blood might be a good alternative to study airway inflammation more specifically, compared to FeNO, and in a less invasive manner, compared to bronchoalveolar lavage, biopsies, or sputum induction. In addition, promising novel biomarkers are discovered in the field of breath metabolomics (eg, volatile organic compounds and (pharmacogenomics. Biomarker research in asthma is increasingly shifting from the assessment of the value of single biomarkers to multidimensional approaches in which the clinical value of a combination of various markers is studied. This could eventually lead to the development of a clinically applicable algorithm composed of various markers and clinical features to phenotype asthma and improve diagnosis and asthma management

  16. Clinical Risk Assessment in the Antiphospholipid Syndrome: Current Landscape and Emerging Biomarkers.

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    Chaturvedi, Shruti; McCrae, Keith R

    2017-07-01

    Laboratory criteria for the classification of antiphospholipid syndrome include the detection of a lupus anticoagulant and/or anticardiolipin and anti-β2-glycoprotein I antibodies. However, the majority of patients who test positive in these assays do not have thrombosis. Current risk-stratification tools are largely limited to the antiphospholipid antibody profile and traditional thrombotic risk factors. Novel biomarkers that correlate with disease activity and potentially provide insight into future clinical events include domain 1 specific anti-β 2 GPI antibodies, antibodies to other phospholipids or phospholipid/protein antigens (such as anti-PS/PT), and functional/biological assays such as thrombin generation, complement activation, levels of circulating microparticles, and annexin A5 resistance. Clinical risk scores may also have value in predicting clinical events. Biomarkers that predict thrombosis risk in patients with antiphospholipid antibodies have been long sought, and several biomarkers have been proposed. Ultimately, integration of biomarkers with established assays and clinical characteristics may offer the best chance of identifying patients at highest risk of APS-related complications.

  17. Association between biomarkers and clinical characteristics in chronic subdural hematoma patients assessed with lasso regression.

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    Are Hugo Pripp

    Full Text Available Chronic subdural hematoma (CSDH is characterized by an "old" encapsulated collection of blood and blood breakdown products between the brain and its outermost covering (the dura. Recognized risk factors for development of CSDH are head injury, old age and using anticoagulation medication, but its underlying pathophysiological processes are still unclear. It is assumed that a complex local process of interrelated mechanisms including inflammation, neomembrane formation, angiogenesis and fibrinolysis could be related to its development and propagation. However, the association between the biomarkers of inflammation and angiogenesis, and the clinical and radiological characteristics of CSDH patients, need further investigation. The high number of biomarkers compared to the number of observations, the correlation between biomarkers, missing data and skewed distributions may limit the usefulness of classical statistical methods. We therefore explored lasso regression to assess the association between 30 biomarkers of inflammation and angiogenesis at the site of lesions, and selected clinical and radiological characteristics in a cohort of 93 patients. Lasso regression performs both variable selection and regularization to improve the predictive accuracy and interpretability of the statistical model. The results from the lasso regression showed analysis exhibited lack of robust statistical association between the biomarkers in hematoma fluid with age, gender, brain infarct, neurological deficiencies and volume of hematoma. However, there were associations between several of the biomarkers with postoperative recurrence requiring reoperation. The statistical analysis with lasso regression supported previous findings that the immunological characteristics of CSDH are local. The relationship between biomarkers, the radiological appearance of lesions and recurrence requiring reoperation have been inclusive using classical statistical methods on these data

  18. Molecular Biomarkers in the Clinical Management of Prostate Cancer.

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    Udager, Aaron M; Tomlins, Scott A

    2018-01-08

    Prostate cancer, one of the most common noncutaneous malignancies in men, is a heterogeneous disease with variable clinical outcome. Although the majority of patients harbor indolent tumors that are essentially cured by local therapy, subsets of patients present with aggressive disease or recur/progress after primary treatment. With this in mind, modern clinical approaches to prostate cancer emphasize the need to reduce overdiagnosis and overtreatment via personalized medicine. Advances in our understanding of prostate cancer pathogenesis, coupled with recent technologic innovations, have facilitated the development and validation of numerous molecular biomarkers, representing a range of macromolecules assayed from a variety of patient sample types, to help guide the clinical management of prostate cancer, including early detection, diagnosis, prognostication, and targeted therapeutic selection. Herein, we review the current state of the art regarding prostate cancer molecular biomarkers, emphasizing those with demonstrated utility in clinical practice. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

  19. Prominent deep medullary veins: a predictive biomarker for stroke risk from transient ischemic attack?

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    Duan, Yang; Xu, Zhihua; Li, Hongyi; Cai, Xiaonan; Chang, Cancan; Yang, Benqiang

    2018-05-01

    Background Deep medullary veins (DMVs) are a biomarker of severity and prognosis in patients with acute cerebral infarction. However, their clinical significance remains unclear in patients with transient ischemic attack (TIA). Purpose To determine whether prominent deep medullary veins (PDMVs) are a predictive biomarker for stroke risk after TIA. Material and Methods Clinical and imaging data of 49 patients with TIA and 49 sex- and age-matched controls were studied. PDMVs were defined as DMVs with a score of 3 (TDMVs) or asymmetric DMVs (ADMVs), and the relationship between PDMVs and clinical features was analyzed. The DMV score based on susceptibility weighted imaging (SWI) ranged from 0 (not visible) to 3 (very prominent) and was calculated for both hemispheres separately. A different score in each hemisphere was defined as ADMVs and an equal score was defined as symmetric DMVs. The asymmetry and score of DMVs were compared between the two groups and with respect to the time from TIA onset to imaging analysis. Results Agreement between neuroradiologists for the DMV asymmetry/score on SWI was excellent. The frequency of ADMVs and TDMVs was significantly higher in patients with TIA than controls ( P  0.05); PDMVs were not correlated with age, blood pressure, or diabetes. However, PDMVs were associated with the ABCD2 score (≥4), clinical symptoms, and duration of TIA (≥10 min). Conclusion Prominent deep medullary veins is a predictive biomarker for the risk of stroke in many patients having suffered from TIA.

  20. Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder.

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    Gottschalk, M G; Cooper, J D; Chan, M K; Bot, M; Penninx, B W J H; Bahn, S

    2015-08-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention. Copyright © 2015 Elsevier Inc. All rights reserved.

  1. Variability of CSF Alzheimer's disease biomarkers: implications for clinical practice.

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    Stephanie J B Vos

    Full Text Available BACKGROUND: Cerebrospinal fluid (CSF biomarkers are increasingly being used for diagnosis of Alzheimer's disease (AD. OBJECTIVE: We investigated the influence of CSF intralaboratory and interlaboratory variability on diagnostic CSF-based AD classification of subjects and identified causes of this variation. METHODS: We measured CSF amyloid-β (Aβ 1-42, total tau (t-tau, and phosphorylated tau (p-tau by INNOTEST enzyme-linked-immunosorbent assays (ELISA in a memory clinic population (n = 126. Samples were measured twice in a single or two laboratories that served as reference labs for CSF analyses in the Netherlands. Predefined cut-offs were used to classify CSF biomarkers as normal or abnormal/AD pattern. RESULTS: CSF intralaboratory variability was higher for Aβ1-42 than for t-tau and p-tau. Reanalysis led to a change in biomarker classification (normal vs. abnormal of 26% of the subjects based on Aβ1-42, 10% based on t-tau, and 29% based on p-tau. The changes in absolute biomarker concentrations were paralleled by a similar change in levels of internal control samples between different assay lots. CSF interlaboratory variability was higher for p-tau than for Aβ1-42 and t-tau, and reanalysis led to a change in biomarker classification of 12% of the subjects based on Aβ1-42, 1% based on t-tau, and 22% based on p-tau. CONCLUSIONS: Intralaboratory and interlaboratory CSF variability frequently led to change in diagnostic CSF-based AD classification for Aβ1-42 and p-tau. Lot-to-lot variation was a major cause of intralaboratory variability. This will have implications for the use of these biomarkers in clinical practice.

  2. Personalized Cancer Medicine: Molecular Diagnostics, Predictive biomarkers, and Drug Resistance

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    Gonzalez de Castro, D; Clarke, P A; Al-Lazikani, B; Workman, P

    2013-01-01

    The progressive elucidation of the molecular pathogenesis of cancer has fueled the rational development of targeted drugs for patient populations stratified by genetic characteristics. Here we discuss general challenges relating to molecular diagnostics and describe predictive biomarkers for personalized cancer medicine. We also highlight resistance mechanisms for epidermal growth factor receptor (EGFR) kinase inhibitors in lung cancer. We envisage a future requiring the use of longitudinal genome sequencing and other omics technologies alongside combinatorial treatment to overcome cellular and molecular heterogeneity and prevent resistance caused by clonal evolution. PMID:23361103

  3. Biomarkers for predicting type 2 diabetes development-Can metabolomics improve on existing biomarkers?

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    Otto Savolainen

    Full Text Available The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D risk that would improve prediction of T2D over current risk markers.Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based on a screening sample of 64-year-old Caucasian women (n = 629. Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years follow-up. The metabolomics results were used as a standalone prediction model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D.Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin resistance (HOMA, smoking, serum adiponectin alone, and in combination with metabolomics had the largest areas under the curve (AUC (0.794 (95% confidence interval [0.738-0.850] and 0.808 [0.749-0.867] respectively, with the standalone metabolomics model based on nine fasting plasma markers having a lower predictive power (0.657 [0.577-0.736]. Prediction based on non-blood based measures was 0.638 [0.565-0.711].Established measures of T2D risk remain the best predictor of T2D risk in this population. Additional markers detected using metabolomics are likely related to these measures as they did not enhance the overall prediction in a combined model.

  4. Circulating predictive and diagnostic biomarkers for hepatitis B virus-associated hepatocellular carcinoma

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    Van Hees, Stijn; Michielsen, Peter; Vanwolleghem, Thomas

    2016-01-01

    Chronic hepatitis B virus (HBV) infected patients have an almost 100-fold increased risk to develop hepatocellular carcinoma (HCC). HCC is the fifth most common and third most deadly cancer worldwide. Up to 50% of newly diagnosed HCC cases are attributed to HBV infection. Early detection improves survival and can be achieved through regular screening. Six-monthly abdominal ultrasound, either alone or in combination with alpha-fetoprotein serum levels, has been widely endorsed for this purpose. Both techniques however yield limited diagnostic accuracy, which is not improved when they are combined. Alternative circulating or histological markers to predict or diagnose HCC are therefore urgently needed. Recent advances in systems biology technologies have enabled the identification of several new putative circulating biomarkers. Although results from studies assessing combinations of these biomarkers are promising, evidence for their clinical utility remains low. In addition, most of the studies conducted so far show limitations in design. Attention must be paid for instance to different ethnicities and different etiologies when studying biomarkers for hepatocellular carcinoma. This review provides an overview on the current understandings and recent progress in the field of diagnostic and predictive circulating biomarkers for hepatocellular carcinoma in chronically infected HBV patients and discusses the future prospects. PMID:27729734

  5. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

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    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  6. Robust prediction of anti-cancer drug sensitivity and sensitivity-specific biomarker.

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    Heewon Park

    Full Text Available The personal genomics era has attracted a large amount of attention for anti-cancer therapy by patient-specific analysis. Patient-specific analysis enables discovery of individual genomic characteristics for each patient, and thus we can effectively predict individual genetic risk of disease and perform personalized anti-cancer therapy. Although the existing methods for patient-specific analysis have successfully uncovered crucial biomarkers, their performance takes a sudden turn for the worst in the presence of outliers, since the methods are based on non-robust manners. In practice, clinical and genomic alterations datasets usually contain outliers from various sources (e.g., experiment error, coding error, etc. and the outliers may significantly affect the result of patient-specific analysis. We propose a robust methodology for patient-specific analysis in line with the NetwrokProfiler. In the proposed method, outliers in high dimensional gene expression levels and drug response datasets are simultaneously controlled by robust Mahalanobis distance in robust principal component space. Thus, we can effectively perform for predicting anti-cancer drug sensitivity and identifying sensitivity-specific biomarkers for individual patients. We observe through Monte Carlo simulations that the proposed robust method produces outstanding performances for predicting response variable in the presence of outliers. We also apply the proposed methodology to the Sanger dataset in order to uncover cancer biomarkers and predict anti-cancer drug sensitivity, and show the effectiveness of our method.

  7. Inflammatory and Other Biomarkers: Role in Pathophysiology and Prediction of Gestational Diabetes Mellitus

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    Abell, Sally K.; De Courten, Barbora; Boyle, Jacqueline A.; Teede, Helena J.

    2015-01-01

    Understanding pathophysiology and identifying mothers at risk of major pregnancy complications is vital to effective prevention and optimal management. However, in current antenatal care, understanding of pathophysiology of complications is limited. In gestational diabetes mellitus (GDM), risk prediction is mostly based on maternal history and clinical risk factors and may not optimally identify high risk pregnancies. Hence, universal screening is widely recommended. Here, we will explore the literature on GDM and biomarkers including inflammatory markers, adipokines, endothelial function and lipids to advance understanding of pathophysiology and explore risk prediction, with a goal to guide prevention and treatment of GDM. PMID:26110385

  8. Prospective evaluation of biomarkers for prediction of quality of life in community-acquired pneumonia.

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    Nickler, Manuela; Schaffner, Daniela; Christ-Crain, Mirjam; Ottiger, Manuel; Thomann, Robert; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

    2016-11-01

    Most clinical research investigated prognostic biomarkers for their ability to predict cardiovascular events or mortality. It is unknown whether biomarkers allow prediction of quality of life (QoL) after survival of the acute event. Herein, we investigated the prognostic potential of well-established inflammatory/cardiovascular blood biomarkers including white blood cells (WBC), C-reactive protein (CRP), procalcitonin (PCT), pro-adrenomedullin (proADM) and pro-atrial natriuretic peptide (proANP) in regard to a decline in QoL in a well-defined cohort of patients with community-acquired pneumonia (CAP). Within this secondary analysis including 753 patients with a final inpatient diagnosis of CAP from a multicenter trial, we investigated associations between admission biomarker levels and decline in QoL assessed by the EQ-5D health questionnaire from admission to day 30 and after 6 years. Admission proADM and proANP levels significantly predicted decline of the weighted EQ-5D index after 30 days (n=753) with adjusted odds ratios (ORs) of 2.0 ([95% CI 1.1-3.8]; p=0.027) and 3.7 ([95% CI 2.2-6.0]; pscale (VAS). Initial WBC, PCT and CRP values did not well predict QoL at any time point. ProADM and proANP accurately predict short- and long-term decline in QoL across most dimensions in CAP patients. It will be interesting to reveal underlying physiopathology in future studies.

  9. Biomarker kinetics in the prediction of VAP diagnosis: results from the BioVAP study

    NARCIS (Netherlands)

    Póvoa, Pedro; Martin-Loeches, Ignacio; Ramirez, Paula; Bos, Lieuwe D.; Esperatti, Mariano; Silvestre, Joana; Gili, Gisela; Goma, Gema; Berlanga, Eugenio; Espasa, Mateu; Gonçalves, Elsa; Torres, Antoni; Artigas, Antonio

    2016-01-01

    Prediction of diagnosis of ventilator-associated pneumonia (VAP) remains difficult. Our aim was to assess the value of biomarker kinetics in VAP prediction. We performed a prospective, multicenter, observational study to evaluate predictive accuracy of biomarker kinetics, namely C-reactive protein

  10. Improving diagnosis, prognosis and prediction by using biomarkers in CRC patients (Review).

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    Nikolouzakis, Taxiarchis Konstantinos; Vassilopoulou, Loukia; Fragkiadaki, Persefoni; Mariolis Sapsakos, Theodoros; Papadakis, Georgios Z; Spandidos, Demetrios A; Tsatsakis, Aristides M; Tsiaoussis, John

    2018-06-01

    Colorectal cancer (CRC) is among the most common cancers. In fact, it is placed in the third place among the most diagnosed cancer in men, after lung and prostate cancer, and in the second one for the most diagnosed cancer in women, following breast cancer. Moreover, its high mortality rates classifies it among the leading causes of cancer‑related death worldwide. Thus, in order to help clinicians to optimize their practice, it is crucial to introduce more effective tools that will improve not only early diagnosis, but also prediction of the most likely progression of the disease and response to chemotherapy. In that way, they will be able to decrease both morbidity and mortality of their patients. In accordance with that, colon cancer research has described numerous biomarkers for diagnostic, prognostic and predictive purposes that either alone or as part of a panel would help improve patient's clinical management. This review aims to describe the most accepted biomarkers among those proposed for use in CRC divided based on the clinical specimen that is examined (tissue, faeces or blood) along with their restrictions. Lastly, new insight in CRC monitoring will be discussed presenting promising emerging biomarkers (telomerase activity, telomere length and micronuclei frequency).

  11. Utility of Urinary Biomarkers in Predicting Loss of Residual Renal Function: The balANZ Trial

    Science.gov (United States)

    Cho, Yeoungjee; Johnson, David W.; Vesey, David A.; Hawley, Carmel M.; Clarke, Margaret; Topley, Nicholas

    2015-01-01

    ♦ Background: The ability of urinary biomarkers to predict residual renal function (RRF) decline in peritoneal dialysis (PD) patients has not been defined. The present study aimed to explore the utility of established biomarkers from kidney injury models for predicting loss of RRF in incident PD patients, and to evaluate the impact on RRF of using neutral-pH PD solution low in glucose degradation products. ♦ Methods: The study included 50 randomly selected participants from the balANZ trial who had completed 24 months of follow-up. A change in glomerular filtration rate (GFR) was used as the primary clinical outcome measure. In a mixed-effects general linear model, baseline measurements of 18 novel urinary biomarkers and albumin were used to predict GFR change. The model was further used to evaluate the impact of biocompatible PD solution on RRF, adjusted for each biomarker. ♦ Results: Baseline albuminuria was not a useful predictor of change in RRF in PD patients (p = 0.84). Only clusterin was a significant predictor of GFR decline in the whole population (p = 0.04, adjusted for baseline GFR and albuminuria). However, the relationship was no longer apparent when albuminuria was removed from the model (p = 0.31). When the effect of the administered PD solutions was examined using a model adjusted for PD solution type, baseline albuminuria, and GFR, higher baseline urinary concentrations of trefoil factor 3 (TFF3, p = 0.02), kidney injury molecule 1 (KIM-1, p = 0.04), and interferon γ-induced protein 10 (IP-10, p = 0.03) were associated with more rapid decline of RRF in patients receiving conventional PD solution compared with biocompatible PD solution. ♦ Conclusions: Higher urinary levels of kidney injury biomarkers (TFF3, KIM-1, IP-10) at baseline predicted significantly slower RRF decline in patients receiving biocompatible PD solutions. Findings from the present investigation should help to guide future studies to validate the utility of urinary

  12. IGFBP3 methylation is a novel diagnostic and predictive biomarker in colorectal cancer.

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    Lucia Perez-Carbonell

    Full Text Available Aberrant hypermethylation of cancer-related genes has emerged as a promising strategy for the development of diagnostic, prognostic and predictive biomarkers in human cancer, including colorectal cancer (CRC. The aim of this study was to perform a systematic and comprehensive analysis of a panel of CRC-specific genes as potential diagnostic, prognostic and predictive biomarkers in a large, population-based CRC cohort.Methylation status of the SEPT9, TWIST1, IGFBP3, GAS7, ALX4 and miR137 genes was studied by quantitative bisulfite pyrosequencing in a population-based cohort of 425 CRC patients.Methylation levels of all genes analyzed were significantly higher in tumor tissues compared to normal mucosa (p<0.0001; however, cancer-associated hypermethylation was most frequently observed for miR137 (86.7% and IGFBP3 (83% in CRC patients. Methylation analysis using the combination of these two genes demonstrated greatest accuracy for the identification of colonic tumors (sensitivity 95.5%; specificity 90.5%. Low levels of IGFBP3 promoter methylation emerged as an independent risk factor for predicting poor disease free survival in stage II and III CRC patients (HR = 0.49, 95% CI: 0.28-0.85, p = 0.01. Our results also suggest that stage II & III CRC patients with high levels of IGFBP3 methylation do not benefit from adjuvant 5FU-based chemotherapy.By analyzing a large, population-based CRC cohort, we demonstrate the potential clinical significance of miR137 and IGFBP3 hypermethylation as promising diagnostic biomarkers in CRC. Our data also revealed that IGFBP3 hypermethylation may serve as an independent prognostic and predictive biomarker in stage II and III CRC patients.

  13. Improved prediction of breast cancer outcome by identifying heterogeneous biomarkers.

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    Choi, Jonghwan; Park, Sanghyun; Yoon, Youngmi; Ahn, Jaegyoon

    2017-11-15

    Identification of genes that can be used to predict prognosis in patients with cancer is important in that it can lead to improved therapy, and can also promote our understanding of tumor progression on the molecular level. One of the common but fundamental problems that render identification of prognostic genes and prediction of cancer outcomes difficult is the heterogeneity of patient samples. To reduce the effect of sample heterogeneity, we clustered data samples using K-means algorithm and applied modified PageRank to functional interaction (FI) networks weighted using gene expression values of samples in each cluster. Hub genes among resulting prioritized genes were selected as biomarkers to predict the prognosis of samples. This process outperformed traditional feature selection methods as well as several network-based prognostic gene selection methods when applied to Random Forest. We were able to find many cluster-specific prognostic genes for each dataset. Functional study showed that distinct biological processes were enriched in each cluster, which seems to reflect different aspect of tumor progression or oncogenesis among distinct patient groups. Taken together, these results provide support for the hypothesis that our approach can effectively identify heterogeneous prognostic genes, and these are complementary to each other, improving prediction accuracy. https://github.com/mathcom/CPR. jgahn@inu.ac.kr. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  14. Correlation between Circulating Fungal Biomarkers and Clinical Outcome in Invasive Aspergillosis.

    Directory of Open Access Journals (Sweden)

    Dionysios Neofytos

    Full Text Available Objective means are needed to predict and assess clinical response in patients treated for invasive aspergillosis (IA. We examined whether early changes in serum galactomannan (GM and/or β-D-glucan (BDG can predict clinical outcomes. Patients with proven or probable IA were prospectively enrolled, and serial GM and BDG levels and GM optical density indices (GMI were calculated twice weekly for 6 weeks following initiation of standard-of-care antifungal therapy. Changes in these biomarkers during the first 2 and 6 weeks of treatment were analyzed for associations with clinical response and survival at weeks 6 and 12. Among 47 patients with IA, 53.2% (25/47 and 65.9% (27/41 had clinical response by weeks 6 and 12, respectively. Changes in biomarkers during the first 2 weeks were associated with clinical response at 6 weeks (GMI, P = 0.03 and 12 weeks (GM+BDG composite, P = 0.05; GM, P = 0.04; GMI, P = 0.02. Changes in biomarkers during the first 6 weeks were also associated with clinical response at 6 weeks (GM, P = 0.05; GMI, P = 0.03 and 12 weeks (BDG+GM, P = 0.02; GM, P = 0.02; GMI, P = 0.01. Overall survival rates at 6 weeks and 12 weeks were 87.2% (41/47 and 79.1% (34/43, respectively. Decreasing biomarkers in the first 2 weeks were associated with survival at 6 weeks (BDG+GM, P = 0.03; BDG, P = 0.01; GM, P = 0.03 and at 12 weeks (BDG+GM, P = 0.01; BDG, P = 0.03; GM, P = 0.01; GMI, P = 0.007. Similar correlations occurred for biomarkers measured over 6 weeks. Patients with negative baseline GMI and/or persistently negative GMI during the first 2 weeks were more likely to have CR and survival. These results suggest that changes of biomarkers may be informative to predict and/or assess response to therapy and survival in patients treated for IA.

  15. Cardiovascular biomarkers in clinical studies of type 2 diabetes

    DEFF Research Database (Denmark)

    Baldassarre, M P A; Andersen, A; Consoli, A

    2018-01-01

    biomarkers and 3) novel biomarkers (oxidative stress and endothelial dysfunction biomarkers). Within each category we present the currently best validated biomarkers with special focus on the population of interest (type 2 diabetes). For each individual biomarker, the physiological role, the validation...

  16. Predicting Age Using Neuroimaging: Innovative Brain Ageing Biomarkers.

    Science.gov (United States)

    Cole, James H; Franke, Katja

    2017-12-01

    The brain changes as we age and these changes are associated with functional deterioration and neurodegenerative disease. It is vital that we better understand individual differences in the brain ageing process; hence, techniques for making individualised predictions of brain ageing have been developed. We present evidence supporting the use of neuroimaging-based 'brain age' as a biomarker of an individual's brain health. Increasingly, research is showing how brain disease or poor physical health negatively impacts brain age. Importantly, recent evidence shows that having an 'older'-appearing brain relates to advanced physiological and cognitive ageing and the risk of mortality. We discuss controversies surrounding brain age and highlight emerging trends such as the use of multimodality neuroimaging and the employment of 'deep learning' methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Clinical librarian support for rapid review of clinical utility of cancer molecular biomarkers.

    Science.gov (United States)

    Geng, Yimin; Fowler, Clara S; Fulton, Stephanie

    2015-01-01

    The clinical librarian used a restricted literature searching and quality-filtering approach to provide relevant clinical evidence for the use of cancer molecular biomarkers by institutional policy makers and clinicians in the rapid review process. The librarian-provided evidence was compared with the cited references in the institutional molecular biomarker algorithm. The overall incorporation rate of the librarian-provided references into the algorithm was above 80%. This study suggests the usefulness of clinical librarian expertise for clinical practice. The searching and filtering methods for high-level evidence can be adopted by information professionals who are involved in the rapid literature review.

  18. Predictive cytogenetic biomarkers for colorectal neoplasia in medium risk patients.

    Science.gov (United States)

    Ionescu, E M; Nicolaie, T; Ionescu, M A; Becheanu, G; Andrei, F; Diculescu, M; Ciocirlan, M

    2015-01-01

    DNA damage and chromosomal alterations in peripheral lymphocytes parallels DNA mutations in tumor tissues. The aim of our study was to predict the presence of neoplastic colorectal lesions by specific biomarkers in "medium risk" individuals (age 50 to 75, with no personal or family of any colorectal neoplasia). We designed a prospective cohort observational study including patients undergoing diagnostic or opportunistic screening colonoscopy. Specific biomarkers were analyzed for each patient in peripheral lymphocytes - presence of micronuclei (MN), nucleoplasmic bridges (NPB) and the Nuclear Division Index (NDI) by the cytokinesis-blocked micronucleus assay (CBMN). Of 98 patients included, 57 were "medium risk" individuals. MN frequency and NPB presence were not significantly different in patients with neoplastic lesions compared to controls. In "medium risk" individuals, mean NDI was significantly lower for patients with any neoplastic lesions (adenomas and adenocarcinomas, AUROC 0.668, p 00.5), for patients with advanced neoplasia (advanced adenoma and adenocarcinoma, AUROC 0.636 p 0.029) as well as for patients with adenocarcinoma (AUROC 0.650, p 0.048), for each comparison with the rest of the population. For a cut-off of 1.8, in "medium risk" individuals, an NDI inferior to that value may predict any neoplastic lesion with a sensitivity of 97.7%, an advanced neoplastic lesion with a sensitivity of 97% and adenocarcinoma with a sensitivity of 94.4%. NDI score may have a role as a colorectal cancer-screening test in "medium risk" individuals. DNA = deoxyribonucleic acid; CRC = colorectal cancer; EU = European Union; WHO = World Health Organization; FOBT = fecal occult blood test; CBMN = cytokinesis-blocked micronucleus assay; MN = micronuclei; NPB = nucleoplasmic bridges; NDI = Nuclear Division Index; FAP = familial adenomatous polyposis; HNPCC = hereditary non-polypoid colorectal cancer; IBD = inflammatory bowel diseases; ROC = receiver operating

  19. Biomarkers of atherosclerotic plaque vulnerability and their clinical significance

    Directory of Open Access Journals (Sweden)

    Ran LIU

    2016-09-01

    Full Text Available Inflammatory reaction plays a crucial role in the occurence and development of atherosclerosis. Both basic and clinical trials have provided evidence that the expression of inflammatory biomarkers are closely related with the degree of atherosclerosis. Treatment towards inflammatory factors would bring benefit to atherosclerotic patients. This review highlighted the mechanistic rationale and specific therapies targeting traditional and novel inflammatory biomarkers, including C-reactive protein (CRP, interleukin-17 (IL-17, secretory phospholipase A2 (sPLA2, lipoprotein-associated phospholipase A2 (Lp-PLA2, endoglin, chemokine receptor and 5-lipoxygenase (5-LO, so as to review its mechanism of action and treatment prospect. DOI: 10.3969/j.issn.1672-6731.2016.09.004

  20. Plasma sCD14 as a biomarker to predict pulmonary exacerbations in cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Bradley S Quon

    Full Text Available BACKGROUND: One in four cystic fibrosis (CF patients diagnosed with a pulmonary exacerbation will not recover their baseline lung function despite standard treatment. This highlights the importance of preventing such events. Clinical decision-making can be improved through a simple blood test that predicts individuals at elevated short-term risk of an exacerbation. METHODS: We obtained plasma samples from 30 stable CF patients from the St. Paul's Hospital Adult CF Clinic (Vancouver, Canada. For 15 patients, an additional plasma sample was obtained during an exacerbation. Soluble CD14 (sCD14 and C-reactive protein (CRP were quantified using ELISA kits. Myeloperoxidase (MPO, interleukin(IL-6, IL-1β, monocyte chemoattractant protein-1 (MCP-1, vascular endothelial growth factor (VEGF, and granulocyte colony-stimulating factor (G-CSF were quantified using Luminex™ immunoassays. Stable state biomarker levels were examined in their ability to predict individuals that would experience a pulmonary exacerbation requiring intravenous (IV antibiotics within 4 months. Paired stable and exacerbation plasma biomarker levels were also compared. RESULTS: sCD14 levels were significantly higher in patients that experienced a pulmonary exacerbation requiring IV antibiotics within 4 months (p = 0.001. sCD14 cut-off value of 1450 ng/mL was associated with an area under the curve of 0.91 (95% CI 0.83-0.99 for predicting an exacerbation within 4 months of a stable visit, with a sensitivity of 100% and specificity of 82%. Plasma sCD14 levels were significantly higher during exacerbations than during periods of clinical stability (p = 0.03. CONCLUSIONS: Plasma sCD14 is a promising biomarker for identifying CF patients who will exacerbate within 4 months of a stable visit but requires further study in larger, independent cohorts.

  1. Feasibility of Conducting Autism Biomarker Research in the Clinical Setting.

    Science.gov (United States)

    Sices, Laura; Pawlowski, Katherine; Farfel, Laura; Phillips, Deirdre; Howe, Yamini; Cochran, David M; Choueiri, Roula; Forbes, Peter W; Brewster, Stephanie J; Frazier, Jean A; Neumeyer, Ann; Bridgemohan, Carolyn

    2017-09-01

    Recruitment and completion of research activities during regular clinical care has the potential to increase research participation in complex neurodevelopmental disorders. We evaluated the feasibility, and effect on clinical care, of conducting biomarker research within a subspecialty clinical visit for autism spectrum disorder (ASD). Children, aged 5 to 10 years, were recruited by providers in ASD clinics at 5 institutions. Biomarkers collected were growth measurements, head circumference, neurologic and dysmorphology examinations, digit ratio (2D:4D) measurement, and platelet serotonin and urinary melatonin sulfate excretion levels. Parents completed the Aberrant Behavior Checklist-Community and a medical/demographic questionnaire. Cognitive level was abstracted from the medical record. Parents and clinicians completed surveys on the effect of the study on the clinical visit. Eighty-three children and their caregivers participated. Factors limiting participation included difficulty reaching families by phone and parent concern about the study blood draw requirement. All children completed at least 4 of 7 planned research activities. Demographic factors, educational placement, and child behavior were not associated with completion of study activities. Lower nonverbal cognitive function was weakly associated with fewer activities completed. Forty-four percent of clinicians reported an effect of the research study on the clinical visit. However, neither parent-reported nor clinician-reported effect was associated with the degree of study activity completion. Recruiting study participants in the context of scheduled ASD clinical visits required significant effort. However, once recruited, participants completed most study activities, regardless of behavioral symptom severity. Research activities did not adversely affect the clinical visit.

  2. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology.

    Science.gov (United States)

    Ganau, Mario; Paris, Marco; Syrmos, Nikolaos; Ganau, Laura; Ligarotti, Gianfranco K I; Moghaddamjou, Ali; Prisco, Lara; Ambu, Rossano; Chibbaro, Salvatore

    2018-02-26

    The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1) the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2) a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3) the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  3. How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1 the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2 a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3 the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

  4. A Proteomic Approach Identifies Candidate Early Biomarkers to Predict Severe Dengue in Children.

    Directory of Open Access Journals (Sweden)

    Dang My Nhi

    2016-02-01

    Full Text Available Severe dengue with severe plasma leakage (SD-SPL is the most frequent of dengue severe form. Plasma biomarkers for early predictive diagnosis of SD-SPL are required in the primary clinics for the prevention of dengue death.Among 63 confirmed dengue pediatric patients recruited, hospital based longitudinal study detected six SD-SPL and ten dengue with warning sign (DWS. To identify the specific proteins increased or decreased in the SD-SPL plasma obtained 6-48 hours before the shock compared with the DWS, the isobaric tags for relative and absolute quantification (iTRAQ technology was performed using four patients each group. Validation was undertaken in 6 SD-SPL and 10 DWS patients.Nineteen plasma proteins exhibited significantly different relative concentrations (p<0.05, with five over-expressed and fourteen under-expressed in SD-SPL compared with DWS. The individual protein was classified to either blood coagulation, vascular regulation, cellular transport-related processes or immune response. The immunoblot quantification showed angiotensinogen and antithrombin III significantly increased in SD-SPL whole plasma of early stage compared with DWS subjects. Even using this small number of samples, antithrombin III predicted SD-SPL before shock occurrence with accuracy.Proteins identified here may serve as candidate predictive markers to diagnose SD-SPL for timely clinical management. Since the number of subjects are small, so further studies are needed to confirm all these biomarkers.

  5. Harnessing Cerebrospinal Fluid Biomarkers in Clinical Trials for Treating Alzheimer's and Parkinson's Diseases: Potential and Challenges.

    Science.gov (United States)

    Kim, Dana; Kim, Young Sam; Shin, Dong Wun; Park, Chang Shin; Kang, Ju Hee

    2016-10-01

    No disease-modifying therapies (DMT) for neurodegenerative diseases (NDs) have been established, particularly for Alzheimer's disease (AD) and Parkinson's disease (PD). It is unclear why candidate drugs that successfully demonstrate therapeutic effects in animal models fail to show disease-modifying effects in clinical trials. To overcome this hurdle, patients with homogeneous pathologies should be detected as early as possible. The early detection of AD patients using sufficiently tested biomarkers could demonstrate the potential usefulness of combining biomarkers with clinical measures as a diagnostic tool. Cerebrospinal fluid (CSF) biomarkers for NDs are being incorporated in clinical trials designed with the aim of detecting patients earlier, evaluating target engagement, collecting homogeneous patients, facilitating prevention trials, and testing the potential of surrogate markers relative to clinical measures. In this review we summarize the latest information on CSF biomarkers in NDs, particularly AD and PD, and their use in clinical trials. The large number of issues related to CSF biomarker measurements and applications has resulted in relatively few clinical trials on CSF biomarkers being conducted. However, the available CSF biomarker data obtained in clinical trials support the advantages of incorporating CSF biomarkers in clinical trials, even though the data have mostly been obtained in AD trials. We describe the current issues with and ongoing efforts for the use of CSF biomarkers in clinical trials and the plans to harness CSF biomarkers for the development of DMT and clinical routines. This effort requires nationwide, global, and multidisciplinary efforts in academia, industry, and regulatory agencies to facilitate a new era.

  6. Searching for Clinically Relevant Biomarkers in Geriatric Oncology.

    Science.gov (United States)

    Katsila, Theodora; Patrinos, George P; Kardamakis, Dimitrios

    2018-01-01

    Ageing, which is associated with a progressive decline and functional deterioration in multiple organ systems, is highly heterogeneous, both inter- and intraindividually. For this, tailored-made theranostics and optimum patient stratification become fundamental, when decision-making in elderly patients is considered. In particular, when cancer incidence and cancer-related mortality and morbidity are taken into account, elderly patient care is a public health concern. In this review, we focus on oncogeriatrics and highlight current opportunities and challenges with an emphasis on the unmet need of clinically relevant biomarkers in elderly cancer patients. We performed a literature search on PubMed and Scopus databases for articles published in English between 2000 and 2017 coupled to text mining and analysis. Considering the top insights, we derived from our literature analysis that information knowledge needs to turn into knowledge growth in oncogeriatrics towards clinically relevant biomarkers, cost-effective practices, updated educational schemes for health professionals (in particular, geriatricians and oncologists), and awareness of ethical issues. We conclude with an interdisciplinary call to omics, geriatricians, oncologists, informatics, and policy-makers communities that Big Data should be translated into decision-making in the clinic.

  7. Biomarkers in Scleroderma: Progressing from Association to Clinical Utility.

    Science.gov (United States)

    Ligon, Colin; Hummers, Laura K

    2016-03-01

    Scleroderma is a heterogenous disease characterized by autoimmunity, a characteristic vasculopathy, and often widely varying extents of deep organ fibrosis. Recent advances in the understanding of scleroderma's evolution have improved the ability to identify subgroups of patients with similar prognosis in order to improve risk stratification, enrich clinical trials for patients likely to benefit from specific therapies, and identify promising therapeutic targets for intervention. High-throughput technologies have recently identified fibrotic and inflammatory effectors in scleroderma that exhibit strong prognostic ability and may be tied to disease evolution. Increasingly, the use of collections of assayed circulating proteins and patterns of gene expression in tissue has replaced single-marker investigations in understanding the evolution of scleroderma and in objectively characterizing disease extent. Lastly, identification of shared patterns of disease evolution has allowed classification of patients into latent disease subtypes, which may allow rapid clinical prognostication and targeted management in both clinical and research settings. The concept of biomarkers in scleroderma is expanding to include nontraditional measures of aggregate protein signatures and disease evolution. This review examines the recent advances in biomarkers with a focus on those approaches poised to guide prospective management or themselves serve as quantitative surrogate disease outcomes.

  8. Integration of gene expression, clinical, and demographic information in relation to asthma status to identify biomarkers associated with subtypes of childhood asthma

    Science.gov (United States)

    Advances in biomarker development have improved our ability to detect early changes at the molecular, cellular, and pre-clinical level that are often predictive of adverse health outcomes. Biomarkers for monitoring the underlying molecular mechanisms of disease are of increasing...

  9. A biomarker profile for predicting efficacy of cisplatin-vinorelbine therapy in malignant pleural mesothelioma

    DEFF Research Database (Denmark)

    Zimling, Zarah Glad; Sørensen, Jens Benn; Gerds, Thomas Alexander

    2012-01-01

    Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated with cispl......Malignant pleural mesothelioma (MPM) has a dismal prognosis. Treatment results may be improved by biomarker-directed therapy. We investigated the baseline expression and impact on outcome of predictive biomarkers ERCC1, BRCA1, and class III β-tubulin in a cohort of MPM patients treated...

  10. Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects.

    Science.gov (United States)

    Hinton, David J; Vázquez, Marely Santiago; Geske, Jennifer R; Hitschfeld, Mario J; Ho, Ada M C; Karpyak, Victor M; Biernacka, Joanna M; Choi, Doo-Sup

    2017-05-31

    Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

  11. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study

    OpenAIRE

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    Background No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Methods Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; th...

  12. Breast cancer biomarkers predict weight loss after gastric bypass surgery

    Directory of Open Access Journals (Sweden)

    Sauter Edward R

    2012-01-01

    Full Text Available Abstract Background Obesity has long been associated with postmenopausal breast cancer risk and more recently with premenopausal breast cancer risk. We previously observed that nipple aspirate fluid (n levels of prostate specific antigen (PSA were associated with obesity. Serum (s levels of adiponectin are lower in women with higher body mass index (BMI and with breast cancer. We conducted a prospective study of obese women who underwent gastric bypass surgery to determine: 1 change in n- and s-adiponectin and nPSA after surgery and 2 if biomarker change is related to change in BMI. Samples (30-s, 28-n and BMI were obtained from women 0, 3, 6 and 12 months after surgery. Findings There was a significant increase after surgery in pre- but not postmenopausal women at all time points in s-adiponectin and at 3 and 6 months in n-adiponectin. Low n-PSA and high s-adiponectin values were highly correlated with decrease in BMI from baseline. Conclusions Adiponectin increases locally in the breast and systemically in premenopausal women after gastric bypass. s-adiponectin in pre- and nPSA in postmenopausal women correlated with greater weight loss. This study provides preliminary evidence for biologic markers to predict weight loss after gastric bypass surgery.

  13. DR6 as a diagnostic and predictive biomarker in adult sarcoma.

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    Kun Yang

    Full Text Available The Death Receptor 6 (DR6 protein is elevated in the serum of ovarian cancer patients. We tested DR6 serum protein levels as a diagnostic/predictive biomarker in several epithelial tumors and sarcomas.DR6 gene expression profiles were screened in publically available arrays of solid tumors. A quantitative immunofluorescent western blot analysis was developed to test the serum of healthy controls and patients with sarcoma, uterine carcinosarcoma, bladder, liver, and pancreatic carcinomas. Change in DR6 serum levels was used to assay the ability of DR6 to predict the response to therapy of sarcoma patients.DR6 mRNA is highly expressed in all tumor types assayed. Western blot analysis of serum DR6 protein demonstrated high reproducibility (r = 0.97. Compared to healthy donor controls, DR6 serum levels were not elevated in patients with uterine carcinosarcoma, bladder, liver, or pancreatic cancers. Serum DR6 protein levels from adult sarcoma patients were significantly elevated (p<0.001. This was most evident for patients with synovial sarcoma. Change in serum DR6 levels during therapy correlated with clinical benefit from therapy (sensitivity 75%, and positive predictive value 87%.DR6 may be a clinically useful diagnostic and predictive serum biomarker for some adult sarcoma subtypes.Diagnosis of sarcoma can be difficult and can lead to improper management of these cancers. DR6 serum protein may be a tool to aid in the diagnosis of some sarcomatous tumors to improve treatment planning. For patients with advanced disease, rising DR6 levels predict non-response to therapy and may expedite therapeutic decision making and reduce reliance on radiologic imaging.

  14. Urinary aminopeptidase activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats.

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    Andrés Quesada

    Full Text Available This study analyzes the fluorimetric determination of alanyl- (Ala, glutamyl- (Glu, leucyl-cystinyl- (Cys and aspartyl-aminopeptidase (AspAp urinary enzymatic activities as early and predictive biomarkers of renal dysfunction in cisplatin-treated rats. Male Wistar rats (n = 8 each group received a single subcutaneous injection of either saline or cisplatin 3.5 or 7 mg/kg, and urine samples were taken at 0, 1, 2, 3 and 14 days after treatment. In urine samples we determined Ala, Glu, Cys and AspAp activities, proteinuria, N-acetyl-β-D-glucosaminidase (NAG, albumin, and neutrophil gelatinase-associated lipocalin (NGAL. Plasma creatinine, creatinine clearance and renal morphological variables were measured at the end of the experiment. CysAp, NAG and albumin were increased 48 hours after treatment in the cisplatin 3.5 mg/kg treated group. At 24 hours, all urinary aminopeptidase activities and albuminuria were significantly increased in the cisplatin 7 mg/kg treated group. Aminopeptidase urinary activities correlated (p0.259 with plasma creatinine, creatinine clearance and/or kidney weight/body weight ratio at the end of the experiment and they could be considered as predictive biomarkers of renal injury severity. ROC-AUC analysis was made to study their sensitivity and specificity to distinguish between treated and untreated rats at day 1. All aminopeptidase activities showed an AUC>0.633. We conclude that Ala, Cys, Glu and AspAp enzymatic activities are early and predictive urinary biomarkers of the renal dysfunction induced by cisplatin. These determinations can be very useful in the prognostic and diagnostic of renal dysfunction in preclinical research and clinical practice.

  15. Canine babesiosis: a perspective on clinical complications, biomarkers, and treatment

    Directory of Open Access Journals (Sweden)

    Köster LS

    2015-04-01

    Full Text Available Liza S Köster,1 Remo G Lobetti,2 Patrick Kelly1 1Department of Clinical Sciences, One Health Center for Zoonoses and Tropical Veterinary Medicine, Ross University School of Veterinary Medicine, St Kitts, West Indies; 2Bryanston Veterinary Hospital, Bryanston, South Africa Abstract: Canine babesiosis is a common tick transmitted disease of dogs worldwide. A number of Babesia sp. can infect dogs and the spectrum is increasing as molecular methods are developed to differentiate organisms. Clinical signs are generally attributed to hemolysis caused by the organisms in the erythrocytes but in some animals with some Babesia spp. there can be an immune mediated component to the anemia and/or a severe inflammatory reaction associated. This complicated form of canine babesiosis is associated with high morbidity and mortality. A variety of clinical markers has been investigated to enable clinicians to provide more accurate prognoses and adapt their treatments which vary according to the infecting species. In this review, we discuss the taxonomy, clinical signs, diagnostic imaging, clinical biomarkers, treatment, and prophylaxis of one of the most common and important diseases of dogs worldwide. Keywords: babesiosis, vector-borne disease, dog

  16. Clinical proteomics: Applications for prostate cancer biomarker discovery and detection.

    Science.gov (United States)

    Petricoin, Emanuel F; Ornstein, David K; Liotta, Lance A

    2004-01-01

    The science of proteomics comprises much more than simply generating lists of proteins that change in expression as a cause of or consequence of pathophysiology. The goal of proteomics should be to characterize the information flow through the intercellular protein circuitry that communicates with the extracellular microenvironment and then ultimately to the serum/plasma macroenvironment. Serum proteomic pattern diagnostics is a new type of proteomic concept in which patterns of ion signatures generated from high dimensional mass spectrometry data are used as diagnostic classifiers. This recent approach has exciting potential for clinical utility of diagnostic patterns because low molecular weight metabolites, peptides, and protein fragments may have higher accuracy than traditional biomarkers of cancer detection. Intriguingly, we now have discovered that this diagnostic information exists in a bound state, complexed with circulating highly abundant carrier proteins. These diagnostic fragments may one day be harvested by circulating nanoparticles, designed to absorb, enrich, and amplify the repertoire of diagnostic biomarkers generated-even at the critical, initial stages of carcinogenesis. Copyright 2004 Elsevier Inc.

  17. Biomarkers of World Trade Center Particulate Matter Exposure: Physiology of distal airway and blood biomarkers that predict FEV1 decline

    Science.gov (United States)

    Weiden, Michael D.; Kwon, Sophia; Caraher, Erin; Berger, Kenneth I.; Reibman, Joan; Rom, William N.; Prezant, David J.; Nolan, Anna

    2016-01-01

    Biomarkers can be important predictors of disease severity and progression. The intense exposure to particulates and other toxins from the destruction of the World Trade Center (WTC) overwhelmed the lung’s normal protective barriers. The Fire Department of New York (FDNY) cohort not only had baseline pre-exposure lung function measures but also had serum samples banked soon after their WTC exposure. This well phenotyped group of highly exposed first responders is an ideal cohort for biomarker discovery and eventual validation. Disease progression was heterogeneous in this group in that some individuals subsequently developed abnormal lung function while others recovered. Airflow obstruction predominated in WTC exposed patients who were symptomatic. Multiple independent disease pathways may cause this abnormal FEV1 after irritant exposure. WTC exposure activates one or more of these pathways causing abnormal FEV1 in an individual. Our hypothesis was that serum biomarkers expressed within 6 months after World Trade Center (WTC) exposure reflect active disease pathways and predict subsequent development or protection from abnormal FEV1predictive biomarkers of WTC-LI. We have identified biomarkers of Inflammation, metabolic derangement, protease/antiprotease balance and vascular injury expressed in serum within 6 months of WTC exposure that were predictive of their FEV1 up to 7 years after their WTC exposure. Predicting future risk of airway injury after particulate exposures can focus monitoring and early treatment on a subset of patients in greatest need of these services. PMID:26024341

  18. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: Application of a biomarker development strategy

    Directory of Open Access Journals (Sweden)

    Daniel S. Barron

    2015-01-01

    No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons. Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

  19. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    Science.gov (United States)

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  20. Identification of predictive biomarkers of disease state in transition dairy cows.

    Science.gov (United States)

    Hailemariam, D; Mandal, R; Saleem, F; Dunn, S M; Wishart, D S; Ametaj, B N

    2014-05-01

    phosphatidylcholine diacyl C42:6, could be used to discriminate healthy controls from diseased cows 1 wk before parturition. A 3-metabolite plasma biomarker profile was developed that could predict which cows would develop periparturient diseases, up to 4 wk before clinical symptoms appearing, with a sensitivity of 87% and a specificity of 85%. This is the first report showing that periparturient diseases can be predicted in dairy cattle before their development using a multimetabolite biomarker model. Further research is warranted to validate these potential predictive biomarkers. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

  1. Biomarkers of evasive resistance predict disease progression in cancer patients treated with antiangiogenic therapies

    Science.gov (United States)

    Pircher, Andreas; Jöhrer, Karin; Kocher, Florian; Steiner, Normann; Graziadei, Ivo; Heidegger, Isabel; Pichler, Renate; Leonhartsberger, Nicolai; Kremser, Christian; Kern, Johann; Untergasser, Gerold; Gunsilius, Eberhard; Hilbe, Wolfgang

    2016-01-01

    Numerous antiangiogenic agents are approved for the treatment of oncological diseases. However, almost all patients develop evasive resistance mechanisms against antiangiogenic therapies. Currently no predictive biomarker for therapy resistance or response has been established. Therefore, the aim of our study was to identify biomarkers predicting the development of therapy resistance in patients with hepatocellular cancer (n = 11), renal cell cancer (n = 7) and non-small cell lung cancer (n = 2). Thereby we measured levels of angiogenic growth factors, tumor perfusion, circulating endothelial cells (CEC), circulating endothelial progenitor cells (CEP) and tumor endothelial markers (TEM) in patients during the course of therapy with antiangiogenic agents, and correlated them with the time to antiangiogenic progression (aTTP). Importantly, at disease progression, we observed an increase of proangiogenic factors, upregulation of CEC/CEP levels and downregulation of TEMs, such as Robo4 and endothelial cell-specific chemotaxis regulator (ECSCR), reflecting the formation of torturous tumor vessels. Increased TEM expression levels tended to correlate with prolonged aTTP (ECSCR high = 275 days vs. ECSCR low = 92.5 days; p = 0.07 and for Robo4 high = 387 days vs. Robo4 low = 90.0 days; p = 0.08). This indicates that loss of vascular stabilization factors aggravates the development of antiangiogenic resistance. Thus, our observations confirm that CEP/CEC populations, proangiogenic cytokines and TEMs contribute to evasive resistance in antiangiogenic treated patients. Higher TEM expression during disease progression may have clinical and pathophysiological implications, however, validation of our results is warranted for further biomarker development. PMID:26956051

  2. Clinical and Biomarkers Difference in Prepartum and Postpartum Eclampsia.

    Science.gov (United States)

    Berhan, Yifru; Endeshaw, Gezahegn

    2015-07-01

    There is a large body of literature which assessed the incidence and risk factors of eclampsia, but little was done in assessing the association of clinical features and biological markers with prepartum and postpartum eclampsia. A total of 361 eclamptic women admitted to three teaching hospitals between 2008 and 2013 were included in this analysis. A comparative analysis was done for several clinical and biological variables to assess their association with prepartum and postpartum eclampsia. The overall incidence of eclampsia was 1.2% (prepartum 71% and postpartum 29%). The majority of women with prepartum eclampsia were young, primigravida, more hypertensive, symptomatic and proteinuric. Conversely, the majorities of the women with post-partum eclampsia were adult, multiparous, carrying pregnancy to term, anemic, thrombocytopenic, and with hepatic dysfunction. The commonest severity symptom (headache) was less common in postpartum eclamptic women. The incidence of eclampsia was among the highest in the world. And, the analysis has shown that the clinical and biochemical spectrum of prepartum and postpartum eclampsia were apparently different. The majority of the women who developed postpartum eclampsia were multiparous and adult. Derangement of biomarkers was also more common in women with postpartum eclampsia.

  3. Developing risk prediction models for kidney injury and assessing incremental value for novel biomarkers.

    Science.gov (United States)

    Kerr, Kathleen F; Meisner, Allison; Thiessen-Philbrook, Heather; Coca, Steven G; Parikh, Chirag R

    2014-08-07

    The field of nephrology is actively involved in developing biomarkers and improving models for predicting patients' risks of AKI and CKD and their outcomes. However, some important aspects of evaluating biomarkers and risk models are not widely appreciated, and statistical methods are still evolving. This review describes some of the most important statistical concepts for this area of research and identifies common pitfalls. Particular attention is paid to metrics proposed within the last 5 years for quantifying the incremental predictive value of a new biomarker. Copyright © 2014 by the American Society of Nephrology.

  4. The Clinical Prediction of Dangerousness.

    Science.gov (United States)

    1985-05-01

    8217 8 ings. Szasz (1963) has argued persuasively that clinical predictions of future dangerous behavior are unfairly focused on the mentally ill...Persons labeled paranoid, Szasz states, are readily commitable, while highly dangerous drunken drivers are not. Indeed, dangerousness such as that...Psychology, 31, 492-494. Szasz , T. (1963). Law, liberty and psychiatry. New York: Macmillan. Taft, R. (1955). The ability to judge people. Psychological

  5. Identification of potential prognostic microRNA biomarkers for predicting survival in patients with hepatocellular carcinoma

    Directory of Open Access Journals (Sweden)

    Liao X

    2018-04-01

    Full Text Available Xiwen Liao,1 Guangzhi Zhu,1 Rui Huang,2 Chengkun Yang,1 Xiangkun Wang,1 Ketuan Huang,1 Tingdong Yu,1 Chuangye Han,1 Hao Su,1 Tao Peng1 1Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China; 2Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China Background: The aim of the present study was to identify potential prognostic microRNA (miRNA biomarkers for hepatocellular carcinoma (HCC prognosis prediction based on a dataset from The Cancer Genome Atlas (TCGA. Materials and methods: A miRNA sequencing dataset and corresponding clinical parameters of HCC were obtained from TCGA. Genome-wide univariate Cox regression analysis was used to screen prognostic differentially expressed miRNAs (DEMs, and multivariable Cox regression analysis was used for prognostic signature construction. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Results: Five miRNAs were regarded as prognostic DEMs and used for prognostic signature construction. The five-DEM prognostic signature performed well in prognosis prediction (adjusted P < 0.0001, adjusted hazard ratio = 2.249, 95% confidence interval =1.491–3.394, and time-dependent receiver–operating characteristic (ROC analysis showed an area under the curve (AUC of 0.765, 0.745, 0.725, and 0.687 for 1-, 2-, 3-, and 5-year HCC overall survival (OS prediction, respectively. Comprehensive survival analysis of the prognostic signature suggests that the risk score model could serve as an independent factor of HCC and perform better in prognosis prediction than other traditional clinical indicators. Functional assessment of the target genes of hsa-mir-139 and hsa-mir-5003 indicates that they were significantly enriched in multiple biological processes and pathways, including cell proliferation and cell migration

  6. DNA Repair Biomarkers Predict Response to Neoadjuvant Chemoradiotherapy in Esophageal Cancer

    International Nuclear Information System (INIS)

    Alexander, Brian M.; Wang Xiaozhe; Niemierko, Andrzej; Weaver, David T.; Mak, Raymond H.; Roof, Kevin S.; Fidias, Panagiotis; Wain, John; Choi, Noah C.

    2012-01-01

    Purpose: The addition of neoadjuvant chemoradiotherapy prior to surgical resection for esophageal cancer has improved clinical outcomes in some trials. Pathologic complete response (pCR) following neoadjuvant therapy is associated with better clinical outcome in these patients, but only 22% to 40% of patients achieve pCR. Because both chemotherapy and radiotherapy act by inducing DNA damage, we analyzed proteins selected from multiple DNA repair pathways, using quantitative immunohistochemistry coupled with a digital pathology platform, as possible biomarkers of treatment response and clinical outcome. Methods and Materials: We identified 79 patients diagnosed with esophageal cancer between October 1994 and September 2002, with biopsy tissue available, who underwent neoadjuvant chemoradiotherapy prior to surgery at the Massachusetts General Hospital and used their archived, formalin-fixed, paraffin-embedded biopsy samples to create tissue microarrays (TMA). TMA sections were stained using antibodies against proteins in various DNA repair pathways including XPF, FANCD2, PAR, MLH1, PARP1, and phosphorylated MAPKAP kinase 2 (pMK2). Stained TMA slides were evaluated using machine-based image analysis, and scoring incorporated both the intensity and the quantity of positive tumor nuclei. Biomarker scores and clinical data were assessed for correlations with clinical outcome. Results: Higher scores for MLH1 (p = 0.018) and lower scores for FANCD2 (p = 0.037) were associated with pathologic response to neoadjuvant chemoradiation on multivariable analysis. Staining of MLH1, PARP1, XPF, and PAR was associated with recurrence-free survival, and staining of PARP1 and FANCD2 was associated with overall survival on multivariable analysis. Conclusions: DNA repair proteins analyzed by immunohistochemistry may be useful as predictive markers for response to neoadjuvant chemoradiotherapy in patients with esophageal cancer. These results are hypothesis generating and need

  7. What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema.

    Science.gov (United States)

    Ptolemy, Adam S; Rifai, Nader

    2010-01-01

    A continual trend of annual growth can be seen within research devoted to the discovery and validation of disease biomarkers within both the natural and clinical sciences. This expansion of intellectual endeavours was quantified through database searches of (a) research grant awards provided by the various branches of the National Institutes of Health (NIH) and (b) academic publications. A search of awards presented between 1986 and 2009 revealed a total of 28,856 grants awarded by the NIH containing the term "biomarker". The total funds for these awards in 2008 and 2009 alone were over $2.5 billion. During the same respective time frames, searches of "biomarker" and either "discovery", "genomics", "proteomics" or "metabolomics" yielded a total of 4,928 NIH grants whose combined funding exceeded $1.2 billion. The derived trend in NIH awards paralleled the annual expansion in "biomarker" literature. A PubMed search for the term, between 1990 and 2009, revealed a total of 441,510 published articles, with 38,457 published in 2008. These enormous investments and academic outputs however have not translated into the expected integration of new biomarkers for patient care. For example no proteomics derived biomarkers are currently being utilized in routine clinical management. This translational chasm necessitates a review of the previously proposed biomarker definitions and evaluation schema. A subsequent discussion of both the analytical and pre-analytical considerations for such research is also presented within. This required knowledge should aid scientists in their pursuit and validation of new biological markers of disease.

  8. Integration and relative value of biomarkers for prediction of MCI to AD progression: Spatial patterns of brain atrophy, cognitive scores, APOE genotype and CSF biomarkers

    Directory of Open Access Journals (Sweden)

    Xiao Da

    2014-01-01

    Full Text Available This study evaluates the individual, as well as relative and joint value of indices obtained from magnetic resonance imaging (MRI patterns of brain atrophy (quantified by the SPARE-AD index, cerebrospinal fluid (CSF biomarkers, APOE genotype, and cognitive performance (ADAS-Cog in progression from mild cognitive impairment (MCI to Alzheimer's disease (AD within a variable follow-up period up to 6 years, using data from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1. SPARE-AD was first established as a highly sensitive and specific MRI-marker of AD vs. cognitively normal (CN subjects (AUC = 0.98. Baseline predictive values of all aforementioned indices were then compared using survival analysis on 381 MCI subjects. SPARE-AD and ADAS-Cog were found to have similar predictive value, and their combination was significantly better than their individual performance. APOE genotype did not significantly improve prediction, although the combination of SPARE-AD, ADAS-Cog and APOE ε4 provided the highest hazard ratio estimates of 17.8 (last vs. first quartile. In a subset of 192 MCI patients who also had CSF biomarkers, the addition of Aβ1–42, t-tau, and p-tau181p to the previous model did not improve predictive value significantly over SPARE-AD and ADAS-Cog combined. Importantly, in amyloid-negative patients with MCI, SPARE-AD had high predictive power of clinical progression. Our findings suggest that SPARE-AD and ADAS-Cog in combination offer the highest predictive power of conversion from MCI to AD, which is improved, albeit not significantly, by APOE genotype. The finding that SPARE-AD in amyloid-negative MCI patients was predictive of clinical progression is not expected under the amyloid hypothesis and merits further investigation.

  9. Nanomaterial-Based Electrochemical Immunosensors for Clinically Significant Biomarkers

    Directory of Open Access Journals (Sweden)

    Niina J. Ronkainen

    2014-06-01

    Full Text Available Nanotechnology has played a crucial role in the development of biosensors over the past decade. The development, testing, optimization, and validation of new biosensors has become a highly interdisciplinary effort involving experts in chemistry, biology, physics, engineering, and medicine. The sensitivity, the specificity and the reproducibility of biosensors have improved tremendously as a result of incorporating nanomaterials in their design. In general, nanomaterials-based electrochemical immunosensors amplify the sensitivity by facilitating greater loading of the larger sensing surface with biorecognition molecules as well as improving the electrochemical properties of the transducer. The most common types of nanomaterials and their properties will be described. In addition, the utilization of nanomaterials in immunosensors for biomarker detection will be discussed since these biosensors have enormous potential for a myriad of clinical uses. Electrochemical immunosensors provide a specific and simple analytical alternative as evidenced by their brief analysis times, inexpensive instrumentation, lower assay cost as well as good portability and amenability to miniaturization. The role nanomaterials play in biosensors, their ability to improve detection capabilities in low concentration analytes yielding clinically useful data and their impact on other biosensor performance properties will be discussed. Finally, the most common types of electroanalytical detection methods will be briefly touched upon.

  10. Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

    Science.gov (United States)

    Lam, Raymond W; Milev, Roumen; Rotzinger, Susan; Andreazza, Ana C; Blier, Pierre; Brenner, Colleen; Daskalakis, Zafiris J; Dharsee, Moyez; Downar, Jonathan; Evans, Kenneth R; Farzan, Faranak; Foster, Jane A; Frey, Benicio N; Geraci, Joseph; Giacobbe, Peter; Feilotter, Harriet E; Hall, Geoffrey B; Harkness, Kate L; Hassel, Stefanie; Ismail, Zahinoor; Leri, Francesco; Liotti, Mario; MacQueen, Glenda M; McAndrews, Mary Pat; Minuzzi, Luciano; Müller, Daniel J; Parikh, Sagar V; Placenza, Franca M; Quilty, Lena C; Ravindran, Arun V; Salomons, Tim V; Soares, Claudio N; Strother, Stephen C; Turecki, Gustavo; Vaccarino, Anthony L; Vila-Rodriguez, Fidel; Kennedy, Sidney H

    2016-04-16

    Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants

  11. Target biomarker profile for the clinical management of paracetamol overdose

    Science.gov (United States)

    Vliegenthart, A D Bastiaan; Antoine, Daniel J; Dear, James W

    2015-01-01

    Paracetamol (acetaminophen) overdose is one of the most common causes of acute liver injury in the Western world. To improve patient care and reduce pressure on already stretched health care providers new biomarkers are needed that identify or exclude liver injury soon after an overdose of paracetamol is ingested. This review highlights the current state of paracetamol poisoning management and how novel biomarkers could improve patient care and save healthcare providers money. Based on the widely used concept of defining a target product profile, a target biomarker profile is proposed that identifies desirable and acceptable key properties for a biomarker in development to enable the improved treatment of this patient population. The current biomarker candidates, with improved hepatic specificity and based on the fundamental mechanistic basis of paracetamol-induced liver injury, are reviewed and their performance compared with our target profile. PMID:26076366

  12. The Functional Diffusion Map: An Imaging Biomarker for the Early Prediction of Cancer Treatment Outcome

    Directory of Open Access Journals (Sweden)

    Bradford A. Moffat

    2006-04-01

    Full Text Available Functional diffusion map (fDM has been recently reported as an early and quantitative biomarker of clinical brain tumor treatment outcome. This MRI approach spatially maps and quantifies treatment-induced changes in tumor water diffusion values resulting from alterations in cell density/cell membrane function and microenvironment. This current study was designed to evaluate the capability of fDM for preclinical evaluation of dose escalation studies and to determine if these changes were correlated with outcome measures (cell kill and overall survival. Serial T2-weighted and diffusion MRI were carried out on rodents with orthotopically implanted 9L brain tumors receiving three doses of 1,3-bis(2-chloroethyl-1-nitrosourea (6.65, 13.3, and 26.6 mg/kg, i.p.. All images were coregistered to baseline T2-weighted images for fDM analysis. Analysis of tumor fDM data on day 4 posttreatment detected dosedependent changes in tumor diffusion values, which were also found to be spatially dependent. Histologic analysis of treated tumors confirmed spatial changes in cellularity as observed by fDM. Early changes in tumor diffusion values were found to be highly correlative with drug dose and independent biologic outcome measures (cell kill and survival. Therefore, the fDM imaging biomarker for early prediction of treatment efficacy can be used in the drug development process.

  13. Biomarker pattern of ARIA-E participants in phase 3 randomized clinical trials with bapineuzumab.

    Science.gov (United States)

    Liu, Enchi; Wang, Dai; Sperling, Reisa; Salloway, Stephen; Fox, Nick C; Blennow, Kaj; Scheltens, Philip; Schmidt, Mark E; Streffer, Johannes; Novak, Gerald; Einstein, Steve; Booth, Kevin; Ketter, Nzeera; Brashear, H Robert

    2018-03-06

    To evaluate whether amyloid-related imaging abnormalities with edema/effusion (ARIA-E) observed in bapineuzumab clinical trials was associated with specific biomarker patterns. Bapineuzumab, an anti-β-amyloid monoclonal antibody, was evaluated in patients with mild to moderate Alzheimer disease. Amyloid PET imaging, CSF biomarkers, or volumetric MRI (vMRI) were assessed. A total of 1,512 participants underwent one or more biomarker assessments; 154 developed incident ARIA-E. No differences were observed at baseline between ARIA-E and non-ARIA-E participants in brain amyloid burden by PET, the majority of vMRI measures, or CSF biomarkers, with the exception of lower baseline CSF Aβ 42 in APOE ε4 noncarrier ARIA-E vs non-ARIA-E groups (bapineuzumab non-ARIA-E p = 0.027; placebo non-ARIA-E p = 0.012). At week 71, bapineuzumab-treated participants with ARIA-E vs non-ARIA-E showed greater reduction in brain amyloid PET, greater reductions in CSF phosphorylated tau (p-tau) (all comparisons p < 0.01), and total tau (t-tau) (all comparisons p < 0.025), and greater hippocampal volume reduction and ventricular enlargement (all p < 0.05). Greater reduction in CSF Aβ 40 concentrations was observed for ARIA-E versus both non-ARIA-E groups (bapineuzumab/placebo non-ARIA-E p = 0.015/0.049). No group differences were observed at week 71 for changes in whole brain volume or CSF Aβ 42 . Baseline biomarkers largely do not predict risk for developing ARIA-E. ARIA-E was associated with significant longitudinal changes in several biomarkers, with larger reductions in amyloid PET and CSF p-tau and t-tau concentrations, and paradoxically greater hippocampal volume reduction and ventricular enlargement, suggesting that ARIA-E in bapineuzumab-treated cases may be related to increased Aβ efflux from the brain and affecting downstream pathogenic processes. © 2018 American Academy of Neurology.

  14. Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

    Science.gov (United States)

    Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

    2015-01-01

    Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

  15. Predictive biomarkers for death and rehospitalization in comorbid frail elderly heart failure patients.

    Science.gov (United States)

    Pacho, Cristina; Domingo, Mar; Núñez, Raquel; Lupón, Josep; Núñez, Julio; Barallat, Jaume; Moliner, Pedro; de Antonio, Marta; Santesmases, Javier; Cediel, Germán; Roura, Santiago; Pastor, M Cruz; Tor, Jordi; Bayes-Genis, Antoni

    2018-05-09

    Heart failure (HF) is associated with a high rate of readmissions within 30 days post-discharge and in the following year, especially in frail elderly patients. Biomarker data are scarce in this high-risk population. This study assessed the value of early post-discharge circulating levels of ST2, NT-proBNP, CA125, and hs-TnI for predicting 30-day and 1-year outcomes in comorbid frail elderly patients with HF with mainly preserved ejection fraction (HFpEF). Blood samples were obtained at the first visit shortly after discharge (4.9 ± 2 days). The primary endpoint was the composite of all-cause mortality or HF-related rehospitalization at 30 days and at 1 year. All-cause mortality alone at one year was also a major endpoint. HF-related rehospitalizations alone were secondary end-points. From February 2014 to November 2016, 522 consecutive patients attending the STOP-HF Clinic were included (57.1% women, age 82 ± 8.7 years, mean Barthel index 70 ± 25, mean Charlson comorbidity index 5.6 ± 2.2). The composite endpoint occurred in 8.6% patients at 30 days and in 38.5% at 1 year. In multivariable analysis, ST2 [hazard ratio (HR) 1.53; 95% CI 1.19-1.97; p = 0.001] was the only predictive biomarker at 30 days; at 1 year, both ST2 (HR 1.34; 95% CI 1.15-1.56; p < 0.001) and NT-proBNP (HR 1.19; 95% CI 1.02-1.40; p = 0.03) remained significant. The addition of ST2 and NT-proBNP into a clinical predictive model increased the AUC from 0.70 to 0.75 at 30 days (p = 0.02) and from 0.71 to 0.74 at 1 year (p < 0.05). For all-cause death at 1 year, ST2 (HR 1.50; 95% CI 1.26-1.80; p < 0.001), and CA125 (HR 1.41; 95% CI 1.21-1.63; p < 0.001) remained independent predictors in multivariable analysis. The addition of ST2 and CA125 into a clinical predictive model increased the AUC from 0.74 to 0.78 (p = 0.03). For HF-related hospitalizations, ST2 was the only predictive biomarker in multivariable analyses, both at 30

  16. Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

    Directory of Open Access Journals (Sweden)

    Karacali Bilge

    2007-10-01

    Full Text Available Abstract Background Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a all genes on the microarray platform and b a list of known disease-related genes (a priori selection. We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms. Results Highly discriminative expression profiles were produced on both simulated gene expression data and expression data from breast cancer and lymphoma datasets on the basis of ER and BCL-6 expression, respectively. Use of relapse-free status to identify profiles for prognosis prediction resulted in poorly discriminative decision rules. Supervised feature selection resulted in more accurate classifications than random or a priori selection, however, the difference in prediction error decreased as the number of features increased. These results held when decision rules were applied across-datasets to samples profiled on the same microarray platform. Conclusion Our results show that many gene sets predict molecular phenotypes accurately. Given this, expression profiles identified using different training datasets should be expected to show little agreement. In addition, we demonstrate the difficulty in predicting relapse directly from microarray data using supervised machine

  17. Potential Immune Biomarkers in Diagnosis and Clinical Management for Systemic Lupus Erythematosus

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    Zecevic Lamija

    2018-04-01

    Full Text Available Background: There is still no reliable, specific biomarker for precision diagnosis and clinical monitoring of systemic lupus erythematosus. The aim of this study was to investigate the importance of the determination of immunofenotypic profiles (T, B lymphocytes and NK cells and serum cytokine concentrations (IL-17 and IFN-alpha as potential biomarkers for this disease.

  18. Biomarkers and insulin sensitivity in women with Polycystic Ovary Syndrome: Characteristics and predictive capacity.

    Science.gov (United States)

    Cassar, Samantha; Teede, Helena J; Harrison, Cheryce L; Joham, Anju E; Moran, Lisa J; Stepto, Nigel K

    2015-07-01

    Polycystic ovary syndrome (PCOS) is a common endocrine disorder associated with metabolic complications. Metabolic biomarkers with roles in obesity, glycaemic control and lipid metabolism are potentially relevant in PCOS. The aim was to investigate metabolic biomarkers in lean and overweight women with and without PCOS and to determine whether any biomarker was able to predict insulin resistance in PCOS. Cross-sectional study. Eighty-four women (22 overweight and 22 lean women with PCOS, 18 overweight and 22 lean women without PCOS) were recruited from the community and categorized based on PCOS and BMI status. Primary outcomes were metabolic biomarkers [ghrelin, resistin, visfatin, glucagon-like peptide-1 (GLP-1), leptin, plasminogen activator inhibitor -1 (PAI-1), glucose-dependent insulinotropic polypeptide (GIP) and C-Peptide] measured using the Bio-Plex Pro Diabetes assay and insulin sensitivity as assessed by glucose infusion rate on euglycaemic-hyperinsulinaemic clamp. The biomarkers C-peptide, leptin, ghrelin and visfatin were different between overweight and lean women, irrespective of PCOS status. The concentration of circulating biomarkers did not differ between women with PCOS diagnosed by the Rotterdam criteria or National Institute of Health criteria. PAI-1 was the only biomarker that significantly predicted insulin resistance in both control women (P = 0.04) and women with PCOS (P = 0.01). Biomarkers associated with metabolic diseases appear more strongly associated with obesity rather than PCOS status. PAI-1 may also be a novel independent biomarker and predictor of insulin resistance in women with and without PCOS. © 2014 John Wiley & Sons Ltd.

  19. Targeted genomic biomarkers for diagnosis and therapy: from basic research to clinical perspective

    International Nuclear Information System (INIS)

    Thakur, Mathew L.

    2014-01-01

    In 2010, more than 30,000 men succumbed to prostate cancer (PC) and more than 240,000 new PC cases were identified in the USA. Digital rectal examination, MRI, and a blood test for prostate specific antigen (PSA) determination play a significant role in detecting advanced PC. However, they are not considered reliable tools for early warning of PC, to detect recurrent cancer or to determine metastatic status of the disease. Unreliable diagnosis results in undertreatment or overtreatment of patients with minimal benefit, enormous morbidity, incontinence, and/or impotence. Histology remains the mainstay of PC confirmation. However, out of >750,000 biopsies performed each year in the USA, >65% show benign pathology, causing patient morbidity and costing hundreds of millions of healthcare dollars. Biological fluids, including urine, represent a promising source of biomarkers for detection and prediction of PC prognosis. Because urine is available non-invasively and readily, numerous studies targeting DNA, RNA, protein and metabolite based biomarkers have been performed. However, none have yet reached the clinic. Even FDA approved PCA3 test has low sensitivity and limitations in predicting aggressive PC

  20. Prognostic and predictive potential molecular biomarkers in colon cancer.

    Science.gov (United States)

    Nastase, A; Pâslaru, L; Niculescu, A M; Ionescu, M; Dumitraşcu, T; Herlea, V; Dima, S; Gheorghe, C; Lazar, V; Popescu, I

    2011-01-01

    An important objective in nowadays research is the discovery of new biomarkers that can detect colon tumours in early stages and indicate with accuracy the status of the disease. The aim of our study was to identify potential biomarkers for colon cancer onset and progression. We assessed gene expression profiles of a list of 10 candidate genes (MMP-1, MMP-3, MMP-7, DEFA 1, DEFA-5, DEFA-6, IL-8, CXCL-1, SPP-1, CTHRC-1) by quantitative real time PCR in triplets of colonic mucosa (normal, adenoma, tumoral tissue) collected from the same patient during surgery for a group of 20 patients. Additionally we performed immunohistochemistry for DEFA1-3 and SPP1. We remarked that DEFA5 and DEFA6 are key factors in adenoma formation (p<0.05). MMP7 is important in the transition from a benign to a malignant status (p <0.01) and further in metastasis being a prognostic indicator for tumor transformation and for the metastatic potential of cancer cells. IL8, irrespective of tumor stage, has a high mRNA level in adenocarcinoma (p< 0.05). The level of expression for SPP1 is correlated with tumor level. We suggest that high levels of DEFAS, DEFA6 (key elements in adenoma formation), MMP7 (marker of colon cancer onset and progression to metastasis), SPP1 (marker of progression) and IL8 could be used to diagnose an early stage colon cancer and to evaluate the prognostic of progression for colon tumors. Further, if DEFA5 and DEFA6 level of expression are low but MMP7, SPP1 and IL8 level are high we could point out that the transition from adenoma to adenocarcinoma had already occurred. Thus, DEFA5, DEFA6, MMP7, IL8 and SPP1 consist in a valuable panel of biomarkers, whose detection can be used in early detection and progressive disease and also in prognostic of colon cancer.

  1. A statistical approach to evaluate the performance of cardiac biomarkers in predicting death due to acute myocardial infarction: time-dependent ROC curve

    Science.gov (United States)

    Karaismailoğlu, Eda; Dikmen, Zeliha Günnur; Akbıyık, Filiz; Karaağaoğlu, Ahmet Ergun

    2018-04-30

    Background/aim: Myoglobin, cardiac troponin T, B-type natriuretic peptide (BNP), and creatine kinase isoenzyme MB (CK-MB) are frequently used biomarkers for evaluating risk of patients admitted to an emergency department with chest pain. Recently, time- dependent receiver operating characteristic (ROC) analysis has been used to evaluate the predictive power of biomarkers where disease status can change over time. We aimed to determine the best set of biomarkers that estimate cardiac death during follow-up time. We also obtained optimal cut-off values of these biomarkers, which differentiates between patients with and without risk of death. A web tool was developed to estimate time intervals in risk. Materials and methods: A total of 410 patients admitted to the emergency department with chest pain and shortness of breath were included. Cox regression analysis was used to determine an optimal set of biomarkers that can be used for estimating cardiac death and to combine the significant biomarkers. Time-dependent ROC analysis was performed for evaluating performances of significant biomarkers and a combined biomarker during 240 h. The bootstrap method was used to compare statistical significance and the Youden index was used to determine optimal cut-off values. Results : Myoglobin and BNP were significant by multivariate Cox regression analysis. Areas under the time-dependent ROC curves of myoglobin and BNP were about 0.80 during 240 h, and that of the combined biomarker (myoglobin + BNP) increased to 0.90 during the first 180 h. Conclusion: Although myoglobin is not clinically specific to a cardiac event, in our study both myoglobin and BNP were found to be statistically significant for estimating cardiac death. Using this combined biomarker may increase the power of prediction. Our web tool can be useful for evaluating the risk status of new patients and helping clinicians in making decisions.

  2. The Growing Need for Validated Biomarkers and Endpoints for Dry Eye Clinical Research.

    Science.gov (United States)

    Roy, Neeta S; Wei, Yi; Kuklinski, Eric; Asbell, Penny A

    2017-05-01

    Biomarkers with minimally invasive and reproducible objective metrics provide the key to future paradigm shifts in understanding of the underlying causes of dry eye disease (DED) and approaches to treatment of DED. We review biomarkers and their validity in providing objective metrics for DED clinical research and patient care. The English-language literature in PubMed primarily over the last decade was surveyed for studies related to identification of biomarkers of DED: (1) inflammation, (2) point-of-care, (3) ocular imaging, and (4) genetics. Relevant studies in each group were individually evaluated for (1) methodological and analytical details, (2) data and concordance with other similar studies, and (3) potential to serve as validated biomarkers with objective metrics. Significant work has been done to identify biomarkers for DED clinical trials and for patient care. Interstudy variation among studies dealing with the same biomarker type was high. This could be attributed to biologic variations and/or differences in processing, and data analysis. Correlation with other signs and symptoms of DED was not always clear or present. Many of the biomarkers reviewed show the potential to serve as validated and objective metrics for clinical research and patient care in DED. Interstudy variation for a given biomarker emphasizes the need for detailed reporting of study methodology, including information on subject characteristics, quality control, processing, and analysis methods to optimize development of nonsubjective metrics. Biomarker development offers a rich opportunity to significantly move forward clinical research and patient care in DED. DED is an unmet medical need - a chronic pain syndrome associated with variable vision that affects quality of life, is common with advancing age, interferes with the comfortable use of contact lenses, and can diminish results of eye surgeries, such as cataract extraction, LASIK, and glaucoma procedures. It is a worldwide

  3. Predictive biomarkers for type 2 of diabetes mellitus: Bridging the gap between systems research and personalized medicine.

    Science.gov (United States)

    Kraniotou, Christina; Karadima, Vasiliki; Bellos, George; Tsangaris, George Th

    2018-03-05

    The global incidence of metabolic disorders like type 2 diabetes mellitus (DM2) has assumed epidemic proportions, leading to adverse health and socio-economic impacts. It is therefore of critical importance the early diagnosis of DM2 patients and the detection of those at increased risk of disease. In this respect, Precision Medicine (PM) is an emerging approach that includes practices, tests, decisions and treatments adapted to the characteristics of each patient. With regard to DM2, PM manages a wealth of "omics" data (genomic, metabolic, proteomic, environmental, clinical and paraclinical) to increase the number of clinically validated biomarkers in order to identify patients in early stage even before the prediabetic phase. In this paper, we discuss the epidemic dimension of metabolic disorders like type 2 diabetes mellitus (DM2) and the urgent demand for novel biomarkers to reduce the incidence or even delay the onset of DM2. Recent research data produced by "multi-omics" technologies (genomics/epigenomics, transcriptomics, proteomics and metabolomics), suggest that many potential biomarkers might be helpful in the prediction and early diagnosis of DM2. Predictive, Preventive and Personalized Medicine (PPPM) manages and integrates these data to apply personalized, preventive, and therapeutic approaches. This is significant because there is an emerging need for establishing channels for communication and personalized consultation between systems research and precision medicine, as the medicine of the future. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Reinventing clinical trials: a review of innovative biomarker trial designs in cancer therapies.

    Science.gov (United States)

    Lin, Ja-An; He, Pei

    2015-06-01

    Recently, new clinical trial designs involving biomarkers have been studied and proposed in cancer clinical research, in the hope of incorporating the rapid growing basic research into clinical practices. Journal articles related to various biomarkers and their role in cancer clinical trial, articles and books about statistical issues in trial design, and regulatory website, documents, and guidance for submission of targeted cancer therapies. The drug development process involves four phases. The confirmatory Phase III is essential in regulatory approval of a special treatment. Regulatory agency has restrictions on confirmatory trials 'using adaptive designs'. No rule of thumb to pick the most appropriate design for biomarker-related trials. Statistical issues to solve in new designs. Regulatory acceptance of the 'newly proposed trial designs'. Biomarker-related trial designs that can resolve the statistical issues and satisfy the regulatory requirement. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Identification of airway mucosal type 2 inflammation by using clinical biomarkers in asthmatic patients.

    Science.gov (United States)

    Silkoff, Philip E; Laviolette, Michel; Singh, Dave; FitzGerald, J Mark; Kelsen, Steven; Backer, Vibeke; Porsbjerg, Celeste M; Girodet, Pierre-Olivier; Berger, Patrick; Kline, Joel N; Chupp, Geoffrey; Susulic, Vedrana S; Barnathan, Elliot S; Baribaud, Frédéric; Loza, Matthew J

    2017-09-01

    The Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study profiled patients with mild, moderate, and severe asthma and nonatopic healthy control subjects. We explored this data set to define type 2 inflammation based on airway mucosal IL-13-driven gene expression and how this related to clinically accessible biomarkers. IL-13-driven gene expression was evaluated in several human cell lines. We then defined type 2 status in 25 healthy subjects, 28 patients with mild asthma, 29 patients with moderate asthma, and 26 patients with severe asthma based on airway mucosal expression of (1) CCL26 (the most differentially expressed gene), (2) periostin, or (3) a multigene IL-13 in vitro signature (IVS). Clinically accessible biomarkers included fraction of exhaled nitric oxide (Feno) values, blood eosinophil (bEOS) counts, serum CCL26 expression, and serum CCL17 expression. Expression of airway mucosal CCL26, periostin, and IL-13-IVS all facilitated segregation of subjects into type 2-high and type 2-low asthmatic groups, but in the ADEPT study population CCL26 expression was optimal. All subjects with high airway mucosal CCL26 expression and moderate-to-severe asthma had Feno values (≥35 ppb) and/or high bEOS counts (≥300 cells/mm 3 ) compared with a minority (36%) of subjects with low airway mucosal CCL26 expression. A combination of Feno values, bEOS counts, and serum CCL17 and CCL26 expression had 100% positive predictive value and 87% negative predictive value for airway mucosal CCL26-high status. Clinical variables did not differ between subjects with type 2-high and type 2-low status. Eosinophilic inflammation was associated with but not limited to airway mucosal type 2 gene expression. A panel of clinical biomarkers accurately classified type 2 status based on airway mucosal CCL26, periostin, or IL-13-IVS gene expression. Use of Feno values, bEOS counts, and serum marker levels (eg, CCL26 and CCL17) in combination might allow patient

  6. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2012-01-31

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15+\\/-1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15+\\/-1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  7. Robust Early Pregnancy Prediction of Later Preeclampsia Using Metabolomic Biomarkers.

    LENUS (Irish Health Repository)

    Kenny, Louise C

    2010-09-13

    Preeclampsia is a pregnancy-specific syndrome that causes substantial maternal and fetal morbidity and mortality. The etiology is incompletely understood, and there is no clinically useful screening test. Current metabolomic technologies have allowed the establishment of metabolic signatures of preeclampsia in early pregnancy. Here, a 2-phase discovery\\/validation metabolic profiling study was performed. In the discovery phase, a nested case-control study was designed, using samples obtained at 15±1 weeks\\' gestation from 60 women who subsequently developed preeclampsia and 60 controls taking part in the prospective Screening for Pregnancy Endpoints cohort study. Controls were proportionally population matched for age, ethnicity, and body mass index at booking. Plasma samples were analyzed using ultra performance liquid chromatography-mass spectrometry. A multivariate predictive model combining 14 metabolites gave an odds ratio for developing preeclampsia of 36 (95% CI: 12 to 108), with an area under the receiver operator characteristic curve of 0.94. These findings were then validated using an independent case-control study on plasma obtained at 15±1 weeks from 39 women who subsequently developed preeclampsia and 40 similarly matched controls from a participating center in a different country. The same 14 metabolites produced an odds ratio of 23 (95% CI: 7 to 73) with an area under receiver operator characteristic curve of 0.92. The finding of a consistent discriminatory metabolite signature in early pregnancy plasma preceding the onset of preeclampsia offers insight into disease pathogenesis and offers the tantalizing promise of a robust presymptomatic screening test.

  8. Clinical, functional, behavioural and epigenomic biomarkers of obesity.

    Science.gov (United States)

    Lafortuna, Claudio L; Tovar, Armando R; Rastelli, Fabio; Tabozzi, Sarah A; Caramenti, Martina; Orozco-Ruiz, Ximena; Aguilar-Lopez, Miriam; Guevara-Cruz, Martha; Avila-Nava, Azalia; Torres, Nimbe; Bertoli, Gloria

    2017-06-01

    Overweight and obesity are highly prevalent conditions worldwide, linked to an increased risk for death, disability and disease due to metabolic and biochemical abnormalities affecting the biological human system throughout different domains. Biomarkers, defined as indicators of biological processes in health and disease, relevant for body mass excess management have been identified according to different criteria, including anthropometric and molecular indexes, as well as physiological and behavioural aspects. Analysing these different biomarkers, we identified their potential role in diagnosis, prognosis and treatment. Epigenetic biomarkers, cellular mediators of inflammation and factors related to microbiota-host interactions may be considered to have a theranostic value. Though, the molecular processes responsible for the biological phenomenology detected by the other analysed markers, is not clear yet. Nevertheless, these biomarkers possess valuable diagnostic and prognostic power. A new frontier for theranostic biomarkers can be foreseen in the exploitation of parameters defining behaviours and lifestyles linked to the risk of obesity, capable to describe the effects of interventions for obesity prevention and treatment which include also behaviour change strategies.

  9. Prediction of Chronic Kidney Disease Stage 3 by CKD273, a Urinary Proteomic Biomarker

    DEFF Research Database (Denmark)

    Pontillo, Claudia; Zhang, Zhen-Yu; Schanstra, Joost P

    2017-01-01

    Introduction: CKD273 is a urinary biomarker, which in advanced chronic kidney disease predicts further deterioration. We investigated whether CKD273 can also predict a decline of estimated glomerular filtration rate (eGFR) to ... threshold (P = 0.086). Discussion: In conclusion, while accounting for baseline eGFR, albuminuria, and covariables, CKD273 adds to the prediction of stage 3 chronic kidney disease, at which point intervention remains an achievable therapeutic target....

  10. Can common serum biomarkers predict complicated appendicitis in children?

    Science.gov (United States)

    Zani, Augusto; Teague, Warwick J; Clarke, Simon A; Haddad, Munther J; Khurana, Sanjeev; Tsang, Thomas; Nataraja, Ramesh M

    2017-07-01

    As appendicitis in children can be managed differently according to the severity of the disease, we investigated whether commonly used serum biomarkers on admission could distinguish between simple and complicated appendicitis. Admission white blood cell (WBC), neutrophil (NEU), and C-reactive protein (CRP) levels were analysed by ROC curve, and Kruskal-Wallis and contingency tests. Patients were divided according to age and histology [normal appendix (NA), simple appendicitis (SA), complicated appendicitis (CA)]. Of 1197 children (NA = 186, SA = 685, CA = 326), 7% were 40 mg/L in 58% CA and 37% SA (p 15 × 10 9 /L in 58% CA and 43% SA (p appendicitis in children older than 5 years of age. Early distinction of appendicitis severity using these tests may guide caregivers in the preoperative decision-making process.

  11. Usability of cerebrospinal fluid biomarkers in a tertiary memory clinic

    DEFF Research Database (Denmark)

    Brandt, C.; Bahl, J.C.; Heegaard, N.H.

    2008-01-01

    AIM: Assays for cerebrospinal fluid (CSF) levels of total tau, phospho-tau protein and beta-amyloid 1-42 have been available for some years. The aim of the study was to assess the usability of these biomarkers in a mixed population of tertiary dementia referral patients in a university-based memory......, the sensitivity of a single abnormal value was between 33 and 66%. The specificity was high except when discriminating AD from amnestic mild cognitive impairment. Two or more abnormal markers further increased the specificity and decreased the sensitivity. CONCLUSION: In a tertiary setting, abnormal CSF biomarker...

  12. The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

    Science.gov (United States)

    Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark

    2016-01-01

    ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479

  13. Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma

    DEFF Research Database (Denmark)

    Lauss, Martin; Donia, Marco; Harbst, Katja

    2017-01-01

    Adoptive T-cell therapy (ACT) is a highly intensive immunotherapy regime that has yielded remarkable response rates and many durable responses in clinical trials in melanoma; however, 50-60% of the patients have no clinical benefit. Here, we searched for predictive biomarkers to ACT in melanoma. ...

  14. Long-term Prognosis in COPD Exacerbation: Role of Biomarkers, Clinical Variables and Exacerbation Type.

    Science.gov (United States)

    Grolimund, Eva; Kutz, Alexander; Marlowe, Robert J; Vögeli, Alaadin; Alan, Murat; Christ-Crain, Mirjam; Thomann, Robert; Falconnier, Claudine; Hoess, Claus; Henzen, Christoph; Zimmerli, Werner; Mueller, Beat; Schuetz, Philipp

    2015-06-01

    Long-term outcome prediction in COPD is challenging. We conducted a prospective 5-7-year follow-up study in patients with COPD to determine the association of exacerbation type, discharge levels of inflammatory biomarkers including procalctionin (PCT), C-reactive protein (CRP), white blood cell count (WBC) and plasma proadrenomedullin (ProADM), alone or combined with demographic/clinical characteristics, with long-term all-cause mortality in the COPD setting. The analyzed cohort comprised 469 patients with index hospitalization for pneumonic (n = 252) or non-pneumonic (n = 217) COPD exacerbation. Five-to-seven-year vital status was ascertained via structured phone interviews with patients or their household members/primary care physicians. We investigated predictive accuracy using univariate and multivariate Cox regression models and area under the receiver operating characteristic curve (AUC). After a median [25th-75th percentile] 6.1 [5.6-6.5] years, mortality was 55% (95%CI 50%-59%). Discharge ProADM concentration was strongly associated with 5-7-year non-survival: adjusted hazard ratio (HR)/10-fold increase (95%CI) 10.4 (6.2-17.7). Weaker associations were found for PCT and no significant associations were found for CRP or WBC. Combining ProADM with demographic/clinical variables including age, smoking status, BMI, New York Heart Association dyspnea class, exacerbation type, and comorbidities significantly improved long-term predictive accuracy over that of the demographic/clinical model alone: AUC (95%CI) 0.745 (0.701-0.789) versus 0.727 (0.681-0.772), (p) = .043. In patients hospitalized for COPD exacerbation, discharge ProADM levels appeared to accurately predict 5-7-year all-cause mortality and to improve long-term prognostic accuracy of multidimensional demographic/clinical mortality risk assessment.

  15. Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

    Science.gov (United States)

    Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

    2013-01-01

    Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

  16. Clinical evaluation of chemokine and enzymatic biomarkers of Gaucher disease

    NARCIS (Netherlands)

    Deegan, Patrick B.; Moran, Mary Teresa; McFarlane, Ian; Schofield, J. Paul; Boot, Rolf G.; Aerts, Johannes M. F. G.; Cox, Timothy M.

    2005-01-01

    Purpose: Gaucher disease is an exemplary orphan disorder. Enzyme replacement therapy with imiglucerase is effective, but very expensive. To improve the assessment of severity of disease and responses to this costly treatment, we have evaluated several enzymatic biomarkers and a newly-described

  17. Identification of Biomarkers for Endometriosis Using Clinical Proteomics

    Directory of Open Access Journals (Sweden)

    Yang Zhao

    2015-01-01

    Full Text Available Background: We investigated possible biomarkers for endometriosis (EM using the ClinProt technique and proteomics methods. Methods: We enrolled 50 patients with EM, 34 with benign ovarian neoplasms and 40 healthy volunteers in this study. Serum proteomic spectra were generated by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MS combined with weak cationic exchange (WCX magnetic beads. Possible biomarkers were analyzed by a random and repeat pattern model-validation method that we designed, and ClinProtools software, results were refined using online liquid chromatography-tandem MS. Results: We found a cluster of 5 peptides (4210, 5264, 2660, 5635, and 5904 Da, using 3 peptides (4210, 5904, 2660 Da to discriminate EM patients from healthy volunteers, with 96.67% sensitivity and 100% specificity. We selected 4210 and 5904 m/z, which differed most between patients with EM and controls, and identified them as fragments of ATP1B4, and the fibrinogen alpha (FGA isoform 1/2 of the FGA chain precursor, respectively. Conclusions: ClinProt can identify EM biomarkers, which - most notably - distinguish even early-stage or minimal disease. We found 5 stable peaks at 4210, 5264, 2660, 5635, and 5904 Da as potential EM biomarkers, the strongest of which were associated with ATP1B4 (4210 Da and FGA (5904 Da; this indicates that ATP1B4 and FGA are associated with EM pathogenesis.

  18. Cerebrospinal Fluid Biomarkers in Diagnosing Alzheimer's Disease in Clinical Practice

    DEFF Research Database (Denmark)

    Slats, Diane; Spies, Petra E; Sjögren, Magnus J C

    2010-01-01

    Analysis of the brain specific biomarkers amyloid beta(42) (Abeta(42)) and total tau (t-tau) protein in cerebrospinal fluid (CSF) has a sensitivity and specificity of more than 85% for differentiating Alzheimer's Disease (AD) from non-demented controls. International guidelines are contradictory...

  19. Current and Future Applications of Biomedical Engineering for Proteomic Profiling: Predictive Biomarkers in Neuro-Traumatology

    Directory of Open Access Journals (Sweden)

    Mario Ganau

    2018-02-01

    Full Text Available This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers in patients with traumatic brain injury (TBI, a critical worldwide health problem with an estimated 10 billion people affected annually worldwide. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials. Only experimental articles revolving around the management of TBI, in which the role of new devices based on innovative discoveries coming from the field of nanotechnology and biomedical engineering were highlighted, have been included and analyzed in this study. Based on theresults gathered from this research on innovative methods for genomics, epigenomics, and proteomics, their future application in this field seems promising. Despite the outstanding technical challenges of identifying reliable biosignatures for TBI and the mixed nature of studies herein described (single cells proteomics, biofilms, sensors, etc., the clinical implementation of those discoveries will allow us to gain confidence in the use of advanced neuromonitoring modalities with a potential dramatic improvement in the management of those patients.

  20. Systems Biology-Derived Biomarkers to Predict Progression of Renal Function Decline in Type 2 Diabetes

    NARCIS (Netherlands)

    Mayer, Gert; Heerspink, Hiddo J. L.; Aschauer, Constantin; Heinzel, Andreas; Heinze, Georg; Kainz, Alexander; Sunzenauer, Judith; Perco, Paul; de Zeeuw, Dick; Rossing, Peter; Pena, Michelle; Oberbauer, Rainer

    OBJECTIVE: Chronic kidney disease (CKD) in diabetes has a complex molecular and likely multifaceted pathophysiology. We aimed to validate a panel of biomarkers identified using a systems biology approach to predict the individual decline of estimated glomerular filtration rate (eGFR) in a large

  1. Identification of a 5-protein biomarker molecular signature for predicting Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Martín Gómez Ravetti

    Full Text Available BACKGROUND: Alzheimer's disease (AD is a progressive brain disease with a huge cost to human lives. The impact of the disease is also a growing concern for the governments of developing countries, in particular due to the increasingly high number of elderly citizens at risk. Alzheimer's is the most common form of dementia, a common term for memory loss and other cognitive impairments. There is no current cure for AD, but there are drug and non-drug based approaches for its treatment. In general the drug-treatments are directed at slowing the progression of symptoms. They have proved to be effective in a large group of patients but success is directly correlated with identifying the disease carriers at its early stages. This justifies the need for timely and accurate forms of diagnosis via molecular means. We report here a 5-protein biomarker molecular signature that achieves, on average, a 96% total accuracy in predicting clinical AD. The signature is composed of the abundances of IL-1alpha, IL-3, EGF, TNF-alpha and G-CSF. METHODOLOGY/PRINCIPAL FINDINGS: Our results are based on a recent molecular dataset that has attracted worldwide attention. Our paper illustrates that improved results can be obtained with the abundance of only five proteins. Our methodology consisted of the application of an integrative data analysis method. This four step process included: a abundance quantization, b feature selection, c literature analysis, d selection of a classifier algorithm which is independent of the feature selection process. These steps were performed without using any sample of the test datasets. For the first two steps, we used the application of Fayyad and Irani's discretization algorithm for selection and quantization, which in turn creates an instance of the (alpha-beta-k-Feature Set problem; a numerical solution of this problem led to the selection of only 10 proteins. CONCLUSIONS/SIGNIFICANCE: the previous study has provided an extremely

  2. Current Role for Biomarkers in Clinical Diagnosis of Alzheimer Disease and Frontotemporal Dementia.

    Science.gov (United States)

    Sheikh-Bahaei, Nasim; Sajjadi, Seyed Ahmad; Pierce, Aimee L

    2017-11-14

    Purpose of review Alzheimer's disease (AD) and frontotemporal dementia can often be diagnosed accurately with careful clinical history, cognitive testing, neurological examination, and structural brain MRI. However, there are certain circumstances wherein detection of specific biomarkers of neurodegeneration or underlying AD pathology will impact the clinical diagnosis or treatment plan. We will review the currently available biomarkers for AD and frontotemporal dementia (FTD) and discuss their clinical importance. Recent findings With the advent of 18 F-labeled tracers that bind amyloid plaques, amyloid PET is now clinically available for the detection of amyloid pathology and to aid in a biomarker-supported diagnosis of AD or mild cognitive impairment (MCI) due to AD. It is not yet possible to test for the specific FTD pathologies (tau or TDP-43); however, a diagnosis of FTD may be "imaging supported" based upon specific MRI or FDG-PET findings. Cerebrospinal fluid measures of amyloid-beta, total-tau, and phospho-tau are clinically available and allow detection of both of the cardinal pathologies of AD: amyloid and tau pathology. Summary It is appropriate to pursue biomarker testing in cases of MCI and dementia when there remains diagnostic uncertainty and the result will impact diagnosis or treatment. Practically speaking, due to the rising prevalence of amyloid positivity with advancing age, measurement of biomarkers in cases of MCI and dementia is most helpful in early-onset patients, patients with atypical clinical presentations, or when considering referral for AD clinical trials.

  3. A Contemporary Review of the Treatment Landscape and the Role of Predictive and Prognostic Biomarkers in Pancreatic Adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Irene S. Yu

    2018-01-01

    Full Text Available Pancreatic cancer continues to represent one of the leading causes of cancer-related morbidity and mortality in the developed world. Over the past decade, novel systemic therapy combination regimens have contributed to clinically meaningful and statistically significant improvements in overall survival as compared to conventional monotherapy. However, the prognosis for most patients remains guarded secondary to the advanced stages of disease at presentation. There is growing consensus that outcomes can be further optimized with the use of predictive and prognostic biomarkers whereby the former can be enriching for patients who would benefit from therapies and the latter can inform decision-making regarding the need and timing of advanced care planning. One of the challenges of current biomarkers is the lack of standardization across clinical practices such that comparability between jurisdictions can be difficult or even impossible. This inconsistency can impede widespread implementation of their use. In this review article, we provide a comprehensive overview of the contemporary treatment options for pancreatic cancer and we offer some insights into the existing landscape and future directions of biomarker development for this disease.

  4. Clinical Relevance of Prognostic and Predictive Molecular Markers in Gliomas.

    Science.gov (United States)

    Siegal, Tali

    2016-01-01

    Sorting and grading of glial tumors by the WHO classification provide clinicians with guidance as to the predicted course of the disease and choice of treatment. Nonetheless, histologically identical tumors may have very different outcome and response to treatment. Molecular markers that carry both diagnostic and prognostic information add useful tools to traditional classification by redefining tumor subtypes within each WHO category. Therefore, molecular markers have become an integral part of tumor assessment in modern neuro-oncology and biomarker status now guides clinical decisions in some subtypes of gliomas. The routine assessment of IDH status improves histological diagnostic accuracy by differentiating diffuse glioma from reactive gliosis. It carries a favorable prognostic implication for all glial tumors and it is predictive for chemotherapeutic response in anaplastic oligodendrogliomas with codeletion of 1p/19q chromosomes. Glial tumors that contain chromosomal codeletion of 1p/19q are defined as tumors of oligodendroglial lineage and have favorable prognosis. MGMT promoter methylation is a favorable prognostic marker in astrocytic high-grade gliomas and it is predictive for chemotherapeutic response in anaplastic gliomas with wild-type IDH1/2 and in glioblastoma of the elderly. The clinical implication of other molecular markers of gliomas like mutations of EGFR and ATRX genes and BRAF fusion or point mutation is highlighted. The potential of molecular biomarker-based classification to guide future therapeutic approach is discussed and accentuated.

  5. Circulating biomarkers for predicting cardiovascular disease risk; a systematic review and comprehensive overview of meta-analyses.

    Directory of Open Access Journals (Sweden)

    Thijs C van Holten

    Full Text Available BACKGROUND: Cardiovascular disease is one of the major causes of death worldwide. Assessing the risk for cardiovascular disease is an important aspect in clinical decision making and setting a therapeutic strategy, and the use of serological biomarkers may improve this. Despite an overwhelming number of studies and meta-analyses on biomarkers and cardiovascular disease, there are no comprehensive studies comparing the relevance of each biomarker. We performed a systematic review of meta-analyses on levels of serological biomarkers for atherothrombosis to compare the relevance of the most commonly studied biomarkers. METHODS AND FINDINGS: Medline and Embase were screened on search terms that were related to "arterial ischemic events" and "meta-analyses". The meta-analyses were sorted by patient groups without pre-existing cardiovascular disease, with cardiovascular disease and heterogeneous groups concerning general populations, groups with and without cardiovascular disease, or miscellaneous. These were subsequently sorted by end-point for cardiovascular disease or stroke and summarized in tables. We have identified 85 relevant full text articles, with 214 meta-analyses. Markers for primary cardiovascular events include, from high to low result: C-reactive protein, fibrinogen, cholesterol, apolipoprotein B, the apolipoprotein A/apolipoprotein B ratio, high density lipoprotein, and vitamin D. Markers for secondary cardiovascular events include, from high to low result: cardiac troponins I and T, C-reactive protein, serum creatinine, and cystatin C. For primary stroke, fibrinogen and serum uric acid are strong risk markers. Limitations reside in that there is no acknowledged search strategy for prognostic studies or meta-analyses. CONCLUSIONS: For primary cardiovascular events, markers with strong predictive potential are mainly associated with lipids. For secondary cardiovascular events, markers are more associated with ischemia. Fibrinogen is a

  6. Predictive Biomarkers of Gastroesophageal Reflux Disease and Barrett's Esophagus in World Trade Center Exposed Firefighters: a 15 Year Longitudinal Study.

    Science.gov (United States)

    Haider, Syed H; Kwon, Sophia; Lam, Rachel; Lee, Audrey K; Caraher, Erin J; Crowley, George; Zhang, Liqun; Schwartz, Theresa M; Zeig-Owens, Rachel; Liu, Mengling; Prezant, David J; Nolan, Anna

    2018-02-15

    Gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE), which are prevalent in the World Trade Center (WTC) exposed and general populations, negatively impact quality of life and cost of healthcare. GERD, a risk factor of BE, is linked to obstructive airways disease (OAD). We aim to identify serum biomarkers of GERD/BE, and assess the respiratory and clinical phenotype of a longitudinal cohort of never-smoking, male, WTC-exposed rescue workers presenting with pulmonary symptoms. Biomarkers collected soon after WTC-exposure were evaluated in optimized predictive models of GERD/BE. In the WTC-exposed cohort, the prevalence of BE is at least 6 times higher than in the general population. GERD/BE cases had similar lung function, D LCO , bronchodilator response and long-acting β-agonist use compared to controls. In confounder-adjusted regression models, TNF-α ≥ 6 pg/mL predicted both GERD and BE. GERD was also predicted by C-peptide ≥ 360 pg/mL, while BE was predicted by fractalkine ≥ 250 pg/mL and IP-10 ≥ 290 pg/mL. Finally, participants with GERD had significantly increased use of short-acting β-agonist compared to controls. Overall, biomarkers sampled prior to GERD/BE presentation showed strong predictive abilities of disease development. This study frames future investigations to further our understanding of aerodigestive pathology due to particulate matter exposure.

  7. Evaluation of candidate biomarkers to predict cancer cell sensitivity or resistance to PARP-1 inhibitor treatment

    DEFF Research Database (Denmark)

    Oplustilova, L.; Wolanin, K.; Bartkova, J.

    2012-01-01

    combinations with camptothecin or ionizing radiation. Furthermore, monitoring pARsylation and Rad51 foci formation as surrogate markers for PARP activity and HR, respectively, supported their candidacy for biomarkers of PARP-1i responses. As to resistance mechanisms, we confrmed the role of the multidrug......(ADp-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response...

  8. Taxane resistance in breast cancer: mechanisms, predictive biomarkers and circumvention strategies.

    Science.gov (United States)

    Murray, S; Briasoulis, E; Linardou, H; Bafaloukos, D; Papadimitriou, C

    2012-11-01

    prominent finding is that pharmaceutical down-regulation of HER-2 appears to reverse the taxane resistance. Currently no valid practical biomarkers exist that can predict resistance to the taxanes in breast cancer supporting the principle of individualized cancer therapy. The incorporation of several biomarker analyses into prospectively designed studies in this setting are needed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  9. FDG-PET as a predictive biomarker for therapy with everolimus in metastatic renal cell cancer

    International Nuclear Information System (INIS)

    Chen, James L; Appelbaum, Daniel E; Kocherginsky, Masha; Cowey, Charles L; Kimryn Rathmell, Wendy; McDermott, David F; Stadler, Walter M

    2013-01-01

    The mTOR (mammalian target of rapamycin) inhibitor, everolimus, affects tumor growth by targeting cellular metabolic proliferation pathways and delays renal cell carcinoma (RCC) progression. Preclinical evidence suggests that baseline elevated tumor glucose metabolism as quantified by FDG-PET ([ 18 F] fluorodeoxy-glucose positron emission tomography) may predict antitumor activity. Metastatic RCC (mRCC) patients refractory to vascular endothelial growth factor (VEGF) pathway inhibition were treated with standard dose everolimus. FDG-PET scans were obtained at baseline and 2 weeks; serial computed tomography (CT) scans were obtained at baseline and every 8 weeks. Maximum standardized uptake value (SUVmax) of the most FDG avid lesion, average SUVmax of all measured lesions and their corresponding 2-week relative changes were examined for association with 8-week change in tumor size. A total of 63 patients were enrolled; 50 were evaluable for the primary endpoint of which 48 had both PET scans. Patient characteristics included the following: 36 (72%) clear cell histology and median age 59 (range: 37–80). Median pre- and 2-week treatment average SUVmax were 6.6 (1–17.9) and 4.2 (1–13.9), respectively. Response evaluation criteria in solid tumors (RECIST)-based measurements demonstrated an average change in tumor burden of 0.2% (−32.7% to 35.9%) at 8 weeks. Relative change in average SUVmax was the best predictor of change in tumor burden (all evaluable P = 0.01; clear cell subtype P = 0.02), with modest correlation. Baseline average SUVmax was correlated with overall survival and progression-free survival (PFS) (P = 0.023; 0.020), but not with change in tumor burden. Everolimus therapy decreased SUVs on follow-up PET scans in mRCC patients, but changes were only modestly correlated with changes in tumor size. Thus, clinical use of FDG-PET-based biomarkers is challenged by high variability. In this phase II trial, FDG-PET was explored as a predictive biomarker

  10. A prospective phase II trial exploring the association between tumor microenvironment biomarkers and clinical activity of ipilimumab in advanced melanoma

    Directory of Open Access Journals (Sweden)

    Hamid Omid

    2011-11-01

    ipilimumab clinical activity. The observed pharmacodynamic changes in gene expression warrant further analysis to determine whether treatment-emergent changes in gene expression may be associated with clinical efficacy. Further studies are required to determine the predictive value of these and other potential biomarkers associated with clinical response to ipilimumab.

  11. Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research.

    Science.gov (United States)

    W Adams, Zachary; McClure, Erin A; Gray, Kevin M; Danielson, Carla Kmett; Treiber, Frank A; Ruggiero, Kenneth J

    2017-02-01

    Psychiatric disorders are linked to a variety of biological, psychological, and contextual causes and consequences. Laboratory studies have elucidated the importance of several key physiological and behavioral biomarkers in the study of psychiatric disorders, but much less is known about the role of these biomarkers in naturalistic settings. These gaps are largely driven by methodological barriers to assessing biomarker data rapidly, reliably, and frequently outside the clinic or laboratory. Mobile health (mHealth) tools offer new opportunities to study relevant biomarkers in concert with other types of data (e.g., self-reports, global positioning system data). This review provides an overview on the state of this emerging field and describes examples from the literature where mHealth tools have been used to measure a wide array of biomarkers in the context of psychiatric functioning (e.g., psychological stress, anxiety, autism, substance use). We also outline advantages and special considerations for incorporating mHealth tools for remote biomarker measurement into studies of psychiatric illness and treatment and identify several specific opportunities for expanding this promising methodology. Integrating mHealth tools into this area may dramatically improve psychiatric science and facilitate highly personalized clinical care of psychiatric disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Alzheimer Disease Biomarkers as Outcome Measures for Clinical Trials in MCI.

    Science.gov (United States)

    Caroli, Anna; Prestia, Annapaola; Wade, Sara; Chen, Kewei; Ayutyanont, Napatkamon; Landau, Susan M; Madison, Cindee M; Haense, Cathleen; Herholz, Karl; Reiman, Eric M; Jagust, William J; Frisoni, Giovanni B

    2015-01-01

    The aim of this study was to compare the performance and power of the best-established diagnostic biological markers as outcome measures for clinical trials in patients with mild cognitive impairment (MCI). Magnetic resonance imaging, F-18 fluorodeoxyglucose positron emission tomography markers, and Alzheimer's Disease Assessment Scale-cognitive subscale were compared in terms of effect size and statistical power over different follow-up periods in 2 MCI groups, selected from Alzheimer's Disease Neuroimaging Initiative data set based on cerebrospinal fluid (abnormal cerebrospinal fluid Aβ1-42 concentration-ABETA+) or magnetic resonance imaging evidence of Alzheimer disease (positivity to hippocampal atrophy-HIPPO+). Biomarkers progression was modeled through mixed effect models. Scaled slope was chosen as measure of effect size. Biomarkers power was estimated using simulation algorithms. Seventy-four ABETA+ and 51 HIPPO+ MCI patients were included in the study. Imaging biomarkers of neurodegeneration, especially MR measurements, showed highest performance. For all biomarkers and both MCI groups, power increased with increasing follow-up time, irrespective of biomarker assessment frequency. These findings provide information about biomarker enrichment and outcome measurements that could be employed to reduce MCI patient samples and treatment duration in future clinical trials.

  13. Ebola hemorrhagic Fever: novel biomarker correlates of clinical outcome.

    Science.gov (United States)

    McElroy, Anita K; Erickson, Bobbie R; Flietstra, Timothy D; Rollin, Pierre E; Nichol, Stuart T; Towner, Jonathan S; Spiropoulou, Christina F

    2014-08-15

    Ebola hemorrhagic fever (EHF) outbreaks occur sporadically in Africa and result in high rates of death. The 2000-2001 outbreak of Sudan virus-associated EHF in the Gulu district of Uganda led to 425 cases, of which 216 were laboratory confirmed, making it the largest EHF outbreak on record. Serum specimens from this outbreak had been preserved in liquid nitrogen from the time of collection and were available for analysis. Available samples were tested using a series of multiplex assays to measure the concentrations of 55 biomarkers. The data were analyzed to identify statistically significant associations between the tested biomarkers and hemorrhagic manifestations, viremia, and/or death. Death, hemorrhage, and viremia were independently associated with elevated levels of several chemokines and cytokines. Death and hemorrhage were associated with elevated thrombomodulin and ferritin levels. Hemorrhage was also associated with elevated levels of soluble intracellular adhesion molecule. Viremia was independently associated with elevated levels of tissue factor and tissue plasminogen activator. Finally, samples from nonfatal cases had higher levels of sCD40L. These novel associations provide a better understanding of EHF pathophysiology and a starting point for researching new potential targets for therapeutic interventions. Published by Oxford University Press on behalf of the Infectious Diseases Society of America 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  14. Clinical chemistry in higher dimensions: Machine-learning and enhanced prediction from routine clinical chemistry data.

    Science.gov (United States)

    Richardson, Alice; Signor, Ben M; Lidbury, Brett A; Badrick, Tony

    2016-11-01

    Big Data is having an impact on many areas of research, not the least of which is biomedical science. In this review paper, big data and machine learning are defined in terms accessible to the clinical chemistry community. Seven myths associated with machine learning and big data are then presented, with the aim of managing expectation of machine learning amongst clinical chemists. The myths are illustrated with four examples investigating the relationship between biomarkers in liver function tests, enhanced laboratory prediction of hepatitis virus infection, the relationship between bilirubin and white cell count, and the relationship between red cell distribution width and laboratory prediction of anaemia. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  15. Taking a new biomarker into routine use – A perspective from the routine clinical biochemistry laboratory

    Science.gov (United States)

    Sturgeon, Catharine; Hill, Robert; Hortin, Glen L; Thompson, Douglas

    2010-01-01

    There is increasing pressure to provide cost-effective healthcare based on “best practice.” Consequently, new biomarkers are only likely to be introduced into routine clinical biochemistry departments if they are supported by a strong evidence base and if the results will improve patient management and outcome. This requires convincing evidence of the benefits of introducing the new test, ideally reflected in fewer hospital admissions, fewer additional investigations and/or fewer clinic visits. Carefully designed audit and cost-benefit studies in relevant patient groups must demonstrate that introducing the biomarker delivers an improved and more effective clinical pathway. From the laboratory perspective, pre-analytical requirements must be thoroughly investigated at an early stage. Good stability of the biomarker in relevant physiological matrices is essential to avoid the need for special processing. Absence of specific timing requirements for sampling and knowledge of the effect of medications that might be used to treat the patients in whom the biomarker will be measured is also highly desirable. Analytically, automation is essential in modern high-throughput clinical laboratories. Assays must therefore be robust, fulfilling standard requirements for linearity on dilution, precision and reproducibility, both within- and between-run. Provision of measurements by a limited number of specialized reference laboratories may be most appropriate, especially when a new biomarker is first introduced into routine practice. PMID:21137030

  16. The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Hui; Shi, Tujin; Qian, Wei-Jun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2015-12-04

    Mass spectrometry-based proteomics has become an indispensable tool in biomedical research with broad applications ranging from fundamental biology, systems biology, and biomarker discovery. Recent advances in LC-MS have made it become a major technology in clinical applications, especially in cancer biomarker discovery and verification. To overcome the challenges associated with the analysis of clinical samples, such as extremely wide dynamic range of protein concentrations in biofluids and the need to perform high throughput and accurate quantification, significant efforts have been devoted to improve the overall performance of LC-MS bases clinical proteomics. In this review, we summarize the recent advances in LC-MS in the aspect of cancer biomarker discovery and quantification, and discuss its potentials, limitations, and future perspectives.

  17. APRIL is a novel clinical chemo-resistance biomarker in colorectal adenocarcinoma identified by gene expression profiling

    International Nuclear Information System (INIS)

    Petty, Russell D; Wang, Weiguang; Gilbert, Fiona; Semple, Scot; Collie-Duguid, Elaina SR; Samuel, Leslie M; Murray, Graeme I; MacDonald, Graham; O'Kelly, Terrence; Loudon, Malcolm; Binnie, Norman; Aly, Emad; McKinlay, Aileen

    2009-01-01

    5-Fluorouracil(5FU) and oral analogues, such as capecitabine, remain one of the most useful agents for the treatment of colorectal adenocarcinoma. Low toxicity and convenience of administration facilitate use, however clinical resistance is a major limitation. Investigation has failed to fully explain the molecular mechanisms of resistance and no clinically useful predictive biomarkers for 5FU resistance have been identified. We investigated the molecular mechanisms of clinical 5FU resistance in colorectal adenocarcinoma patients in a prospective biomarker discovery project utilising gene expression profiling. The aim was to identify novel 5FU resistance mechanisms and qualify these as candidate biomarkers and therapeutic targets. Putative treatment specific gene expression changes were identified in a transcriptomics study of rectal adenocarcinomas, biopsied and profiled before and after pre-operative short-course radiotherapy or 5FU based chemo-radiotherapy, using microarrays. Tumour from untreated controls at diagnosis and resection identified treatment-independent gene expression changes. Candidate 5FU chemo-resistant genes were identified by comparison of gene expression data sets from these clinical specimens with gene expression signatures from our previous studies of colorectal cancer cell lines, where parental and daughter lines resistant to 5FU were compared. A colorectal adenocarcinoma tissue microarray (n = 234, resected tumours) was used as an independent set to qualify candidates thus identified. APRIL/TNFSF13 mRNA was significantly upregulated following 5FU based concurrent chemo-radiotherapy and in 5FU resistant colorectal adenocarcinoma cell lines but not in radiotherapy alone treated colorectal adenocarcinomas. Consistent withAPRIL's known function as an autocrine or paracrine secreted molecule, stromal but not tumour cell protein expression by immunohistochemistry was correlated with poor prognosis (p = 0.019) in the independent set

  18. Perceived age as clinically useful biomarker of ageing: cohort study

    DEFF Research Database (Denmark)

    Christensen, Kaare; Thinggaard, Mikael; McGue, Matt

    2009-01-01

    OBJECTIVE: To determine whether perceived age correlates with survival and important age related phenotypes. DESIGN: Follow-up study, with survival of twins determined up to January 2008, by which time 675 (37%) had died. SETTING: Population based twin cohort in Denmark. PARTICIPANTS: 20 nurses, 10...... young men, and 11 older women (assessors); 1826 twins aged >or=70. MAIN OUTCOME MEASURES: Assessors: perceived age of twins from photographs. Twins: physical and cognitive tests and molecular biomarker of ageing (leucocyte telomere length). RESULTS: For all three groups of assessors, perceived age...... increased with increasing discordance in perceived age within the twin pair-that is, the bigger the difference in perceived age within the pair, the more likely that the older looking twin died first. Twin analyses suggested that common genetic factors influence both perceived age and survival. Perceived...

  19. An etiologic prediction model incorporating biomarkers to predict the bladder cancer risk associated with occupational exposure to aromatic amines: a pilot study.

    Science.gov (United States)

    Mastrangelo, Giuseppe; Carta, Angela; Arici, Cecilia; Pavanello, Sofia; Porru, Stefano

    2017-01-01

    No etiological prediction model incorporating biomarkers is available to predict bladder cancer risk associated with occupational exposure to aromatic amines. Cases were 199 bladder cancer patients. Clinical, laboratory and genetic data were predictors in logistic regression models (full and short) in which the dependent variable was 1 for 15 patients with aromatic amines related bladder cancer and 0 otherwise. The receiver operating characteristics approach was adopted; the area under the curve was used to evaluate discriminatory ability of models. Area under the curve was 0.93 for the full model (including age, smoking and coffee habits, DNA adducts, 12 genotypes) and 0.86 for the short model (including smoking, DNA adducts, 3 genotypes). Using the "best cut-off" of predicted probability of a positive outcome, percentage of cases correctly classified was 92% (full model) against 75% (short model). Cancers classified as "positive outcome" are those to be referred for evaluation by an occupational physician for etiological diagnosis; these patients were 28 (full model) or 60 (short model). Using 3 genotypes instead of 12 can double the number of patients with suspect of aromatic amine related cancer, thus increasing costs of etiologic appraisal. Integrating clinical, laboratory and genetic factors, we developed the first etiologic prediction model for aromatic amine related bladder cancer. Discriminatory ability was excellent, particularly for the full model, allowing individualized predictions. Validation of our model in external populations is essential for practical use in the clinical setting.

  20. L-Dopa decarboxylase (DDC) constitutes an emerging biomarker in predicting patients' survival with stomach adenocarcinomas.

    Science.gov (United States)

    Florou, Dimitra; Papadopoulos, Iordanis N; Fragoulis, Emmanuel G; Scorilas, Andreas

    2013-02-01

    Stomach adenocarcinoma represents a major health problem and is regarded as the second commonest cause of cancer-associated mortality, universally, since it is still difficult to be perceived at a curable stage. Several lines of evidence have pointed out that the expression of L-Dopa decarboxylase (DDC) gene and/or protein becomes distinctively modulated in several human neuroendocrine neoplasms as well as adenocarcinomas. In order to elucidate the clinical role of DDC on primary gastric adenocarcinomas, we determined qualitatively and quantitatively the mRNA levels of the gene with regular PCR and real-time PCR by using the comparative threshold cycle method, correspondingly, and detected the expression of DDC protein by immunoblotting in cancerous and normal stomach tissue specimens. A statistically significant association was disclosed between DDC expression and gastric intestinal histotype as well as tumor localization at the distal third part of the stomach (p = 0.025 and p = 0.029, respectively). Univariate and multivariate analyses highlighted the powerful prognostic importance of DDC in relation to disease-free survival and overall survival of gastric cancer patients. According to Kaplan-Meier curves, the relative risk of relapse was found to be decreased in DDC-positive (p = 0.031) patients who, also, exhibited higher overall survival rates (p = 0.016) than those with DDC-negative tumors. This work is the first to shed light on the potential clinical usefulness of DDC, as an efficient tumor biomarker in gastric cancer. The provided evidence underlines the propitious predictive value of DDC expression in the survival of stomach adenocarcinoma patients.

  1. A tool to facilitate clinical biomarker studies - a tissue dictionary based on the Human Protein Atlas

    Directory of Open Access Journals (Sweden)

    Kampf Caroline

    2012-09-01

    Full Text Available Abstract The complexity of tissue and the alterations that distinguish normal from cancer remain a challenge for translating results from tumor biological studies into clinical medicine. This has generated an unmet need to exploit the findings from studies based on cell lines and model organisms to develop, validate and clinically apply novel diagnostic, prognostic and treatment predictive markers. As one step to meet this challenge, the Human Protein Atlas project has been set up to produce antibodies towards human protein targets corresponding to all human protein coding genes and to map protein expression in normal human tissues, cancer and cells. Here, we present a dictionary based on microscopy images created as an amendment to the Human Protein Atlas. The aim of the dictionary is to facilitate the interpretation and use of the image-based data available in the Human Protein Atlas, but also to serve as a tool for training and understanding tissue histology, pathology and cell biology. The dictionary contains three main parts, normal tissues, cancer tissues and cells, and is based on high-resolution images at different magnifications of full tissue sections stained with H & E. The cell atlas is centered on immunofluorescence and confocal microscopy images, using different color channels to highlight the organelle structure of a cell. Here, we explain how this dictionary can be used as a tool to aid clinicians and scientists in understanding the use of tissue histology and cancer pathology in diagnostics and biomarker studies.

  2. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

    OpenAIRE

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

    2014-01-01

    Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

  3. Innovative biomarkers for predicting type 2 diabetes mellitus: relevance to dietary management of frailty in older adults.

    Science.gov (United States)

    Ikwuobe, John; Bellary, Srikanth; Griffiths, Helen R

    2016-06-01

    Type 2 diabetes mellitus (T2DM) increases in prevalence in the elderly. There is evidence for significant muscle loss and accelerated cognitive impairment in older adults with T2DM; these comorbidities are critical features of frailty. In the early stages of T2DM, insulin sensitivity can be improved by a "healthy" diet. Management of insulin resistance by diet in people over 65 years of age should be carefully re-evaluated because of the risk for falling due to hypoglycaemia. To date, an optimal dietary programme for older adults with insulin resistance and T2DM has not been described. The use of biomarkers to identify those at risk for T2DM will enable clinicians to offer early dietary advice that will delay onset of disease and of frailty. Here we have used an in silico literature search for putative novel biomarkers of T2DM risk and frailty. We suggest that plasma bilirubin, plasma, urinary DPP4-positive microparticles and plasma pigment epithelium-derived factor merit further investigation as predictive biomarkers for T2DM and frailty risk in older adults. Bilirubin is screened routinely in clinical practice. Measurement of specific microparticle frequency in urine is less invasive than a blood sample so is a good choice for biomonitoring. Future studies should investigate whether early dietary changes, such as increased intake of whey protein and micronutrients that improve muscle function and insulin sensitivity, affect biomarkers and can reduce the longer term complication of frailty in people at risk for T2DM.

  4. Blood biomarkers are helpful in the prediction of response to chemoradiation in rectal cancer: A prospective, hypothesis driven study on patients with locally advanced rectal cancer

    International Nuclear Information System (INIS)

    Buijsen, Jeroen; Stiphout, Ruud G. van; Menheere, Paul P.C.A.; Lammering, Guido; Lambin, Philippe

    2014-01-01

    Purpose/objective: Chemoradiation (CRT) has been shown to lead to downsizing of an important portion of rectal cancers. In order to tailor treatment at an earlier stage during treatment, predictive models are being developed. Adding blood biomarkers may be attractive for prediction, as they can be collected very easily and determined with excellent reproducibility in clinical practice. The hypothesis of this study was that blood biomarkers related to tumor load, hypoxia and inflammation can help to predict response to CRT in rectal cancer. Material/methods: 295 patients with locally advanced rectal cancer who were planned to undergo CRT were prospectively entered into a biobank protocol ( (NCT01067872)). Blood samples were drawn before start of CRT. Nine biomarkers were selected, based on a previously defined hypothesis, and measured in a standardized way by a certified lab: CEA, CA19-9, LDH, CRP, IL-6, IL-8, CA IX, osteopontin and 25-OH-vitamin D. Outcome was analyzed in two ways: pCR vs. non-pCR and responders (defined as ypT0-2N0) vs. non-responders (all other ypTN stages). Results: 276 patients could be analyzed. 20.7% developed a pCR and 47.1% were classified as responders. In univariate analysis CEA (p = 0.001) and osteopontin (p = 0.012) were significant predictors for pCR. Taking response as outcome CEA (p < 0.001), IL-8 (p < 0.001) and osteopontin (p = 0.004) were significant predictors. In multivariate analysis CEA was the strongest predictor for pCR (OR 0.92, p = 0.019) and CEA and IL-8 predicted for response (OR 0.97, p = 0.029 and OR 0.94, p = 0.036). The model based on biomarkers only had an AUC of 0.65 for pCR and 0.68 for response; the strongest model included clinical data, PET-data and biomarkers and had an AUC of 0.81 for pCR and 0.78 for response. Conclusion: CEA and IL-8 were identified as predictive biomarkers for tumor response and PCR after CRT in rectal cancer. Incorporation of these blood biomarkers leads to an additional accuracy of

  5. Relationships between Rapid Eye Movement Sleep Behavior Disorder and Neurodegenerative Diseases: Clinical Assessments, Biomarkers, and Treatment

    Directory of Open Access Journals (Sweden)

    Min Li

    2018-01-01

    Conclusions: More longitudinal studies should be conducted to evaluate the predictive value of biomarkers of RBD. Moreover, because the glucose and dopamine metabolisms are not specific for assessing cognitive cognition, the molecular metabolism directly related to cognition should be investigated. There is a need for more treatment trials to determine the effectiveness of interventions of RBD on preventing the conversion to neurodegenerative diseases.

  6. AUC-based biomarker ensemble with an application on gene scores predicting low bone mineral density.

    Science.gov (United States)

    Zhao, X G; Dai, W; Li, Y; Tian, L

    2011-11-01

    The area under the receiver operating characteristic (ROC) curve (AUC), long regarded as a 'golden' measure for the predictiveness of a continuous score, has propelled the need to develop AUC-based predictors. However, the AUC-based ensemble methods are rather scant, largely due to the fact that the associated objective function is neither continuous nor concave. Indeed, there is no reliable numerical algorithm identifying optimal combination of a set of biomarkers to maximize the AUC, especially when the number of biomarkers is large. We have proposed a novel AUC-based statistical ensemble methods for combining multiple biomarkers to differentiate a binary response of interest. Specifically, we propose to replace the non-continuous and non-convex AUC objective function by a convex surrogate loss function, whose minimizer can be efficiently identified. With the established framework, the lasso and other regularization techniques enable feature selections. Extensive simulations have demonstrated the superiority of the new methods to the existing methods. The proposal has been applied to a gene expression dataset to construct gene expression scores to differentiate elderly women with low bone mineral density (BMD) and those with normal BMD. The AUCs of the resulting scores in the independent test dataset has been satisfactory. Aiming for directly maximizing AUC, the proposed AUC-based ensemble method provides an efficient means of generating a stable combination of multiple biomarkers, which is especially useful under the high-dimensional settings. lutian@stanford.edu. Supplementary data are available at Bioinformatics online.

  7. UPLC-based metabonomic applications for discovering biomarkers of diseases in clinical chemistry.

    Science.gov (United States)

    Zhao, Ying-Yong; Cheng, Xian-Long; Vaziri, Nosratola D; Liu, Shuman; Lin, Rui-Chao

    2014-10-01

    Metabonomics is a powerful and promising analytic tool that allows assessment of global low-molecular-weight metabolites in biological systems. It has a great potential for identifying useful biomarkers for early diagnosis, prognosis and assessment of therapeutic interventions in clinical practice. The aim of this review is to provide a brief summary of the recent advances in UPLC-based metabonomic approach for biomarker discovery in a variety of diseases, and to discuss their significance in clinical chemistry. All the available information on UPLC-based metabonomic applications for discovering biomarkers of diseases were collected via a library and electronic search (using Web of Science, Pubmed, ScienceDirect, Springer, Google Scholar, etc.). Metabonomics has been used in clinical chemistry to identify and evaluate potential biomarkers and therapeutic targets in various diseases affecting the liver (hepatocarcinoma and liver cirrhosis), lung (lung cancer and pneumonia), gastrointestinal tract (colorectal cancer) and urogenital tract (prostate cancer, ovarian cancer and chronic kidney disease), as well as metabolic diseases (diabetes) and neuropsychiatric disorders (Alzheimer's disease and schizophrenia), etc. The information provided highlights the potential value of determination of endogenous low-molecular-weight metabolites and the advantages and potential drawbacks of the application of UPLC-based metabonomics in clinical setting. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  8. Alzheimer biomarkers and clinical Alzheimer disease were not associated with increased cerebrovascular disease in a memory clinic population.

    Science.gov (United States)

    Spies, Petra E; Verbeek, Marcel M; Sjogren, Magnus J C; de Leeuw, Frank-Erik; Claassen, Jurgen A H R

    2014-01-01

    Preclinical and post-mortem studies suggest that Alzheimer disease (AD) causes cerebrovascular dysfunction, and therefore may enhance susceptibility to cerebrovascular disease (CVD). The objective of this study was to investigate this association in a memory clinic population. The AD biomarkers CSF amyloid β42, amyloid β40 and APOE-ε4 status have all been linked to increased CVD risk in AD, and therefore the first aim of this study was to analyze the association between these biomarkers and CVD. In 92 memory clinic patients the cross-sectional association between AD biomarkersand the severity of CVD was investigated with linear regression analysis. Additionally, we studied whether AD biomarkers modified the relation between vascular risk factors and CVD. CVD was assessed on MRI through a visual rating scale.Analyses were adjusted for age. The second aim of this study was to investigate the association between clinical AD and CVD, where 'clinical AD' was defined as follows: impairment in episodic memory, hippocampal atrophy and an aberrant concentration of cerebrospinal fluid (CSF) biomarkers. 47 of the 92 patients had AD. No association between CSF amyloid β42, amyloid β40 or APOE-ε4 status and CVD severity was found, nor did these AD biomarkers modify the relation between vascular risk factors and CVD. Clinical AD was not associated with CVD severity (p=0.83). Patients with more vascular risk factors had more CVD, but this relationship was not convincingly modified by AD (p=0.06). In this memory clinic population, CVD in patients with AD was related to vascular risk factors and age, comparable to patients without AD. Therefore, in our study, the preclinical and post-mortem evidence that AD would predispose to CVD could not be translated clinically. Further work, including replication of this work in a different and larger sample, is warranted.

  9. Biomarkers and Microscopic Colitis: An Unmet Need in Clinical Practice

    Directory of Open Access Journals (Sweden)

    Laura Francesca Pisani

    2017-05-01

    Full Text Available One of the most common causes of chronic diarrhea is ascribed to microscopic colitis (MC. MC is classified in subtypes: collagenous colitis (CC and lymphocytic colitis (LC. Patients with MC report watery, non-bloody diarrhea of chronic course, abdominal pain, weight loss, and fatigue that may impair patient’s health-related quality of life. A greater awareness, and concomitantly an increasing number of diagnoses over the last years, has demonstrated that the incidence and prevalence of MC are on the rise. To date, colonoscopy with histological analysis on multiple biopsies collected along the colon represents the unique accepted procedure used to assess the diagnosis of active MC and to evaluate the response to medical therapy. Therefore, the emerging need for less-invasive procedures that are also rapid, convenient, standardized, and reproducible, has encouraged scientists to turn their attention to the identification of inflammatory markers and other molecules in blood or feces and within the colonic tissue that can confirm a MC diagnosis. This review gives an update on the biomarkers that are potentially available for the identification of inflammatory activity, related to CC and LC.

  10. The potential biomarkers in predicting pathologic response of breast cancer to three different chemotherapy regimens: a case control study

    Directory of Open Access Journals (Sweden)

    Xu Chaoyang

    2009-07-01

    Full Text Available Abstract Background Preoperative chemotherapy (PCT has become the standard of care in locally advanced breast cancer. The identification of patient-specific tumor characteristics that can improve the ability to predict response to therapy would help optimize treatment, improve treatment outcomes, and avoid unnecessary exposure to potential toxicities. This study is to determine whether selected biomarkers could predict pathologic response (PR of breast tumors to three different PCT regimens, and to identify a subset of patients who would benefit from a given type of treatment. Methods 118 patients with primary breast tumor were identified and three PCT regimens including DEC (docetaxel+epirubicin+cyclophosphamide, VFC (vinorelbine/vincristine+5-fluorouracil+cyclophosphamide and EFC (epirubicin+5-fluorouracil+cyclophosphamide were investigated. Expression of steroid receptors, HER2, P-gp, MRP, GST-pi and Topo-II was evaluated by immunohistochemical scoring on tumor tissues obtained before and after PCT. The PR of breast carcinoma was graded according to Sataloff's classification. Chi square test, logistic regression and Cochran-Mantel-Haenszel assay were performed to determine the association between biomarkers and PR, as well as the effectiveness of each regimen on induction of PR. Results There was a clear-cut correlation between the expression of ER and decreased PR to PCT in all three different regimens (p p Conclusion ER is an independent predictive factor for PR to PCT regimens including DEC, VFC and EFC in primary breast tumors, while HER2 is only predictive for DEC regimen. Expression of PgR, Topo-II, P-gp, MRP and GST-pi are not predictive for PR to any PCT regimens investigated. Results obtained in this clinical study may be helpful for the selection of appropriate treatments for breast cancer patients.

  11. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials

    Directory of Open Access Journals (Sweden)

    Nils Ternès

    2017-05-01

    Full Text Available Abstract Background Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions. Methods Based on a parsimonious biomarker selection in a penalized high-dimensional Cox model (lasso or adaptive lasso, we propose a unified framework to: estimate internally the predictive accuracy metrics of the developed model (using double cross-validation; estimate the individual survival probabilities at a given timepoint; construct confidence intervals thereof (analytical or bootstrap; and visualize them graphically (pointwise or smoothed with spline. We compared these strategies through a simulation study covering scenarios with or without biomarker effects. We applied the strategies to a large randomized phase III clinical trial that evaluated the effect of adding trastuzumab to chemotherapy in 1574 early breast cancer patients, for which the expression of 462 genes was measured. Results In our simulations, penalized regression models using the adaptive lasso estimated the survival probability of new patients with low bias and standard error; bootstrapped confidence intervals had empirical coverage probability close to the nominal level across very different scenarios. The double cross-validation performed on the training data set closely mimicked the predictive accuracy of the selected models in external validation data. We also propose a useful visual representation of the expected survival probabilities using splines. In the breast cancer trial, the adaptive lasso penalty selected a prediction model with 4

  12. Cross-validation of biomarkers for the early differential diagnosis and prognosis of dementia in a clinical setting

    International Nuclear Information System (INIS)

    Perani, Daniela; Cerami, Chiara; Caminiti, Silvia Paola; Santangelo, Roberto; Coppi, Elisabetta; Ferrari, Laura; Magnani, Giuseppe; Pinto, Patrizia; Passerini, Gabriella; Falini, Andrea; Iannaccone, Sandro; Cappa, Stefano Francesco; Comi, Giancarlo; Gianolli, Luigi

    2016-01-01

    The aim of this study was to evaluate the supportive role of molecular and structural biomarkers (CSF protein levels, FDG PET and MRI) in the early differential diagnosis of dementia in a large sample of patients with neurodegenerative dementia, and in determining the risk of disease progression in subjects with mild cognitive impairment (MCI). We evaluated the supportive role of CSF Aβ 42 , t-Tau, p-Tau levels, conventional brain MRI and visual assessment of FDG PET SPM t-maps in the early diagnosis of dementia and the evaluation of MCI progression. Diagnosis based on molecular biomarkers showed the best fit with the final diagnosis at a long follow-up. FDG PET SPM t-maps had the highest diagnostic accuracy in Alzheimer's disease and in the differential diagnosis of non-Alzheimer's disease dementias. The p-tau/Aβ 42 ratio was the only CSF biomarker providing a significant classification rate for Alzheimer's disease. An Alzheimer's disease-positive metabolic pattern as shown by FDG PET SPM in MCI was the best predictor of conversion to Alzheimer's disease. In this clinical setting, FDG PET SPM t-maps and the p-tau/Aβ 42 ratio improved clinical diagnostic accuracy, supporting the importance of these biomarkers in the emerging diagnostic criteria for Alzheimer's disease dementia. FDG PET using SPM t-maps had the highest predictive value by identifying hypometabolic patterns in different neurodegenerative dementias and normal brain metabolism in MCI, confirming its additional crucial exclusionary role. (orig.)

  13. Cross-validation of biomarkers for the early differential diagnosis and prognosis of dementia in a clinical setting

    Energy Technology Data Exchange (ETDEWEB)

    Perani, Daniela [Vita-Salute San Raffaele University, Milan (Italy); San Raffaele Scientific Institute, Division of Neuroscience, Milan (Italy); San Raffaele Hospital, Nuclear Medicine Unit, Milan (Italy); Cerami, Chiara [Vita-Salute San Raffaele University, Milan (Italy); San Raffaele Scientific Institute, Division of Neuroscience, Milan (Italy); San Raffaele Hospital, Clinical Neuroscience Department, Milan (Italy); Caminiti, Silvia Paola [Vita-Salute San Raffaele University, Milan (Italy); San Raffaele Scientific Institute, Division of Neuroscience, Milan (Italy); Santangelo, Roberto; Coppi, Elisabetta; Ferrari, Laura; Magnani, Giuseppe [San Raffaele Hospital, Department of Neurology, Milan (Italy); Pinto, Patrizia [Papa Giovanni XXIII Hospital, Department of Neurology, Bergamo (Italy); Passerini, Gabriella [Servizio di Medicina di Laboratorio OSR, Milan (Italy); Falini, Andrea [Vita-Salute San Raffaele University, Milan (Italy); San Raffaele Scientific Institute, Division of Neuroscience, Milan (Italy); San Raffaele Hospital, CERMAC - Department of Neuroradiology, Milan (Italy); Iannaccone, Sandro [San Raffaele Hospital, Clinical Neuroscience Department, Milan (Italy); Cappa, Stefano Francesco [San Raffaele Scientific Institute, Division of Neuroscience, Milan (Italy); IUSS Pavia, Pavia (Italy); Comi, Giancarlo [Vita-Salute San Raffaele University, Milan (Italy); San Raffaele Hospital, Department of Neurology, Milan (Italy); Gianolli, Luigi [San Raffaele Hospital, Nuclear Medicine Unit, Milan (Italy)

    2016-03-15

    The aim of this study was to evaluate the supportive role of molecular and structural biomarkers (CSF protein levels, FDG PET and MRI) in the early differential diagnosis of dementia in a large sample of patients with neurodegenerative dementia, and in determining the risk of disease progression in subjects with mild cognitive impairment (MCI). We evaluated the supportive role of CSF Aβ{sub 42}, t-Tau, p-Tau levels, conventional brain MRI and visual assessment of FDG PET SPM t-maps in the early diagnosis of dementia and the evaluation of MCI progression. Diagnosis based on molecular biomarkers showed the best fit with the final diagnosis at a long follow-up. FDG PET SPM t-maps had the highest diagnostic accuracy in Alzheimer's disease and in the differential diagnosis of non-Alzheimer's disease dementias. The p-tau/Aβ{sub 42} ratio was the only CSF biomarker providing a significant classification rate for Alzheimer's disease. An Alzheimer's disease-positive metabolic pattern as shown by FDG PET SPM in MCI was the best predictor of conversion to Alzheimer's disease. In this clinical setting, FDG PET SPM t-maps and the p-tau/Aβ{sub 42} ratio improved clinical diagnostic accuracy, supporting the importance of these biomarkers in the emerging diagnostic criteria for Alzheimer's disease dementia. FDG PET using SPM t-maps had the highest predictive value by identifying hypometabolic patterns in different neurodegenerative dementias and normal brain metabolism in MCI, confirming its additional crucial exclusionary role. (orig.)

  14. MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

    Energy Technology Data Exchange (ETDEWEB)

    Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J., E-mail: bje@mayo.edu [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Coufalova, Lucie [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Department of Neurosurgery of First Faculty of Medicine, Charles University in Prague, Military University Hospital, Prague 128 21 (Czech Republic); International Clinical Research Center, St. Anne’s University Hospital Brno, Brno 656 91 (Czech Republic); Lachance, Daniel H. [Department of Neurology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Parney, Ian F. [Department of Neurologic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Carter, Rickey E. [Department of Health Sciences Research, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Buckner, Jan C. [Department of Medical Oncology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States)

    2016-06-15

    Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

  15. MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

    International Nuclear Information System (INIS)

    Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.; Coufalova, Lucie; Lachance, Daniel H.; Parney, Ian F.; Carter, Rickey E.; Buckner, Jan C.

    2016-01-01

    Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O 6 -methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

  16. Ex vivo metabolic fingerprinting identifies biomarkers predictive of prostate cancer recurrence following radical prostatectomy.

    Science.gov (United States)

    Braadland, Peder R; Giskeødegård, Guro; Sandsmark, Elise; Bertilsson, Helena; Euceda, Leslie R; Hansen, Ailin F; Guldvik, Ingrid J; Selnæs, Kirsten M; Grytli, Helene H; Katz, Betina; Svindland, Aud; Bathen, Tone F; Eri, Lars M; Nygård, Ståle; Berge, Viktor; Taskén, Kristin A; Tessem, May-Britt

    2017-11-21

    Robust biomarkers that identify prostate cancer patients with high risk of recurrence will improve personalised cancer care. In this study, we investigated whether tissue metabolites detectable by high-resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS MRS) were associated with recurrence following radical prostatectomy. We performed a retrospective ex vivo study using HR-MAS MRS on tissue samples from 110 radical prostatectomy specimens obtained from three different Norwegian cohorts collected between 2002 and 2010. At the time of analysis, 50 patients had experienced prostate cancer recurrence. Associations between metabolites, clinicopathological variables, and recurrence-free survival were evaluated using Cox proportional hazards regression modelling, Kaplan-Meier survival analyses and concordance index (C-index). High intratumoural spermine and citrate concentrations were associated with longer recurrence-free survival, whereas high (total-choline+creatine)/spermine (tChoCre/Spm) and higher (total-choline+creatine)/citrate (tChoCre/Cit) ratios were associated with shorter time to recurrence. Spermine concentration and tChoCre/Spm were independently associated with recurrence in multivariate Cox proportional hazards modelling after adjusting for clinically relevant risk factors (C-index: 0.769; HR: 0.72; P=0.016 and C-index: 0.765; HR: 1.43; P=0.014, respectively). Spermine concentration and tChoCre/Spm ratio in prostatectomy specimens were independent prognostic markers of recurrence. These metabolites can be noninvasively measured in vivo and may thus offer predictive value to establish preoperative risk assessment nomograms.

  17. Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jiangang Liu

    Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

  18. Biomarkers in Airway Diseases

    Directory of Open Access Journals (Sweden)

    Janice M Leung

    2013-01-01

    Full Text Available The inherent limitations of spirometry and clinical history have prompted clinicians and scientists to search for surrogate markers of airway diseases. Although few biomarkers have been widely accepted into the clinical armamentarium, the authors explore three sources of biomarkers that have shown promise as indicators of disease severity and treatment response. In asthma, exhaled nitric oxide measurements can predict steroid responsiveness and sputum eosinophil counts have been used to titrate anti-inflammatory therapies. In chronic obstructive pulmonary disease, inflammatory plasma biomarkers, such as fibrinogen, club cell secretory protein-16 and surfactant protein D, can denote greater severity and predict the risk of exacerbations. While the multitude of disease phenotypes in respiratory medicine make biomarker development especially challenging, these three may soon play key roles in the diagnosis and management of airway diseases.

  19. Development and validation of a Luminex assay for detection of a predictive biomarker for PROSTVAC-VF therapy

    Science.gov (United States)

    Lucas, Julie L.; Tacheny, Erin A.; Ferris, Allison; Galusha, Michelle; Srivastava, Apurva K.; Ganguly, Aniruddha; Williams, P. Mickey; Sachs, Michael C.; Thurin, Magdalena; Tricoli, James V.; Ricker, Winnie; Gildersleeve, Jeffrey C.

    2017-01-01

    Cancer therapies can provide substantially improved survival in some patients while other seemingly similar patients receive little or no benefit. Strategies to identify patients likely to respond well to a given therapy could significantly improve health care outcomes by maximizing clinical benefits while reducing toxicities and adverse effects. Using a glycan microarray assay, we recently reported that pretreatment serum levels of IgM specific to blood group A trisaccharide (BG-Atri) correlate positively with overall survival of cancer patients on PROSTVAC-VF therapy. The results suggested anti-BG-Atri IgM measured prior to treatment could serve as a biomarker for identifying patients likely to benefit from PROSTVAC-VF. For continued development and clinical application of serum IgM specific to BG-Atri as a predictive biomarker, a clinical assay was needed. In this study, we developed and validated a Luminex-based clinical assay for measuring serum IgM specific to BG-Atri. IgM levels were measured with the Luminex assay and compared to levels measured using the microarray for 126 healthy individuals and 77 prostate cancer patients. This assay provided reproducible and consistent results with low %CVs, and tolerance ranges were established for the assay. IgM levels measured using the Luminex assay were found to be highly correlated to the microarray results with R values of 0.93–0.95. This assay is a Laboratory Developed Test (LDT) and is suitable for evaluating thousands of serum samples in CLIA certified laboratories that have validated the assay. In addition, the study demonstrates that discoveries made using neoglycoprotein-based microarrays can be readily migrated to a clinical assay. PMID:28771597

  20. Clinical drug development using dynamic biomarkers to enable personalized health care in Chronic Obstructive Pulmonary Disease

    DEFF Research Database (Denmark)

    Bihlet, Asger R; Karsdal, Morten A; Bay-Jensen, Anne-Christine

    2015-01-01

    Despite massive investments in development of novel treatments for heterogeneous diseases such as Chronic Obstructive Pulmonary Disease (COPD), the resources spent have only benefitted a fraction of the population treated. Personalized Health Care to guide selection of a suitable patient population...... at higher risk of progression. We review the role of extra-cellular matrix proteins found to be upregulated in COPD. Novel biomarkers of connective tissue remodeling which may provide added value for a personalized approach by detecting subgroups of patients with active disease suitable for pharmacological...... already in the clinical development of new compounds could offer a solution. In this review, we discuss past successes and failures in drug development and biomarker research in COPD. We describe research in COPD phenotypes, and the required characteristics of a suitable biomarker for identifying patients...

  1. Precision Oncology Medicine: The Clinical Relevance of Patient-Specific Biomarkers Used to Optimize Cancer Treatment.

    Science.gov (United States)

    Schmidt, Keith T; Chau, Cindy H; Price, Douglas K; Figg, William D

    2016-12-01

    Precision medicine in oncology is the result of an increasing awareness of patient-specific clinical features coupled with the development of genomic-based diagnostics and targeted therapeutics. Companion diagnostics designed for specific drug-target pairs were the first to widely utilize clinically applicable tumor biomarkers (eg, HER2, EGFR), directing treatment for patients whose tumors exhibit a mutation susceptible to an FDA-approved targeted therapy (eg, trastuzumab, erlotinib). Clinically relevant germline mutations in drug-metabolizing enzymes and transporters (eg, TPMT, DPYD) have been shown to impact drug response, providing a rationale for individualized dosing to optimize treatment. The use of multigene expression-based assays to analyze an array of prognostic biomarkers has been shown to help direct treatment decisions, especially in breast cancer (eg, Oncotype DX). More recently, the use of next-generation sequencing to detect many potential "actionable" cancer molecular alterations is further shifting the 1 gene-1 drug paradigm toward a more comprehensive, multigene approach. Currently, many clinical trials (eg, NCI-MATCH, NCI-MPACT) are assessing novel diagnostic tools with a combination of different targeted therapeutics while also examining tumor biomarkers that were previously unexplored in a variety of cancer histologies. Results from ongoing trials such as the NCI-MATCH will help determine the clinical utility and future development of the precision-medicine approach. © 2016, The American College of Clinical Pharmacology.

  2. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  3. Imaging studies and biomarkers to detect clinically meaningful vesicoureteral reflux

    Directory of Open Access Journals (Sweden)

    Michaella Maloney Prasad

    2017-06-01

    Full Text Available The work-up of a febrile urinary tract infection is generally performed to detect vesicoureteral reflux (VUR and its possible complications. The imaging modalities most commonly used for this purpose are renal-bladder ultrasound, voiding cystourethrogram and dimercapto-succinic acid scan. These studies each contribute valuable information, but carry individual benefits and limitations that may impact their efficacy. Biochemical markers are not commonly used in pediatric urology to diagnose or differentiate high-risk disease, but this is the emerging frontier, which will hopefully change our approach to VUR in the future. As it becomes more apparent that there is tremendous clinical variation within grades of VUR, the need to distinguish clinically significant from insignificant disease grows. The unfortunate truth about VUR is that recommendations for treatment may be inconsistent. Nuances in clinical decision-making will always exist, but opinions for medical versus surgical intervention should be more standardized, based on risk of injury to the kidney.

  4. Predictive inference for best linear combination of biomarkers subject to limits of detection.

    Science.gov (United States)

    Coolen-Maturi, Tahani

    2017-08-15

    Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  5. Performance of diagnostic biomarkers in predicting liver fibrosis among hepatitis C virus-infected Egyptian children

    Directory of Open Access Journals (Sweden)

    Yasser E Nassef

    2013-11-01

    Full Text Available The aim of the present study was to identify specific markers that mirror liver fibrosis progression as an alternative to biopsy when biopsy is contraindicated, especially in children. After liver biopsies were performed, serum samples from 30 hepatitis C virus (HCV paediatric patients (8-14 years were analysed and compared with samples from 30 healthy subjects. All subjects were tested for the presence of serum anti-HCV antibodies. Direct biomarkers for liver fibrosis, including transforming growth factor-β1, tissue inhibitor of matrix metalloproteinase-1 (TIMP-1, hyaluronic acid (HA, procollagen type III amino-terminal peptide (PIIINP and osteopontin (OPN, were measured. The indirect biomarkers aspartate and alanine aminotransferases, albumin and bilirubin were also tested. The results revealed a significant increase in the serum marker levels in HCV-infected children compared with the healthy group, whereas albumin levels exhibited a significant decrease. Significantly higher levels of PIIINP, TIMP-1, OPN and HA were detected in HCV-infected children with moderate to severe fibrosis compared with children with mild fibrosis (p < 0.05. The diagnostic accuracy of these direct biomarkers, represented by sensitivity, specificity and positive predictive value, emphasises the utility of PIIINP, TIMP-1, OPN and HA as indicators of liver fibrosis among HCV-infected children.

  6. Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

    Science.gov (United States)

    Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

    2016-05-01

    Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. Association of oxidative stress biomarkers with adiposity and clinical staging in women with breast cancer.

    Science.gov (United States)

    Carioca, A A F; Verde, S M M L; Luzia, L A; Rondó, P H C; Latorre, M R D O; Ellery, T H P; Damasceno, N R T

    2015-11-01

    Breast cancer is a disease characterised by both oxidative reactions and inflammation. However, few studies have focused on the oxidative and inflammatory biomarkers. The aim of the present study was to evaluate the association between oxidative stress markers and adiposity and clinical staging, as well as the association between the oxidative and the antioxidant biomarkers of women with breast cancer. A total of 135 cases of breast cancer occurring in 2011 and 2012 were assessed. After exclusions, 101 pre- and post-menopausal women with clinical staging I to IV were eligible to participate in the study. The anthropometric evaluation was performed by collecting data on waist circumference, body mass index and body composition. The socioeconomic and clinical profiles were determined using a standard questionnaire. For the oxidative biomarkers, thiobarbituric acid reactive substances (TBARS), oxidative DNA damage (8-hydroxy-2-deoxyguanosine (8-OHdG)), low-density lipoprotein(-) (LDL(-)), autoantibody anti-LDL(-) and liposoluble antioxidants (α-tocopherol, retinol and β-carotene) were analysed. The data were analysed using differences in the mean values, correlation tests and multiple linear regression. The antioxidant levels were higher in postmenopausal women with clinical staging I and II and negative lymph nodes. The TBARS level was associated with clinical staging. Adiposity was associated with levels of retinol and 8-OHdG, whereas LDL(-), 8-OHdG and TBARS were correlated with liposoluble antioxidants after adjusting for the confounders. The adiposity and clinical staging of patients were associated with oxidative stress. The oxidative and antioxidant biomarkers showed a negative correlation in patients with breast cancer.

  8. Potential of Mass Spectrometry in Developing Clinical Laboratory Biomarkers of Nonvolatiles in Exhaled Breath.

    Science.gov (United States)

    Beck, Olof; Olin, Anna-Carin; Mirgorodskaya, Ekaterina

    2016-01-01

    Exhaled breath contains nonvolatile substances that are part of aerosol particles of submicrometer size. These particles are formed and exhaled as a result of normal breathing and contain material from distal airways of the respiratory system. Exhaled breath can be used to monitor biomarkers of both endogenous and exogenous origin and constitutes an attractive specimen for medical investigations. This review summarizes the present status regarding potential biomarkers of nonvolatile compounds in exhaled breath. The field of exhaled breath condensate is briefly reviewed, together with more recent work on more selective collection procedures for exhaled particles. The relation of these particles to the surfactant in the terminal parts of the respiratory system is described. The literature on potential endogenous low molecular weight compounds as well as protein biomarkers is reviewed. The possibility to measure exposure to therapeutic and abused drugs is demonstrated. Finally, the potential future role and importance of mass spectrometry is discussed. Nonvolatile compounds exit the lung as aerosol particles that can be sampled easily and selectively. The clinical applications of potential biomarkers in exhaled breath comprise diagnosis of disease, monitoring of disease progress, monitoring of drug therapy, and toxicological investigations. © 2015 American Association for Clinical Chemistry.

  9. Exploring the Limitations of Peripheral Blood Transcriptional Biomarkers in Predicting Influenza Vaccine Responsiveness

    Directory of Open Access Journals (Sweden)

    Luca Marchetti

    2017-01-01

    Full Text Available Systems biology has been recently applied to vaccinology to better understand immunological responses to the influenza vaccine. Particular attention has been paid to the identification of early signatures capable of predicting vaccine immunogenicity. Building from previous studies, we employed a recently established algorithm for signature-based clustering of expression profiles, SCUDO, to provide new insights into why blood-derived transcriptome biomarkers often fail to predict the seroresponse to the influenza virus vaccination. Specifically, preexisting immunity against one or more vaccine antigens, which was found to negatively affect the seroresponse, was identified as a confounding factor able to decouple early transcriptome from later antibody responses, resulting in the degradation of a biomarker predictive power. Finally, the broadly accepted definition of seroresponse to influenza virus vaccine, represented by the maximum response across the vaccine-targeted strains, was compared to a composite measure integrating the responses against all strains. This analysis revealed that composite measures provide a more accurate assessment of the seroresponse to multicomponent influenza vaccines.

  10. Biomarker-driven phenotyping in Parkinson disease: a translational missing link in disease-modifying clinical trials

    Science.gov (United States)

    Espay, Alberto J.; Schwarzschild, Michael A.; Tanner, Caroline M.; Fernandez, Hubert H; Simon, David K.; Leverenz, James B.; Merola, Aristide; Chen-Plotkin, Alice; Brundin, Patrik; Kauffman, Marcelo A.; Erro, Roberto; Kieburtz, Karl; Woo, Daniel; Macklin, Eric A.; Standaert, David G.; Lang, Anthony E.

    2016-01-01

    Past clinical trials of putative neuroprotective therapies have targeted Parkinson disease (PD) as a single pathogenic disease entity. From an Oslerian clinico-pathologic perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: a single-mechanism therapy can affect most of those sharing the classic pathologic hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers) rather than clinical definitions are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller but well-defined subsets of PD amenable to successful neuroprotection. PMID:28233927

  11. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

    Studies on the genetic basis of normal tissue radiosensitivity, or  'radiogenomics', aims at predicting clinical radiosensitivity and optimize treatment from individual genetic profiles. Several studies have now reported links between variations in certain genes related to the biological response...... to radiation injury and risk of normal tissue morbidity in cancer patients treated with radiotherapy. However, after these initial association studies including few genes, we are still far from being able to predict clinical radiosensitivity on an individual level. Recent data from our own studies on risk...

  12. Biomarkers for Early Detection of Clinically Relevant Prostate Cancer: A Multi-Institutional Validation Trial

    Science.gov (United States)

    2015-10-01

    biomarkers; prediction models; PCA3; TMPRSS2: ERG ; kallikreins; 4KScore; OncotypeDX; 5 3. ACCOMPLISHMENTS What were the major goals and...urine, alone or in combination with TMPRSS2: ERG mRNA. (Lead site: FHCRC) Milestone 10. Urine specimens identified for analysis. Due 12/30/2014...COMPLETED Milestone 11. PCA3 and TMPRSS2: ERG validation complete in PASS cohort. Due 12/30/2015 Milestone 12. Manuscript submission of PCA3 and TMPRSS2: ERG

  13. Evaluation of different biomarkers to predict individual radiosensitivity in an inter-laboratory comparison--lessons for future studies.

    Directory of Open Access Journals (Sweden)

    Burkhard Greve

    Full Text Available Radiotherapy is a powerful cure for several types of solid tumours, but its application is often limited because of severe side effects in individual patients. With the aim to find biomarkers capable of predicting normal tissue side reactions we analysed the radiation responses of cells from individual head and neck tumour and breast cancer patients of different clinical radiosensitivity in a multicentric study. Multiple parameters of cellular radiosensitivity were analysed in coded samples of peripheral blood lymphocytes (PBLs and derived lymphoblastoid cell lines (LCLs from 15 clinical radio-hypersensitive tumour patients and compared to age- and sex-matched non-radiosensitive patient controls and 15 lymphoblastoid cell lines from age- and sex- matched healthy controls of the KORA study. Experimental parameters included ionizing radiation (IR-induced cell death (AnnexinV, induction and repair of DNA strand breaks (Comet assay, induction of yH2AX foci (as a result of DNA double strand breaks, and whole genome expression analyses. Considerable inter-individual differences in IR-induced DNA strand breaks and their repair and/or cell death could be detected in primary and immortalised cells with the applied assays. The group of clinically radiosensitive patients was not unequivocally distinguishable from normal responding patients nor were individual overreacting patients in the test system unambiguously identified by two different laboratories. Thus, the in vitro test systems investigated here seem not to be appropriate for a general prediction of clinical reactions during or after radiotherapy due to the experimental variability compared to the small effect of radiation sensitivity. Genome-wide expression analysis however revealed a set of 67 marker genes which were differentially induced 6 h after in vitro-irradiation in lymphocytes from radio-hypersensitive and non-radiosensitive patients. These results warrant future validation in larger

  14. Omalizumab for severe asthma: toward personalized treatment based on biomarker profile and clinical history

    Directory of Open Access Journals (Sweden)

    Tabatabaian F

    2018-04-01

    Full Text Available Farnaz Tabatabaian, Dennis K Ledford Division of Allergy and Immunology, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA Abstract: Asthma is a heterogeneous syndrome with numerous underlining molecular and inflammatory mechanisms contributing to the wide spectrum of clinical phenotypes. Multiple therapies targeting severe asthma with type 2 (T2 high inflammation are or soon will be available. T2 high inflammation is defined as inflammation associated with atopy or eosinophilia or an increase in cytokines associated with T-helper 2 lymphocytes. Omalizumab is a humanized anti-IgE monoclonal antibody and the first biologic therapy approved for moderate–severe allergic asthma. Despite the specificity of biologic therapies like omalizumab, clinical response is variable, with approximately 50% of treated patients achieving the primary outcome. A prior identification of the ideal candidate for therapy would improve patient outcomes and optimize the use of health care resources. As the number of biologic therapies for asthma increases, the goal is identification of biomarkers or clinical phenotypes likely to respond to a specific therapy. This review focuses on potential biomarkers and clinical history that may identify responders to omalizumab therapy for asthma. Keywords: severe persistent asthma, asthma phenotype and endotype, T2 high inflammation, omalizumab, asthma biomarkers, eosinophils, fractional exhaled nitric oxide, IgE

  15. What predicts performance during clinical psychology training?

    OpenAIRE

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2013-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

  16. Nephron segment specific microRNA biomarkers of pre-clinical drug-induced renal toxicity: Opportunities and challenges

    Energy Technology Data Exchange (ETDEWEB)

    Nassirpour, Rounak, E-mail: Rounak.nassirpour@pfizer.com [Drug Safety, Pfizer Worldwide Research and Development, 1 Burtt Rd, Andover, MA 01810 (United States); Ramaiah, Shashi K. [Drug Safety, Pfizer Worldwide Research and Development, 610 Main Street, Cambridge, MA 02139 (United States); Whiteley, Laurence O. [Drug Safety, Pfizer Worldwide Research and Development, 1 Burtt Rd, Andover, MA 01810 (United States)

    2016-12-01

    Drug-induced nephrotoxicity is a common drug development complication for pharmaceutical companies. Sensitive, specific, translatable and non-invasive biomarkers of renal toxicity are urgently needed to diagnose nephron segment specific injury. The currently available gold standard biomarkers for nephrotoxicity are not kidney-specific, lack sensitivity for early detection, and are not suitable for renal damage localization (glomerular vs tubulointerstitial injury). MicroRNAs (miRNAs) are increasingly gaining momentum as promising biomarkers of various organ toxicities, including drug induced renal injury. This is mostly due to their stability in easily accessible biofluids, ease of developing nucleic acids detection compared to protein detection assays, as well as their interspecies translatability. Increasing concordance of miRNA findings by standardizing methodology most suitable for their detection and quantitation, as well as characterization of their expression pattern in a cell type specific manner, will accelerate progress toward validation of these miRNAs as biomarkers in pre-clinical, and clinical settings. This review aims to highlight the current pre-clinical findings surrounding miRNAs as biomarkers in two important segments of the nephron, the glomerulus and tubules. - Highlights: • miRNAs are promising biomarkers of drug-induced kidney injury. • Summarized pre-clinical miRNA biomarkers of drug-induced nephrotoxicity. • Described the strengths and challenges associated with miRNAs as biomarkers.

  17. Genomic biomarkers and clinical outcomes of physical activity.

    Science.gov (United States)

    Izzotti, Alberto

    2011-07-01

    Clinical and experimental studies in humans provide evidence that moderate physical activity significantly decreases artery oxidative damage to nuclear DNA, DNA-adducts related to age and dyslipedemia, and mitochondrial DNA damage. Maintenance of adequate mitochondrial function is crucial for preventing lipid accumulation and peroxidation occurring in atherosclerosis. Studies performed on human muscle biopsies analyzing gene expression in living humans reveal that physically active subjects improve the expression of genes involved in mitochondrial function and of related microRNAs. The attenuation of oxidative damage to nuclear and mitochondrial DNA by physical activity resulted in beneficial effects due to polymorphisms of glutathione S-transferases genes. Subjects bearing null GSTM1/T1 polymorphisms have poor life expectancy in the case of being sedentary, which was increased 2.6-fold in case they performed physical activity. These findings indicate that the preventive effect of physical activity undergoes interindividual variation affected by genetic polymorphisms. © 2011 New York Academy of Sciences.

  18. Evaluation of biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes mellitus: A systematic review.

    Science.gov (United States)

    Wotherspoon, Amy C; Young, Ian S; McCance, David R; Holmes, Valerie A

    2016-07-01

    Pre-eclampsia is a leading cause of maternal and perinatal morbidity and mortality. Women with type 1 diabetes are considered a high-risk group for developing pre-eclampsia. Much research has focused on biomarkers as a means of screening for pre-eclampsia in the general maternal population; however, there is a lack of evidence for women with type 1 diabetes. To undertake a systematic review to identify potential biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes. We searched Medline, EMBASE, Maternity and Infant Care, Scopus, Web of Science and CINAHL SELECTION CRITERIA: Studies were included if they measured biomarkers in blood or urine of women who developed pre-eclampsia and had pre-gestational type 1 diabetes mellitus Data collection and analysis A narrative synthesis was adopted as a meta-analysis could not be performed, due to high study heterogeneity. A total of 72 records were screened, with 21 eligible studies being included in the review. A wide range of biomarkers was investigated and study size varied from 34 to 1258 participants. No single biomarker appeared to be effective in predicting pre-eclampsia; however, glycaemic control was associated with an increased risk while a combination of angiogenic and anti-angiogenic factors seemed to be potentially useful. Limited evidence suggests that combinations of biomarkers may be more effective in predicting pre-eclampsia than single biomarkers. Further research is needed to verify the predictive potential of biomarkers that have been measured in the general maternal population, as many studies exclude women with diabetes preceding pregnancy. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

    Science.gov (United States)

    Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

    2011-01-01

    Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

  20. Subtype classification for prediction of prognosis of breast cancer from a biomarker panel: correlations and indications

    Directory of Open Access Journals (Sweden)

    Chen C

    2014-02-01

    Full Text Available Chuang Chen,1 Jing-Ping Yuan,2,3 Wen Wei,1 Yi Tu,1 Feng Yao,1 Xue-Qin Yang,4 Jin-Zhong Sun,1 Sheng-Rong Sun,1 Yan Li2 1Department of Breast and Thyroid Surgery, Wuhan University, Renmin Hospital, Wuhan, 2Department of Oncology, Zhongnan Hospital of Wuhan University and Hubei Key Laboratory of Tumor Biological Behaviors and Hubei Cancer Clinical Study Center, Wuhan, 3Department of Pathology, The Central Hospital of Wuhan, Wuhan, 4Medical School of Jingchu University of Technology, Jingmen, People’s Republic of China Background: Hormone receptors, including the estrogen receptor and progesterone receptor, human epidermal growth factor receptor 2 (HER2, and other biomarkers like Ki67, epidermal growth factor receptor (EGFR, also known as HER1, the androgen receptor, and p53, are key molecules in breast cancer. This study evaluated the relationship between HER2 and hormone receptors and explored the additional prognostic value of Ki67, EGFR, the androgen receptor, and p53. Methods: Quantitative determination of HER2 and EGFR was performed in 240 invasive breast cancer tissue microarray specimens using quantum dot (QD-based nanotechnology. We identified two subtypes of HER2, ie, high total HER2 load (HTH2 and low total HER2 load (LTH2, and three subtypes of hormone receptor, ie, high hormone receptor (HHR, low hormone receptor (LHR, and no hormone receptor (NHR. Therefore, breast cancer patients could be divided into five subtypes according to HER2 and hormone receptor status. Ki67, p53, and the androgen receptor were determined by traditional immunohistochemistry techniques. The relationship between hormone receptors and HER2 was investigated and the additional value of Ki67, EGFR, the androgen receptor, and p53 for prediction of 5-year disease-free survival was assessed. Results: In all patients, quantitative determination showed a statistically significant (P<0.001 negative correlation between HER2 and the hormone receptors and a significant

  1. Clinical utility and development of biomarkers in invasive aspergillosis.

    Science.gov (United States)

    Patterson, Thomas F

    2011-01-01

    The diagnosis of invasive aspergillosis remains very difficult, and there are limited treatment options for the disease. Pre-clinical models have been used to evaluate the diagnosis and treatment of Aspergillus infection and to assess the pathogenicity and virulence of the organism. Extensive efforts in Aspergillus research have significantly expanded the genomic information about this microorganism. The standardization of animal models of invasive aspergillosis can be used to enhance the evaluation of genomic information about the organism to improve the diagnosis and treatment of invasive aspergillosis. One approach to this process has been the award of a contract by the National Institute of Allergy and Infectious Diseases of the National Institutes of Health to establish and standardize animal models of invasive aspergillosis for the development of new diagnostic technologies for both pulmonary and disseminated Aspergillus infection. This work utilizes molecular approaches for the genetic manipulation of Aspergillus strains that can be tested in animal-model systems to establish new diagnostic targets and tools. Studies have evaluated the performance characteristics of assays for cell-wall antigens of Aspergillus including galactomannan and beta-D-glucan, as well as for DNA targets in the organism, through PCR. New targets, such as proteomic and genomic approaches, and novel detection methods, such as point-of-care lateral-flow devices, have also been evaluated. The goal of this paper is to provide a framework for evaluating genomic targets in animal models to improve the diagnosis and treatment of invasive aspergillosis toward ultimately improving the outcomes for patients with this frequently fatal infection.

  2. Clinical significance of the serum biomarker index detection in children with Henoch-Schonlein purpura.

    Science.gov (United States)

    Purevdorj, Narangerel; Mu, Yun; Gu, Yajun; Zheng, Fang; Wang, Ran; Yu, Jinwei; Sun, Xuguo

    2018-02-01

    To explore a panel of serum biomarkers for laboratory diagnosis of pediatric Henoch-Schönlein purpura (HSP). The blood white blood cells (WBC) and serum levels of serum amyloid A (SAA), interleukin 6 (IL-6), immunoglobulin A (IgA), immunoglobulin G (IgG), immunoglobulin M (IgM), immunoglobulin E (IgE), C-reactive protein (CRP), complement component 3 (C3), complement component 4 (C4), and ASO (anti-streptolysin O) were detected in 127 patients with Henoch-Schonlein purpura (HSP), 110 cases of septicemia patients, and 121 healthy volunteers. The diagnostic ability of biomarkers selected from HSP and septicemia patients was analyzed by ROC curve. By designing the calculation model, the biomarker index was calculated for laboratory diagnosis of HSP and differential diagnosis between HSP and septicemia. The levels of serum WBC, CRP, IL-6 and SAA in the septicemia patients were significantly higher than those in the control group (p<0.05). Compared with the healthy individuals, serum levels of WBC, CRP, IL-6, SAA, IgA and IgM were significantly increased in patients with HSP (p<0.05). The area under the curve (AUC) of SAA, IgA, IgM, WBC, IL-6, and CRP in the patients with HSP was 0.964, 0.855, 0.849, 0.787, 0.765, and 0.622, respectively. The values of SAA, IgA, IgM, WBC, IL-6, and CRP in septicemia patients were 0.700, 0.428, 0.689, 0.682, 0.891, and 0.853, respectively. Biomarker index=SAA+IgA/4000+IgM/4000×0.4CRPmean valueCRPi . The biomarker index in HSP patients was significantly higher than that of the healthy controls. However, the biomarker index in septicemia patients was significantly lower than the control. The biomarker index of HSP patients is higher than that of the control group. While in the infectious disease represented by septicemia, it is decreased. The detection of biomarker index could exclude the interference of infection as the auxiliary examination to HSP patients. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by

  3. Physiotherapy clinical educators' perceptions and experiences of clinical prediction rules.

    Science.gov (United States)

    Knox, Grahame M; Snodgrass, Suzanne J; Rivett, Darren A

    2015-12-01

    Clinical prediction rules (CPRs) are widely used in medicine, but their application to physiotherapy practice is more recent and less widespread, and their implementation in physiotherapy clinical education has not been investigated. This study aimed to determine the experiences and perceptions of physiotherapy clinical educators regarding CPRs, and whether they are teaching CPRs to students on clinical placement. Cross-sectional observational survey using a modified Dillman method. Clinical educators (n=211, response rate 81%) supervising physiotherapy students from 10 universities across 5 states and territories in Australia. Half (48%) of respondents had never heard of CPRs, and a further 25% had never used CPRs. Only 27% reported using CPRs, and of these half (51%) were rarely if ever teaching CPRs to students in the clinical setting. However most respondents (81%) believed CPRs assisted in the development of clinical reasoning skills and few (9%) were opposed to teaching CPRs to students. Users of CPRs were more likely to be male (pphysiotherapy (pStudents are unlikely to be learning about CPRs on clinical placement, as few clinical educators use them. Clinical educators will require training in CPRs and assistance in teaching them if students are to better learn about implementing CPRs in physiotherapy clinical practice. Copyright © 2015 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

  4. An Evidence-Based Approach to the Use of Predictive Biomarkers in the Treatment of Non- Small Cell Lung Cancer (NSCLC)

    International Nuclear Information System (INIS)

    Quinton, Cindy; Ellis, Peter M.

    2011-01-01

    Recent advances in the treatment of non-small cell lung cancer (NSCLC) have led to improvements in patient survival and quality of life. It is unclear whether molecular abnormalities associated with NSCLC cell survival, growth and proliferation are useful in predicting treatment benefit. We conducted a systematic review to establish which biomarkers contribute meaningfully to the management of NSCLC. A team of researchers searched PubMed and conference proceedings (ASCO, ESMO, IASLC, USCAP) using MESH terms for NSCLC and randomized trials (RCT), plus keywords for variables of interest. Evidence from multiple RCTs confirmed that histologic subtype is prognostic for survival and predictive of treatment efficacy and/or toxicity in NSCLC. Likewise, activating mutations of the epidermal growth factor receptor (EGFR) are associated with benefit from EGFR tyrosine kinase inhibitors in patients with advanced non-squamous NSCLC and should be assessed routinely. No biomarkers to date reliably predict response to anti-Vascular Endothelial Growth Factor (VEGF) therapies. There are inconsistent data on the role of ERCC1, BRCA, Beta tubulin III, RRM1, K-RAS, or TP-53 in treatment decisions. These tests should not be routinely used in selecting treatment at this time, whereas EML4/ALK translocations predict responses to specific targeted agents, the optimal assessment of this molecular abnormality has yet to be established. Personalized care of patients with NSCLC based on biomarkers is increasingly important to both clinical practice and research

  5. Biomarkers for Early Detection of Clinically Relevant Prostate Cancer. A Multi-Institutional Validation Trial

    Science.gov (United States)

    2016-10-01

    aim 2: Evaluate a panel of four-kallikrein plasma-based markers to determine the presence of or progression to clinically relevant prostate cancer...and sent to Genomic Health, Inc. for processing. Task 3: Analysis of scientific Aim 2: Evaluate a panel of four-kallikrein plasma-based markers to...site: FHCRC) PCA3 and the TMPRSS2:ERG fusion are prostate cancer-specific biomarkers that hold promise for stratifying risk in the setting of AS

  6. MMP-7 is a predictive biomarker of disease progression in patients with idiopathic pulmonary fibrosis

    Directory of Open Access Journals (Sweden)

    Yasmina Bauer

    2017-03-01

    Full Text Available Idiopathic pulmonary fibrosis (IPF is a progressive interstitial lung disease with poor prognosis, which is characterised by destruction of normal lung architecture and excessive deposition of lung extracellular matrix. The heterogeneity of disease progression in patients with IPF poses significant obstacles to patient care and prevents efficient development of novel therapeutic interventions. Blood biomarkers, reflecting pathobiological processes in the lung, could provide objective evidence of the underlying disease. Longitudinally collected serum samples from the Bosentan Use in Interstitial Lung Disease (BUILD-3 trial were used to measure four biomarkers (metalloproteinase-7 (MMP-7, Fas death receptor ligand, osteopontin and procollagen type I C-peptide, to assess their potential prognostic capabilities and to follow changes during disease progression in patients with IPF. In baseline BUILD-3 samples, only MMP-7 showed clearly elevated protein levels compared with samples from healthy controls, and further investigations demonstrated that MMP-7 levels also increased over time. Baseline levels of MMP-7 were able to predict patients who had higher risk of worsening and, notably, baseline levels of MMP-7 could predict changes in FVC as early as month 4. MMP-7 shows potential to be a reliable predictor of lung function decline and disease progression.

  7. Screening Preoperative Peptide Biomarkers for Predicting Postoperative Myocardial Infarction after Coronary Artery Bypass Grafting

    Science.gov (United States)

    Jiang, Zhibin; Hu, Ping; Liu, Jianxin; Wang, Dianjun; Jin, Longyu; Hong, Chao

    2014-01-01

    Postoperative myocardial infarction (PMI) is one of the most serious complications of cardiac surgeries. No preoperative biomarker is currently available for predicting PMI after cardiac surgeries. In the present study, we used a phage display peptide library to screen potential preoperative peptide biomarkers for predicting PMI after coronary artery bypass grafting (CABG) surgery. Twenty patients who developed PMI after CABG and 20 age-, sex-, and body mass index-matched patients without PMI after CABG were enrolled as a discovery cohort. Another 50 patients who developed PMI after CABG and 50 randomly selected patients without PMI after CABG were enrolled as a validation cohort to validate the potential peptide biomarkers identified in the discovery cohort. Fifty randomly selected healthy volunteers were also enrolled in the validation phase as a healthy control group. In the discovery/screening phase, 17 out of 20 randomly selected phage clones exhibited specific reaction with purified sera IgG from the PMI group, among which 11 came from the same phage clone with inserted peptide sequence GVIMVIAVSCVF (named PMI-1). In the validation phase, phage ELISA showed that serum IgG from 90% of patients in the PMI group had a positive reaction with PMI-1; in contrast, only 14% and 6% of patients in the non-PMI group and the healthy control group had a positive reaction with PMI-1, respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the PMI-1 phage clone to preoperatively identify patients who would develop PMI after CABG were 90.0%, 86.0%, 86.5, 89.5% and 88.0%, respectively. The absorbance value of the PMI-1 phage clone showed statistically significant correlation with the peak postoperative serum cardiac troponin I level (r = 0.349, p = 0.012) in the PMI group. In conclusion, we for the first time identified a mimic peptide (PMI-1) with high validity in preoperative prediction of PMI after CABG. PMID

  8. Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies

    DEFF Research Database (Denmark)

    Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta

    2015-01-01

    concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable...

  9. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker

    NARCIS (Netherlands)

    Cole, James H.; Poudel, Rudra P. K.; Tsagkrasoulis, Dimosthenis; Caan, Matthan W. A.; Steves, Claire; Spector, Tim D.; Montana, Giovanni

    2017-01-01

    Machine learning analysis of neuroimaging data can accurately predict chronological age in healthy people. Deviations from healthy brain ageing have been associated with cognitive impairment and disease. Here we sought to further establish the credentials of 'brain-predicted age' as a biomarker of

  10. Fluid biomarkers in clinical trials of Alzheimer’s disease therapeutics

    Directory of Open Access Journals (Sweden)

    Aaron eRitter

    2015-08-01

    Full Text Available With the demographic shift of the global population towards longer life expectancy, the number of people living with Alzheimer’s disease (AD has rapidly expanded and is projected to triple by the year 2050. Current treatments provide symptomatic relief but do not affect the underlying pathology of the disease. Therapies that prevent or slow the progression of the disease are urgently needed to avoid this growing public health emergency. Insights gained from decades of research have begun to unlock the pathophysiology of this complex disease and have provided targets for disease modifying therapies. In the last decade, few therapeutic agents designed to modify the underlying disease process have progressed to clinical trials and none have been brought to market. With the focus on disease modification, biomarkers promise to play an increasingly important role in clinical trials. Six biomarkers have now been included in diagnostic criteria for AD and are regularly incorporated into clinical trials. Three biomarkers are neuroimaging measures—hippocampal atrophy measured by magnetic resonance imaging (MRI, amyloid uptake as measured by Pittsburg compound B positron emission tomography (PiB PET, and decreased fluorodeoxyglucose (18F uptake as measured by positron emission tomography (FDG PET—and three are sampled from fluid sources—cerebrospinal fluid (CSF levels

  11. Innovative biomarkers in psychiatric disorders: a major clinical challenge in psychiatry.

    Science.gov (United States)

    Lozupone, Madia; Seripa, Davide; Stella, Eleonora; La Montagna, Maddalena; Solfrizzi, Vincenzo; Quaranta, Nicola; Veneziani, Federica; Cester, Alberto; Sardone, Rodolfo; Bonfiglio, Caterina; Giannelli, Gianluigi; Bisceglia, Paola; Bringiotti, Roberto; Daniele, Antonio; Greco, Antonio; Bellomo, Antonello; Logroscino, Giancarlo; Panza, Francesco

    2017-09-01

    Currently, the diagnosis of psychiatric illnesses is based upon DSM-5 criteria. Although endophenotype-specificity for a particular disorder is discussed, the identification of objective biomarkers is ongoing for aiding diagnosis, prognosis, or clinical response to treatment. We need to improve the understanding of the biological abnormalities in psychiatric illnesses across conventional diagnostic boundaries. The present review investigates the innovative post-genomic knowledge used for psychiatric illness diagnostics and treatment response, with a particular focus on proteomics. Areas covered: This review underlines the contribution that psychiatric innovative biomarkers have reached in relation to diagnosis and theragnosis of psychiatric illnesses. Furthermore, it encompasses a reliable representation of their involvement in disease through proteomics, metabolomics/pharmacometabolomics and lipidomics techniques, including the possible role that gut microbiota and CYP2D6 polimorphisms may play in psychiatric illnesses. Expert opinion: Etiologic heterogeneity, variable expressivity, and epigenetics may impact clinical manifestations, making it difficult for a single measurement to be pathognomonic for multifaceted psychiatric disorders. Academic, industry, or government's partnerships may successfully identify and validate new biomarkers so that unfailing clinical tests can be developed. Proteomics, metabolomics, and lipidomics techniques are considered to be helpful tools beyond neuroimaging and neuropsychology for the phenotypic characterization of brain diseases.

  12. Toxicogenomic multigene biomarker for predicting the future onset of proximal tubular injury in rats

    International Nuclear Information System (INIS)

    Minowa, Yohsuke; Kondo, Chiaki; Uehara, Takeki; Morikawa, Yuji; Okuno, Yasushi; Nakatsu, Noriyuki; Ono, Atsushi; Maruyama, Toshiyuki; Kato, Ikuo; Yamate, Jyoji; Yamada, Hiroshi; Ohno, Yasuo; Urushidani, Tetsuro

    2012-01-01

    Drug-induced renal tubular injury is a major concern in the preclinical safety evaluation of drug candidates. Toxicogenomics is now a generally accepted tool for identifying chemicals with potential safety problems. The specific aim of the present study was to develop a model for use in predicting the future onset of drug-induced proximal tubular injury following repeated dosing with various nephrotoxicants. In total, 41 nephrotoxic and nonnephrotoxic compounds were used for the present analysis. Male Sprague-Dawley rats were dosed orally or intravenously once daily. Animals were exposed to three different doses (low, middle, and high) of each compound, and kidney tissue was collected at 3, 6, 9, and 24 h after single dosing, and on days 4, 8, 15, and 29 after repeated dosing. Gene expression profiles were generated from kidney total RNA using Affymetrix DNA microarrays. Filter-type gene selection and linear classification algorithms were employed to discriminate future onset of proximal tubular injury. We identified genomic biomarkers for use in future onset prediction using the gene expression profiles determined on day 1, when most of the nephrotoxicants had yet to produce detectable histopathological changes. The model was evaluated using a five-fold cross validation, and achieved a sensitivity of 93% and selectivity of 90% with 19 probes. We also found that the prediction accuracy of the optimized model was substantially higher than that produced by any of the single genomic biomarkers or histopathology. The genes included in our model were primarily involved in DNA replication, cell cycle control, apoptosis, and responses to oxidative stress and chemical stimuli. In summary, our toxicogenomic model is particularly useful for predicting the future onset of proximal tubular injury.

  13. Biomarkers of PTSD: military applications and considerations

    Directory of Open Access Journals (Sweden)

    Amy Lehrner

    2014-08-01

    Full Text Available Background: Although there are no established biomarkers for posttraumatic stress disorder (PTSD as yet, biological investigations of PTSD have made progress identifying the pathophysiology of PTSD. Given the biological and clinical complexity of PTSD, it is increasingly unlikely that a single biomarker of disease will be identified. Rather, investigations will more likely identify different biomarkers that indicate the presence of clinically significant PTSD symptoms, associate with risk for PTSD following trauma exposure, and predict or identify recovery. While there has been much interest in PTSD biomarkers, there has been less discussion of their potential clinical applications, and of the social, legal, and ethical implications of such biomarkers. Objective: This article will discuss possible applications of PTSD biomarkers, including the social, legal, and ethical implications of such biomarkers, with an emphasis on military applications. Method: Literature on applications of PTSD biomarkers and on potential ethical and legal implications will be reviewed. Results: Biologically informed research findings hold promise for prevention, assessment, treatment planning, and the development of prophylactic and treatment interventions. As with any biological indicator of disorder, there are potentially positive and negative clinical, social, legal, and ethical consequences of using such biomarkers. Conclusions: Potential clinical applications of PTSD biomarkers hold promise for clinicians, patients, and employers. The search for biomarkers of PTSD should occur in tandem with an interdisciplinary discussion regarding the potential implications of applying biological findings in clinical and employment settings.

  14. Biomarkers of PTSD: military applications and considerations.

    Science.gov (United States)

    Lehrner, Amy; Yehuda, Rachel

    2014-01-01

    Although there are no established biomarkers for posttraumatic stress disorder (PTSD) as yet, biological investigations of PTSD have made progress identifying the pathophysiology of PTSD. Given the biological and clinical complexity of PTSD, it is increasingly unlikely that a single biomarker of disease will be identified. Rather, investigations will more likely identify different biomarkers that indicate the presence of clinically significant PTSD symptoms, associate with risk for PTSD following trauma exposure, and predict or identify recovery. While there has been much interest in PTSD biomarkers, there has been less discussion of their potential clinical applications, and of the social, legal, and ethical implications of such biomarkers. This article will discuss possible applications of PTSD biomarkers, including the social, legal, and ethical implications of such biomarkers, with an emphasis on military applications. Literature on applications of PTSD biomarkers and on potential ethical and legal implications will be reviewed. Biologically informed research findings hold promise for prevention, assessment, treatment planning, and the development of prophylactic and treatment interventions. As with any biological indicator of disorder, there are potentially positive and negative clinical, social, legal, and ethical consequences of using such biomarkers. Potential clinical applications of PTSD biomarkers hold promise for clinicians, patients, and employers. The search for biomarkers of PTSD should occur in tandem with an interdisciplinary discussion regarding the potential implications of applying biological findings in clinical and employment settings.

  15. Enhancing the 'real world' prediction of cardiovascular events and major bleeding with the CHA2DS2-VASc and HAS-BLED scores using multiple biomarkers.

    Science.gov (United States)

    Roldán, Vanessa; Rivera-Caravaca, José Miguel; Shantsila, Alena; García-Fernández, Amaya; Esteve-Pastor, María Asunción; Vilchez, Juan Antonio; Romera, Marta; Valdés, Mariano; Vicente, Vicente; Marín, Francisco; Lip, Gregory Y H

    2018-02-01

    Atrial fibrillation (AF)-European guidelines suggest the use of biomarkers to stratify patients for stroke and bleeding risks. We investigated if a multibiomarker strategy improved the predictive performance of CHA 2 DS 2 -VASc and HAS-BLED in anticoagulated AF patients. We included consecutive patients stabilized for six months on vitamin K antagonists (INRs 2.0-3.0). High sensitivity troponin T, NT-proBNP, interleukin-6, von Willebrand factor concentrations and glomerular filtration rate (eGFR; using MDRD-4 formula) were quantified at baseline. Time in therapeutic range (TTR) was recorded at six months after inclusion. Patients were follow-up during a median of 2375 (IQR 1564-2887) days and all adverse events were recorded. In 1361 patients, adding four blood biomarkers, TTR and MDRD-eGFR, the predictive value of CHA 2 DS 2 -VASc increased significantly by c-index (0.63 vs. 0.65; p = .030) and IDI (0.85%; p originals scores. Addition of biomarkers enhanced the predictive value of CHA 2 DS 2 -VASc and HAS-BLED, although the overall improvement was modest and the added predictive advantage over original scores was marginal. Key Messages Recent atrial fibrillation (AF)-European guidelines for the first time suggest the use of biomarkers to stratify patients for stroke and bleeding risks, but their usefulness in real world for risk stratification is still questionable. In this cohort study involving 1361 AF patients optimally anticoagulated with vitamin K antagonists, adding high sensitivity troponin T, N-terminal pro-B-type natriuretic peptide, interleukin 6, von Willebrand factor, glomerular filtration rate (by the MDRD-4 formula) and time in therapeutic range, increased the predictive value of CHA 2 DS 2 -VASc for cardiovascular events, but not the predictive value of HAS-BLED for major bleeding. Reclassification analyses did not show improvement adding multiple biomarkers. Despite the improvement observed, the added predictive advantage is marginal and

  16. Analysis of a urinary biomarker panel for obstructive nephropathy and clinical outcomes.

    Directory of Open Access Journals (Sweden)

    Yuanyuan Xie

    Full Text Available To follow up renal function changes in patients with obstructive nephropathy and to evaluate the predictive value of biomarker panel in renal prognosis.A total of 108 patients with obstructive nephropathy were enrolled in the study; 90 patients completed the follow-up. At multiple time points before and after obstruction resolution, urinary samples were prospectively collected in patients with obstructive nephropathy; the levels of urinary kidney injury molecule-1 (uKIM-1, liver-type fatty acid-binding protein (uL-FABP, and neutrophil gelatinase associated lipocalin (uNGAL were determined by enzyme-linked immunosorbent assay (ELISA. After 1 year of follow-up, the predictive values of biomarker panel for determining the prognosis of obstructive nephropathy were evaluated.uKIM-1 (r = 0.823, uL-FABP (r = 0.670, and uNGAL (r = 0.720 levels were positively correlated with the serum creatinine level (all P96.69 pg/mg creatinine (Cr, a preoperative uL-FABP>154.62 ng/mg Cr, and a 72-h postoperative uL-FABP>99.86 ng/mg Cr were all positively correlated with poor prognosis (all P<0.01.Biomarker panel may be used as a marker for early screening of patients with obstructive nephropathy and for determining poor prognosis.

  17. An early-biomarker algorithm predicts lethal graft-versus-host disease and survival.

    Science.gov (United States)

    Hartwell, Matthew J; Özbek, Umut; Holler, Ernst; Renteria, Anne S; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J; Ayuk, Francis; Efebera, Yvonne A; Hexner, Elizabeth O; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Pawarode, Attaphol; Chen, Yi-Bin; Devine, Steven; Harris, Andrew C; Jagasia, Madan; Kitko, Carrie L; Litzow, Mark R; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Wudhikarn, Kitsada; Yanik, Gregory A; Levine, John E; Ferrara, James L M

    2017-02-09

    BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set ( n = 309) and validation set ( n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group ( P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation.

  18. Fetal hemoglobin, α1-microglobulin and hemopexin are potential predictive first trimester biomarkers for preeclampsia.

    Science.gov (United States)

    Anderson, Ulrik Dolberg; Gram, Magnus; Ranstam, Jonas; Thilaganathan, Basky; Kerström, Bo; Hansson, Stefan R

    2016-04-01

    Overproduction of cell-free fetal hemoglobin (HbF) in the preeclamptic placenta has been recently implicated as a new etiological factor of preeclampsia. In this study, maternal serum levels of HbF and the endogenous hemoglobin/heme scavenging systems were evaluated as predictive biomarkers for preeclampsia in combination with uterine artery Doppler ultrasound. Case-control study including 433 women in early pregnancy (mean 13.7weeks of gestation) of which 86 subsequently developed preeclampsia. The serum concentrations of HbF, total cell-free hemoglobin, hemopexin, haptoglobin and α1-microglobulin were measured in maternal serum. All patients were examined with uterine artery Doppler ultrasound. Logistic regression models were developed, which included the biomarkers, ultrasound indices, and maternal risk factors. There were significantly higher serum concentrations of HbF and α1-microglobulin and significantly lower serum concentrations of hemopexin in patients who later developed preeclampsia. The uterine artery Doppler ultrasound results showed significantly higher pulsatility index values in the preeclampsia group. The optimal prediction model was obtained by combining HbF, α1-microglobulin and hemopexin in combination with the maternal characteristics parity, diabetes and pre-pregnancy hypertension. The optimal sensitivity for all preeclampsia was 60% at 95% specificity. Overproduction of placentally derived HbF and depletion of hemoglobin/heme scavenging mechanisms are involved in the pathogenesis of preeclampsia. The combination of HbF and α1-microglobulin and/or hemopexin may serve as a prediction model for preeclampsia in combination with maternal risk factors and/or uterine artery Doppler ultrasound. Copyright © 2016 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

  19. Precision diagnostics: moving towards protein biomarker signatures of clinical utility in cancer.

    Science.gov (United States)

    Borrebaeck, Carl A K

    2017-03-01

    Interest in precision diagnostics has been fuelled by the concept that early detection of cancer would benefit patients; that is, if detected early, more tumours should be resectable and treatment more efficacious. Serum contains massive amounts of potentially diagnostic information, and affinity proteomics has risen as an accurate approach to decipher this, to generate actionable information that should result in more precise and evidence-based options to manage cancer. To achieve this, we need to move from single to multiplex biomarkers, a so-called signature, that can provide significantly increased diagnostic accuracy. This Opinion article focuses on the progress being made in identifying protein biomarker signatures of clinical utility, using blood-based proteomics.

  20. Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2017-10-01

    Full Text Available We outline an automated computational and machine learning framework that predicts disease severity and stratifies patients. We apply our framework to available clinical data. Our algorithm automatically generates insights and predicts disease severity with minimal operator intervention. The computational framework presented here can be used to stratify patients, predict disease severity and propose novel biomarkers for disease. Insights from machine learning algorithms coupled with clinical data may help guide therapy, personalize treatment and help clinicians understand the change in disease over time. Computational techniques like these can be used in translational medicine in close collaboration with clinicians and healthcare providers. Our models are also interpretable, allowing clinicians with minimal machine learning experience to engage in model building. This work is a step towards automated machine learning in the clinic.

  1. MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction.

    Science.gov (United States)

    Nassar, Farah J; Nasr, Rihab; Talhouk, Rabih

    2017-04-01

    Breast cancer is a major health problem that affects one in eight women worldwide. As such, detecting breast cancer at an early stage anticipates better disease outcome and prolonged patient survival. Extensive research has shown that microRNA (miRNA) are dysregulated at all stages of breast cancer. miRNA are a class of small noncoding RNA molecules that can modulate gene expression and are easily accessible and quantifiable. This review highlights miRNA as diagnostic, prognostic and therapy predictive biomarkers for early breast cancer with an emphasis on the latter. It also examines the challenges that lie ahead in their use as biomarkers. Noteworthy, this review addresses miRNAs reported in patients with early breast cancer prior to chemotherapy, radiotherapy, surgical procedures or distant metastasis (unless indicated otherwise). In this context, miRNA that are mentioned in this review were significantly modulated using more than one statistical test and/or validated by at least two studies. A standardized protocol for miRNA assessment is proposed starting from sample collection to data analysis that ensures comparative analysis of data and reproducibility of results. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Genomic biomarkers of prenatal intrauterine inflammation in umbilical cord tissue predict later life neurological outcomes.

    Directory of Open Access Journals (Sweden)

    Sloane K Tilley

    Full Text Available Preterm birth is a major risk factor for neurodevelopmental delays and disorders. This study aimed to identify genomic biomarkers of intrauterine inflammation in umbilical cord tissue in preterm neonates that predict cognitive impairment at 10 years of age.Genome-wide messenger RNA (mRNA levels from umbilical cord tissue were obtained from 43 neonates born before 28 weeks of gestation. Genes that were differentially expressed across four indicators of intrauterine inflammation were identified and their functions examined. Exact logistic regression was used to test whether expression levels in umbilical cord tissue predicted neurocognitive function at 10 years of age.Placental indicators of inflammation were associated with changes in the mRNA expression of 445 genes in umbilical cord tissue. Transcripts with decreased expression showed significant enrichment for biological signaling processes related to neuronal development and growth. The altered expression of six genes was found to predict neurocognitive impairment when children were 10 years old These genes include two that encode for proteins involved in neuronal development.Prenatal intrauterine inflammation is associated with altered gene expression in umbilical cord tissue. A set of six of the differentially expressed genes predict cognitive impairment later in life, suggesting that the fetal environment is associated with significant adverse effects on neurodevelopment that persist into later childhood.

  3. Clinical Significance of Cerebrovascular Biomarkers and White Matter Tract Integrity in Alzheimer Disease: Clinical correlations With Neurobehavioral Data in Cross-Sectional and After 18 Months Follow-ups.

    Science.gov (United States)

    Wu, Ming-Kung; Lu, Yan-Ting; Huang, Chi-Wei; Lin, Pin-Hsuan; Chen, Nai-Ching; Lui, Chun-Chung; Chang, Wen-Neng; Lee, Chen-Chang; Chang, Ya-Ting; Chen, Sz-Fan; Chang, Chiung-Chih

    2015-07-01

    Cerebrovascular risk factors and white matter (WM) damage lead to worse cognitive performance in Alzheimer dementia (AD). This study investigated WM microstructure using diffusion tensor imaging in patients with mild to moderate AD and investigated specific fiber tract involvement with respect to predefined cerebrovascular risk factors and neurobehavioral data prediction cross-sectionally and after 18 months. To identify the primary pathoanatomic relationships of risk biomarkers to fiber tract integrity, we predefined 11 major association tracts and calculated tract specific fractional anisotropy (FA) values. Eighty-five patients with AD underwent neurobehavioral assessments including the minimental state examination (MMSE) and 12-item neuropsychiatric inventory twice with a 1.5-year interval to represent major outcome factors. In the cross-sectional data, total cholesterol, low-density lipoprotein, vitamin B12, and homocysteine levels correlated variably with WM FA values. After entering the biomarkers and WM FA into a regression model to predict neurobehavioral outcomes, only fiber tract FA or homocysteine level predicted the MMSE score, and fiber tract FA or age predicted the neuropsychiatric inventory total scores and subdomains of apathy, disinhibition, and aberrant motor behavior. In the follow-up neurobehavioral data, the mean global FA value predicted the MMSE and aberrant motor behavior subdomain, while age predicted the anxiety and elation subdomains. Cerebrovascular risk biomarkers may modify WM microstructural organization, while the association with fiber integrity showed greater clinical significance to the prediction of neurobehavioral outcomes both cross-sectionally and longitudinally.

  4. Searching for neurodegeneration in multiple sclerosis at clinical onset: Diagnostic value of biomarkers.

    Science.gov (United States)

    Novakova, Lenka; Axelsson, Markus; Malmeström, Clas; Imberg, Henrik; Elias, Olle; Zetterberg, Henrik; Nerman, Olle; Lycke, Jan

    2018-01-01

    Neurodegeneration occurs during the early stages of multiple sclerosis. It is an essential, devastating part of the pathophysiology. Tools for measuring the degree of neurodegeneration could improve diagnostics and patient characterization. This study aimed to determine the diagnostic value of biomarkers of degeneration in patients with recent clinical onset of suspected multiple sclerosis, and to evaluate these biomarkers for characterizing disease course. This cross-sectional study included 271 patients with clinical features of suspected multiple sclerosis onset and was the baseline of a prospective study. After diagnostic investigations, the patients were classified into the following disease groups: patients with clinically isolated syndrome (n = 4) or early relapsing remitting multiple sclerosis (early RRMS; n = 93); patients with relapsing remitting multiple sclerosis with disease durations ≥2 years (established RRMS; n = 39); patients without multiple sclerosis, but showing symptoms (symptomatic controls; n = 89); and patients diagnosed with other diseases (n = 46). In addition, we included healthy controls (n = 51) and patients with progressive multiple sclerosis (n = 23). We analyzed six biomarkers of neurodegeneration: cerebrospinal fluid neurofilament light chain levels; cerebral spinal fluid glial fibrillary acidic protein; cerebral spinal fluid tau; retinal nerve fiber layer thickness; macula volume; and the brain parenchymal fraction. Except for increased cerebral spinal fluid neurofilament light chain levels, median 670 ng/L (IQR 400-2110), we could not find signs of early degeneration in the early disease group with recent clinical onset. However, the intrathecal immunoglobin G production and cerebral spinal fluid neurofilament light chain levels showed diagnostic value. Moreover, elevated levels of cerebral spinal fluid glial fibrillary acidic protein, thin retinal nerve fiber layers, and low brain parenchymal fractions were associated with

  5. Tissue Biomarkers in Predicting Response to Sunitinib Treatment of Metastatic Renal Cell Carcinoma.

    Science.gov (United States)

    Trávníček, Ivan; Branžovský, Jindřich; Kalusová, Kristýna; Hes, Ondřej; Holubec, Luboš; Pele, Kevin Bauleth; Ürge, Tomáš; Hora, Milan

    2015-10-01

    To identify tissue biomarkers that are predictive of the therapeutic effect of sunitinib in treatment of metastatic clear cell renal cell carcinoma (mCRCC). Our study included 39 patients with mCRCC treated with sunitinib. Patients were stratified into two groups based on their response to sunitinib treatment: non-responders (progression), and responders (stable disease, regression). The effect of treatment was measured by comparing imaging studies before the initiation treatment with those performed at between 3rd and 7th months of treatment, depending on the patient. Histological samples of tumor tissue and healthy renal parenchyma, acquired during surgery of the primary tumor, were examined with immunohistochemistry to detect tissue targets involved in the signaling pathways of tumor growth and neoangiogenesis. We selected mammalian target of rapamycine, p53, vascular endothelial growth factor, hypoxia-inducible factor 1 and 2 and carbonic anhydrase IX. We compared the average levels of biomarker expression in both, tumor tissue, as well as in healthy renal parenchyma. Results were evaluated using the Student's t-test. For responders, statistically significant differences in marker expression in tumor tissue versus healthy parenchyma were found for mTOR (4%/16.7%; p=0.01031), p53 (4%/12.7%; p=0.042019), VEGF (62.7%/45%; p=0.019836) and CAIX (45%/15.33%; p=0.001624). A further significant difference was found in the frequency of high expression (more than 60%) between tumor tissue and healthy parenchyma in VEGF (65%/35%; p=0.026487) and CAIX (42%/8%; p=0.003328). CAIX was expressed at high levels in the tumor tissue in both evaluated groups. A significantly higher expression of VEGF in CRCC in comparison to healthy parenchyma can predict a better response to sunitinib. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  6. Prediction of postpercutaneous coronary intervention myocardial infarction: insights from intravascular imaging, coronary flow, and biomarker evaluation.

    Science.gov (United States)

    Hoole, Stephen P; Hernández-Sánchez, Jules; Brown, Adam J; Giblett, Joel P; Bennett, Martin R; West, Nick E J

    2018-05-01

    Percutaneous coronary intervention-induced myocardial infarction (PMI) has prognostic significance. Identifying patients at high risk for PMI is desirable as it may alter strategy and facilitate early preventative therapy. We therefore sought to establish whether preprocedural demographic, interventional (plaque characteristics and coronary microcirculatory function), and inflammatory, endothelial damage, and platelet-derived biomarker data could predict the risk of PMI. We performed target vessel pressure wire to assess fractional flow reserve, index of microcirculatory resistance (IMR) and coronary flow reserve, plaque characterization by virtual histology intravascular ultrasound, and assayed peripheral biomarkers before uncomplicated PCI in 88 patients. We then analyzed post-PCI cardiac troponin level to adjudicate PMI based on the third universal definition of myocardial infarction. Overall incidence of PMI was 27%. Women [10/15 (66%) vs. 14/73 (19%), PPMI. Preprocedural coronary flow reserve was lower in individuals with a subsequent PMI (1.8±1.2 vs. 2.1±1.3. P=0.03), and patients with higher pre-PCI IMR were more likely to sustain PMI [IMR>22: 10/23 (44%) vs. ≤22: 14/65 (22%), P=0.04], although neither was predictive after multivariate analysis. Plaque characterization by virtual histology intravascular ultrasound did not discriminate those at risk of PMI. However, peripheral venous interleukin (IL)-18 and IL-8 levels were independently negatively and positively associated with PMI, respectively. Women and those with low BMI, particularly when associated with high IL-8 and low IL-18 levels, appear to be at increased risk of PMI.

  7. Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

    Science.gov (United States)

    Wostyn, Peter; De Deyn, Peter Paul

    2017-11-01

    A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

  8. Profiling inflammatory biomarkers in cervico-vaginal mucus (CVM) postpartum: Potential early indicators of bovine clinical endometritis?

    Science.gov (United States)

    Adnane, Mounir; Chapwanya, Aspinas; Kaidi, Rachid; Meade, Kieran G; O'Farrelly, Cliona

    2017-11-01

    Endometritis significantly impacts fertility and milk yield, thus reducing profitability of the dairy production. In cows that develop endometritis, normal postpartum endometrial inflammation is dysregulated. Here, we propose that endometrial inflammation is reflected in cervico-vaginal mucus (CVM) which could therefore be used as a prognostic tool. CVM was collected from 20 dairy cows (10 with clinical endometritis and 10 healthy) 7 and 21 days postpartum (DPP). Polymorphonuclear (PMN), mononuclear leukocyte and epithelial cells were counted, total protein levels were estimated and levels of IL-1β, IL-6, IL-8, serum amyloid A (SAA), haptoglobin (Hp) and C5b were analyzed by ELISA in CVM. PMN were consistently high in CVM from 7 to 21 DPP, but were higher in CVM from cows with clinical endometritis 21 DPP compared with healthy cows. In contrast, there were more epithelial cells in healthy cows 21 DPP than in clinical endometritis animals. Total protein levels decreased significantly in CVM from healthy cows between days 7 and 21 postpartum. All inflammatory biomarkers except C5b, remained high in cows with clinical endometritis from 7 to 21 DPP, indicating sustained and chronic endometrial inflammation. IL1, IL-6, IL-8 and Hp levels were higher in CVM from cows with clinical endometritis compared to healthy cows 21 DPP. Interestingly IL-1β levels were raised in CVM from clinical endometritis but not in healthy cows 7 DPP suggesting that early measurement of IL-1β levels might provide a useful predictive marker of clinical endometritis. In contrast, SAA and C5b levels were increased in healthy cows 21 DPP, compared to cows with clinical endometritis suggesting that these acute phase proteins might have an anti-inflammatory role. Our results show that CVM is convenient for profiling disease-associated changes in key inflammatory molecules postpartum and reaffirms that sustained inflammation is a key feature of clinical endometritis in the dairy cow. Copyright

  9. Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

    Science.gov (United States)

    Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

    2015-02-10

    Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

  10. Response-driven imaging biomarkers for predicting radiation necrosis of the brain

    International Nuclear Information System (INIS)

    Nazem-Zadeh, Mohammad-Reza; Chapman, Christopher H; Lawrence, Theodore S; Ten Haken, Randall K; Tsien, Christina I; Cao, Yue; Chenevert, Thomas

    2014-01-01

    Radiation necrosis is an uncommon but severe adverse effect of brain radiation therapy (RT). Current predictive models based on radiation dose have limited accuracy. We aimed to identify early individual response biomarkers based upon diffusion tensor (DT) imaging and incorporated them into a response model for prediction of radiation necrosis. Twenty-nine patients with glioblastoma received six weeks of intensity modulated RT and concurrent temozolomide. Patients underwent DT-MRI scans before treatment, at three weeks during RT, and one, three, and six months after RT. Cases with radiation necrosis were classified based on generalized equivalent uniform dose (gEUD) of whole brain and DT index early changes in the corpus callosum and its substructures. Significant covariates were used to develop normal tissue complication probability models using binary logistic regression. Seven patients developed radiation necrosis. Percentage changes of radial diffusivity (RD) in the splenium at three weeks during RT and at six months after RT differed significantly between the patients with and without necrosis (p = 0.05 and p = 0.01). Percentage change of RD at three weeks during RT in the 30 Gy dose–volume of the splenium and brain gEUD combined yielded the best-fit logistic regression model. Our findings indicate that early individual response during the course of RT, assessed by radial diffusivity, has the potential to aid the prediction of delayed radiation necrosis, which could provide guidance in dose-escalation trials. (paper)

  11. Thymus and activation-regulated chemokine as a clinical biomarker in atopic dermatitis.

    Science.gov (United States)

    Kataoka, Yoko

    2014-03-01

    Thymus and activation-regulated chemokine (TARC/CCL17) is a member of the T-helper 2 chemokine family. In Japan, serum TARC level has been commercially measured since 2008. After years of experience, we realized that TARC is an extremely useful clinical biomarker for atopic dermatitis (AD) treatment. Usually, physicians conduct a visual examination to determine whether their treatment has been successful; however, the visual examination results may not always be accurate; in such cases, serum TARC levels should be measured to eliminate any ambiguity regarding the treatment outcome. When the waning and waxing of eczema and fluctuations in the serum TARC levels were considered, we frequently found that AD does not follow a natural course but follows non-regulated inflammatory floating caused by insufficient intermittent topical treatment. Serum TARC is a promising biomarker for remission and can be used for accurately monitoring proactive treatment for long-term control. Abnormally high serum TARC levels indicate accelerated pathogenesis of cutaneous inflammation. Rapid normalization and maintaining normal serum TARC levels using appropriate topical treatment is a reasonable strategy for alleviating inflammation without upregulating cytokine expression. Observing serum TARC levels during early intervention for severe infantile AD is worthwhile to determine initial disease activity and evaluate treatment efficacy. Appropriate control of severe early-onset infantile AD is important for improving prognosis of eczema and for preventing food allergies. Additionally, this biomarker is useful for improving patient adherence. Dermatologists will be able to make great progress in treating AD by adopting biomarkers such as TARC for accurately assessing non-visible subclinical disorders. © 2014 Japanese Dermatological Association.

  12. A three-protein biomarker panel assessed in diagnostic tissue predicts death from prostate cancer for men with localized disease

    International Nuclear Information System (INIS)

    Severi, Gianluca; FitzGerald, Liesel M; Muller, David C; Pedersen, John; Longano, Anthony; Southey, Melissa C; Hopper, John L; English, Dallas R; Giles, Graham G; Mills, John

    2014-01-01

    Only a minority of prostate cancers lead to death. Because no tissue biomarkers of aggressiveness other than Gleason score are available at diagnosis, many nonlethal cancers are treated aggressively. We evaluated whether a panel of biomarkers, associated with a range of disease outcomes in previous studies, could predict death from prostate cancer for men with localized disease. Using a case-only design, subjects were identified from three Australian epidemiological studies. Men who had died of their disease, “cases” (N = 83), were matched to “referents” (N = 232), those who had not died of prostate cancer, using incidence density sampling. Diagnostic tissue was retrieved to assess expression of AZGP1, MUC1, NKX3.1, p53, and PTEN by semiquantitative immunohistochemistry (IHC). Poisson regression was used to estimate mortality rate ratios (MRRs) adjusted for age, Gleason score, and stage and to estimate survival probabilities. Expression of MUC1 and p53 was associated with increased mortality (MRR 2.51, 95% CI 1.14–5.54, P = 0.02 and 3.08, 95% CI 1.41–6.95, P = 0.005, respectively), whereas AZGP1 expression was associated with decreased mortality (MRR 0.44, 95% CI 0.20–0.96, P = 0.04). Analyzing all markers under a combined model indicated that the three markers were independent predictors of prostate cancer death and survival. For men with localized disease at diagnosis, assessment of AZGP1, MUC1, and p53 expression in diagnostic tissue by IHC could potentially improve estimates of risk of dying from prostate cancer based only on Gleason score and clinical stage

  13. PD-L1 expression as a predictive biomarker in advanced non-small-cell lung cancer: updated survival data.

    Science.gov (United States)

    Aguiar, Pedro N; De Mello, Ramon Andrade; Hall, Peter; Tadokoro, Hakaru; Lima Lopes, Gilberto de

    2017-05-01

    The treatment of non-small-cell lung cancer has changed after the development of the immune checkpoint inhibitors. Although the most studied biomarker is PD-L1 expression, its clinical significance is still debatable. In this article, we show the updated survival analysis of all published data. We searched in network and conference data sources for relevant clinical studies of immunotherapy for non-small-cell lung cancer that assessed the PD-L1 expression even as an exploratory analysis. The updated survival hazard ratios (HR) were included in the analysis. 14 studies with 2857 patients were included (2019 treated with immunotherapy). The response rate was as higher among PD-L1-positive patients (RR: 2.19, 95% CI: 1.63-2.94). PD-L1 expression was also related to better progression-free survival (HR: 0.69, 95% CI: 0.57-0.85) and better overall survival (HR: 0.77, 95% CI: 0.67-0.89). PD-L1 overexpression predicts activity as well as better survival for patients treated with immune checkpoint inhibitors.

  14. Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

    Science.gov (United States)

    Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

    2018-03-20

    Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

  15. Prognostic biomarkers in osteoarthritis

    Science.gov (United States)

    Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

    2013-01-01

    Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

  16. Admission biomarkers of trauma-induced secondary cardiac injury predict adverse cardiac events and are associated with plasma catecholamine levels.

    Science.gov (United States)

    Naganathar, Sriveena; De'Ath, Henry D; Wall, Johanna; Brohi, Karim

    2015-07-01

    Secondary cardiac injury and dysfunction may be important contributors to poor outcomes in trauma patients, but the pathophysiology and clinical impact remain unclear. Early elevations in cardiac injury markers have been associated with the development of adverse cardiac events (ACEs), prolonged intensive care unit stays, and increased mortality. Studies of preinjury β-blocker use suggest a potential protective effect in critically ill trauma patients. This study aimed to prospectively examine the association of early biomarker evidence of trauma-induced secondary cardiac injury (TISCI) and ACEs and to examine the potential contribution of circulating catecholamines to its pathophysiology. Injured patients who met the study criteria were recruited at a single major trauma center. A blood sample was collected immediately on arrival. Serum epinephrine (E), norepinephrine (NE), and cardiac biomarkers including heart-related fatty acid binding protein (H-FABP) were assayed. Data were prospectively collected on ACEs. Of 300 patients recruited, 38 (13%) developed an ACE and had increased mortality (19% vs. 9%, p = 0.01) and longer intensive care unit stays (13 days, p < 0.001). H-FABP was elevated on admission in 56% of the patients, predicted the development of ACE, and was associated with higher mortality (14% vs. 5%, p = 0.01). Admission E and NE levels were strongly associated with elevations in H-FABP and ACEs (E, 274.0 pg/mL vs. 622.5 pg/mL, p < 0.001; NE, 1,063.2 pg/mL vs. 2,032.6 pg/mL, p < 0.001). Catecholamine effect on the development of TISCI or ACEs was not statistically independent of injury severity or depth of shock. Admission levels of H-FABP predict the development of ACEs and may be useful for prognosis and stratification of trauma patients. The development of TISCI and ACEs was associated with high admission levels of catecholamines, but their role in pathogenesis remains unclear. Clinical trials of adrenergic blockade may have the potential to

  17. Urinary biomarkers TIMP-2 and IGFBP7 early predict acute kidney injury after major surgery.

    Directory of Open Access Journals (Sweden)

    Ivan Gocze

    Full Text Available To assess the ability of the urinary biomarkers IGFBP7 (insulin-like growth factor-binding protein 7 and TIMP-2 (tissue inhibitor of metalloproteinase 2 to early predict acute kidney injury (AKI in high-risk surgical patients.Postoperative AKI is associated with an increase in short and long-term mortality. Using IGFBP7 and TIMP-2 for early detection of cellular kidney injury, thus allowing the early initiation of renal protection measures, may represent a new concept of evaluating renal function.In this prospective study, urinary [TIMP-2]×[IGFBP7] was measured in surgical patients at high risk for AKI. A predefined cut-off value of [TIMP-2]×[IGFBP7] >0.3 was used for assessing diagnostic accuracy. Perioperative characteristics were evaluated, and ROC analyses as well as logistic regression models of risk assessment were calculated with and without a [TIMP-2]×[IGFBP7] test.107 patients were included in the study, of whom 45 (42% developed AKI. The highest median values of biomarker were detected in septic, transplant and patients after hepatic surgery (1.24 vs 0.45 vs 0.47 ng/l²/1000. The area under receiving operating characteristic curve (AUC for the risk of any AKI was 0.85, for early use of RRT 0.83 and for 28-day mortality 0.77. In a multivariable model with established perioperative risk factors, the [TIMP-2]×[IGFBP7] test was the strongest predictor of AKI and significantly improved the risk assessment (p<0.001.Urinary [TIMP-2]×[IGFBP7] test sufficiently detect patients with risk of AKI after major non-cardiac surgery. Due to its rapid responsiveness it extends the time frame for intervention to prevent development of AKI.

  18. [Alzheimer's disease cerebro-spinal fluid biomarkers: A clinical research tool sometimes useful in daily clinical practice of memory clinics for the diagnosis of complex cases].

    Science.gov (United States)

    Magnin, E; Dumurgier, J; Bouaziz-Amar, E; Bombois, S; Wallon, D; Gabelle, A; Lehmann, S; Blanc, F; Bousiges, O; Hannequin, D; Jung, B; Miguet-Alfonsi, C; Quillard, M; Pasquier, F; Peoc'h, K; Laplanche, J-L; Hugon, J; Paquet, C

    2017-04-01

    The role of biomarkers in clinical research was recently highlighted in the new criteria for the diagnosis of Alzheimer's disease. Cerebro-spinal fluid (CSF) biomarkers (total Tau protein, threonine 181 phosphorylated Tau protein and amyloid Aβ1-42 peptide) are associated with cerebral neuropathological lesions observed in Alzheimer's disease (neuronal death, neurofibrillary tangle with abnormal Tau deposits and amyloid plaque). Aβ1-40 amyloid peptide dosage helps to interpret Aβ1-42 results. As suggested in the latest international criteria and the French HAS (Haute Autorité de santé) recommendations, using theses CSF biomarkers should not be systematic but sometimes could be performed to improve confidence about the diagnostic of Alzheimer's disease in young subjects or in complex clinical situations. Future biomarkers actually in development will additionally help in diagnostic process (differential diagnosis) and in prognostic evaluation of neurodegenerative diseases. Copyright © 2016 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

  19. The potential of predictive analytics to provide clinical decision support in depression treatment planning.

    Science.gov (United States)

    Kessler, Ronald C

    2018-01-01

    To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD). Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem. Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

  20. The relevance of gastric cancer biomarkers in prognosis and pre- and post- chemotherapy in clinical practice.

    Science.gov (United States)

    Abbas, Muhammad; Habib, Murad; Naveed, Muhammad; Karthik, Kumaragurubaran; Dhama, Kuldeep; Shi, Meiqi; Dingding, Chen

    2017-11-01

    Gastric cancer (GC) is one among the major cancer types, causing human deaths and present noticeable heterogeneity. The incidences and mortality rates are higher in males in comparison to females with a male to female ratio of 2.3:1. A lot of studies have revealed out the molecular basis, pathogenesis, invasion and metastasis related findings of gastric stomach cancer. Present review encompasses the salient information on various biomarkers for the early diagnosis, treatment and prognosis of gastric cancer elaborate the clinical importance of serum tumor markers in patients with this cancer as well as checking the growths, together with epigenetic changes and genetic polymorphisms. A deep and rigorous search was carried out in Pub Med/MEDLINE using specific key words; "gastric cancer", with "tumor marker". Our search yielded 4947 important reports about related topic from books and articles that were published before the end of August 2017. Conclusively, Scientists are utilizing high time and resource to salvage this nemesis which is of global importance and cause health burden. Classical and novel biomarkers are important for treatment as well as pre- and post- diagnosis of GC. Major causes for GC are cigarette smoking, infection by Helicobacter pylori, atrophic gastritis, sex/gender, and high salt intake. Early diagnoses of GC is important for the management, treatment, pathological diagnoses by stage prognosis and metastatic setting; although the treatment outcome proved to be not much fruitful following chemotherapy, and oral medication with oxaliplatin, capecitabine, cisplatin and 5- fluorouracil (5-FU). More research studies and exploring the practical usage of gastric cancer biomarkers in diagnosis, prognosis and pre- and post- chemotherapy in clinical practice for countering gastric cancers would alleviate to some extent the ill health sufferings of humans being caused by this important and common cancerous condition. Copyright © 2017 Elsevier Masson SAS

  1. Intracellular signaling entropy can be a biomarker for predicting the development of cervical intraepithelial neoplasia.

    Directory of Open Access Journals (Sweden)

    Masakazu Sato

    Full Text Available While the mortality rates for cervical cancer have been drastically reduced after the introduction of the Pap smear test, it still is one of the leading causes of death in women worldwide. Additionally, studies that appropriately evaluate the risk of developing cervical lesions are needed. Therefore, we investigated whether intracellular signaling entropy, which is measured with microarray data, could be useful for predicting the risks of developing cervical lesions. We used three datasets, GSE63514 (histology, GSE27678 (cytology and GSE75132 (cytology, a prospective study. From the data in GSE63514, the entropy rate was significantly increased with disease progression (normal < cervical intraepithelial neoplasia, CIN < cancer (Kruskal-Wallis test, p < 0.0001. From the data in GSE27678, similar results (normal < low-grade squamous intraepithelial lesions, LSILs < high-grade squamous intraepithelial lesions, HSILs ≤ cancer were obtained (Kruskal-Wallis test, p < 0.001. From the data in GSE75132, the entropy rate tended to be higher in the HPV-persistent groups than the HPV-negative group. The group that was destined to progress to CIN 3 or higher had a tendency to have a higher entropy rate than the HPV16-positive without progression group. In conclusion, signaling entropy was suggested to be different for different lesion statuses and could be a useful biomarker for predicting the development of cervical intraepithelial neoplasia.

  2. Quantitative imaging biomarkers: the application of advanced image processing and analysis to clinical and preclinical decision making.

    Science.gov (United States)

    Prescott, Jeffrey William

    2013-02-01

    The importance of medical imaging for clinical decision making has been steadily increasing over the last four decades. Recently, there has also been an emphasis on medical imaging for preclinical decision making, i.e., for use in pharamaceutical and medical device development. There is also a drive towards quantification of imaging findings by using quantitative imaging biomarkers, which can improve sensitivity, specificity, accuracy and reproducibility of imaged characteristics used for diagnostic and therapeutic decisions. An important component of the discovery, characterization, validation and application of quantitative imaging biomarkers is the extraction of information and meaning from images through image processing and subsequent analysis. However, many advanced image processing and analysis methods are not applied directly to questions of clinical interest, i.e., for diagnostic and therapeutic decision making, which is a consideration that should be closely linked to the development of such algorithms. This article is meant to address these concerns. First, quantitative imaging biomarkers are introduced by providing definitions and concepts. Then, potential applications of advanced image processing and analysis to areas of quantitative imaging biomarker research are described; specifically, research into osteoarthritis (OA), Alzheimer's disease (AD) and cancer is presented. Then, challenges in quantitative imaging biomarker research are discussed. Finally, a conceptual framework for integrating clinical and preclinical considerations into the development of quantitative imaging biomarkers and their computer-assisted methods of extraction is presented.

  3. Circulating biomarkers for predicting cardiovascular disease risk : a systematic review and comprehensive overview of meta-analyses

    NARCIS (Netherlands)

    Holten, van T.C.; Waanders, L.F.; Groot, de P.G.; Vissers, J.; Hoefer, I.E.; Pasterkamp, G.; Prins, M.W.J.; Roest, M.

    2013-01-01

    Background : Cardiovascular disease is one of the major causes of death worldwide. Assessing the risk for cardiovascular disease is an important aspect in clinical decision making and setting a therapeutic strategy, and the use of serological biomarkers may improve this. Despite an overwhelming

  4. Prediction of non-recovery from ventilator-demanding acute respiratory failure, ARDS and death using lung damage biomarkers

    DEFF Research Database (Denmark)

    Jensen, Jens Ulrik Stæhr; Itenov, Theis Skovsgaard; Thormar, Katrin M

    2016-01-01

    BACKGROUND: It is unclear whether biomarkers of alveolar damage (surfactant protein D, SPD) or conductive airway damage (club cell secretory protein 16, CC16) measured early after intensive care admittance are associated with one-month clinical respiratory prognosis. If patients who do not recove...

  5. Clinical significance of circulating miR-25-3p as a novel diagnostic and prognostic biomarker in osteosarcoma.

    Science.gov (United States)

    Fujiwara, Tomohiro; Uotani, Koji; Yoshida, Aki; Morita, Takuya; Nezu, Yutaka; Kobayashi, Eisuke; Yoshida, Akihiko; Uehara, Takenori; Omori, Toshinori; Sugiu, Kazuhisa; Komatsubara, Tadashi; Takeda, Ken; Kunisada, Toshiyuki; Kawamura, Machiko; Kawai, Akira; Ochiya, Takahiro; Ozaki, Toshifumi

    2017-05-16

    Emerging evidence has suggested that circulating microRNAs (miRNAs) in body fluids have novel diagnostic and prognostic significance for patients with malignant diseases. The lack of useful biomarkers is a crucial problem of bone and soft tissue sarcomas; therefore, we investigated the circulating miRNA signature and its clinical relevance in osteosarcoma. Global miRNA profiling was performed using patient serum collected from a discovery cohort of osteosarcoma patients and controls and cell culture media. The secretion of the detected miRNAs from osteosarcoma cells and clinical relevance of serum miRNA levels were evaluated using in vitro and in vivo models and a validation patient cohort. Discovery screening identified 236 serum miRNAs that were highly expressed in osteosarcoma patients compared with controls, and eight among these were also identified in the cell culture media. Upregulated expression levels of miR-17-5p and miR-25-3p were identified in osteosarcoma cells, and these were abundantly secreted into the culture media in tumor-derived exosomes. Serum miR-25-3p levels were significantly higher in osteosarcoma patients than in control individuals in the validation cohort, with favorable sensitivity and specificity compared with serum alkaline phosphatase. Furthermore, serum miR-25-3p levels at diagnosis were correlated with patient prognosis and reflected tumor burden in both in vivo models and patients; these associations were more sensitive than those of serum alkaline phosphatase. Serum-based circulating miR-25-3p may serve as a non-invasive blood-based biomarker for tumor monitoring and prognostic prediction in osteosarcoma patients.

  6. Measurement and Clinical Significance of Biomarkers of Oxidative Stress in Humans

    Directory of Open Access Journals (Sweden)

    Ilaria Marrocco

    2017-01-01

    Full Text Available Oxidative stress is the result of the imbalance between reactive oxygen species (ROS formation and enzymatic and nonenzymatic antioxidants. Biomarkers of oxidative stress are relevant in the evaluation of the disease status and of the health-enhancing effects of antioxidants. We aim to discuss the major methodological bias of methods used for the evaluation of oxidative stress in humans. There is a lack of consensus concerning the validation, standardization, and reproducibility of methods for the measurement of the following: (1 ROS in leukocytes and platelets by flow cytometry, (2 markers based on ROS-induced modifications of lipids, DNA, and proteins, (3 enzymatic players of redox status, and (4 total antioxidant capacity of human body fluids. It has been suggested that the bias of each method could be overcome by using indexes of oxidative stress that include more than one marker. However, the choice of the markers considered in the global index should be dictated by the aim of the study and its design, as well as by the clinical relevance in the selected subjects. In conclusion, the clinical significance of biomarkers of oxidative stress in humans must come from a critical analysis of the markers that should give an overall index of redox status in particular conditions.

  7. Biomarkers, lactate, and clinical scores as outcome predictors in systemic poisons exposures.

    Science.gov (United States)

    Lionte, C; Sorodoc, V; Tuchilus, C; Cimpoiesu, D; Jaba, E

    2017-07-01

    Acute exposure to systemic poisons represents an important challenge in clinical toxicology. We aimed to analyze the potential role of cardiac biomarkers, routine laboratory tests, and clinical scores as morbidity and in-hospital mortality predictors in patients intoxicated with various systemic poisons. We conducted a prospective study on adults acutely exposed to systemic poisons. We determined the PSS, Glasgow Coma Scale (GCS), and we performed electrocardiogram, laboratory tests, lactate and cardiac biomarkers (which were reassessed 4 h, respectively 6 h later). Of 120 patients included, 45% developed complications, 19.2% had a poor outcome, and 5% died. Multivariate logistic regression sustained lactate (odds ratio (OR) 1.58; confidence interval (CI) 95%: 0.97-2.59; p 0.066), MB isoenzyme of creatine kinase (6h-CKMB; OR 1.08; CI 95%: 1.02-1.16; p 0.018) as predictors for a poor outcome. A GCS poisons exposure. Receiver operating characteristic analysis showed that brain natriuretic peptide (area under the curve (AUC), 0.96; CI 95%: 0.92-0.99; p poisons exposure.

  8. Role of biomarkers in predicting CVD risk in the setting of HIV infection?

    DEFF Research Database (Denmark)

    Worm, Signe W; Hsue, Priscilla

    2010-01-01

    with risk of CVD. Biomarkers associated with inflammation such as C-reactive protein and interleukin-6 have been suggested to improve risk stratification among intermediate-risk persons; however, their routine use is not recommended in the general population. Both biomarkers have recently been reported......-infected population and will increase as this population continues to age. Identification of intermediate-risk individuals using biomarkers will be an important tool for clinicians in the future to be able to treat HIV-infected individuals aggressively. Future studies of biomarkers among individuals with HIV...

  9. Cardiovascular Disease Biomarkers Predict Susceptibility or Resistance to Lung Injury in World Trade Center Dust Exposed Firefighters

    Science.gov (United States)

    Weiden, Michael D.; Naveed, Bushra; Kwon, Sophia; Cho, Soo Jung; Comfort, Ashley L.; Prezant, David J.; Rom, William N.; Nolan, Anna

    2013-01-01

    Pulmonary vascular loss is an early feature of chronic obstructive pulmonary disease. Biomarkers of inflammation and of metabolic syndrome, predicts loss of lung function in World Trade Center Lung Injury (WTC-LI). We investigated if other cardiovascular disease (CVD) biomarkers also predicted WTC-LI. This nested case-cohort study used 801 never smoker, WTC exposed firefighters with normal pre-9/11 lung function presenting for subspecialty pulmonary evaluation (SPE) before March, 2008. A representative sub-cohort of 124/801 with serum drawn within six months of 9/11 defined CVD biomarker distribution. Post-9/11/01 FEV1 at subspecialty exam defined cases: susceptible WTC-LI cases with FEV1≤77% predicted (66/801) and resistant WTC-LI cases with FEV1≥107% (68/801). All models were adjusted for WTC exposure intensity, BMI at SPE, age at 9/11, and pre-9/11 FEV1. Susceptible WTC-LI cases had higher levels of Apo-AII, CRP, and MIP-4 with significant RRs of 3.85, 3.93, and 0.26 respectively with an area under the curve (AUC) of 0.858. Resistant WTC-LI cases had significantly higher sVCAM and lower MPO with RRs of 2.24, and 2.89 respectively; AUC 0.830. Biomarkers of CVD in serum six-month post-9/11 predicted either susceptibility or resistance to WTC-LI. These biomarkers may define pathways producing or protecting subjects from pulmonary vascular disease and associated loss of lung function after an irritant exposure. PMID:22903969

  10. Tailoring the implementation of new biomarkers based on their added predictive value in subgroups of individuals.

    Directory of Open Access Journals (Sweden)

    A van Giessen

    Full Text Available The value of new biomarkers or imaging tests, when added to a prediction model, is currently evaluated using reclassification measures, such as the net reclassification improvement (NRI. However, these measures only provide an estimate of improved reclassification at population level. We present a straightforward approach to characterize subgroups of reclassified individuals in order to tailor implementation of a new prediction model to individuals expected to benefit from it.In a large Dutch population cohort (n = 21,992 we classified individuals to low (< 5% and high (≥ 5% fatal cardiovascular disease risk by the Framingham risk score (FRS and reclassified them based on the systematic coronary risk evaluation (SCORE. Subsequently, we characterized the reclassified individuals and, in case of heterogeneity, applied cluster analysis to identify and characterize subgroups. These characterizations were used to select individuals expected to benefit from implementation of SCORE.Reclassification after applying SCORE in all individuals resulted in an NRI of 5.00% (95% CI [-0.53%; 11.50%] within the events, 0.06% (95% CI [-0.08%; 0.22%] within the nonevents, and a total NRI of 0.051 (95% CI [-0.004; 0.116]. Among the correctly downward reclassified individuals cluster analysis identified three subgroups. Using the characterizations of the typically correctly reclassified individuals, implementing SCORE only in individuals expected to benefit (n = 2,707,12.3% improved the NRI to 5.32% (95% CI [-0.13%; 12.06%] within the events, 0.24% (95% CI [0.10%; 0.36%] within the nonevents, and a total NRI of 0.055 (95% CI [0.001; 0.123]. Overall, the risk levels for individuals reclassified by tailored implementation of SCORE were more accurate.In our empirical example the presented approach successfully characterized subgroups of reclassified individuals that could be used to improve reclassification and reduce implementation burden. In particular when newly

  11. Biomarkers of the Dementia

    Directory of Open Access Journals (Sweden)

    Mikio Shoji

    2011-01-01

    Full Text Available Recent advances in biomarker studies on dementia are summarized here. CSF Aβ40, Aβ42, total tau, and phosphorylated tau are the most sensitive biomarkers for diagnosis of Alzheimer's disease (AD and prediction of onset of AD from mild cognitive impairment (MCI. Based on this progress, new diagnostic criteria for AD, MCI, and preclinical AD were proposed by National Institute of Aging (NIA and Alzheimer's Association in August 2010. In these new criteria, progress in biomarker identification and amyloid imaging studies in the past 10 years have added critical information. Huge contributions of basic and clinical studies have established clinical evidence supporting these markers. Based on this progress, essential therapy for cure of AD is urgently expected.

  12. Clinical value of renal injury biomarkers in diagnosis of chronic kidney disease

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    Cheng-lu ZHANG

    2011-12-01

    Full Text Available Objective To investigate the levels of renal injury biomarkers in patients with chronic kidney disease(CKD and evaluate their clinical significances in diagnosis of CKD.Methods A total of 66 subjects(37 patients with CKD and 29 healthy individuals were involved in this study.Serum blood urea nitrogen(SBUN was determined by Glutamate dehydrogenase method;serum creatinine(SCr and urinary creatinine(UCr were detected by sarcosine oxidase method;serum uric acid(SUA was measured by uricase colorimetry;serum cystatin C(Cys C and urinary microalbumin(UmAlbwere analyzed by immunological transmission turbidimetry;urinary protein(U-PROwas measured by Coomassies Brilliant Blue(CBB assay.The UmAlb and U-PRO levels were expressed in units of mg/mmolUCr.Results The results of independent samples t test indicated that significant differences were found in SBUN,SCr,SUA,Cys C,UmAlb and U-PRO(P < 0.05 between patient group and healthy control group.The evaluation of diagnostic effects showed that the areas under the curve at ROC plot for SBUN,SCr,SUA,Cys C,UmAlb and U-PRO were 0.907,0.912,0.742,0.982,0.984 and 0.991,respectively.Conclusions U-PRO,UmAlb and Cys C are ideal biomarkers,SCr and SBUN come next,SUA is the weakest when the above biomarkers are applied to evaluate the renal injury and its severity of the patients with CKD.

  13. Differences in abundances of cell-signalling proteins in blood reveal novel biomarkers for early detection of clinical Alzheimer's disease.

    Directory of Open Access Journals (Sweden)

    Mateus Rocha de Paula

    Full Text Available BACKGROUND: In November 2007 a study published in Nature Medicine proposed a simple test based on the abundance of 18 proteins in blood to predict the onset of clinical symptoms of Alzheimer's Disease (AD two to six years before these symptoms manifest. Later, another study, published in PLoS ONE, showed that only five proteins (IL-1, IL-3, EGF, TNF- and G-CSF have overall better prediction accuracy. These classifiers are based on the abundance of 120 proteins. Such values were standardised by a Z-score transformation, which means that their values are relative to the average of all others. METHODOLOGY: The original datasets from the Nature Medicine paper are further studied using methods from combinatorial optimisation and Information Theory. We expand the original dataset by also including all pair-wise differences of z-score values of the original dataset ("metafeatures". Using an exact algorithm to solve the resulting Feature Set problem, used to tackle the feature selection problem, we found signatures that contain either only features, metafeatures or both, and evaluated their predictive performance on the independent test set. CONCLUSIONS: It was possible to show that a specific pattern of cell signalling imbalance in blood plasma has valuable information to distinguish between NDC and AD samples. The obtained signatures were able to predict AD in patients that already had a Mild Cognitive Impairment (MCI with up to 84% of sensitivity, while maintaining also a strong prediction accuracy of 90% on a independent dataset with Non Demented Controls (NDC and AD samples. The novel biomarkers uncovered with this method now confirms ANG-2, IL-11, PDGF-BB, CCL15/MIP-1; and supports the joint measurement of other signalling proteins not previously discussed: GM-CSF, NT-3, IGFBP-2 and VEGF-B.

  14. NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

    Science.gov (United States)

    Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

    2015-10-15

    In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to

  15. An overview of children as a special population-Relevance to predictive biomarkers

    International Nuclear Information System (INIS)

    Kimmel, Gary L.

    2005-01-01

    There has been an increasing focus on children as a special population in the fields of toxicology and epidemiology. At the same time, there has been considerable improvement in the technology for defining normal development and pathways of pathogenesis. Increased support of these areas has culminated in stronger research programs and greater professional involvement in addressing the specific challenges of applying new techniques and data to the improvement of children's health. Part of these challenges relates to the ever changing environment of the child. Not only does a child's anatomy, physiology, and metabolism change with time, but their lifestyle and awareness change as well. All of these can have a significant impact on a child's exposure and the potential of that exposure to have an effect on health and development. This paper will provide a brief overview of the susceptibility of the child relative to sensitive developmental life stages, the changing nature of exposure parameters during development, and how these factors can impact the relevance of predictive biomarkers of chemical toxicity in children

  16. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. The Role of BRCA2 Mutation Status as Diagnostic, Predictive, and Prognosis Biomarker for Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Javier Martinez-Useros

    2016-01-01

    Full Text Available Pancreatic cancer is one of the deadliest cancers worldwide, and life expectancy after diagnosis is often short. Most pancreatic tumours appear sporadically and have been highly related to habits such as cigarette smoking, high alcohol intake, high carbohydrate, and sugar consumption. Other observational studies have suggested the association between pancreatic cancer and exposure to arsenic, lead, or cadmium. Aside from these factors, chronic pancreatitis and diabetes have also come to be considered as risk factors for these kinds of tumours. Studies have found that 10% of pancreatic cancer cases arise from an inherited syndrome related to some genetic alterations. One of these alterations includes mutation in BRCA2 gene. BRCA2 mutations impair DNA damage response and homologous recombination by direct regulation of RAD51. In light of these findings that link genetic factors to tumour development, DNA damage agents have been proposed as target therapies for pancreatic cancer patients carrying BRCA2 mutations. Some of these drugs include platinum-based agents and PARP inhibitors. However, the acquired resistance to PARP inhibitors has created a need for new chemotherapeutic strategies to target BRCA2. The present systematic review collects and analyses the role of BRCA2 alterations to be used in early diagnosis of an inherited syndrome associated with familiar cancer and as a prognostic and predictive biomarker for the management of pancreatic cancer patients.

  18. DNA Methylation Biomarkers: Cancer and Beyond

    Directory of Open Access Journals (Sweden)

    Thomas Mikeska

    2014-09-01

    Full Text Available Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

  19. Innovative methods for the identification of predictive biomarker signatures in oncology: Application to bevacizumab

    Directory of Open Access Journals (Sweden)

    Paul Delmar

    2017-03-01

    Full Text Available Current methods for subgroup analyses of data collected from randomized clinical trials (RCTs may lead to false-positives from multiple testing, lack power to detect moderate but clinically meaningful differences, or be too simplistic in characterizing patients who may benefit from treatment. Herein, we present a general procedure based on a set of newly developed statistical methods for the identification and evaluation of complex multivariate predictors of treatment effect. Furthermore, we implemented this procedure to identify a subgroup of patients who may receive the largest benefit from bevacizumab treatment using a panel of 10 biomarkers measured at baseline in patients enrolled on two RCTs investigating bevacizumab in metastatic breast cancer. Data were collected from patients with human epidermal growth factor receptor 2 (HER2-negative (AVADO and HER2-positive (AVEREL metastatic breast cancer. We first developed a classification rule based on an estimated individual scoring system, using data from the AVADO study only. The classification rule takes into consideration a panel of biomarkers, including vascular endothelial growth factor (VEGF-A. We then classified the patients in the independent AVEREL study into patient groups according to “promising” or “not-promising” treatment benefit based on this rule and conducted a statistical analysis within these subgroups to compute point estimates, confidence intervals, and p-values for treatment effect and its interaction. In the group with promising treatment benefit in the AVEREL study, the estimated hazard ratio of bevacizumab versus placebo for progression-free survival was 0.687 (95% confidence interval [CI]: 0.462–1.024, p = 0.065, while in the not-promising group the hazard ratio (HR was 1.152 (95% CI: 0.526–2.524, p = 0.723. Using the median level of VEGF-A from the AVEREL study to divide the study population, then the HR becomes 0.711 (95% CI: 0.435–1.163, p = 0

  20. PET imaging-based phenotyping as a predictive biomarker of response to tyrosine kinase inhibitor therapy in non-small cell lung cancer: Are we there yet?

    Energy Technology Data Exchange (ETDEWEB)

    Gerbaudo, Victor H.; Kim, Chun K. [Div. of Nuclear Medicine and Molecular Imaging, Dept. of Radiology,Brigham and Women' s Hospital and Harvard Medical School, Boston (United States)

    2017-03-15

    The increased understanding of the molecular pathology of different malignancies, especially lung cancer, has directed investigational efforts to center on the identification of different molecular targets and on the development of targeted therapies against these targets. A good representative is the epidermal growth factor receptor (EGFR); a major driver of non-small cell lung cancer tumorigenesis. Today, tumor growth inhibition is possible after treating lung tumors expressing somatic mutations of the EGFR gene with tyrosine kinase inhibitors (TKI). This opened the doors to biomarker-directed precision or personalized treatments for lung cancer patients. The success of these targeted anticancer therapies depends in part on being able to identify biomarkers and their patho-molecular make-up in order to select patients that could respond to specific therapeutic agents. While the identification of reliable biomarkers is crucial to predict response to treatment before it begins, it is also essential to be able to monitor treatment early during therapy to avoid the toxicity and morbidity of futile treatment in non-responding patients. In this context, we share our perspective on the role of PET imaging-based phenotyping in the personalized care of lung cancer patients to non-invasively direct and monitor the treatment efficacy of TKIs in clinical practice.

  1. Pain in the Blood? Envisioning Mechanism-Based Diagnoses and Biomarkers in Clinical Pain Medicine

    Directory of Open Access Journals (Sweden)

    Emmanuel Bäckryd

    2015-03-01

    Full Text Available Chronic pain is highly prevalent, and pain medicine lacks objective biomarkers to guide diagnosis and choice of treatment. The current U.S. “opioid epidemic” is a reminder of the paucity of effective and safe treatment options. Traditional pain diagnoses according to the International Classification of Diseases are often unspecific, and analgesics are often prescribed on a trial-and-error basis. In contrast to this current state of affairs, the vision of future mechanism-based diagnoses of chronic pain conditions is presented in this non-technical paper, focusing on the need for biomarkers and the theoretical complexity of the task. Pain is and will remain a subjective experience, and as such is not objectively measurable. Therefore, the concept of “noci-marker” is presented as an alternative to “pain biomarker”, the goal being to find objective, measurable correlates of the pathophysiological processes involved in different chronic pain conditions. This vision entails a call for more translational pain research in order to bridge the gap between clinical pain medicine and preclinical science.

  2. Ribosomal proteins as biomarkers for bacterial identification by mass spectrometry in the clinical microbiology laboratory.

    Science.gov (United States)

    Suarez, Stéphanie; Ferroni, Agnès; Lotz, Aurélie; Jolley, Keith A; Guérin, Philippe; Leto, Julie; Dauphin, Brunhilde; Jamet, Anne; Maiden, Martin C J; Nassif, Xavier; Armengaud, Jean

    2013-09-01

    Whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is a rapid method for identification of microorganisms that is increasingly used in microbiology laboratories. This identification is based on the comparison of the tested isolate mass spectrum with reference databases. Using Neisseria meningitidis as a model organism, we showed that in one of the available databases, the Andromas database, 10 of the 13 species-specific biomarkers correspond to ribosomal proteins. Remarkably, one biomarker, ribosomal protein L32, was subject to inter-strain variability. The analysis of the ribosomal protein patterns of 100 isolates for which whole genome sequences were available, confirmed the presence of inter-strain variability in the molecular weight of 29 ribosomal proteins, thus establishing a correlation between the sequence type (ST) and/or clonal complex (CC) of each strain and its ribosomal protein pattern. Since the molecular weight of three of the variable ribosomal proteins (L30, L31 and L32) was included in the spectral window observed by MALDI-TOF MS in clinical microbiology, i.e., 3640-12000 m/z, we were able by analyzing the molecular weight of these three ribosomal proteins to classify each strain in one of six subgroups, each of these subgroups corresponding to specific STs and/or CCs. Their detection by MALDI-TOF allows therefore a quick typing of N. meningitidis isolates. © 2013 Elsevier B.V. All rights reserved.

  3. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    International Nuclear Information System (INIS)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A.; De Amorim Bernstein, Karen; Halpern, Elkan F.

    2016-01-01

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  4. Adipose tissue and muscle attenuation as novel biomarkers predicting mortality in patients with extremity sarcomas

    Energy Technology Data Exchange (ETDEWEB)

    Veld, Joyce; Vossen, Josephina A.; Torriani, Martin; Bredella, Miriam A. [Massachusetts General Hospital and Harvard Medical School, Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Boston, MA (United States); De Amorim Bernstein, Karen [Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Francis H Burr Proton Therapy Center, Boston, MA (United States); Halpern, Elkan F. [Massachusetts General Hospital and Harvard Medical School, Institute of Technology Assessment, Boston, MA (United States)

    2016-12-15

    To assess CT-attenuation of abdominal adipose tissue and psoas muscle as predictors of mortality in patients with sarcomas of the extremities. Our study was IRB approved and HIPAA compliant. The study group comprised 135 patients with history of extremity sarcoma (mean age: 53 ± 17 years) who underwent whole body PET/CT. Abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and psoas muscle attenuation (HU) was assessed on non-contrast, attenuation-correction CT. Clinical information including survival, tumour stage, sarcoma type, therapy and pre-existing comorbidities were recorded. Cox proportional hazard models were used to determine longitudinal associations between adipose tissue and muscle attenuation and mortality. There were 47 deaths over a mean follow-up period of 20 ± 17 months. Higher SAT and lower psoas attenuation were associated with increased mortality (p = 0.03 and p = 0.005, respectively), which remained significant after adjustment for age, BMI, sex, tumor stage, therapy, and comorbidities (p = 0.002 and p = 0.02, respectively). VAT attenuation was not associated with mortality. Attenuation of SAT and psoas muscle, assessed on non-contrast CT, are predictors of mortality in patients with extremity sarcomas, independent of other established prognostic factors, suggesting that adipose tissue and muscle attenuation could serve as novel biomarkers for mortality in patients with sarcomas. (orig.)

  5. Pharmacogenomic Biomarkers

    Directory of Open Access Journals (Sweden)

    Sandra C. Kirkwood

    2002-01-01

    Full Text Available Pharmacogenomic biomarkers hold great promise for the future of medicine and have been touted as a means to personalize prescriptions. Genetic biomarkers for disease susceptibility including both Mendelian and complex disease promise to result in improved understanding of the pathophysiology of disease, identification of new potential therapeutic targets, and improved molecular classification of disease. However essential to fulfilling the promise of individualized therapeutic intervention is the identification of drug activity biomarkers that stratify individuals based on likely response to a particular therapeutic, both positive response, efficacy, and negative response, development of side effect or toxicity. Prior to the widespread clinical application of a genetic biomarker multiple scientific studies must be completed to identify the genetic variants and delineate their functional significance in the pathophysiology of a carefully defined phenotype. The applicability of the genetic biomarker in the human population must then be verified through both retrospective studies utilizing stored or clinical trial samples, and through clinical trials prospectively stratifying patients based on the biomarker. The risk conferred by the polymorphism and the applicability in the general population must be clearly understood. Thus, the development and widespread application of a pharmacogenomic biomarker is an involved process and for most disease states we are just at the beginning of the journey towards individualized therapy and improved clinical outcome.

  6. SNPs in genes implicated in radiation response are associated with radiotoxicity and evoke roles as predictive and prognostic biomarkers

    International Nuclear Information System (INIS)

    Alsbeih, Ghazi; El-Sebaie, Medhat; Al-Harbi, Najla; Al-Hadyan, Khaled; Shoukri, Mohamed; Al-Rajhi, Nasser

    2013-01-01

    Biomarkers are needed to individualize cancer radiation treatment. Therefore, we have investigated the association between various risk factors, including single nucleotide polymorphisms (SNPs) in candidate genes and late complications to radiotherapy in our nasopharyngeal cancer patients. A cohort of 155 patients was included. Normal tissue fibrosis was scored using RTOG/EORTC grading system. A total of 45 SNPs in 11 candidate genes (ATM, XRCC1, XRCC3, XRCC4, XRCC5, PRKDC, LIG4, TP53, HDM2, CDKN1A, TGFB1) were genotyped by direct genomic DNA sequencing. Patients with severe fibrosis (cases, G3-4, n = 48) were compared to controls (G0-2, n = 107). Univariate analysis showed significant association (P < 0.05) with radiation complications for 6 SNPs (ATM G/A rs1801516, HDM2 promoter T/G rs2279744 and T/A rs1196333, XRCC1 G/A rs25487, XRCC5 T/C rs1051677 and TGFB1 C/T rs1800469). In addition, Kaplan-Meier analyses have also highlighted significant association between genotypes and length of patients’ follow-up after radiotherapy. Multivariate logistic regression has further sustained these results suggesting predictive and prognostic roles of SNPs. Univariate and multivariate analysis suggest that radiation toxicity in radiotherapy patients are associated with certain SNPs, in genes including HDM2 promoter studied for the 1st time. These results support the use of SNPs as genetic predictive markers for clinical radiosensitivity and evoke a prognostic role for length of patients’ follow-up after radiotherapy

  7. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort.

    Science.gov (United States)

    Caminiti, Silvia Paola; Ballarini, Tommaso; Sala, Arianna; Cerami, Chiara; Presotto, Luca; Santangelo, Roberto; Fallanca, Federico; Vanoli, Emilia Giovanna; Gianolli, Luigi; Iannaccone, Sandro; Magnani, Giuseppe; Perani, Daniela

    2018-01-01

    In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p CSF biomarkers.

  8. Identification, validation, and clinical implementation of tumor-associated biomarkers to improve therapy concepts, survival, and quality of life of cancer patients: tasks of the Receptor and Biomarker Group of the European Organization for Research and Treatment of Cancer.

    NARCIS (Netherlands)

    Schmitt, M.; Harbeck, N.; Daidone, M.G.; Brynner, N.; Duffy, M.J.; Foekens, J.A.; Sweep, C.G.J.

    2004-01-01

    Guiding principles are provided and discussed on how to inform the physician scientist and cancer researcher about quality control systems to enable a consistent assessment of the clinical value of tumor-associated biomarkers. Next to cancer research itself, the Receptor and Biomarker Group of the

  9. Identification of airway mucosal type 2 inflammation by using clinical biomarkers in asthmatic patients

    DEFF Research Database (Denmark)

    Silkoff, Philip E; Laviolette, Michel; Singh, Dave

    2017-01-01

    BACKGROUND: The Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study profiled patients with mild, moderate, and severe asthma and nonatopic healthy control subjects. OBJECTIVE: We explored this data set to define type 2 inflammation based on airway mucosal IL-13-driven gene...... expression and how this related to clinically accessible biomarkers. METHODS: IL-13-driven gene expression was evaluated in several human cell lines. We then defined type 2 status in 25 healthy subjects, 28 patients with mild asthma, 29 patients with moderate asthma, and 26 patients with severe asthma based...... accurately classified type 2 status based on airway mucosal CCL26, periostin, or IL-13-IVS gene expression. Use of Feno values, bEOS counts, and serum marker levels (eg, CCL26 and CCL17) in combination might allow patient selection for novel type 2 therapeutics....

  10. The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer.

    LENUS (Irish Health Repository)

    Tonry, Claire L

    2016-07-18

    Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and\\/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

  11. A utilitarian comparison of two alcohol use biomarkers with self-reported drinking history collected in antenatal clinics.

    Science.gov (United States)

    May, Philip A; Hasken, Julie M; De Vries, Marlene M; Marais, Anna-Susan; Stegall, Julie M; Marsden, Daniel; Parry, Charles D H; Seedat, Soraya; Tabachnick, Barbara

    2018-04-01

    Alcohol use is reported accurately among pregnant women in some populations. Self-reported alcohol use via the AUDIT and 90-day recall for 193 women from antenatal clinics was compared to biomarker results: phosphatidylethanol (PEth) from bloodspots and ethyl glucuronide (EtG) in fingernails. AUDIT was positive for 67.9% of respondents, and 65.3% directly reported drinking. Individual biomarkers detected less drinking (PEth = 57.0%, EtG = 38.9%) than self-report. But 64.8% had drinking-positive values (>8 ng) on one or both biomarkers, which was not significantly different from self-report. Biomarkers indicated that 3.1% -6.8% of drinkers denied drinking. Combined biomarker sensitivity was 95% -80% and specificity 49% -76% for drinking in the previous 7-90 days. Combined biomarker results have their best yield (89.6%) and accuracy (78.8%) when measuring 90 day drinking. Women reported their alcohol use accurately, and the combined use of PEth and EtG is supported. Copyright © 2018 Elsevier Inc. All rights reserved.

  12. The Role of Proteomics in Biomarker Development for Improved Patient Diagnosis and Clinical Decision Making in Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Claire L. Tonry

    2016-07-01

    Full Text Available Prostate Cancer (PCa is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i might best receive no treatment (active surveillance of the disease; (ii would benefit from existing treatments; or (iii those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making.

  13. Data from a targeted proteomics approach to discover biomarkers in saliva for the clinical diagnosis of periodontitis

    Directory of Open Access Journals (Sweden)

    V. Orti

    2018-06-01

    Full Text Available This study focused on the search for new biomarkers based on liquid chromatography-multiple reaction monitoring (LC-MRM proteomics profiling of whole saliva from patients with periodontitis compared to healthy subjects. The LC-MRM profiling approach is a new and innovative method that has already been validated for the absolute and multiplexed quantification of biomarkers in several diseases. The dataset for this study was produced using LC-MRM to monitor protein levels in a multiplex assay, it provides clinical information on salivary biomarkers of periodontitis. The data presented here is an extension of our recently published research article (Mertens et al., 2017 [1]. Keywords: Clinical chemistry, Mass spectrometry, Proteomics, Saliva biochemistry, Oral disease, Periodontitis

  14. BISAP, RANSON, lactate and others biomarkers in prediction of severe acute pancreatitis in a European cohort.

    Science.gov (United States)

    Valverde-López, Francisco; Matas-Cobos, Ana M; Alegría-Motte, Carlos; Jiménez-Rosales, Rita; Úbeda-Muñoz, Margarita; Redondo-Cerezo, Eduardo

    2017-09-01

    The study aims to assess and compare the predicting ability of some scores and biomarkers in acute pancreatitis. We prospectively collected data from 269 patients diagnosed of acute pancreatitis, admitted to Virgen de las Nieves University Hospital between June 2010 and June 2012. Blood urea nitrogen (BUN), C-reactive protein, and creatinine were measured on admission and after 48 h, lactate and bedside index for severity acute pancreatitis (BISAP) only on admission and RANSON within the first 48 h. Definitions from 2012 Atlanta Classification were used. Area under the curve (AUC) was calculated for each scoring system for predicting severe acute pancreatitis (SAP), mortality, and intensive care unit (ICU) admission, obtaining optimal cut-off values from the receiver operating characteristic curves. Eight (3%) patients died, 17 (6.3%) were classified as SAP, and 10 (3.7%) were admitted in ICU. BISAP was the best predictor on admission for SAP, mortality, and ICU admission with an AUC of 0.9 (95% CI 0.83-0.97); 0.97 (95% CI 0.95-0.99); and 0.89 (95% CI 0.79-0.99), respectively. After 48 h, BUN 48 h was the best predictor of SAP (AUC = 0.96 CI: 0.92-0.99); BUN 48 h and BISAP were the best predictors for mortality (AUC = 0.97 CI: 0.95-0.99) and creatinine 48 h for ICU admission (AUC = 0.96 CI: 0.92-0.99). Lactate showed an AUC of 0.79 (CI: 0.71-0.88), 0.87 (CI: 0.78-0.96), and 0.77 (CI: 0.67-0.87) for SAP, mortality, and ICU admission, respectively. All parameters were predictors for SAP, mortality, and ICU admission, but C-reactive protein on admission was only a significant predictor of SAP. Bedside index for severity acute pancreatitis is a good predictive system for SAP, mortality, and ICU admission, being useful for triaging patients for ICU management. Lactate could be useful for developing new scores. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

  15. Predictive Potential of Twenty-Two Biochemical Biomarkers for Coronary Artery Disease in Type 2 Diabetes Mellitus

    Directory of Open Access Journals (Sweden)

    Edimar Cristiano Pereira

    2015-01-01

    Full Text Available We investigated the potential of a panel of 22 biomarkers to predict the presence of coronary artery disease (CAD in type 2 diabetes mellitus (DM2 patients. The study enrolled 96 DM2 patients with (n = 75 and without (n = 21 evidence of CAD. We assessed a biochemical profile that included 22 biomarkers: total cholesterol, LDL, HDL, LDL/HDL, triglycerides, glucose, glycated hemoglobin, fructosamine, homocysteine, cysteine, methionine, reduced glutathione, oxidized glutathione, reduced glutathione/oxidized glutathione, L-arginine, asymmetric dimethyl-L-arginine, symmetric dimethyl-L-arginine, asymmetric dimethyl-L-arginine/L-arginine, nitrate plus nitrite, S-nitrosothiols, nitrotyrosine, and n-acetyl-β-glucosaminidase. Prediction models were built using logistic regression models. We found that eight biomarkers (methionine, nitratate plus nitrite, n-acetyl-β-glucosaminidase, BMI, LDL, HDL, reduced glutathione, and L-arginine/asymmetric dimethyl-L-arginine along with gender and BMI were significantly associated with the odds of CAD in DM2. These preliminary findings support the notion that emerging biochemical markers might be used for CAD prediction in patients with DM2. Our findings warrant further investigation with large, well-designed studies.

  16. Pretreatment data is highly predictive of liver chemistry signals in clinical trials.

    Science.gov (United States)

    Cai, Zhaohui; Bresell, Anders; Steinberg, Mark H; Silberg, Debra G; Furlong, Stephen T

    2012-01-01

    The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy's law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.

  17. Mass spectrometry in biomarker applications: from untargeted discovery to targeted verification, and implications for platform convergence and clinical application

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Richard D.

    2012-03-01

    It is really only in the last ten years that mass spectrometry (MS) has had a truly significant (but still small) impact on biomedical research. Much of this impact can be attributed to proteomics and its more basic applications. Early biomedical applications have included a number of efforts aimed at developing new biomarkers; however, the success of these endeavors to date have been quite modest - essentially confined to preclinical applications - and have often suffered from combinations of immature technology and hubris. Now that MS-based proteomics is reaching adolescence, it is appropriate to ask if and when biomarker-related applications will extend to the clinical realm, and what developments will be essential for this transition. Biomarker development can be described as a multistage process consisting of discovery, qualification, verification, research assay optimization, validation, and commercialization (1). From a MS perspective, it is possible to 'bin' measurements into 1 of 2 categories - those aimed at discovering potential protein biomarkers and those seeking to verify and validate biomarkers. Approaches in both categories generally involve digesting proteins (e.g., with trypsin) as a first step to yield peptides that can be effectively detected and identified with MS. Discovery-based approaches use broad 'unbiased' or 'undirected' measurements that attempt to cover as many proteins as possible in the hope of revealing promising biomarker candidates. A key challenge with this approach stems from the extremely large dynamic range (i.e., relative stoichiometry) of proteins of potential interest in biofluids such as plasma and the expectation that biomarker proteins of the greatest clinical value for many diseases may very well be present at low relative abundances (2). Protein concentrations in plasma extend from approximately 10{sup 10} pg/mL for albumin to approximately 10 pg/mL and below for interleukins and other

  18. Role of the adverse outcome pathway framework in the validation of predictive biomarkers

    Science.gov (United States)

    Gene expression, enzyme activities, changes in endogenous metabolite or hormone titers, altered histology, etc. are widely used as biomarkers, but rarely, if ever, used for regulatory decision-making or to define management objectives. The disconnect between the measurements comm...

  19. CircRNA-0004904, CircRNA-0001855, and PAPP-A: Potential Novel Biomarkers for the Prediction of Preeclampsia

    Directory of Open Access Journals (Sweden)

    Min Jiang

    2018-05-01

    Full Text Available Background/Aims: Circular RNAs (circRNAs are transcribed prevalently in the genome; however, their potential roles in multiple cardiovascular diseases, particularly preeclampsia (PE, are not yet well understood. This study investigated the expression profiles of circRNAs and explored circRNA-mediated pregnancy-associated plasma protein A (PAPP-A expression as a potential biomarker for PE before 20 weeks of pregnancy. Methods: A nested case-control two-phase screening/validation study was performed in pregnant women before 20 weeks of gestation (before clinical diagnosis at Guangzhou Women and Children’s Medical Center from 2012 to 2015. In the screening phase, circRNA expression profiles of blood cells were assessed using a human circRNA microarray, which was designed to detect simultaneously 5396 circRNAs, in 5 patients with PE and 5 age- and gestational week-matched controls. In the validation phase, 18 circRNAs in blood cells predicted by bioinformatics tools were validated by quantitative reverse transcription PCR in a cohort of 60 patients (PE and age-, gestational week-, and sample storage time-matched controls. Then, we examined the involvement of circRNAs in PE-related pathways via interactions with miRNAs by multiple bioinformatics approaches. Bioinformatics analysis predicted that hsa_circ_0004904 and hsa_circ_0001855 miRNA sponges directly target PAPP-A. PAPP-A was verified in the serum of the same cohort of patients using an enzyme-linked immunosorbent assay. Finally, we combined PAPP-A with circRNAs to create a novel preclinical diagnostic model for PE with logistic regression and evaluated the efficiency of this model with receiver operating curve analysis. Results: Volcano plot analysis using various parameters showed that circRNAs were differentially expressed among both groups (P < 0.01, fold change > 2. In the screening phase, we found that 2178 circRNAs were differentially expressed between the control and PE groups, in

  20. BIOMARKERS S100B AND NSE PREDICT OUTCOME IN HYPOTHERMIA-TREATED ENCEPHALOPATHIC NEWBORNS

    Science.gov (United States)

    Massaro, An N.; Chang, Taeun; Baumgart, Stephen; McCarter, Robert; Nelson, Karin B.; Glass, Penny

    2014-01-01

    Objective To evaluate if serum S100B protein and neuron specific enolase (NSE) measured during therapeutic hypothermia are predictive of neurodevelopmental outcome at 15 months in children with neonatal encephalopathy (NE). Design Prospective longitudinal cohort study Setting A level IV neonatal intensive care unit in a free-standing children’s hospital. Patients Term newborns with moderate to severe NE referred for therapeutic hypothermia during the study period. Interventions Serum NSE and S100B were measured at 0, 12, 24 and 72 hrs of hypothermia. Measurements and Main Reseults Of the 83 infants were enrolled, fifteen (18%) died in the newborn period. Survivors were evaluated by the Bayley Scales of Infant Development (BSID-II) at 15 months of age. Outcomes were assessed in 49/68 (72%) survivors at a mean age of 15.2±2.7 months. Neurodevelopmental outcome was classified by BSID-II Mental (MDI) and Psychomotor (PDI) Developmental Index scores, reflecting cognitive and motor outcomes respectively. Four-level outcome classifications were defined a priori: normal= MDI/PDI within 1SD (>85), mild= MDI/PDI <1SD (70–85), moderate/severe= MDI/PDI <2SD (<70), or died. Elevated serum S100B and NSE levels measured during hypothermia were associated with increasing outcome severity after controlling for baseline and soceioeconomic characteristics in ordinal regression models. Adjusted odds ratios for cognitive outcome were: S100B 2.5 (95% CI 1.3–4.8) and NSE 2.1 (1.2–3.6); for motor outcome: S100B 2.6 (1.2–5.6) and NSE 2.1 (1.2–3.6). Conclusions Serum S100B and NSE levels in babies with NE are associated with neurodevelopmental outcome at 15 months. These putative biomarkers of brain injury may help direct care during therapeutic hypothermia. PMID:24777302

  1. Prognostic stratification of acute pulmonary embolism: Focus on clinical aspects, imaging, and biomarkers

    Directory of Open Access Journals (Sweden)

    Luca Masotti

    2009-07-01

    Full Text Available Luca Masotti1, Marc Righini2, Nicolas Vuilleumier3, Fabio Antonelli4, Giancarlo Landini5, Roberto Cappelli6, Patrick Ray71Internal Medicine, 4Clinical Chemistry, Cecina Hospital, Cecina, Italy; 2Division of Angiology and Haemostasis, Department of Internal Medicine, Geneva University Hospital, Switzerland; 3Division of Laboratory Medicine, Department of Genetics and Laboratory Medicine, Geneva University Hospitals and University of Geneva, Switzerland; 5Internal Medicine, Santa Maria Nuova Hospital, Florence, Italy; 6Thrombosis Center, University of Siena, Siena, Italy; 7Department of Emergency Medicine, Centre Hospitalo-Universitaire Pitié-Salpêtrière, UPMC Paris 6, Paris, FranceAbstract: Pulmonary embolism (PE represents a common disease in emergency medicine and guidelines for diagnosis and treatment have had wide diffusion. However, PE morbidity and mortality remain high, especially when associated to hemodynamic instability or right ventricular dysfunction. Prognostic stratification to identify high risk patients needing to receive more aggressive pharmacological and closer monitoring is of utmost importance. Modern guidelines for management of acute PE are based on risk stratification using either clinical, radiological, or laboratory findings. This article reviews the modern treatment of acute PE, which is customized upon patient prognosis. Accordingly the current risk stratification tools described in the literature such as clinical scores, echocardiography, helical computer tomography, and biomarkers will be reviewed.Keywords: pulmonary embolism, prognosis, troponin, BNP, NT-proBNP, echocardiography, computer tomography

  2. Risk stratification in non-ST elevation acute coronary syndromes: Risk scores, biomarkers and clinical judgment

    Directory of Open Access Journals (Sweden)

    David Corcoran

    2015-09-01

    Clinical guidelines recommend an early invasive strategy in higher risk NSTE-ACS. The Global Registry of Acute Coronary Events (GRACE risk score is a validated risk stratification tool which has incremental prognostic value for risk stratification compared with clinical assessment or troponin testing alone. In emergency medicine, there has been a limited adoption of the GRACE score in some countries (e.g. United Kingdom, in part related to a delay in obtaining timely blood biochemistry results. Age makes an exponential contribution to the GRACE score, and on an individual patient basis, the risk of younger patients with a flow-limiting culprit coronary artery lesion may be underestimated. The future incorporation of novel cardiac biomarkers into this diagnostic pathway may allow for earlier treatment stratification. The cost-effectiveness of the new diagnostic pathways based on high-sensitivity troponin and copeptin must also be established. Finally, diagnostic tests and risk scores may optimize patient care but they cannot replace patient-focused good clinical judgment.

  3. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

    Science.gov (United States)

    Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

    2015-06-25

    Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

  4. Immunohistochemical and molecular imaging biomarker signature for the prediction of failure site after chemoradiation for head and neck squamous cell carcinoma

    DEFF Research Database (Denmark)

    Rasmussen, Gregers Brünnich; Håkansson, Katrin E; Vogelius, Ivan R

    2017-01-01

    .23; p: .025), Bcl-2 (HR: 2.6; p: .08), SUVmax (HR: 3.5; p: .095) and GTV (HR: 1.7; p: .063). CONCLUSIONS: The models successfully distinguished between risk of locoregional failure and risk of distant metastasis, which is important information for clinical decision-making. High p53 expression has......OBJECTIVE: To identify a failure site-specific prognostic model by combining immunohistochemistry (IHC) and molecular imaging information to predict long-term failure type in squamous cell carcinoma of the head and neck. PATIENT AND METHODS: Tissue microarray blocks of 196 head and neck squamous...... cell carcinoma cases were stained for a panel of biomarkers using IHC. Gross tumor volume (GTV) from the PET/CT radiation treatment planning CT scan, maximal Standard Uptake Value (SUVmax) of fludeoxyglucose (FDG) and clinical information were included in the model building using Cox proportional...

  5. Biomarkers of adverse drug reactions.

    Science.gov (United States)

    Carr, Daniel F; Pirmohamed, Munir

    2018-02-01

    Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue

  6. Connecting clinical and actuarial prediction with rule-based methods

    NARCIS (Netherlands)

    Fokkema, M.; Smits, N.; Kelderman, H.; Penninx, B.W.J.H.

    2015-01-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction

  7. Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification

    Directory of Open Access Journals (Sweden)

    Smolich Beverly D

    2003-02-01

    Full Text Available Abstract Background Microarray-based gene expression profiling is a powerful approach for the identification of molecular biomarkers of disease, particularly in human cancers. Utility of this approach to measure responses to therapy is less well established, in part due to challenges in obtaining serial biopsies. Identification of suitable surrogate tissues will help minimize limitations imposed by those challenges. This study describes an approach used to identify gene expression changes that might serve as surrogate biomarkers of drug activity. Methods Expression profiling using microarrays was applied to peripheral blood mononuclear cell (PBMC samples obtained from patients with advanced colorectal cancer participating in a Phase III clinical trial. The PBMC samples were harvested pre-treatment and at the end of the first 6-week cycle from patients receiving standard of care chemotherapy or standard of care plus SU5416, a vascular endothelial growth factor (VEGF receptor tyrosine kinase (RTK inhibitor. Results from matched pairs of PBMC samples from 23 patients were queried for expression changes that consistently correlated with SU5416 administration. Results Thirteen transcripts met this selection criterion; six were further tested by quantitative RT-PCR analysis of 62 additional samples from this trial and a second SU5416 Phase III trial of similar design. This method confirmed four of these transcripts (CD24, lactoferrin, lipocalin 2, and MMP-9 as potential biomarkers of drug treatment. Discriminant analysis showed that expression profiles of these 4 transcripts could be used to classify patients by treatment arm in a predictive fashion. Conclusions These results establish a foundation for the further exploration of peripheral blood cells as a surrogate system for biomarker analyses in clinical oncology studies.

  8. Expression profiling of blood samples from an SU5416 Phase III metastatic colorectal cancer clinical trial: a novel strategy for biomarker identification

    International Nuclear Information System (INIS)

    DePrimo, Samuel E; Wong, Lily M; Khatry, Deepak B; Nicholas, Susan L; Manning, William C; Smolich, Beverly D; O'Farrell, Anne-Marie; Cherrington, Julie M

    2003-01-01

    Microarray-based gene expression profiling is a powerful approach for the identification of molecular biomarkers of disease, particularly in human cancers. Utility of this approach to measure responses to therapy is less well established, in part due to challenges in obtaining serial biopsies. Identification of suitable surrogate tissues will help minimize limitations imposed by those challenges. This study describes an approach used to identify gene expression changes that might serve as surrogate biomarkers of drug activity. Expression profiling using microarrays was applied to peripheral blood mononuclear cell (PBMC) samples obtained from patients with advanced colorectal cancer participating in a Phase III clinical trial. The PBMC samples were harvested pre-treatment and at the end of the first 6-week cycle from patients receiving standard of care chemotherapy or standard of care plus SU5416, a vascular endothelial growth factor (VEGF) receptor tyrosine kinase (RTK) inhibitor. Results from matched pairs of PBMC samples from 23 patients were queried for expression changes that consistently correlated with SU5416 administration. Thirteen transcripts met this selection criterion; six were further tested by quantitative RT-PCR analysis of 62 additional samples from this trial and a second SU5416 Phase III trial of similar design. This method confirmed four of these transcripts (CD24, lactoferrin, lipocalin 2, and MMP-9) as potential biomarkers of drug treatment. Discriminant analysis showed that expression profiles of these 4 transcripts could be used to classify patients by treatment arm in a predictive fashion. These results establish a foundation for the further exploration of peripheral blood cells as a surrogate system for biomarker analyses in clinical oncology studies

  9. Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

    Directory of Open Access Journals (Sweden)

    Gregory A Light

    Full Text Available Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1 associated with schizophrenia, 2 stable over time, independent of state-related changes, and 3 free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ and nonpsychiatric comparison subjects (NCS. Stability of clinical and functional measures was also assessed.Participants (SZ n = 341; NCS n = 205 completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade, neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II. In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF. 223 subjects (SZ n = 163; NCS n = 58 returned for retesting after 1 year.Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria.The majority of neurophysiological and neurocognitive measures exhibited deficits in

  10. Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

    Science.gov (United States)

    Light, Gregory A; Swerdlow, Neal R; Rissling, Anthony J; Radant, Allen; Sugar, Catherine A; Sprock, Joyce; Pela, Marlena; Geyer, Mark A; Braff, David L

    2012-01-01

    Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1) associated with schizophrenia, 2) stable over time, independent of state-related changes, and 3) free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ) and nonpsychiatric comparison subjects (NCS). Stability of clinical and functional measures was also assessed. Participants (SZ n = 341; NCS n = 205) completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade), neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II). In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF). 223 subjects (SZ n = 163; NCS n = 58) returned for retesting after 1 year. Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS) was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria. The majority of neurophysiological and neurocognitive measures exhibited deficits in patients

  11. Relevance of Follow-Up in Patients with Core Clinical Criteria for Alzheimer Disease and Normal CSF biomarkers.

    Science.gov (United States)

    Vercruysse, Olivier; Paquet, Claire; Gabelle, Audrey; Delbeuck, Xavier; Blanc, Frederic; Wallon, David; Dumurgier, Julien; Magnin, Eloi; Martinaud, Olivier; Jung, Barbara; Bousiges, Olivier; Lehmann, Sylvain; Delaby, Constance; Quillard-Murain, Muriel; Peoc'h, Katell; Laplanche, Jean-Louis; Bouaziz-Amar, Elodie; Hannequin, Didier; Sablonniere, Bernard; Buee, Luc; Hugon, Jacques; Schraen, Susanna; Pasquier, Florence; Bombois, Stephanie

    2018-01-09

    Few patients with a normal cerebrospinal fluid (CSF) biomarker profile fulfill the clinical criteria for Alzheimer disease (AD). The aim of this study was to test the hypothesis of misdiagnoses for these patients. Patients from the e-PLM centers fulfilling the core clinical criteria for probable AD dementia or mild cognitive impairment due to AD (AD-MCI), with normal CSF A1-42, T-tau and P-tau biomarkers and clinical follow-up, were included. Clinical and imaging data were reviewed by an independent board, from baseline (visit with clinical evaluation and CSF analysis) to the end of the follow-up, for a final diagnosis. In the e-PLM cohort of 1098 AD patients with CSF analysis, 37 (3.3%) patients (20 with AD dementia core clinical criteria and 17 with AD-MCI core clinical criteria) had normal CSF biomarker profile and a clinical follow-up. All patients presented with episodic memory impairment and 27 (73%) had medial temporal lobe atrophy on MRI-scan. After a median follow-up of 36 months (range 7-74), the final diagnosis was AD MCI or dementia for 9 (24%) patients, and unlikely due to AD for 28 (76%) patients. A misdiagnosis was corrected in 18 (49%) patients (mood disorders, non-AD degenerative dementia, vascular cognitive impairment, alcohol cognitive disorders, temporal epilepsy and hippocampal sclerosis), and 10 (27%) patients had cognitive disorders of undetermined etiology. AD diagnosis (MCI or dementia) with normal CSF biomarkers is a rare condition. A clinical follow-up is particularly recommended to consider an alternative diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Biomarkers of systemic inflammation and depression and fatigue in moderate clinically stable COPD

    Directory of Open Access Journals (Sweden)

    Singh Dave

    2011-01-01

    Full Text Available Abstract Introduction COPD is an inflammatory disease with major co-morbidities. It has recently been suggested that depression may be the result of systemic inflammation. We aimed to explore the association between systemic inflammation and symptoms of depression and fatigue in patients with mainly moderate and clinically stable COPD using a range of inflammatory biomarkers, 2 depression and 2 fatigue scales. Method We assessed 120 patients with moderate COPD (FEV1% 52, men 62%, age 66. Depression was assessed using the BASDEC and CES-D scales. Fatigue was assessed using the Manchester COPD-fatigue scale (MCFS and the Borg scale before and after 6MWT. We measured systemic TNF-α, CRP, TNF-α-R1, TNF-α-R2 and IL-6. Results A multivariate linear model of all biomarkers showed that TNF-α only had a positive correlation with BASDEC depression score (p = 0.007. TNF-α remained positively correlated with depression (p = 0.024 after further adjusting for TNF-α-R1, TNF-α-R2, 6MWD, FEV1%, and pack-years. Even after adding the MCFS score, body mass and body composition to the model TNF-α was still associated with the BASDEC score (p = 0.044. Furthermore, patients with higher TNF-α level (> 3 pg/ml, n = 7 had higher mean CES-D depression score than the rest of the sample (p = 0.03. Borg fatigue score at baseline were weakly correlated with TNF-α and CRP, and with TNF-α only after 6MWT. Patients with higher TNF-α had more fatigue after 6MWD (p = 0.054. Conclusion This study indicates a possible association between TNF-α and two frequent and major co-morbidities in COPD; i.e., depression and fatigue.

  13. ULK1: a promising biomarker in predicting poor prognosis and therapeutic response in human nasopharygeal carcinoma.

    Directory of Open Access Journals (Sweden)

    Miao Yun

    Full Text Available Plenty of studies have established that dysregulation of autophagy plays an essential role in cancer progression. The autophagy-related proteins have been reported to be closely associated with human cancer patients' prognosis. We explored the expression dynamics and prognostic value of autophagy-related protein ULK1 by immunochemistry (IHC method in two independent cohorts of nasopharygeal carcinoma (NPC cases. The X-tile program was applied to determine the optimal cut-off value in the training cohort. This derived cutoff value was then subjected to analysis the association of ULK1 expression with patients' clinical characteristics and survival outcome in the validation cohort and overall cases. High ULK1 expression was closely associated with aggressive clinical feature of NPC patients. Furthermore, high expression of ULK1 was observed more frequently in therapeutic resistant group than that in therapeutic effective group. Our univariate and multivariate analysis also showed that higher ULK1 expression predicted inferior disease-specific survival (DSS (P<0.05. Consequently, a new clinicopathologic prognostic model with 3 poor prognostic factors (ie, ULK1 expression, overall clinical stage and therapeutic response could significantly stratify risk (low, intermediate and high for DSS in NPC patients (P<0.001. These findings provide evidence that, the examination of ULK1 expression by IHC method, could serve as an effective additional tool for predicting therapeutic response and patients' survival outcome in NPC patients.

  14. Imaging biomarkers to predict response to anti-HER2 (ErbB2) therapy in preclinical models of breast cancer

    Science.gov (United States)

    Shah, Chirayu; Miller, Todd W.; Wyatt, Shelby K.; McKinley, Eliot T.; Olivares, Maria Graciela; Sanchez, Violeta; Nolting, Donald D.; Buck, Jason R.; Zhao, Ping; Ansari, M. Sib; Baldwin, Ronald M.; Gore, John C.; Schiff, Rachel; Arteaga, Carlos L.; Manning, H. Charles

    2010-01-01

    Purpose To evaluate non-invasive imaging methods as predictive biomarkers of response to trastuzumab in mouse models of HER2-overexpressing breast cancer. The correlation between tumor regression and molecular imaging of apoptosis, glucose metabolism, and cellular proliferation was evaluated longitudinally in responding and non-responding tumor-bearing cohorts. Experimental Design Mammary tumors from MMTV/HER2 transgenic female mice were transplanted into syngeneic female mice. BT474 human breast carcinoma cell line xenografts were grown in athymic nude mice. Tumor cell apoptosis (NIR700-Annexin-V accumulation), glucose metabolism ([18F]FDG-PET), and proliferation ([18F]FLT-PET) were evaluated throughout a bi-weekly trastuzumab regimen. Imaging metrics were validated by direct measurement of tumor size and immunohistochemical (IHC) analysis of cleaved caspase-3, phosphorylated AKT (p-AKT) and Ki67. Results NIR700-Annexin-V accumulated significantly in trastuzumab-treated MMTV/HER2 and BT474 tumors that ultimately regressed, but not in non-responding or vehicle-treated tumors. Uptake of [18F]FDG was not affected by trastuzumab treatment in MMTV/HER2 or BT474 tumors. [18F]FLT PET imaging predicted trastuzumab response in BT474 tumors but not in MMTV/HER2 tumors, which exhibited modest uptake of [18F]FLT. Close agreement was observed between imaging metrics and IHC analysis. Conclusions Molecular imaging of apoptosis accurately predicts trastuzumab-induced regression of HER2(+) tumors and may warrant clinical exploration to predict early response to neoadjuvant trastuzumab. Trastuzumab does not appear to alter glucose metabolism substantially enough to afford [18F]FDG-PET significant predictive value in this setting. Although promising in one preclinical model, further studies are required to determine the overall value of [18F]FLT-PET as a biomarker of response to trastuzumab in HER2+ breast cancer. PMID:19584166

  15. HumanMethylation450K Array–Identified Biomarkers Predict Tumour Recurrence/Progression at Initial Diagnosis of High-risk Non-muscle Invasive Bladder Cancer

    Directory of Open Access Journals (Sweden)

    Mark O Kitchen

    2018-01-01

    Full Text Available Background: High-risk non-muscle invasive bladder cancer (HR-NMIBC is a clinically unpredictable disease. Despite clinical risk estimation tools, many patients are undertreated with intra-vesical therapies alone, whereas others may be over-treated with early radical surgery. Molecular biomarkers, particularly DNA methylation, have been reported as predictive of tumour/patient outcomes in numerous solid organ and haematologic malignancies; however, there are few reports in HR-NMIBC and none using genome-wide array assessment. We therefore sought to identify novel DNA methylation markers of HR-NMIBC clinical outcomes that might predict tumour behaviour at initial diagnosis and help guide patient management. Patients and methods: A total of 21 primary initial diagnosis HR-NMIBC tumours were analysed by Illumina HumanMethylation450 BeadChip arrays and subsequently bisulphite Pyrosequencing. In all, 7 had not recurred at 1 year after resection and 14 had recurred and/or progressed despite intra-vesical BCG. A further independent cohort of 32 HR-NMIBC tumours (17 no recurrence and 15 recurrence and/or progression despite BCG were also assessed by bisulphite Pyrosequencing. Results: Array analyses identified 206 CpG loci that segregated non-recurrent HR-NMIBC tumours from clinically more aggressive recurrence/progression tumours. Hypermethylation of CpG cg11850659 and hypomethylation of CpG cg01149192 in combination predicted HR-NMIBC recurrence and/or progression within 1 year of diagnosis with 83% sensitivity, 79% specificity, and 83% positive and 79% negative predictive values. Conclusions: This is the first genome-wide DNA methylation analysis of a unique HR-NMIBC tumour cohort encompassing known 1-year clinical outcomes. Our analyses identified potential novel epigenetic markers that could help guide individual patient management in this clinically unpredictable disease.

  16. A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

    Science.gov (United States)

    Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

    2017-07-01

    Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

  17. Transthyretin levels: Potential biomarker for monitoring nutritional support efficacy and clinical complications risk in patients receiving parenteral nutrition.

    Science.gov (United States)

    Borges de Oliveira Nascimento Freitas, Renata Germano; Hessel, Gabriel; Junqueira Vasques, Ana Carolina; Negrão Nogueira, Roberto José

    2018-04-01

    Nutritional support is an effective strategy to restore or maintain nutritional status, to reduce clinical complications, hospitalization period and the morbidity/mortality risk of hospitalized patients. So, a good marker is important to evaluate the nutritional support. This study aims to evaluate the evolution of transthyretin levels in patients receiving parenteral nutrition (PN) during 14 days. Longitudinal study of 88 hospitalized patients. The assessments and samples were taken during the first 72 h (T0), on the 7th day (T7) and 14th day (T14) of PN. This study was approved by the Ethics Committee of the School of Medical Sciences at UNICAMP (No 538/2011). The C-reactive protein (CRP) levels were high and albumin and transthyretin levels were low at baseline. From T0 to T14, only transthyretin increased (p = 0.03). According to the receiver operation characteristic (ROC) curve, we found that the transthyretin had some improvement when the CRP levels were less than 10.4 mg/dl (T7). According to the CRP/albumin ratio, all patients classified as without risk for complications were discharged from the hospital. In addition, we observed that patients with transthyretin reduction had a concomitant higher risk for complications according to their ratio CRP/albumin (p = 0.03). CRP/albumin ratio was associated with the evolution of transthyretin levels. Transthyretin values showed significant improvement in the 14 days of PN. Especially, less inflamed patients (ie CRP less than 10.4 mg/dl) improved their transthyretin levels. So, CRP value at day 7 that predicts the transthyretin and transthyretin is a good biomarker for classification of nutritional support and clinical complications risk in patients receiving PN. Copyright © 2017 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.

  18. Decorin in human oral cancer: A promising predictive biomarker of S-1 neoadjuvant chemosensitivity

    International Nuclear Information System (INIS)

    Kasamatsu, Atsushi; Uzawa, Katsuhiro; Minakawa, Yasuyuki; Ishige, Shunsaku; Kasama, Hiroki; Endo-Sakamoto, Yosuke; Ogawara, Katsunori; Shiiba, Masashi; Takiguchi, Yuichi; Tanzawa, Hideki

    2015-01-01

    Highlights: • DCN is significantly up-regulated in chemoresistant cancer cell lines. • DCN is a key regulator for chemoresistant mechanisms in vitro and in vivo. • DCN predicts the clinical responses to S-1 NAC for patients with oral cancer. - Abstract: We reported previously that decorin (DCN) is significantly up-regulated in chemoresistant cancer cell lines. DCN is a small leucine-rich proteoglycan that exists and functions in stromal and epithelial cells. Accumulating evidence suggests that DCN affects the biology of several types of cancer by directly/indirectly targeting the signaling molecules involved in cell growth, survival, metastasis, and angiogenesis, however, the molecular mechanisms of DCN in chemoresistance and its clinical relevance are still unknown. Here we assumed that DCN silencing cells increase chemosusceptibility to S-1, consisted of tegafur, prodrug of 5-fluorouracil. We first established DCN knockdown transfectants derived from oral cancer cells for following experiments including chemosusceptibility assay to S-1. In addition to the in vitro data, DCN knockdown zenografting tumors in nude mice demonstrate decreasing cell proliferation and increasing apoptosis with dephosphorylation of AKT after S-1 chemotherapy. We also investigated whether DCN expression predicts the clinical responses of neoadjuvant chemotherapy (NAC) using S-1 (S-1 NAC) for oral cancer patients. Immunohistochemistry data in the preoperative biopsy samples was analyzed to determine the cut-off point for status of DCN expression by receiver operating curve analysis. Interestingly, low DCN expression was observed in five (83%) of six cases with complete responses to S-1 NAC, and in one (10%) case of 10 cases with stable/progressive disease, indicating that S-1 chemosensitivity is dramatically effective in oral cancer patients with low DCN expression compared with high DCN expression. Our findings suggest that DCN is a key regulator for chemoresistant mechanisms, and

  19. Decorin in human oral cancer: A promising predictive biomarker of S-1 neoadjuvant chemosensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Kasamatsu, Atsushi, E-mail: kasamatsua@faculty.chiba-u.jp [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Uzawa, Katsuhiro, E-mail: uzawak@faculty.chiba-u.jp [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Minakawa, Yasuyuki; Ishige, Shunsaku; Kasama, Hiroki [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Endo-Sakamoto, Yosuke; Ogawara, Katsunori [Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan); Shiiba, Masashi; Takiguchi, Yuichi [Medical Oncology, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Tanzawa, Hideki [Department of Oral Science, Graduate School of Medicine, Chiba University, Chiba 260-8670 (Japan); Department of Dentistry and Oral–Maxillofacial Surgery, Chiba University Hospital, Chiba 260-8670 (Japan)

    2015-01-30

    Highlights: • DCN is significantly up-regulated in chemoresistant cancer cell lines. • DCN is a key regulator for chemoresistant mechanisms in vitro and in vivo. • DCN predicts the clinical responses to S-1 NAC for patients with oral cancer. - Abstract: We reported previously that decorin (DCN) is significantly up-regulated in chemoresistant cancer cell lines. DCN is a small leucine-rich proteoglycan that exists and functions in stromal and epithelial cells. Accumulating evidence suggests that DCN affects the biology of several types of cancer by directly/indirectly targeting the signaling molecules involved in cell growth, survival, metastasis, and angiogenesis, however, the molecular mechanisms of DCN in chemoresistance and its clinical relevance are still unknown. Here we assumed that DCN silencing cells increase chemosusceptibility to S-1, consisted of tegafur, prodrug of 5-fluorouracil. We first established DCN knockdown transfectants derived from oral cancer cells for following experiments including chemosusceptibility assay to S-1. In addition to the in vitro data, DCN knockdown zenografting tumors in nude mice demonstrate decreasing cell proliferation and increasing apoptosis with dephosphorylation of AKT after S-1 chemotherapy. We also investigated whether DCN expression predicts the clinical responses of neoadjuvant chemotherapy (NAC) using S-1 (S-1 NAC) for oral cancer patients. Immunohistochemistry data in the preoperative biopsy samples was analyzed to determine the cut-off point for status of DCN expression by receiver operating curve analysis. Interestingly, low DCN expression was observed in five (83%) of six cases with complete responses to S-1 NAC, and in one (10%) case of 10 cases with stable/progressive disease, indicating that S-1 chemosensitivity is dramatically effective in oral cancer patients with low DCN expression compared with high DCN expression. Our findings suggest that DCN is a key regulator for chemoresistant mechanisms, and

  20. Evolution of Neurodegeneration Imaging Biomarkers from Clinically Normal to Dementia in the Alzheimer Disease Spectrum

    Science.gov (United States)

    Knopman, David S.; Jack, Clifford R.; Lundt, Emily S.; Weigand, Stephen D.; Vemuri, Prashanthi; Lowe, Val J.; Kantarci, Kejal; Gunter, Jeffrey L.; Senjem, Matthew L.; Mielke, Michelle M.; Machulda, Mary M.; Roberts, Rosebud O.; Boeve, Bradley F.; Jones, David T.; Petersen, Ronald C.

    2016-01-01

    The availability of antemortem biomarkers for Alzheimer’s Disease (AD) enables monitoring the evolution of neurodegenerative processes in real time. Pittsburgh compound B (PIB) positron emission tomography (PET) was used to select participants in the Mayo Clinic Study of Aging and the Mayo Alzheimer’s Disease Research Center with elevated β-amyloid, designated as “A+,” and hippocampal volume and 18fluorodeoxyglucose (FDG) positron emission tomography were used to characterize participants as having evidence of neurodegeneration (“N+”) at the baseline evaluation. There were 145 clinically normal (CN) A+ individuals, 62 persons with mild cognitive impairment (MCI) who were A+ and 20 with A+ AD dementia. Over a period of 1–6 years, MCI A+N+ individuals showed declines in medial temporal, lateral temporal, lateral parietal, and to a lesser extent, medial parietal regions for both FDG standardized uptake value ratio (SUVR) and grey matter (GM) volume that exceeded declines seen in the CN A+N+ group. The AD dementia group showed declines in the same regions on FDG SUVR and GM volume with rates that exceeded that in MCI A+N+. Expansion of regional involvement and faster rate of neurodegeneration characterizes progression in the AD pathway. PMID:27460147

  1. Evolution of neurodegeneration-imaging biomarkers from clinically normal to dementia in the Alzheimer disease spectrum.

    Science.gov (United States)

    Knopman, David S; Jack, Clifford R; Lundt, Emily S; Weigand, Stephen D; Vemuri, Prashanthi; Lowe, Val J; Kantarci, Kejal; Gunter, Jeffrey L; Senjem, Matthew L; Mielke, Michelle M; Machulda, Mary M; Roberts, Rosebud O; Boeve, Bradley F; Jones, David T; Petersen, Ronald C

    2016-10-01

    The availability of antemortem biomarkers for Alzheimer's disease (AD) enables monitoring the evolution of neurodegenerative processes in real time. Pittsburgh compound B (PIB) positron emission tomography (PET) was used to select participants in the Mayo Clinic Study of Aging and the Mayo Alzheimer's Disease Research Center with elevated β-amyloid, designated as "A+," and hippocampal volume and (18)fluorodeoxyglucose (FDG) positron emission tomography were used to characterize participants as having evidence of neurodegeneration ("N+") at the baseline evaluation. There were 145 clinically normal (CN) A+ individuals, 62 persons with mild cognitive impairment (MCI) who were A+ and 20 with A+ AD dementia. Over a period of 1-6 years, MCI A+N+ individuals showed declines in medial temporal, lateral temporal, lateral parietal, and to a lesser extent, medial parietal regions for both FDG standardized uptake value ratio and gray matter volume that exceeded declines seen in the CN A+N+ group. The AD dementia group showed declines in the same regions on FDG standardized uptake value ratio and gray matter volume with rates that exceeded that in MCI A+N+. Expansion of regional involvement and faster rate of neurodegeneration characterizes progression in the AD pathway. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Relationships between Rapid Eye Movement Sleep Behavior Disorder and Neurodegenerative Diseases: Clinical Assessments, Biomarkers, and Treatment

    Science.gov (United States)

    Li, Min; Wang, Li; Liu, Jiang-Hong; Zhan, Shu-Qin

    2018-01-01

    Objective: Rapid eye movement sleep behavior disorder (RBD) is characterized by dream enactment and loss of muscle atonia during rapid eye movement sleep. RBD is closely related to α-synucleinopathies including Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Many studies have investigated the markers of imaging and neurophysiological, genetic, cognitive, autonomic function of RBD and their predictive value for neurodegenerative diseases. This report reviewed the progress of these studies and discussed their limitations and future research directions. Data Sources: Using the combined keywords: “RBD”, “neurodegenerative disease”, “Parkinson disease”, and “magnetic resonance imaging”, the PubMed/MEDLINE literature search was conducted up to January 1, 2018. Study Selection: A total of 150 published articles were initially identified citations. Of the 150 articles, 92 articles were selected after further detailed review. This study referred to all the important English literature in full. Results: Single-nucleotide polymorphisms in SCARB2 (rs6812193) and MAPT (rs12185268) were significantly associated with RBD. The olfactory loss, autonomic dysfunction, marked electroencephalogram slowing during both wakefulness and rapid eye movement sleep, and cognitive impairments were potential predictive markers for RBD conversion to neurodegenerative diseases. Traditional structural imaging studies reported relatively inconsistent results, whereas reduced functional connectivity between the left putamen and substantia nigra and dopamine transporter uptake demonstrated by functional imaging techniques were relatively consistent findings. Conclusions: More longitudinal studies should be conducted to evaluate the predictive value of biomarkers of RBD. Moreover, because the glucose and dopamine metabolisms are not specific for assessing cognitive cognition, the molecular metabolism directly related to cognition should be investigated

  3. Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clustering

    Directory of Open Access Journals (Sweden)

    Sharma Animesh

    2007-01-01

    Full Text Available Abstract Background The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell tumor (SRBCT and thus often leads to misdiagnosis. Identification of biomarkers for distinguishing these cancers is a well studied problem. Existing methods typically evaluate each gene separately and do not take into account the nonlinear interaction between genes and the tools that are used to design the diagnostic prediction system. Consequently, more genes are usually identified as necessary for prediction. We propose a general scheme for finding a small set of biomarkers to design a diagnostic system for accurate classification of the cancer subgroups. We use multilayer networks with online gene selection ability and relational fuzzy clustering to identify a small set of biomarkers for accurate classification of the training and blind test cases of a well studied data set. Results Our method discerned just seven biomarkers that precisely categorized the four subgroups of cancer both in training and blind samples. For the same problem, others suggested 19–94 genes. These seven biomarkers include three novel genes (NAB2, LSP1 and EHD1 – not identified by others with distinct class-specific signatures and important role in cancer biology, including cellular proliferation, transendothelial migration and trafficking of MHC class antigens. Interestingly, NAB2 is downregulated in other tumors including Non-Hodgkin lymphoma and Neuroblastoma but we observed moderate to high upregulation in a few cases of Ewing sarcoma and Rabhdomyosarcoma, suggesting that NAB2 might be mutated in these tumors. These genes can discover the subgroups correctly with unsupervised learning, can differentiate non-SRBCT samples and they perform equally well with other machine learning tools including support vector machines. These biomarkers lead to four simple human interpretable

  4. Inflammation-regulating factors in ascites as predictive biomarkers of drug resistance and progression-free survival in serous epithelial ovarian cancers

    International Nuclear Information System (INIS)

    Lane, Denis; Matte, Isabelle; Garde-Granger, Perrine; Laplante, Claude; Carignan, Alex; Rancourt, Claudine; Piché, Alain

    2015-01-01

    Platinum-based combination therapy is the standard first-line treatment for women with advanced serous epithelial ovarian carcinoma (EOC). However, about 20 % will not respond and are considered clinically resistant. The availability of biomarkers to predict responses to the initial therapy would provide a practical approach to identify women who would benefit from a more appropriate first-line treatment. Ascites is an attractive inflammatory fluid for biomarker discovery as it is easy and minimally invasive to obtain. The aim of this study was to evaluate whether six selected inflammation-regulating factors in ascites could serve as diagnostic or drug resistance biomarkers in patients with advanced serous EOC. A total of 53 women with stage III/IV serous EOC and 10 women with benign conditions were enrolled in this study. Eleven of the 53 women with serous EOC were considered clinically resistant to treatment with progression-free survival < 6 months. Ascites were collected at the time of the debulking surgery and the levels of cytokines were measured by ELISA. The six selected cytokines were evaluated for their ability to discriminate serous EOC from benign controls, and to discriminate platinum resistant from platinum sensitive patients. Median ascites levels of IL-6, IL-10 and osteoprotegerin (OPG) were significantly higher in women with advanced serous EOC than in controls (P ≤ 0.012). There were no significant difference in the median ascites levels of leptin, soluble urokinase plasminogen activator receptor (suPAR) and CCL18 among serous EOC women and controls. In Receiver Operator curve (ROC) analysis, IL-6, IL-10 and OPG had a high area under the curve value of 0.905, 0.832 and 0.825 respectively for distinguishing EOC from benign controls. ROC analysis of individual cytokines revealed low discriminating potential to stratify patients according to their sensitivity to first-line treatment. The combination of biomarkers with the highest discriminating

  5. Emerging biomarkers in anaplastic oligodendroglioma: implications for clinical investigation and patient management.

    Science.gov (United States)

    Sahebjam, Solmaz; McNamara, Mairéad G; Mason, Warren P

    2013-07-01

    Oligodendrogliomas are heterogeneous tumors with a variable response to treatment. This clinical variability underlines the urgent need for markers that can reliably aid diagnosis and guide clinical decision-making. Long-term follow-up data from the EORTC 26951 and RTOG 9402 clinical trials in newly diagnosed anaplastic oligodendroglioma have established chromosome 1p19q codeletion as a predictive marker of response to procarbazine, lomustine and vincristine chemotherapy in anaplastic oligodendrogliomas. In addition, MGMT promoter hypermethylation has been strongly associated with glioma CpG island hypermethylation phenotype (G-CIMP+) status, this has been suggested as an epiphenomenon of genome-wide methylation, conferring a more favorable prognosis. Molecular profiling of these tumors has identified several other markers with potential clinical significance: mutations of IDH, CIC, FUBP1 and CDKN2A require further validation before they can be implemented as clinical decision-making tools. Additionally, recent data on the clinical significance of intrinsic glioma subtyping appears promising. Indeed, existing evidence suggests that comprehensive analyses such as intrinsic glioma subtyping or G-CIMP status are superior to single molecular markers. Clearly, with evolving treatment strategies and in the era of individualized therapy, broader omics-based molecular evaluations are required to improve outcome prediction and to identify patients who will benefit from specific treatment strategies.

  6. Degradation Rate of 5-Fluorouracil in Metastatic Colorectal Cancer: A New Predictive Outcome Biomarker?

    Directory of Open Access Journals (Sweden)

    Andrea Botticelli

    Full Text Available 5-FU based chemotherapy is the most common first line regimen used for metastatic colorectal cancer (mCRC. Identification of predictive markers of response to chemotherapy is a challenging approach for drug selection. The present study analyzes the predictive role of 5-FU degradation rate (5-FUDR and genetic polymorphisms (MTHFR, TSER, DPYD on survival.Genetic polymorphisms of MTHFR, TSER and DPYD, and the 5-FUDR of homogenous patients with mCRC were retrospectively studied. Genetic markers and the 5-FUDR were correlated with clinical outcome.133 patients affected by mCRC, treated with fluoropyrimidine-based chemotherapy from 2009 to 2014, were evaluated. Patients were classified into three metabolic classes, according to normal distribution of 5-FUDR in more than 1000 patients, as previously published: poor-metabolizer (PM with 5-FU-DR ≤ 0,85 ng/ml/106 cells/min (8 pts; normal metabolizer with 0,85 < 5-FU-DR < 2,2 ng/ml/106 cells/min (119 pts; ultra-rapid metabolizer (UM with 5-FU-DR ≥ 2,2 ng/ml/106 cells/min (6 pts. PM and UM groups showed a longer PFS respect to normal metabolizer group (14.5 and 11 months respectively vs 8 months; p = 0.029. A higher G3-4 toxicity rate was observed in PM and UM, respect to normal metabolizer (50% in both PM and UM vs 18%; p = 0.019. No significant associations between genes polymorphisms and outcomes or toxicities were observed.5-FUDR seems to be significantly involved in predicting survival of patients who underwent 5-FU based CHT for mCRC. Although our findings require confirmation in large prospective studies, they reinforce the concept that individual genetic variation may allow personalized selection of chemotherapy to optimize clinical outcomes.

  7. Evaluation of cardiac injury biomarkers in cattle with acute clinical mastitis

    Directory of Open Access Journals (Sweden)

    meysam fllah

    2016-05-01

       This study was carried out on 30 Holstein dairy cattle with acute clinical mastitis (ACM and 30 healthy ones. After confirmation of ACM through clinical examination, venous blood samples were collected and cardiac troponin I (cTnI was measured using chemiluminescence assay. Cardiac enzymes activities including CK-MB, AST and LDH were analyzed with special kits and spectrophotometric method. According to the findings mean heart rate (p=0.001, respiratory rate (p=0.026, and rectal temperature (p=0.030 were significantly increased in diseased group. cTnI level was 1.018 ± 0.235 ng/ml in cattle with ACM, which was significantly higher than healthy cattle (0.011±0.006 ng/ml; p=0.000. Other cardiac biomarkers were increased in diseased group, however elevation of serum activities of AST (p=0.047 and CK-MB (p=0.000 were statically significant. Although serum LDH activity in diseased group was higher than control group; but this difference was statistically non-significant (p=0.454. There were significant positive correlations between cTnI concentration with heart rate (p=0.018; r=0.853, respiratory rate (p=0.024; r=0.671, and rectal temperature (p=0.038; r=0.542. Heart rates were significantly correlated with serum activities of CK-MB (p=0.047; r=0.722 and AST (p=0.035; r=0.649. These results indicate some degree of heart damage caused by acute clinical mastitis in dairy cattle.

  8. Trends in qualifying biomarkers in drug safety. Consensus of the 2011 meeting of the spanish society of clinical pharmacology.

    Science.gov (United States)

    Agúndez, José A G; Del Barrio, Jaime; Padró, Teresa; Stephens, Camilla; Farré, Magí; Andrade, Raúl J; Badimon, Lina; García-Martín, Elena; Vilahur, Gemma; Lucena, M Isabel

    2012-01-01

    In this paper we discuss the consensus view on the use of qualifying biomarkers in drug safety, raised within the frame of the XXIV meeting of the Spanish Society of Clinical Pharmacology held in Málaga (Spain) in October, 2011. The widespread use of biomarkers as surrogate endpoints is a goal that scientists have long been pursuing. Thirty years ago, when molecular pharmacogenomics evolved, we anticipated that these genetic biomarkers would soon obviate the routine use of drug therapies in a way that patients should adapt to the therapy rather than the opposite. This expected revolution in routine clinical practice never took place as quickly nor with the intensity as initially expected. The concerted action of operating multicenter networks holds great promise for future studies to identify biomarkers related to drug toxicity and to provide better insight into the underlying pathogenesis. Today some pharmacogenomic advances are already widely accepted, but pharmacogenomics still needs further development to elaborate more precise algorithms and many barriers to implementing individualized medicine exist. We briefly discuss our view about these barriers and we provide suggestions and areas of focus to advance in the field.

  9. Traumatic brain injury produced by exposure to blasts, a critical problem in current wars: biomarkers, clinical studies, and animal models

    Science.gov (United States)

    Dixon, C. Edward

    2011-06-01

    Traumatic brain injury (TBI) resulting from exposure to blast energy released by Improvised Explosive Devices (IEDs) has been recognized as the "signature injury" of Operation Iraqi Freedom and Operation Enduring Freedom. Repeated exposure to mild blasts may produce subtle deficits that are difficult to detect and quantify. Several techniques have been used to detect subtle brain dysfunction including neuropsychological assessments, computerized function testing and neuroimaging. Another approach is based on measurement of biologic substances (e.g. proteins) that are released into the body after a TBI. Recent studies measuring biomarkers in CSF and serum from patients with severe TBI have demonstrated the diagnostic, prognostic, and monitoring potential. Advancement of the field will require 1) biochemical mining for new biomarker candidates, 2) clinical validation of utility, 3) technical advances for more sensitive, portable detectors, 4) novel statistical approach to evaluate multiple biomarkers, and 5) commercialization. Animal models have been developed to simulate elements of blast-relevant TBI including gas-driven shock tubes to generate pressure waves similar to those produced by explosives. These models can reproduce hallmark clinical neuropathological responses such as neuronal degeneration and inflammation, as well as behavioral impairments. An important application of these models is to screen novel therapies and conduct proteomic, genomic, and lipodomic studies to mine for new biomarker candidates specific to blast relevant TBI.

  10. Candidate proteins, metabolites and transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA clinical study.

    Directory of Open Access Journals (Sweden)

    Richard S Finkel

    Full Text Available Spinal Muscular Atrophy (SMA is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1 gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets.To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches.A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2-12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS and to a number of secondary clinical measures.A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites and 44 urine metabolites. No transcripts correlated with MHFMS.In this cross-sectional study, "BforSMA" (Biomarkers for SMA, candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm these findings, demonstrate sensitivity to change with

  11. Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

    Science.gov (United States)

    Dehing-Oberije, Cary; Aerts, Hugo; Yu, Shipeng; De Ruysscher, Dirk; Menheere, Paul; Hilvo, Mika; van der Weide, Hiska; Rao, Bharat; Lambin, Philippe

    2011-10-01

    Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival. Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52). The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively. The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. Clinical investigation of TROP-2 as an independent biomarker and potential therapeutic target in colon cancer.

    Science.gov (United States)

    Zhao, Peng; Yu, Hai-Zheng; Cai, Jian-Hui

    2015-09-01

    Colon cancer is associated with a severe demographic and economic burden worldwide. The pathogenesis of colon cancer is highly complex and involves sequential genetic and epigenetic mechanisms. Despite extensive investigation, the pathogenesis of colon cancer remains to be elucidated. As the third most common type of cancer worldwide, the treatment options for colon cancer are currently limited. Human trophoblast cell‑surface marker (TROP‑2), is a cell‑surface transmembrane glycoprotein overexpressed by several types of epithelial carcinoma. In addition, TROP‑2 has been demonstrated to be associated with tumorigenesis and invasiveness in solid types of tumor. The aim of the present study was to investigate the protein expression of TROP‑2 in colon cancer tissues, and further explore the association between the expression of TROP‑2 and clinicopathological features of patients with colon cancer. The expression and localization of the TROP‑2 protein was examined using western blot analysis and immunofluorescence staining. Finally, the expression of TROP‑2 expression was correlated to conventional clinicopathological features of colon cancer using a χ2 test. The results revealed that TROP‑2 protein was expressed at high levels in the colon cancer tissues, which was associated with the development and pathological process of colon cancer. Therefore, TROP‑2 may be used as a biomarker to determine the clinical prognosis, and as a potential therapeutic target in colon cancer.

  13. Clinical usefulness of a biomarker-based diagnostic test for acute stroke: the Biomarker Rapid Assessment in Ischemic Injury (BRAIN) study.

    Science.gov (United States)

    Laskowitz, Daniel T; Kasner, Scott E; Saver, Jeffrey; Remmel, Kerri S; Jauch, Edward C

    2009-01-01

    biomarker based point-of-care algorithm with readily available clinical data to aid in the early evaluation and management of patients at high risk for cerebral ischemia.

  14. The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection.

    Science.gov (United States)

    Ritchie, Scott C; Würtz, Peter; Nath, Artika P; Abraham, Gad; Havulinna, Aki S; Fearnley, Liam G; Sarin, Antti-Pekka; Kangas, Antti J; Soininen, Pasi; Aalto, Kristiina; Seppälä, Ilkka; Raitoharju, Emma; Salmi, Marko; Maksimow, Mikael; Männistö, Satu; Kähönen, Mika; Juonala, Markus; Ripatti, Samuli; Lehtimäki, Terho; Jalkanen, Sirpa; Perola, Markus; Raitakari, Olli; Salomaa, Veikko; Ala-Korpela, Mika; Kettunen, Johannes; Inouye, Michael

    2015-10-28

    The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular disease and all-cause mortality. Here, we characterize biological processes associated with GlycA by leveraging population-based omics data and health records from >10,000 individuals. Our analyses show that GlycA levels are chronic within individuals for up to a decade. In apparently healthy individuals, elevated GlycA corresponded to elevation of myriad inflammatory cytokines, as well as a gene coexpression network indicative of increased neutrophil activity, suggesting that individuals with high GlycA may be in a state of chronic inflammatory response. Accordingly, analysis of infection-related hospitalization and death records showed that increased GlycA increased long-term risk of severe non-localized and respiratory infections, particularly septicaemia and pneumonia. In total, our work demonstrates that GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection. It also illustrates the utility of leveraging multi-layered omics data and health records to elucidate the molecular and cellular processes associated with biomarkers. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

    Science.gov (United States)

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

  16. Risk Factors and Biomarkers of Age-Related Macular Degeneration

    Science.gov (United States)

    Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

    2016-01-01

    A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

  17. Analysis of Plasma Albumin, Vitamin D, and Apolipoproteins A and B as Predictive Coronary Risk Biomarkers in the REGICOR Study.

    Science.gov (United States)

    Vázquez-Oliva, Gabriel; Zamora, Alberto; Ramos, Rafel; Subirana, Isaac; Grau, María; Dégano, Irene R; Muñoz, Daniel; Fitó, Montserrat; Elosua, Roberto; Marrugat, Jaume

    2018-05-12

    New biomarkers could improve the predictive capacity of classic risk functions. The aims of this study were to determine the association between circulating levels of apolipoprotein A1 (apoA1), apolipoprotein B (apoB), albumin, and 25-OH-vitamin D and coronary events and to analyze whether these biomarkers improve the predictive capacity of the Framingham-REGICOR risk function. A case-cohort study was designed. From an initial cohort of 5404 individuals aged 35 to 74 years with a 5-year follow-up, all the participants who had a coronary event (n = 117) and a random group of the cohort (subcohort; n = 667) were selected. Finally, 105 cases and 651 individuals representative of the cohort with an available biological sample were included. The events of interest were angina, fatal and nonfatal myocardial infarction and coronary deaths. Case participants were older, had a higher proportion of men and cardiovascular risk factors, and showed higher levels of apoB and lower levels of apoA1, apoA1/apoB ratio, 25-OH-vitamin D and albumin than the subcohort. In multivariate analyses, plasma albumin concentration was the only biomarker independently associated with coronary events (HR, 0.73; P = .002). The inclusion of albumin in the risk function properly reclassified a significant proportion of individuals, especially in the intermediate risk group (net reclassification improvement, 32.3; P = .048). Plasma albumin levels are inversely associated with coronary risk and improve the predictive capacity of classic risk functions. Copyright © 2018 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  18. Novel biomarkers in primary breast core biopsies to predict poor response to neoadjuvant chemotherapy and appearance of metastases.

    Science.gov (United States)

    Novell, Anna; Morales, Serafin; Valls, Joan; Panadés, Maria José; Salud, Antonieta; Iglesias, Edelmiro; Vilardell, Felip; Matias-Guiu, Xavier; Llombart-Cussac, Antonio

    2017-09-01

    Drug resistance has been one of the major obstacles limiting the success of cancer chemotherapy. In two thirds of breast cancer patients, large (>1cm) residual tumors are present after neoadjuvant chemotherapy (NCT). The residual tumor and involved nodes have been indicators of relapse and survival very important in breast cancer. The goal of this preliminary study was to assess the predictive significance of a panel of molecular biomarkers, related with the response to treatment or drug resistance to NCT, as determined on the diagnostic tumor. The expression of 22 proteins was examined using immunohistochemistry in tissue microarrays (TMA) from 115 patients of stage II-III breast cancer, treated with NCT. Among studied proteins, there are some that are anti-apoptotic, pro-proliferative, cancer stem cell markers and the Vitamin D Receptor. Other proteins are involved in the identification of molecular subtype, cell cycle regulation or DNA repair. Next, a predictive signature of poor response was generated from independent markers of predictive value. Tumors that expressed four or five conditions (biomarkers of chemoresistance with a determinated cutoff) were associated with a 9-fold increase in the chances of these patients of having a poor response to NCT. Additionally, we also found a worse prognostic signature, generated from independent markers of prognostic value. Tumors which expressed two or three conditions of worst prognostic, were associated with a 6-fold reduction in Distant Disease Free Survival. In conclusion, finding biomarkers of chemoresitance (ypTNM II-III) and metastases can become a stepping stone for future studies that will need to be assessed in a bigger scale.

  19. Diagnostic and prognostic epigenetic biomarkers in cancer.

    Science.gov (United States)

    Costa-Pinheiro, Pedro; Montezuma, Diana; Henrique, Rui; Jerónimo, Carmen

    2015-01-01

    Growing cancer incidence and mortality worldwide demands development of accurate biomarkers to perfect detection, diagnosis, prognostication and monitoring. Urologic (prostate, bladder, kidney), lung, breast and colorectal cancers are the most common and despite major advances in their characterization, this has seldom translated into biomarkers amenable for clinical practice. Epigenetic alterations are innovative cancer biomarkers owing to stability, frequency, reversibility and accessibility in body fluids, entailing great potential of assay development to assist in patient management. Several studies identified putative epigenetic cancer biomarkers, some of which have been commercialized. However, large multicenter validation studies are required to foster translation to the clinics. Herein we review the most promising epigenetic detection, diagnostic, prognostic and predictive biomarkers for the most common cancers.

  20. Clinical abdominal palpation for predicting oligohydramnios in ...

    African Journals Online (AJOL)

    with normal AFV being reassuring for expectant management, and reduced AFV a trigger for labour induction.[3] According to textbooks, clinical evidence of reduced AFV (oligohydramnios) includes ... [11,12] AFI was used as the reference.

  1. Identification of clinical biomarkers for pre-analytical quality control of blood samples.

    Science.gov (United States)

    Kang, Hyun Ju; Jeon, Soon Young; Park, Jae-Sun; Yun, Ji Young; Kil, Han Na; Hong, Won Kyung; Lee, Mee-Hee; Kim, Jun-Woo; Jeon, Jae-Pil; Han, Bok Ghee

    2013-04-01

    Pre-analytical conditions are key factors in maintaining the high quality of biospecimens. They are necessary for accurate reproducibility of experiments in the field of biomarker discovery as well as achieving optimal specificity of laboratory tests for clinical diagnosis. In research at the National Biobank of Korea, we evaluated the impact of pre-analytical conditions on the stability of biobanked blood samples by measuring biochemical analytes commonly used in clinical laboratory tests. We measured 10 routine laboratory analytes in serum and plasma samples from healthy donors (n = 50) with a chemistry autoanalyzer (Hitachi 7600-110). The analyte measurements were made at different time courses based on delay of blood fractionation, freezing delay of fractionated serum and plasma samples, and at different cycles (0, 1, 3, 6, 9) of freeze-thawing. Statistically significant changes from the reference sample mean were determined using the repeated-measures ANOVA and the significant change limit (SCL). The serum levels of GGT and LDH were changed significantly depending on both the time interval between blood collection and fractionation and the time interval between fractionation and freezing of serum and plasma samples. The glucose level was most sensitive only to the elapsed time between blood collection and centrifugation for blood fractionation. Based on these findings, a simple formula (glucose decrease by 1.387 mg/dL per hour) was derived to estimate the length of time delay after blood collection. In addition, AST, BUN, GGT, and LDH showed sensitive responses to repeated freeze-thaw cycles of serum and plasma samples. These results suggest that GGT and LDH measurements can be used as quality control markers for certain pre-analytical conditions (eg, delayed processing or repeated freeze-thawing) of blood samples which are either directly used in the laboratory tests or stored for future research in the biobank.

  2. On the assessment of the added value of new predictive biomarkers.

    Science.gov (United States)

    Chen, Weijie; Samuelson, Frank W; Gallas, Brandon D; Kang, Le; Sahiner, Berkman; Petrick, Nicholas

    2013-07-29

    The surge in biomarker development calls for research on statistical evaluation methodology to rigorously assess emerging biomarkers and classification models. Recently, several authors reported the puzzling observation that, in assessing the added value of new biomarkers to existing ones in a logistic regression model, statistical significance of new predictor variables does not necessarily translate into a statistically significant increase in the area under the ROC curve (AUC). Vickers et al. concluded that this inconsistency is because AUC "has vastly inferior statistical properties," i.e., it is extremely conservative. This statement is based on simulations that misuse the DeLong et al. method. Our purpose is to provide a fair comparison of the likelihood ratio (LR) test and the Wald test versus diagnostic accuracy (AUC) tests. We present a test to compare ideal AUCs of nested linear discriminant functions via an F test. We compare it with the LR test and the Wald test for the logistic regression model. The null hypotheses of these three tests are equivalent; however, the F test is an exact test whereas the LR test and the Wald test are asymptotic tests. Our simulation shows that the F test has the nominal type I error even with a small sample size. Our results also indicate that the LR test and the Wald test have inflated type I errors when the sample size is small, while the type I error converges to the nominal value asymptotically with increasing sample size as expected. We further show that the DeLong et al. method tests a different hypothesis and has the nominal type I error when it is used within its designed scope. Finally, we summarize the pros and cons of all four methods we consider in this paper. We show that there is nothing inherently less powerful or disagreeable about ROC analysis for showing the usefulness of new biomarkers or characterizing the performance of classification models. Each statistical method for assessing biomarkers and

  3. PODCAST: From Lost in Translation to Paradise Found: Enabling Protein Biomarker Method Transfer by Mass Spectrometry | Office of Cancer Clinical Proteomics Research

    Science.gov (United States)

    Translation of novel biomarkers into clinical care for the evaluation of therapeutic safety and efficacy has been slow, partly attributable to the cost and complexity of immunoassay development.  The potential for liquid chromatography-tandem mass spectrometry (LC-MS/MS) to streamline the translation of novel protein biomarkers is profound.  Drs. Henry Rodriguez and Andrew Hoofnagle discuss what the future may be for clinical proteomics. This is an American Association for Clinical Chemistry (AACC) podcast.

  4. Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

    Science.gov (United States)

    El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

    2017-01-01

    The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.

  5. Clinical abdominal palpation for predicting oligohydramnios in ...

    African Journals Online (AJOL)

    Objective. In view of the scarcity of ultrasound in low-resource settings, to evaluate abdominal palpation for prediction of oligohydramnios in suspected prolonged pregnancy, using the ultrasound-obtained amniotic fluid index (AFI) as a gold standard, taking into account maternal and fetal factors that may affect amniotic fluid ...

  6. Predicting risk of cancer during HIV infection: the role of inflammatory and coagulation biomarkers.

    Science.gov (United States)

    Borges, Álvaro H; Silverberg, Michael J; Wentworth, Deborah; Grulich, Andrew E; Fätkenheuer, Gerd; Mitsuyasu, Ronald; Tambussi, Giuseppe; Sabin, Caroline A; Neaton, James D; Lundgren, Jens D

    2013-06-01

    To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection. A prospective cohort. HIV-infected patients on continuous antiretroviral therapy (ART) in the control arms of three randomized trials (N=5023) were included in an analysis of predictors of cancer (any type, infection-related or infection-unrelated). Hazard ratios for IL-6, CRP and D-dimer levels (log2-transformed) were calculated using Cox models stratified by trial and adjusted for demographics and CD4+ cell counts and adjusted also for all biomarkers simultaneously. To assess the possibility that biomarker levels were elevated at entry due to undiagnosed cancer, analyses were repeated excluding early cancer events (i.e. diagnosed during first 2 years of follow-up). During approximately 24,000 person-years of follow-up (PYFU), 172 patients developed cancer (70 infection-related; 102 infection-unrelated). The risk of developing cancer was associated with higher levels (per doubling) of IL-6 (hazard ratio 1.38, Passociated with cancer risk when all biomarkers were considered simultaneously. Results for infection-related and infection-unrelated cancers were similar to results for any cancer. Hazard ratios excluding 69 early cancer events were 1.31 (P=0.007), 1.14 (P=0.02) and 1.07 (P=0.49) for IL-6, CRP and D-dimer, respectively. Activated inflammation and coagulation pathways are associated with increased cancer risk during HIV infection. This association was stronger for IL-6 and persisted after excluding early cancer. Trials of interventions may be warranted to assess whether cancer risk can be reduced by lowering IL-6 levels in HIV-positive individuals.

  7. Explorative investigation of biomarkers of brain damage and coagulation system activation in clinical stroke differentiation

    DEFF Research Database (Denmark)

    Undén, Johan; Strandberg, Karin; Malm, Jan

    2009-01-01

    INTRODUCTION: A simple and accurate method of differentiating ischemic stroke and intracerebral hemorrhage (ICH) is potentially useful to facilitate acute therapeutic management. Blood measurements of biomarkers of brain damage and activation of the coagulation system may potentially serve as nov...

  8. High?Sensitivity Troponin: A Clinical Blood Biomarker for Staging Cardiomyopathy in Fabry Disease

    OpenAIRE

    2016-01-01

    Background High?sensitivity troponin (hs?TNT), a biomarker of myocardial damage, might be useful for assessing fibrosis in Fabry cardiomyopathy. We performed a prospective analysis of hs?TNT as a biomarker for myocardial changes in Fabry patients and a retrospective longitudinal follow?up study to assess longitudinal hs?TNT changes relative to fibrosis and cardiomyopathy progression. Methods and Results For the prospective analysis, hs?TNT from 75 consecutive patients with genetically confirm...

  9. Pretreatment data is highly predictive of liver chemistry signals in clinical trials

    Directory of Open Access Journals (Sweden)

    Cai Z

    2012-11-01

    Full Text Available Zhaohui Cai,1,* Anders Bresell,2,* Mark H Steinberg,1 Debra G Silberg,1 Stephen T Furlong11AstraZeneca Pharmaceuticals, Wilmington, DE, USA; 2AstraZeneca Pharmaceuticals, Södertälje, Sweden*These authors contributed equally to this workPurpose: The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline information.Patients and methods: Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results.Results: Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy’s law cases. Baseline γ-glutamyltransferase (GGT level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests.Conclusion: It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.Keywords: bilirubin, Hy’s Law, ALT, GGT, baseline, prediction

  10. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg

    2015-01-01

    BACKGROUND: Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use. CONTENT: In this review, we discuss the key steps...... in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance...... of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before...

  11. Plasma biomarker analysis in pediatric ARDS: generating future framework from a pilot randomized control trial of methylprednisoloneA framework for identifying plasma biomarkers related to clinical outcomes in pediatric ARDS

    Directory of Open Access Journals (Sweden)

    Dai eKimura

    2016-03-01

    Full Text Available Objective: Lung injury activates multiple pro-inflammatory pathways, including neutrophils, epithelial and endothelial injury, and coagulation factors leading to acute respiratory distress syndrome (ARDS. Low-dose methylprednisolone therapy (MPT improved oxygenation and ventilation in early pediatric ARDS without altering duration of mechanical ventilation or mortality. We evaluated the effects of MPT on biomarkers of endothelial (Ang-2, sICAM-1 or epithelial (sRAGE injury, neutrophil activation (MMP-8, and coagulation (PAI-1. Design: Double-blind, placebo-controlled randomized trialSetting: Tertiary-care Pediatric Intensive Care Unit Patients: Mechanically ventilated children (0-18 years with early ARDS.Interventions: Blood samples were collected on Days 0 (before MPT, 7, and 14 during low-dose MPT (n=17 vs. placebo (n=18 therapy. The MPT group received a 2mg/kg loading dose followed by 1mg/kg/day continuous infusions from days 1-7, tapered off over 7 days; placebo group received equivalent amounts of 0.9% saline. We analyzed plasma samples using a multiplex assay for 5 biomarkers of ARDS. Multiple regression models were constructed to predict associations between changes in biomarkers and the clinical outcomes reported earlier including: P/F ratio on days 8&9, plateau pressure on days 1&2, PaCO2 on days 2&3, racemic epinephrine following extubation, and supplemental oxygen at ICU discharge.Results: No differences occurred in biomarker concentrations between the groups on Day 0. On Day 7, reduction in MMP-8 levels (p=0.0016 occurred in the MPT group, whereas increases in sICAM-1 levels (p=0.0005 occurred in the placebo group (no increases in sICAM-1 in the MPT group. sRAGE levels decreased in both MPT and placebo groups (p<0.0001 from Day 0 to Day 7. On Day 7, sRAGE levels were positively correlated with MPT group PaO2/FiO2 ratios on Day 8 (r=0.93, p=0.024. O2 requirements at ICU transfer positively correlated with Day 7 MMP-8 (r=0.85, p=0

  12. A clinical prediction rule for histological chorioamnionitis in preterm newborns.

    Directory of Open Access Journals (Sweden)

    Jasper V Been

    Full Text Available BACKGROUND: Histological chorioamnionitis (HC is an intrauterine inflammatory process highly associated with preterm birth and adverse neonatal outcome. HC is often clinically silent and diagnosed postnatally by placental histology. Earlier identification could facilitate treatment individualisation to improve outcome in preterm newborns. AIM: Develop a clinical prediction rule at birth for HC and HC with fetal involvement (HCF in preterm newborns. METHODS: Clinical data and placental pathology were obtained from singleton preterm newborns (gestational age ≤ 32.0 weeks born at Erasmus UMC Rotterdam from 2001 to 2003 (derivation cohort; n = 216 or Máxima MC Veldhoven from 2009 to 2010 (validation cohort; n = 206. HC and HCF prediction rules were developed with preference for high sensitivity using clinical variables available at birth. RESULTS: HC and HCF were present in 39% and 24% in the derivation cohort and in 44% and 22% in the validation cohort, respectively. HC was predicted with 87% accuracy, yielding an area under ROC curve of 0.95 (95%CI = 0.92-0.98, a positive predictive value of 80% (95%CI = 74-84%, and a negative predictive value of 93% (95%CI = 88-96%. Corresponding figures for HCF were: accuracy 83%, area under ROC curve 0.92 (95%CI = 0.88-0.96, positive predictive value 59% (95%CI = 52-62%, and negative predictive value 97% (95%CI = 93-99%. External validation expectedly resulted in some loss of test performance, preferentially affecting positive predictive rather than negative predictive values. CONCLUSION: Using a clinical prediction rule composed of clinical variables available at birth, HC and HCF could be predicted with good test characteristics in preterm newborns. Further studies should evaluate the clinical value of these rules to guide early treatment individualisation.

  13. Using image analysis as a tool for assessment of prognostic and predictive biomarkers for breast cancer: How reliable is it?

    Directory of Open Access Journals (Sweden)

    Mark C Lloyd

    2010-01-01

    Full Text Available Background : Estrogen receptor (ER, progesterone receptor (PR and human epidermal growth factor receptor-2 (HER2 are important and well-established prognostic and predictive biomarkers for breast cancers and routinely tested on patient′s tumor samples by immunohistochemical (IHC study. The accuracy of these test results has substantial impact on patient management. A critical factor that contributes to the result is the interpretation (scoring of IHC. This study investigates how computerized image analysis can play a role in a reliable scoring, and identifies potential pitfalls with common methods. Materials and Methods : Whole slide images of 33 invasive ductal carcinoma (IDC (10 ER and 23 HER2 were scored by pathologist under the light microscope and confirmed by another pathologist. The HER2 results were additionally confirmed by fluorescence in situ hybridization (FISH. The scoring criteria were adherent to the guidelines recommended by the American Society of Clinical Oncology/College of American Pathologists. Whole slide stains were then scored by commercially available image analysis algorithms from Definiens (Munich, Germany and Aperio Technologies (Vista, CA, USA. Each algorithm was modified specifically for each marker and tissue. The results were compared with the semi-quantitative manual scoring, which was considered the gold standard in this study. Results : For HER2 positive group, each algorithm scored 23/23 cases within the range established by the pathologist. For ER, both algorithms scored 10/10 cases within range. The performance of each algorithm varies somewhat from the percentage of staining as compared to the pathologist′s reading. Conclusions : Commercially available computerized image analysis can be useful in the evaluation of ER and HER2 IHC results. In order to achieve accurate results either manual pathologist region selection is necessary, or an automated region selection tool must be employed. Specificity can

  14. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

    Science.gov (United States)

    Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

    2018-01-01

    The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

  15. Intravoxel incoherent motion (IVIM histogram biomarkers for prediction of neoadjuvant treatment response in breast cancer patients

    Directory of Open Access Journals (Sweden)

    Gene Y. Cho

    Full Text Available Objective: To examine the prognostic capabilities of intravoxel incoherent motion (IVIM metrics and their ability to predict response to neoadjuvant treatment (NAT. Additionally, to observe changes in IVIM metrics between pre- and post-treatment MRI. Methods: This IRB-approved, HIPAA-compliant retrospective study observed 31 breast cancer patients (32 lesions. Patients underwent standard bilateral breast MRI along with diffusion-weighted imaging before and after NAT. Six patients underwent an additional IVIM-MRI scan 12–14 weeks after initial scan and 2 cycles of treatment. In addition to apparent diffusion coefficients (ADC from monoexponential decay, IVIM mean values (tissue diffusivity Dt, perfusion fraction fp, and pseudodiffusivity Dp and histogram metrics were derived using a biexponential model. An additional filter identified voxels of highly vascular tumor tissue (VTT, excluding necrotic or normal tissue. Clinical data include histology of biopsy and clinical response to treatment through RECIST assessment. Comparisons of treatment response were made using Wilcoxon rank-sum tests. Results: Average, kurtosis, and skewness of pseudodiffusion Dp significantly differentiated RECIST responders from nonresponders. ADC and Dt values generally increased (∼70% and VTT% values generally decreased (∼20% post-treatment. Conclusion: Dp metrics showed prognostic capabilities; slow and heterogeneous pseudodiffusion offer poor prognosis. Baseline ADC/Dt parameters were not significant predictors of response. This work suggests that IVIM mean values and heterogeneity metrics may have prognostic value in the setting of breast cancer NAT. Keywords: Breast cancer, Diffusion weighted MRI, Intravoxel incoherent motion, Neoadjuvant treatment, Response evaluation criteria in solid tumors

  16. Inflammatory Biomarkers Predict Airflow Obstruction After Exposure to World Trade Center Dust

    Science.gov (United States)

    Nolan, Anna; Naveed, Bushra; Comfort, Ashley L.; Ferrier, Natalia; Hall, Charles B.; Kwon, Sophia; Kasturiarachchi, Kusali J.; Cohen, Hillel W.; Zeig-Owens, Rachel; Glaser, Michelle S.; Webber, Mayris P.; Aldrich, Thomas K.; Rom, William N.; Kelly, Kerry; Prezant, David J.

    2012-01-01

    Background: The World Trade Center (WTC) collapse on September 11, 2001, produced airflow obstruction in a majority of firefighters receiving subspecialty pulmonary evaluation (SPE) within 6.5 years post-September 11, 2001. Methods: In a cohort of 801 never smokers with normal pre-September 11, 2001, FEV1, we correlated inflammatory biomarkers and CBC counts at monitoring entry within 6 months of September 11, 2001, with a median FEV1 at SPE (34 months; interquartile range, 25-57). Cases of airflow obstruction had FEV1 less than the lower limit of normal (LLN) (100 of 801; 70 of 100 had serum), whereas control subjects had FEV1 greater than or equal to LLN (153 of 801; 124 of 153 had serum). Results: From monitoring entry to SPE years later, FEV1 declined 12% in cases and increased 3% in control subjects. Case subjects had elevated serum macrophage derived chemokine (MDC), granulocyte-macrophage colony-stimulating factor (GM-CSF), granulocyte colony-stimulating factor, and interferon inducible protein-10 levels. Elevated GM-CSF and MDC increased the risk for subsequent FEV1 less than LLN by 2.5-fold (95% CI, 1.2-5.3) and 3.0-fold (95% CI, 1.4-6.1) in a logistic model adjusted for exposure, BMI, age on September 11, 2001, and polymorphonuclear neutrophils. The model had sensitivity of 38% (95% CI, 27-51) and specificity of 88% (95% CI, 80-93). Conclusions: Inflammatory biomarkers can be risk factors for airflow obstruction following dust and smoke exposure. Elevated serum GM-CSF and MDC levels soon after WTC exposure were associated with increased risk of airflow obstruction in subsequent years. Biomarkers of inflammation may help identify pathways producing obstruction after irritant exposure. PMID:21998260

  17. The potential role for use of mitochondrial DNA copy number as predictive biomarker in presbycusis.

    Science.gov (United States)

    Falah, Masoumeh; Houshmand, Massoud; Najafi, Mohammad; Balali, Maryam; Mahmoudian, Saeid; Asghari, Alimohamad; Emamdjomeh, Hessamaldin; Farhadi, Mohammad

    2016-01-01

    Age-related hearing impairment, or presbycusis, is the most common communication disorder and neurodegenerative disease in the elderly. Its prevalence is expected to increase, due to the trend of growth of the elderly population. The current diagnostic test for detection of presbycusis is implemented after there has been a change in hearing sensitivity. Identification of a pre-diagnostic biomarker would raise the possibility of preserving hearing sensitivity before damage occurs. Mitochondrial dysfunction, including the production of reactive oxygen species and induction of expression of apoptotic genes, participates in the progression of presbycusis. Mitochondrial DNA sequence variation has a critical role in presbycusis. However, the nature of the relationship between mitochondrial DNA copy number, an important biomarker in many other diseases, and presbycusis is undetermined. Fifty-four subjects with presbycusis and 29 healthy controls were selected after ear, nose, throat examination and pure-tone audiometry. DNA was extracted from peripheral blood samples. The copy number of mitochondrial DNA relative to the nuclear genome was measured by quantitative real-time polymerase chain reaction. Subjects with presbycusis had a lower median mitochondrial DNA copy number than healthy subjects and the difference was statistically significant ( P =0.007). Mitochondrial DNA copy number was also significantly associated with degree of hearing impairment ( P =0.025) and audiogram configuration ( P =0.022). The findings of this study suggest that lower mitochondrial DNA copy number is responsible for presbycusis through alteration of mitochondrial function. Moreover, the significant association of mitochondrial DNA copy number in peripheral blood samples with the degree of hearing impairment and audiogram configuration has potential for use as a standard test for presbycusis, providing the possibility of the development of an easy-to-use biomarker for the early detection of

  18. The potential role for use of mitochondrial DNA copy number as predictive biomarker in presbycusis

    Directory of Open Access Journals (Sweden)

    Falah M

    2016-10-01

    Full Text Available Masoumeh Falah,1,2 Massoud Houshmand,3 Mohammad Najafi,2 Maryam Balali,1 Saeid Mahmoudian,1 Alimohamad Asghari,4 Hessamaldin Emamdjomeh,1 Mohammad Farhadi1 1ENT and Head & Neck Research Center and Department, Iran University of Medical Sciences, Tehran, Iran; 2Cellular and Molecular Research Center, Biochemistry Department, Iran University of Medical Sciences, Tehran, Iran; 3Department of Medical Genetics, National Institute for Genetic Engineering and Biotechnology, Tehran, Iran; 4Skull base research center, Iran University of Medical Sciences, Tehran, Iran Objectives: Age-related hearing impairment, or presbycusis, is the most common communication disorder and neurodegenerative disease in the elderly. Its prevalence is expected to increase, due to the trend of growth of the elderly population. The current diagnostic test for detection of presbycusis is implemented after there has been a change in hearing sensitivity. Identification of a pre-diagnostic biomarker would raise the possibility of preserving hearing sensitivity before damage occurs. Mitochondrial dysfunction, including the production of reactive oxygen species and induction of expression of apoptotic genes, participates in the progression of presbycusis. Mitochondrial DNA sequence variation has a critical role in presbycusis. However, the nature of the relationship between mitochondrial DNA copy number, an important biomarker in many other diseases, and presbycusis is undetermined.Methods: Fifty-four subjects with presbycusis and 29 healthy controls were selected after ear, nose, throat examination and pure-tone audiometry. DNA was extracted from peripheral blood samples. The copy number of mitochondrial DNA relative to the nuclear genome was measured by quantitative real-time polymerase chain reaction.Results: Subjects with presbycusis had a lower median mitochondrial DNA copy number than healthy subjects and the difference was statistically significant (P=0.007. Mitochondrial DNA

  19. Posttransplant sCD30 as a biomarker to predict kidney graft outcome.

    Science.gov (United States)

    Süsal, Caner; Opelz, Gerhard

    2012-09-08

    In current clinical praxis, monitoring of immunosuppressive agents in organ transplantation is restricted to measurement of drug blood levels and does not consider the drug's variable effect on the individual patient's immune system. Establishment of biological markers that measure the biological effect of immunosuppressive drugs is desirable and would enable the identification of patients who are at risk of developing rejection, or patients who are suitable for minimization or weaning of immunosuppressive therapy. Several studies demonstrated that the technically simple posttransplant measurement in serum of the T cell activation marker soluble CD30 (sCD30) allows prediction of subsequent graft loss in kidney transplant recipients. sCD30 is a relatively large molecule and therefore an attractive biological marker which is resistant to repeated thawing cycles and temperature differences and easily determined using commercial ELISA. Whether sCD30-based prospective adjustment of immunosuppressive therapy can prevent irreversible graft damage and improve long-term graft outcome awaits evaluation in randomized controlled trials. Copyright © 2011 Elsevier B.V. All rights reserved.

  20. Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

    OpenAIRE

    Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

    2014-01-01

    We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

  1. Association of definition of acute kidney injury by cystatin C rise with biomarkers and clinical outcomes in children undergoing cardiac surgery.

    Science.gov (United States)

    Zappitelli, Michael; Greenberg, Jason H; Coca, Steven G; Krawczeski, Catherine D; Li, Simon; Thiessen-Philbrook, Heather R; Bennett, Michael R; Devarajan, Prasad; Parikh, Chirag R

    2015-06-01

    Research has identified improved biomarkers of acute kidney injury (AKI). Cystatin C (CysC) is a better glomerular filtration rate marker than serum creatinine (SCr) and may improve AKI definition. To determine if defining clinical AKI by increases in CysC vs SCr alters associations with biomarkers and clinical outcomes. Three-center prospective cohort study of intensive care units in New Haven, Connecticut, Cincinnati, Ohio, and Montreal, Quebec, Canada. Participants were 287 patients 18 years or younger without preoperative AKI or end-stage renal disease who were undergoing cardiac surgery. The study dates were July 1, 2007, through December 31, 2009. For biomarker vs clinical AKI associations, the exposures were first postoperative (0-6 hours after surgery) urine interleukin 18, neutrophil gelatinase-associated lipocalin, kidney injury molecule 1, and liver fatty acid-binding protein. For clinical AKI outcome associations, the exposure was Kidney Disease: Improving Global Outcomes AKI definition (based on SCr or CysC). Clinical AKI, length of stay, and length of mechanical ventilation. We determined areas under the receiver operating characteristic curve and odds ratios for first postoperative biomarkers to predict AKI. The SCr-defined vs CysC-defined AKI incidence differed substantially (43.6% vs 20.6%). Percentage agreement was 71% (κ = 0.38); stage 2 or worse AKI percentage agreement was 95%. Interleukin 18 and kidney injury molecule 1 discriminated for CysC-defined AKI better than for SCr-defined AKI. For interleukin 18 and kidney injury molecule 1, the areas under the receiver operating characteristic curve were 0.74 and 0.65, respectively, for CysC-defined AKI, and 0.66 and 0.58, respectively, for SCr-defined AKI. Fifth (vs first) quintile concentrations of both biomarkers were more strongly associated with CysC-defined AKI. For interleukin 18 and kidney injury molecule 1, the odds ratios were 16.19 (95% CI, 3.55-73.93) and 6.93 (95% CI, 1

  2. DI/LC-MS/MS-Based Metabolic Profiling for Identification of Early Predictive Serum Biomarkers of Metritis in Transition Dairy Cows.

    Science.gov (United States)

    Zhang, Guanshi; Deng, Qilan; Mandal, Rupasri; Wishart, David S; Ametaj, Burim N

    2017-09-27

    The objectives of this study were to evaluate alterations of metabolites in the blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected from both healthy and metritic cows during -8, -4, disease diagnosis, +4, and +8 wks relative to parturition. Results indicated that cows with metritis experienced altered concentrations of serum amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the entire experimental period. Moreover, two sets of predictive biomarker models and one set of diagnostic biomarker models for metritis were developed, and all of them showed high sensitivity and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for metritis in transition dairy cows.

  3. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  4. The clinical role of microRNA-21 as a promising biomarker in the diagnosis and prognosis of colorectal cancer: a systematic review and meta-analysis.

    Science.gov (United States)

    Peng, Qiliang; Zhang, Xueli; Min, Ming; Zou, Li; Shen, Peipei; Zhu, Yaqun

    2017-07-04

    This systematic analysis aimed to investigate the value of microRNA-21 (miR-21) in colorectal cancer for multiple purposes, including diagnosis and prognosis, as well as its predictive power in combination biomarkers. Fifty-seven eligible studies were included in our meta-analysis, including 25 studies for diagnostic meta-analysis and 32 for prognostic meta-analysis. For the diagnostic meta-analysis of miR-21 alone, the overall pooled results for sensitivity, specificity, and area under the curve (AUC) were 0.64 (95% CI: 0.53-0.74), 0.85 (0.79-0.90), and 0.85 (0.81-0.87), respectively. Circulating samples presented corresponding values of 0.72 (0.63-0.79), 0.84 (0.78-0.89), and 0.86 (0.83-0.89), respectively. For the diagnostic meta-analysis of miR-21-related combination biomarkers, the above three parameters were 0.79 (0.69-0.86), 0.79 (0.68-0.87), and 0.86 (0.83-0.89), respectively. Notably, subgroup analysis suggested that miRNA combination markers in circulation exhibited high predictive power, with sensitivity of 0.85 (0.70-0.93), specificity of 0.86 (0.77-0.92), and AUC of 0.92 (0.89-0.94). For the prognostic meta-analysis, patients with higher expression of miR-21 had significant shorter disease-free survival [DFS; pooled hazard ratio (HR): 1.60; 95% CI: 1.20-2.15] and overall survival (OS; 1.54; 1.27-1.86). The combined HR in tissues for DFS and OS were 1.76 (1.31-2.36) and 1.58 (1.30-1.93), respectively. Our comprehensive systematic review revealed that circulating miR-21 may be suitable as a diagnostic biomarker, while tissue miR-21 could be a prognostic marker for colorectal cancer. In addition, miRNA combination biomarkers may provide a new approach for clinical application.

  5. Methylation of WNT target genes AXIN2 and DKK1 as robust biomarkers for recurrence prediction in stage II colon cancer

    NARCIS (Netherlands)

    Kandimalla, R.; Linnekamp, J. F.; van Hooff, S.; Castells, A.; Llor, X.; Andreu, M.; Jover, R.; Goel, A.; Medema, J. P.

    2017-01-01

    Stage II colon cancer (CC) still remains a clinical challenge with patient stratification for adjuvant therapy (AT) largely relying on clinical parameters. Prognostic biomarkers are urgently needed for better stratification. Previously, we have shown that WNT target genes AXIN2, DKK1, APCDD1, ASCL2

  6. The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

    Science.gov (United States)

    Hsieh, Yu-Wei; Lin, Keh-Chung; Korivi, Mallikarjuna; Lee, Tsong-Hai; Wu, Ching-Yi; Wu, Kuen-Yuh

    2014-01-01

    We evaluated the reliability of 8-hydroxy-2′-deoxyguanosine (8-OHdG), and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76). Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34) and 8-OHdG and pain (r = 0.26, p rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research. PMID:24743892

  7. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Adjustment of Serum HE4 to reduced Glomerular filtration and its use in Biomarker-based prediction of deep Myometrial invasion in endometrial cancer

    DEFF Research Database (Denmark)

    Chovanec, Josef; Selingerova, Iveta; Greplova, Kristina

    2017-01-01

    Background: We investigated the efficacy of circulating biomarkers together with histological grade and age to predict deep myometrial invasion (dMI) in endometrial cancer patients. Methods: HE4ren was developed adjusting HE4 serum levels towards decreased glomerular filtration rate as quantified...... levels to reduced eGFR that enables quantification of time-dependent changes in HE4 production and elimination irrespective of age and renal function in women. Utilizing HE4ren improves performance of biomarker-based models for prediction of dMI in endometrial cancer patients....

  9. A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

    Directory of Open Access Journals (Sweden)

    Albrekt Ann-Sofie

    2011-08-01

    Full Text Available Abstract Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests.

  10. A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

    Science.gov (United States)

    2011-01-01

    Background Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power. Results We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization. Conclusions A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests. PMID:21824406

  11. CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva.

    Science.gov (United States)

    van Dijk, Lisanne V; Brouwer, Charlotte L; van der Schaaf, Arjen; Burgerhof, Johannes G M; Beukinga, Roelof J; Langendijk, Johannes A; Sijtsema, Nanna M; Steenbakkers, Roel J H M

    2017-02-01

    Current models for the prediction of late patient-rated moderate-to-severe xerostomia (XER 12m ) and sticky saliva (STIC 12m ) after radiotherapy are based on dose-volume parameters and baseline xerostomia (XER base ) or sticky saliva (STIC base ) scores. The purpose is to improve prediction of XER 12m and STIC 12m with patient-specific characteristics, based on CT image biomarkers (IBMs). Planning CT-scans and patient-rated outcome measures were prospectively collected for 249 head and neck cancer patients treated with definitive radiotherapy with or without systemic treatment. The potential IBMs represent geometric, CT intensity and textural characteristics of the parotid and submandibular glands. Lasso regularisation was used to create multivariable logistic regression models, which were internally validated by bootstrapping. The prediction of XER 12m could be improved significantly by adding the IBM "Short Run Emphasis" (SRE), which quantifies heterogeneity of parotid tissue, to a model with mean contra-lateral parotid gland dose and XER base . For STIC 12m , the IBM maximum CT intensity of the submandibular gland was selected in addition to STIC base and mean dose to submandibular glands. Prediction of XER 12m and STIC 12m was improved by including IBMs representing heterogeneity and density of the salivary glands, respectively. These IBMs could guide additional research to the patient-specific response of healthy tissue to radiation dose. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  12. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    Science.gov (United States)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-10-01

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  13. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    International Nuclear Information System (INIS)

    Torres Junior, Audalio Rebelo; Sousa, Débora Batista Pinheiro; Neta, Raimunda Nonata Fortes Carvalho

    2014-01-01

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish

  14. An integrated model supporting histological and biometric responses as predictive biomarkers of fish health status

    Energy Technology Data Exchange (ETDEWEB)

    Torres Junior, Audalio Rebelo [Department of Oceanography and Limnology, Federal University of Maranhão (Brazil); Sousa, Débora Batista Pinheiro [Postgraduate Program of Aquatic Resources and Fishery (PPGRAP/UEMA), State University of Maranhão (Brazil); Neta, Raimunda Nonata Fortes Carvalho [Department of Chemistry and Biology, State University of Maranhão (Brazil)

    2014-10-06

    In this work, an experimental system of histological (branchial lesions) biomarkers and biometric data in catfish (Sciades herzbergii) was modeled. The fish were sampled along known pollution areas (S1) and from environmental protect areas (S2) in São Marcos' Bay, Brazil. Gills were fixed in 10% formalin and usual histological techniques were used in the first gill arch right. The lesions were observed by light microscopy. There were no histopathological changes in animals captured at reference site (S1). However, in the catfish collected in the potentially contaminated area (S2) was observed several branchial lesions, such as lifting of the lamellar epithelium, fusion of some secondary lamellae, hypertrophy of epithelial cells and lamellar aneurysm. The analysis using the biometric data showed significant differences, being highest in fish analyzed in the reference area. This approach revealed spatial differences related with biometric patterns and morphological modifications of catfish.

  15. The potential use of biomarkers in predicting contrast-induced acute kidney injury

    Directory of Open Access Journals (Sweden)

    Andreucci M

    2016-09-01

    Full Text Available Michele Andreucci,1 Teresa Faga,1 Eleonora Riccio,2 Massimo Sabbatini,2 Antonio Pisani,2 Ashour Michael,1 1Department of Health Sciences, University “Magna Graecia” of Catanzaro, Catanzaro, 2Department of Public Health, University of Naples Federico II, Naples, Italy Abstract: Contrast-induced acute kidney injury (CI-AKI is a problem associated with the use of iodinated contrast media, causing kidney dysfunction in patients with preexisting renal failure. It accounts for 12% of all hospital-acquired kidney failure and increases the length of hospitalization, a situation that is worsening with increasing numbers of patients with comorbidities, including those requiring cardiovascular interventional procedures. So far, its diagnosis has relied upon the rise in creatinine levels, which is a late marker of kidney damage and is believed to be inadequate. Therefore, there is an urgent need for biomarkers that can detect CI-AKI sooner and more reliably. In recent years, many new biomarkers have been characterized for AKI, and these are discussed particularly with their use in known CI-AKI models and studies and include neutrophil gelatinase-associated lipocalin, cystatin C (Cys-C, kidney injury molecule-1, interleukin-18, N-acetyl-β-d-glucosaminidase, and L-type fatty acid-binding protein (L-FABP. The potential of miRNA and metabolomic technology is also mentioned. Early detection of CI-AKI may lead to early intervention and therefore improve patient outcome, and in future any one or a combination of several of these markers together with development in technology for their analysis may prove effective in this respect. Keywords: radiocontrast media, acute renal failure, markers, renal injury

  16. Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

    Science.gov (United States)

    Phan, John H.; Moffitt, Richard A.; Stokes, Todd H.; Liu, Jian; Young, Andrew N.; Nie, Shuming; Wang, May D.

    2013-01-01

    Recent advances in biomarker discovery, biocomputing, and nanotechnology have raised new opportunities for the emerging field of personalized medicine in which disease detection, diagnosis, and therapy are tailored to each individual’s molecular profile, and also for predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. Here we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, together with prospects and challenges in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases. PMID:19409634

  17. Biomarker assessment and molecular testing for prognostication in breast cancer.

    Science.gov (United States)

    Kos, Zuzana; Dabbs, David J

    2016-01-01

    Current treatment of breast cancer incorporates clinical, pathological and molecular data. Oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) define prognosis and identify tumours for targeted therapy, and remain the sole established single-molecule biomarkers defining the minimum breast cancer pathology data set. Ki67 remains one of the most promising yet controversial biomarkers in breast cancer, implemented routinely in some, but not all, pathology departments. Beyond the single-molecule biomarkers, a host of multigene expression tests have been developed to interrogate the driver pathways and biology of individual breast cancers to predict clinical outcome more accurately. A minority of these assays have entered into clinical practice. This review focuses on the established biomarkers of ER, PR and HER2, the controversial but clinically implemented biomarker Ki67 and the currently marketed gene expression signatures. © 2015 John Wiley & Sons Ltd.

  18. Using data-independent, high-resolution mass spectrometry in protein biomarker research: perspectives and clinical applications.

    Science.gov (United States)

    Sajic, Tatjana; Liu, Yansheng; Aebersold, Ruedi

    2015-04-01

    In medicine, there is an urgent need for protein biomarkers in a range of applications that includes diagnostics, disease stratification, and therapeutic decisions. One of the main technologies to address this need is MS, used for protein biomarker discovery and, increasingly, also for protein biomarker validation. Currently, data-dependent analysis (also referred to as shotgun proteomics) and targeted MS, exemplified by SRM, are the most frequently used mass spectrometric methods. Recently developed data-independent acquisition techniques combine the strength of shotgun and targeted proteomics, while avoiding some of the limitations of the respective methods. They provide high-throughput, accurate quantification, and reproducible measurements within a single experimental setup. Here, we describe and review data-independent acquisition strategies and their recent use in clinically oriented studies. In addition, we also provide a detailed guide for the implementation of SWATH-MS (where SWATH is sequential window acquisition of all theoretical mass spectra)-one of the data-independent strategies that have gained wide application of late. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. The Reliability and Predictive Ability of a Biomarker of Oxidative DNA Damage on Functional Outcomes after Stroke Rehabilitation

    Directory of Open Access Journals (Sweden)

    Yu-Wei Hsieh

    2014-04-01

    Full Text Available We evaluated the reliability of 8-hydroxy-2'-deoxyguanosine (8-OHdG, and determined its ability to predict functional outcomes in stroke survivors. The rehabilitation effect on 8-OHdG and functional outcomes were also assessed. Sixty-one stroke patients received a 4-week rehabilitation. Urinary 8-OHdG levels were determined by liquid chromatography–tandem mass spectrometry. The test-retest reliability of 8-OHdG was good (interclass correlation coefficient = 0.76. Upper-limb motor function and muscle power determined by the Fugl-Meyer Assessment (FMA and Medical Research Council (MRC scales before rehabilitation showed significant negative correlation with 8-OHdG (r = −0.38, r = −0.30; p < 0.05. After rehabilitation, we found a fair and significant correlation between 8-OHdG and FMA (r = −0.34 and 8-OHdG and pain (r = 0.26, p < 0.05. Baseline 8-OHdG was significantly correlated with post-treatment FMA, MRC, and pain scores (r = −0.34, −0.31, and 0.25; p < 0.05, indicating its ability to predict functional outcomes. 8-OHdG levels were significantly decreased, and functional outcomes were improved after rehabilitation. The exploratory study findings conclude that 8-OHdG is a reliable and promising biomarker of oxidative stress and could be a valid predictor of functional outcomes in patients. Monitoring of behavioral indicators along with biomarkers may have crucial benefits in translational stroke research.

  20. ERCC1 and TS Expression as Prognostic and Predictive Biomarkers in Metastatic Colon Cancer.

    Directory of Open Access Journals (Sweden)

    Michel B Choueiri

    Full Text Available In patients with metastatic colon cancer, response to first line chemotherapy is a strong predictor of overall survival (OS. Currently, oncologists lack diagnostic tests to determine which chemotherapy regimen offers the greatest chance for response in an individual patient. Here we present the results of gene expression analysis for two genes, ERCC1 and TS, measured with the commercially available ResponseDX: Colon assay (Response Genetics, Los Angeles, CA in 41 patients with de novo metastatic colon cancer diagnosed between July 2008 and August 2013 at the University of California, San Diego. In addition ERCC1 and TS expression levels as determined by RNAseq and survival data for patients in TCGA were downloaded from the TCGA data portal. We found that patients with low expression of ERCC1 (n = 33 had significantly longer median OS (36.0 vs. 10.1 mo, HR 0.29, 95% CI .095 to .84, log-rank p = 9.0x10-6 and median time to treatment to failure (TTF following first line chemotherapy (14.1 vs. 2.4 mo, HR 0.17, 95% CI 0.048 to 0.58, log-rank p = 5.3x10-4 relative to those with high expression (n = 4. After accounting for the covariates age, sex, tumor grade and ECOG performance status in a Cox proportional hazard model the association of low ERCC1 with longer OS (HR 0.18, 95% CI 0.14 to 0.26, p = 0.0448 and TTF (HR 0.16, 95% CI 0.14 to 0.21, p = 0.0053 remained significant. Patients with low TS expression (n = 29 had significantly longer median OS (36.0 vs. 14.8 mo, HR 0.25, 95% CI 0.074 to 0.82, log-rank p = 0.022 relative to those with high expression (n = 12. The combined low expression of ERCC1/TS was predictive of response in patients treated with FOLFOX (40% vs. 91%, RR 2.3, Fisher's exact test p = 0.03, n = 27, but not with FOLFIRI (71% vs. 71%, RR 1.0, Fisher's exact test p = 1, n = 14. Overall, these findings suggest that measurement of ERCC1 and TS expression has potential clinical utility in managing patients with metastatic colorectal

  1. Lipidomics in translational research and the clinical significance of lipid-based biomarkers.

    Science.gov (United States)

    Stephenson, Daniel J; Hoeferlin, L Alexis; Chalfant, Charles E

    2017-11-01

    Lipidomics is a rapidly developing field of study that focuses on the identification and quantitation of various lipid species in the lipidome. Lipidomics has now emerged in the forefront of scientific research due to the importance of lipids in metabolism, cancer, and disease. Using both targeted and untargeted mass spectrometry as a tool for analysis, progress in the field has rapidly progressed in the last decade. Having the ability to assess these small molecules in vivo has led to better understanding of several lipid-driven mechanisms and the identification of lipid-based biomarkers in neurodegenerative disease, cancer, sepsis, wound healing, and pre-eclampsia. Biomarker identification and mechanistic understanding of specific lipid pathways linked to a disease's pathologies can form the foundation in the development of novel therapeutics in hopes of curing human disease. Published by Elsevier Inc.

  2. miR-125b-1 and miR-378a are predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer.

    Science.gov (United States)

    Tanaka, Hironori; Hazama, Shoichi; Iida, Michihisa; Tsunedomi, Ryouichi; Takenouchi, Hiroko; Nakajima, Masao; Tokumitsu, Yukio; Kanekiyo, Shinsuke; Shindo, Yoshitaro; Tomochika, Shinobu; Tokuhisa, Yoshihiro; Sakamoto, Kazuhiko; Suzuki, Nobuaki; Takeda, Shigeru; Yamamoto, Shigeru; Yoshino, Shigefumi; Ueno, Tomio; Hamamoto, Yoshihiko; Fujita, Yusuke; Tanaka, Hiroaki; Tahara, Ko; Shimizu, Ryoichi; Okuno, Kiyotaka; Fujita, Koji; Kuroda, Masahiko; Nakamura, Yusuke; Nagano, Hiroaki

    2017-11-01

    Many clinical trials of peptide vaccines have been conducted. However, these vaccines have provided clinical benefits in only a small fraction of patients. The purpose of the present study was to explore microRNAs (miRNAs) as novel predictive biomarkers for the efficacy of vaccine treatment against colorectal cancer. First, we carried out microarray analysis of pretreatment cancer tissues in a phase I study, in which peptide vaccines alone were given. Candidate miRNAs were selected by comparison of the better prognosis group with the poorer prognosis group. Next, we conducted microarray analysis of cancer tissues in a phase II study, in which peptide vaccines combined with chemotherapy were given. Candidate miRNAs were further selected by a similar comparison of prognosis. Subsequently, we carried out reverse-transcription PCR analysis of phase II cases, separating cancer tissues into cancer cells and stromal tissue using laser capture microdissection. Treatment effect in relation to overall survival (OS) and miRNA expression was analyzed. Three miRNA predictors were negatively associated with OS: miR-125b-1 in cancer cells (P = 0.040), and miR-378a in both cancer cells (P = 0.009) and stromal cells (P colorectal cancer. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  3. Evaluation of interleukin-6 and serotonin as biomarkers to predict response to fluoxetine.

    Science.gov (United States)

    Manoharan, Aarthi; Rajkumar, Ravi Philip; Shewade, Deepak Gopal; Sundaram, Rajan; Muthuramalingam, Avin; Paul, Abialbon

    2016-05-01

    Only 30% of major depressive disorder (MDD) patients achieve complete remission with a serotonergic antidepressant (selective serotonin reuptake inhibitor). We investigated the potential of serotonin (5-HT) and interleukin-6 (IL-6) to serve as functional biomarkers of fluoxetine response. Serum IL-6 and 5-HT were measured in 73 MDD patients (39 responders and 34 non-responders) pre- and 6 weeks post-treatment and in 44 normal controls with ELISA. Fluoxetine and norfluoxetine were measured using LC MS/MS. IL-6 levels were significantly higher in MDD patients when compared with controls (p Fluoxetine and norfluoxetine concentrations were not significantly different in responders and non-responders, and there was no correlation between fluoxetine concentrations and percentage reduction in 5-HT from week 0 to 6. 5-HT and IL-6 may not serve as useful markers of response to fluoxetine because of inconsistent results across different studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  4. IL-10 and socs3 Are Predictive Biomarkers of Dengue Hemorrhagic Fever

    Directory of Open Access Journals (Sweden)

    Lilian Karem Flores-Mendoza

    2017-01-01

    Full Text Available Background. Cytokines play important roles in the physiopathology of dengue infection; therefore, the suppressors of cytokine signaling (socs that control the type and timing of cytokine functions could be involved in the origin of immune alterations in dengue. Objective. To explore the association of cytokine and socs levels with disease severity in dengue patients. Methods. Blood samples of 48 patients with confirmed dengue infection were analyzed. Amounts of interleukins IL-2, IL-4, IL-6, and IL-10, interferon- (IFN- γ, and tumor necrosis factor- (TNF- α were quantified by flow cytometry, and the relative expression of socs1 and socs3 mRNA was quantified by real-time RT-PCR. Results. Increased levels of IL-10 and socs3 and lower expression of socs1 were found in patients with dengue hemorrhagic fever (DHF with respect to those with dengue fever (DF (p199.8-fold, socs1 (134 pg/ml have the highest sensitivity and specificity to discriminate between DF and DHF. Conclusion. Simultaneous changes in IL-10 and socs1/socs3 could be used as prognostic biomarkers of dengue severity.

  5. Ciculating miRNA-21 as a Biomarker Predicts Polycystic Ovary Syndrome (PCOS) in Patients.

    Science.gov (United States)

    Jiang, Liyan; Li, Wei; Wu, Minmin; Cao, Sifan

    2015-01-01

    Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism, hyperinsulinemia, and infertility. In PCOS, abnormal regulation of relevant genes is required for follicular development. By binding to the 3' untranslated region (3'URT), microRNAs (miRNAs) are widely involved in posttranscriptional gene regulation. However, few studies have been conducted on circulating miRNA expression in PCOS. This study aims to describe altered expression of circulating miR-21 in PCOS. The expression of serum miRNAs of PCOS patients were explored using the TaqMan Low Density Array followed by individual quantitative reverse transcription polymerase chain reaction assays. The protein level of LATS1 was determined using Western blot. To validate whether miR-21 targeted LATS1, the luciferase assay was applied. In comparison with normal subjects, the circulating level of miRNA-21 was significantly enhanced in PCOS patients. In PCOS patients, the expression levels of MST1/2, LATS1/2, TAZ were much lower than the control subjects. Luciferase reporter assay revealed that LATS1 was a downstream target of miR-21. In comparison with normal subjects, serum miR-21 is obviously increased in PCOS patients. Through targeting LATS1, miR-21 could prompt PCOS progression and could act as a novel non-invasive biomarker for diagnosis of PCOS.

  6. Biomarkers for Early Detection of Clinically Relevant Prostate Cancer: A Multi-Institutional Validation Trial

    Science.gov (United States)

    2015-10-01

    provision of law, no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently ...biomarker platforms in our multi-center, prospectively accrued prostate cancer active surveillance cohort – the Canary Prostate Active Surveillance...prostate cancers currently diagnosed are low risk tumors for which there is substantial evidence that the cancer will not cause harm if left untreated

  7. Methionine sulfoxides in serum proteins as potential clinical biomarkers of oxidative stress

    OpenAIRE

    Satoko Suzuki; Yoshio Kodera; Tatsuya Saito; Kazumi Fujimoto; Akari Momozono; Akinori Hayashi; Yuji Kamata; Masayoshi Shichiri

    2016-01-01

    Oxidative stress contributes to the pathophysiology of a variety of diseases, and circulating biomarkers of its severity remains a topic of great interest for researchers. Our peptidomic strategy enables accurate and reproducible analysis of circulating proteins/peptides with or without post-translational modifications. Conventional wisdom holds that hydrophobic methionines exposed to an aqueous environment or experimental handling procedures are vulnerable to oxidation. However, we show that...

  8. Predictive value of eosinophils and neutrophils on clinical effects of ICS in COPD

    DEFF Research Database (Denmark)

    Hartjes, Floor J; Vonk, Judith M; Faiz, Alen

    2018-01-01

    BACKGROUND AND OBJECTIVE: Inflammation is present to a variable degree and composition in patients with COPD. This study investigates associations between both eosinophils and neutrophils in blood, sputum, airway wall biopsies and bronchoalveolar lavage (BAL) and their potential use as biomarkers...... and BAL were evaluated at baseline. In addition, at baseline, 6 and 30 months, forced expiratory flow in 1 s (FEV1 ), residual volume/total lung capacity (hyperinflation) and Clinical COPD Questionnaire were evaluated. RESULTS: Cross-sectional analyses at baseline showed that higher blood eosinophils were...... significantly associated with higher eosinophil counts in sputum, biopsies and BAL. However, blood neutrophils did not significantly correlate with neutrophil counts in the other compartments. Baseline eosinophils and neutrophils, in whichever compartment measured, did not predict longitudinal FEV1 changes...

  9. Clinical utility of pretreatment prediction of chemoradiotherapy response in rectal cancer: a review.

    Science.gov (United States)

    Yoo, Byong Chul; Yeo, Seung-Gu

    2017-03-01

    Approximately 20% of all patients with locally advanced rectal cancer experience pathologically complete responses following neoadjuvant chemoradiotherapy (CRT) and standard surgery. The utility of radical surgery for patients exhibiting good CRT responses has been challenged. Organ-sparing strategies for selected patients exhibiting complete clinical responses include local excision or no immediate surgery. The subjects of this tailored management are patients whose presenting disease corresponds to current indications of neoadjuvant CRT, and their post-CRT tumor response is assessed by clinical and radiological examinations. However, a model predictive of the CRT response, applied before any treatment commenced, would be valuable to facilitate such a personalized approach. This would increase organ preservation, particularly in patients for whom upfront CRT is not generally prescribed. Molecular biomarkers hold the greatest promise for development of a pretreatment predictive model of CRT response. A combination of clinicopathological, radiological, and molecular markers will be necessary to render the model robust. Molecular research will also contribute to the development of drugs that can overcome the radioresistance of rectal tumors. Current treatments for rectal cancer are based on the expected prognosis given the presenting disease extent. In the future, treatment schemes may be modified by including the predicted CRT response evaluated at presentation.

  10. Sphingosine-1-Phosphate (S1P) Is a Feasible Biomarker in Predicting the Efficacy of Polymyxin B-Immobilized Fiber Direct Hemoperfusion (PMX-DHP) in Patients with Septic Shock.

    Science.gov (United States)

    Inoue, Satoshi; Sakamoto, Yuichiro; Koami, Hiroyuki; Yamada C, Kosuke; Nagashima, Futoshi; Miike, Toru; Iwamura, Takashi; Obata, Toru

    2018-01-01

    The aim of this study was to identify a useful biomarker to predict the efficacy of polymyxin B-immobilized fiber direct hemoperfusion (PMX-DHP) in patients with septic shock. The 44 patients included in this study were divided into two groups. Group A had an increase in systolic blood pressure (SBP) over 30 mmHg after PMX-DHP treatment. Group B had an increase in SBP less than 30 mmHg after PMX-DHP treatment. We evaluated the clinical characteristics and demographics of both groups. We also assessed whether the cause of sepsis affected the efficacy of PMX-DHP and compared the prognosis of both groups. Finally, we investigated whether there were any significant differences in the levels of sepsis-related biomarkers, including sphingosine-1-phosphate (S1P), between both groups before PMX-DHP in an effort to identify a biomarker that could predict the efficacy of PMX-DHP. PMX-DHP significantly increased SBP regardless of the cause of sepsis. Although there was some tendency, PMX-DHP did not significantly improve the prognosis of effective cases in comparison with non-effective cases, probably because of the limited number of patients included. Among the sepsis-related biomarkers, only S1P values were significantly different between the two groups before PMX-DHP, and S1P levels were significantly increased after treatment in the effective cases. S1P levels prior to PMX-DHP can be used to predict its efficacy. In addition, continuous monitoring of S1P levels can indicate the effectiveness of PMX-DHP in patients with septic shock.

  11. Self-perceived quality of life predicts mortality risk better than a multi-biomarker panel, but the combination of both does best

    Directory of Open Access Journals (Sweden)

    Nauck Matthias

    2011-07-01

    Full Text Available Abstract Background Associations between measures of subjective health and mortality risk have previously been shown. We assessed the impact and comparative predictive performance of a multi-biomarker panel on this association. Methods Data from 4,261 individuals aged 20-79 years recruited for the population-based Study of Health in Pomerania was used. During an average 9.7 year follow-up, 456 deaths (10.7% occurred. Subjective health was assessed by SF-12 derived physical (PCS-12 and mental component summaries (MCS-12, and a single-item self-rated health (SRH question. We implemented Cox proportional-hazards regression models to investigate the association of subjective health with mortality and to assess the impact of a combination of 10 biomarkers on this association. Variable selection procedures were used to identify a parsimonious set of subjective health measures and biomarkers, whose predictive ability was compared using receiver operating characteristic (ROC curves, C-statistics, and reclassification methods. Results In age- and gender-adjusted Cox models, poor SRH (hazard ratio (HR, 2.07; 95% CI, 1.34-3.20 and low PCS-12 scores (lowest vs. highest quartile: HR, 1.75; 95% CI, 1.31-2.33 were significantly associated with increased risk of all-cause mortality; an association independent of various covariates and biomarkers. Furthermore, selected subjective health measures yielded a significantly higher C-statistic (0.883 compared to the selected biomarker panel (0.872, whereas a combined assessment showed the highest C-statistic (0.887 with a highly significant integrated discrimination improvement of 1.5% (p Conclusion Adding biomarker information did not affect the association of subjective health measures with mortality, but significantly improved risk stratification. Thus, a combined assessment of self-reported subjective health and measured biomarkers may be useful to identify high-risk individuals for intensified monitoring.

  12. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    Energy Technology Data Exchange (ETDEWEB)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan [Department of Occupational and Environmental Medicine, Lund University, S-221 85 Lund (Sweden); Bonassi, Stefano; Lando, Cecilia [Department of Environmental Epidemiology, Istituto Nazionale per la Ricerca sul Cancro, Viale Benedetto XV, I-1016132 Genoa (Italy); Hansteen, Inger-Lise [Department of Occupational Medicine, Telemark Central Hospital, N-3710 Skien (Norway); Montagud, Alicia Huici [Centro Nacional de Condiciones de Trabajo, Instituto Nacional de Seguridad e Higiene en el Trabajo, Dulcet 2-10, ES-08034 Barcelona (Spain); Knudsen, Lisbeth [National Institute of Occupational Health, Lersoe Parkalle 105, DK-2100 Copenhagen (Denmark); Norppa, Hannu [Finnish Institute of Occupational Health, Topeliuksekatu 41 aA, FIN-00250 Helsinki (Finland); Reuterwall, Christina [National Institute of Work Life, S-171 84 Solna (Sweden); Broegger, Anton [Norwegian Radium Hospital, Oslo (Norway); Forni, Alessandra [Istituto di Medicina del Lavoro Clinica del Lavoro `L. Devoto`, Milan (Italy); Hoegstedt, Benkt [Department of Occupational Medicine, Central Hospital, Halmstad (Sweden); Lambert, Bo [Department of Environmental Medicine, Centre for Nutrition and Toxicology, Karolinska Institute, Stockholm (Sweden); Mitelman, Felix [Department of Clinical Genetics, Lund University, Lund (Sweden); Nordenson, Ingrid [National Institute of Work Life, Umea (Sweden); Salomaa, Sisko [Finnish Center for Radiation and Nuclear Safety, Helsinki (Finland)

    1998-09-20

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  13. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    International Nuclear Information System (INIS)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan; Bonassi, Stefano; Lando, Cecilia; Hansteen, Inger-Lise; Montagud, Alicia Huici; Knudsen, Lisbeth; Norppa, Hannu; Reuterwall, Christina; Broegger, Anton; Forni, Alessandra; Hoegstedt, Benkt; Lambert, Bo; Mitelman, Felix; Nordenson, Ingrid; Salomaa, Sisko

    1998-01-01

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  14. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Clinical time series prediction: towards a hierarchical dynamical system framework

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  16. Molecular Profiling of Refractory Adrenocortical Cancers and Predictive Biomarkers to Therapy

    Directory of Open Access Journals (Sweden)

    Sherri Z. Millis

    2015-01-01

    Full Text Available Purpose Current first-line chemotherapy for patients with metastatic adrenocortical cancer (ACC includes doxorubicin, etoposide, cisplatin, and mitotane with a reported response rate of only 23.2%. New therapeutic leads for patients with refractory tumors are needed; there is no standard second-line treatment. Methods Samples from 135 ACC tumors were analyzed by immunohistochemistry, in situ hybridization (FISH or CISH, and/or gene sequencing at a single commercial reference laboratory (Caris Life Sciences to identify markers associated with drug sensitivity and resistance. Results Overexpression of proteins related to demonstrated chemotherapy sensitivity or resistance included topoisomerase 1, progesterone receptor, and topoisomerase 2-alpha in 46%, 63%, and 42% of cases, respectively. Loss of excision repair cross-complementary group 1 (ERCC1, phosophatase and tensin homolog, O(6-methylguanine-methyltransferase, and ribonucleotide reductase M1 (RRM1 was identified in 56%, 59%, 71%, and 58% of cases, respectively. Other aberrations included overexpression of programmed death-ligand 1 or programmed cell death protein 1 tumor-infiltrating lymphocytes in >40% of cases. In all, 35% of cases had a mutation in the canonical Wnt signaling pathway (either CTNNB1 or APC and 48% had a mutation in TP53. No other genomic alterations were identified. Conclusion Biomarker alterations in ACC may be used to direct therapies, including recommendations for and potential resistance of some patients to traditional chemotherapies, which may explain the low response rate in the unselected population. Limited outcomes data support the use of mitotane and platinum therapies for patients with low levels of the proteins RRM1 and ERCC1.

  17. Identification of CREB3L1 as a Biomarker Predicting Doxorubicin Treatment Outcome.

    Directory of Open Access Journals (Sweden)

    Bray Denard

    Full Text Available Doxorubicin has been shown to inhibit proliferation of cancer cells through proteolytic activation of CREB3L1 (cAMP response element binding protein 3-like 1, a transcription factor synthesized as a membrane-bound precursor. Upon doxorubicin treatment, CREB3L1 is cleaved so that the N-terminal domain of the protein can reach the nucleus where it activates transcription of genes that inhibit cell proliferation. These results suggest that the level of CREB3L1 in cancer cells may determine their sensitivity to doxorubicin.Mice transplanted with 6 lines of renal cell carcinoma (RCC were injected with doxorubicin to observe the effect of the chemotherapy on tumor growth. Immunohistochemistry and bioinformatics analyses were performed to compare CREB3L1 levels in types of cancer known to respond to doxorubicin versus those resistant to doxorubicin.Higher levels of CREB3L1 protein are correlated with increased doxorubicin sensitivity of xenograft RCC tumors (p = 0.017 by Pearson analysis. From patient tumor biopsies we analyzed, CREB3L1 was expressed in 19% of RCC, which is generally resistant to doxorubicin, but in 70% of diffuse large B-cell lymphoma that is sensitive to doxorubicin. Doxorubicin is used as the standard treatment for cancers that express the highest levels of CREB3L1 such as osteosarcoma and malignant fibrous histiocytoma but is not generally used to treat those that express the lowest levels of CREB3L1 such as RCC.Identification of CREB3L1 as the biomarker for doxorubicin sensitivity may markedly improve the doxorubicin response rate by applying doxorubicin only to patients with cancers expressing CREB3L1.

  18. Immune Biomarkers Predictive for Disease-Free Survival with Adjuvant Sunitinib in High-Risk Locoregional Renal Cell Carcinoma: From Randomized Phase III S-TRAC Study.

    Science.gov (United States)

    George, Daniel J; Martini, Jean-François; Staehler, Michael; Motzer, Robert J; Magheli, Ahmed; Escudier, Bernard; Gerletti, Paola; Li, Sherry; Casey, Michelle; Laguerre, Brigitte; Pandha, Hardev S; Pantuck, Allan J; Patel, Anup; Lechuga, Maria J; Ravaud, Alain

    2018-04-01

    Purpose: Adjuvant sunitinib therapy compared with placebo prolonged disease-free survival (DFS) in patients with locoregional high-risk renal cell carcinoma (RCC) in the S-TRAC trial (ClinicalTrials.gov number NCT00375674). A prospectively designed exploratory analysis of tissue biomarkers was conducted to identify predictors of treatment benefit. Experimental Design: Tissue blocks were used for immunohistochemistry (IHC) staining of programmed cell death ligand 1 (PD-L1), CD4, CD8, and CD68. DFS was compared between < versus ≥ median IHC parameter using the Kaplan-Meier method. For biomarkers with predictive potential, receiver operating characteristics curves were generated. Results: Baseline characteristics were similar in patients with ( n = 191) and without ( n = 419) IHC analysis. Among patients with IHC, longer DFS was observed in patients with tumor CD8 + T-cell density ≥ versus < median [median (95% CI), not reached (6.83-not reached) versus 3.47 years (1.73-not reached); hazard ratio (HR) 0.40 (95% CI, 0.20-0.81); P = 0.009] treated with sunitinib ( n = 101), but not with placebo ( n = 90). The sensitivity and specificity for CD8 + T-cell density in predicting DFS were 0.604 and 0.658, respectively. Shorter DFS was observed in placebo-treated patients with PD-L1 + versus PD-L1 - tumors (HR 1.75; P = 0.103). Among all patients with PD-L1 + tumors, DFS was numerically longer with sunitinib versus placebo (HR 0.58; P = 0.175). Conclusions: Greater CD8 + T-cell density in tumor tissue was associated with longer DFS with sunitinib but not placebo, suggesting predictive treatment effect utility. Further independent cohort validation studies are warranted. The prognostic value of PD-L1 expression in primary tumors from patients with high-risk nonmetastatic RCC should also be further explored. Clin Cancer Res; 24(7); 1554-61. ©2018 AACR . ©2018 American Association for Cancer Research.

  19. Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia.

    Science.gov (United States)

    Menéndez, R; Martínez, R; Reyes, S; Mensa, J; Filella, X; Marcos, M A; Martínez, A; Esquinas, C; Ramirez, P; Torres, A

    2009-07-01

    Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor alpha (TNFalpha) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, > or = 65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, > or = 65 years of age) scales. A total of 453 hospitalised CAP patients were included. The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

  20. New concepts and challenges in the clinical translation of cancer preventive therapies: the role of pharmacodynamic biomarkers.

    Science.gov (United States)

    Brown, Karen; Rufini, Alessandro

    2015-01-01

    Implementation of therapeutic cancer prevention strategies has enormous potential for reducing cancer incidence and related mortality. Trials of drugs including tamoxifen and aspirin have led the way in demonstrating proof-of-principle that prevention of breast and colorectal cancer is feasible. Many other compounds ranging from drugs in widespread use for various indications, including metformin, bisphosphonates, and vitamin D, to dietary agents such as the phytochemicals resveratrol and curcumin, show preventive activity against several cancers in preclinical models. Notwithstanding the wealth of opportunities, major challenges have hindered the development process and only a handful of therapies are currently approved for cancer risk reduction. One of the major obstacles to successful clinical translation of promising preventive agents is a lack of pharmacodynamic biomarkers to provide an early read out of biological activity in humans and for optimising doses to take into large scale randomised clinical trials. A further confounding factor is a lack of consideration of clinical pharmacokinetics in the design of preclinical experiments, meaning results are frequently reported from studies that use irrelevant or unachievable concentrations. This article focuses on recent findings from investigations with dietary-derived agents to illustrate how a thorough understanding of the mechanisms of action, using models that mimic the clinical scenario, together with the development of compound-specific accompanying pharmacodynamic biomarkers could accelerate the developmental pipeline for preventive agents and maximise the chances of success in future clinical trials. Moreover, the concept of a bell-shaped dose-response curve for therapeutic cancer prevention is discussed, along with the need to rethink the traditional 'more is better' approach for dose selection.

  1. LABORATORY BIOMARKERS FOR ANKYLOSING SPONDYLITIS

    Directory of Open Access Journals (Sweden)

    E. N. Aleksandrova

    2017-01-01

    Full Text Available Ankylosing spondylitis (AS is a chronic inflammatory disease from a group of spondyloarthritis (SpA, which is characterized by lesions of the sacroiliac joints and spine with the common involvement of entheses and peripheral joints in the pathological process. Advances in modern laboratory medicine have contributed to a substantial expansion of the range of pathogenetic, diagnostic, and prognostic biomarkers of AS. As of now, there are key pathogenetic biomarkers of AS (therapeutic targets, which include tumor necrosis factor-α (TNF-α, interleukin 17 (IL-17, and IL-23. Among the laboratory diagnostic and prognostic biomarkers, HLA-B27 and C-reactive protein are of the greatest value in clinical practice; the former for the early diagnosis of the disease and the latter for the assessment of disease activity, the risk of radiographic progression and the efficiency of therapy. Anti-CD74 antibodies are a new biomarker that has high sensitivity and specificity values in diagnosing axial SpA at an early stage. A number of laboratory biomarkers, including calprotectin, matrix metalloproteinase-3 (MMP-3, vascular endothelial growth factor, Dickkopf-1 (Dkk-1, and C-terminal telopeptide of type II collagen (CTX II do not well reflect disease activity, but may predict progressive structural changes in the spine and sacroiliac joints in AS. Blood calprotectin level monitoring allows the effective prediction of a response to therapy with TNF inhibitors and anti-IL-17А monoclonal antibodies. The prospects for the laboratory diagnosis of AS are associated with the clinical validation of candidate biomarkers during large-scale prospective cohort studies and with a search for new proteomic, transcriptomic and genomic markers, by using innovative molecular and cellular technologies.

  2. Proteomic biomarkers predicting lymph node involvement in serum of cervical cancer patients. Limitations of SELDI-TOF MS

    Directory of Open Access Journals (Sweden)

    Van Gorp Toon

    2012-06-01

    Full Text Available Abstract Background Lymph node status is not part of the staging system for cervical cancer, but provides important information for prognosis and treatment. We investigated whether lymph node status can be predicted with proteomic profiling. Material & methods Serum samples of 60 cervical cancer patients (FIGO I/II were obtained before primary treatment. Samples were run through a HPLC depletion column, eliminating the 14 most abundant proteins ubiquitously present in serum. Unbound fractions were concentrated with spin filters. Fractions were spotted onto CM10 and IMAC30 surfaces and analyzed with surface-enhanced laser desorption time of flight (SELDI-TOF mass spectrometry (MS. Unsupervised peak detection and peak clustering was performed using MASDA software. Leave-one-out (LOO validation for weighted Least Squares Support Vector Machines (LSSVM was used for prediction of lymph node involvement. Other outcomes were histological type, lymphvascular space involvement (LVSI and recurrent disease. Results LSSVM models were able to determine LN status with a LOO area under the receiver operating characteristics curve (AUC of 0.95, based on peaks with m/z values 2,698.9, 3,953.2, and 15,254.8. Furthermore, we were able to predict LVSI (AUC 0.81, to predict recurrence (AUC 0.92, and to differentiate between squamous carcinomas and adenocarcinomas (AUC 0.88, between squamous and adenosquamous carcinomas (AUC 0.85, and between adenocarcinomas and adenosquamous carcinomas (AUC 0.94. Conclusions Potential markers related with lymph node involvement were detected, and protein/peptide profiling support differentiation between various subtypes of cervical cancer. However, identification of the potential biomarkers was hampered by the technical limitations of SELDI-TOF MS.

  3. Application of cardiovascular disease risk prediction models and the relevance of novel biomarkers to risk stratification in Asian Indians.

    Science.gov (United States)

    Kanjilal, S; Rao, V S; Mukherjee, M; Natesha, B K; Renuka, K S; Sibi, K; Iyengar, S S; Kakkar, Vijay V

    2008-01-01

    The increasing pressure on health resources has led to the emergence of risk assessment as an essential tool in the management of cardiovascular disease (CVD). Concern exists regarding the validity of their generalization to all populations. Existing risk scoring models do not incorporate emerging 'novel' risk factors. In this context, the aim of the study was to examine the relevance of British, European, and Framingham predictive CVD risk scores to the asymptomatic high risk Indian population. Blood samples drawn from the participants were analyzed for various 'traditional' and 'novel' biomarkers, and their CVD risk factor profiling was also done. The Framingham model defined only 5% of the study cohort to be at high risk, which appears to be an underestimation of CVD risk in this genetically predisposed population. These subjects at high risk had significantly elevated levels of lipid, pro-inflammatory, pro-thrombotic, and serological markers. It is more relevant to develop risk predictive scores for application to the Indian population. This study substantiates the argument that alternative approaches to risk stratification are required in order to make them more adaptable and applicable to different populations with varying risk factor and disease patterns.

  4. Predicting prostate biopsy outcome: prostate health index (phi) and prostate cancer antigen 3 (PCA3) are useful biomarkers.

    Science.gov (United States)

    Ferro, Matteo; Bruzzese, Dario; Perdonà, Sisto; Mazzarella, Claudia; Marino, Ada; Sorrentino, Alessandra; Di Carlo, Angelina; Autorino, Riccardo; Di Lorenzo, Giuseppe; Buonerba, Carlo; Altieri, Vincenzo; Mariano, Angela; Macchia, Vincenzo; Terracciano, Daniela

    2012-08-16

    Indication for prostate biopsy is presently mainly based on prostate-specific antigen (PSA) serum levels and digital-rectal examination (DRE). In view of the unsatisfactory accuracy of these two diagnostic exams, research has focused on novel markers to improve pre-biopsy prostate cancer detection, such as phi and PCA3. The purpose of this prospective study was to assess the diagnostic accuracy of phi and PCA3 for prostate cancer using biopsy as gold standard. Phi index (Beckman coulter immunoassay), PCA3 score (Progensa PCA3 assay) and other established biomarkers (tPSA, fPSA and %fPSA) were assessed before a 18-core prostate biopsy in a group of 251 subjects at their first biopsy. Values of %p2PSA and phi were significantly higher in patients with PCa compared with PCa-negative group (pphi and PCA3 are predictive of malignancy. In conclusion, %p2PSA, phi and PCA3 may predict a diagnosis of PCa in men undergoing their first prostate biopsy. PCA3 score is more useful in discriminating between HGPIN and non-cancer. Copyright © 2012 Elsevier B.V. All rights reserved.

  5. Are traditional cognitive tests useful in predicting clinical success?

    Science.gov (United States)

    Gray, Sarah A; Deem, Lisa P; Straja, Sorin R

    2002-11-01

    The purpose of this research was to determine the predictive value of the Dental Admission Test (DAT) for clinical success using Ackerman's theory of ability determinants of skilled performance. The Ackerman theory is a valid, reliable schema in the applied psychology literature used to predict complex skill acquisition. Inconsistent stimulus-response skill acquisition depends primarily on determinants of cognitive ability. Consistent information-processing tasks have been described as "automatic," in which stimuli and responses are mapped in a manner that allows for complete certainty once the relationships have been learned. It is theorized that the skills necessary for success in the clinical component of dental schools involve a significant amount of automatic processing demands and, as such, student performance in the clinics should begin to converge as task practice is realized and tasks become more consistent. Subtest scores of the DAT of four classes were correlated with final grades in nine clinical courses. Results showed that the DAT subtest scores played virtually no role with regard to the final clinical grades. Based on this information, the DAT scores were determined to be of no predictive value in clinical achievement.

  6. Inflammation biomarkers and mortality prediction in patients with type 2 diabetes (ZODIAC-27)

    NARCIS (Netherlands)

    Landman, Gijs W. D.; Kleefstra, Nanne; Groenier, Klaas H.; Bakker, Stephan J. L.; Groeneveld, Geert H.; Bilo, Henk J. G.; van Hateren, Kornelis J. J.

    Background: C-reactive protein (CRP), procalcitonin (PCT) and pro-adrenomedullin (MR-proADM) are inflammation markers associated with long-term mortality risk. We compared the associations and predictive capacities of CRP, PCT and MR-proADM with cardiovascular and all-cause mortality in patients

  7. Enlarged pulmonary artery is predicted by vascular injury biomarkers and is associated with WTC-Lung Injury in exposed fire fighters: a case–control study

    Science.gov (United States)

    Schenck, Edward J; Echevarria, Ghislaine C; Girvin, Francis G; Kwon, Sophia; Comfort, Ashley L; Rom, William N; Prezant, David J; Weiden, Michael D; Nolan, Anna

    2014-01-01

    Objectives We hypothesise that there is an association between an elevated pulmonary artery/aorta (PA/A) and World Trade Center-Lung Injury (WTC-LI). We assessed if serum vascular disease biomarkers were predictive of an elevated PA/A. Design Retrospective case-cohort analysis of thoracic CT scans of WTC-exposed firefighters who were symptomatic between 9/12/2001 and 3/10/2008. Quantification of vascular-associated biomarkers from serum collected within 200 days of exposure. Setting Urban tertiary care centre and occupational healthcare centre. Participants Male never-smoking firefighters with accurate pre-9/11 forced expiratory volume in 1 s (FEV1) ≥75%, serum sampled ≤200 days of exposure was the baseline cohort (n=801). A subcohort (n=97) with available CT scans and serum biomarkers was identified. WTC-LI was defined as FEV1≤77% at the subspecialty pulmonary evaluation (n=34) and compared with controls (n=63) to determine the associated PA/A ratio. The subcohort was restratified based on PA/A≥0.92 (n=38) and PA/A<0.92(n=59) to determine serum vascular biomarkers that were predictive of this vasculopathy. Outcome measures The primary outcome of this study was to identify a PA/A ratio in a cohort of individuals exposed to WTC dust that was associated with WTC-LI. The secondary outcome was to identify serum biomarkers predictive of the PA/A ratio using logistic regression. Results PA/A≥0.92 was associated with WTC-LI, OR of 4.02 (95% CI 1.21 to 13.41; p=0.023) when adjusted for exposure, body mass index and age at CT. Elevated macrophage derived chemokine and soluble endothelial selectin were predictive of PA/A≥0.92, (OR, 95% CI 2.08, 1.05 to 4.11, p=0.036; 1.33, 1.06 to 1.68, p=0.016, respectively), while the increased total plasminogen activator inhibitor 1 was predictive of not having PA/A≥0.92 (OR 0.88, 0.79 to 0.98; p=0.024). Conclusions Elevated PA/A was associated with WTC-LI. Development of an elevated PA/A was predicted by biomarkers of

  8. Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

    Science.gov (United States)

    El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

    2015-04-01

    This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

  9. DW-MRI as a Predictive Biomarker of Radiosensitization of GBM through Targeted Inhibition of Checkpoint Kinases.

    Science.gov (United States)

    Williams, Terence M; Galbán, Stefanie; Li, Fei; Heist, Kevin A; Galbán, Craig J; Lawrence, Theodore S; Holland, Eric C; Thomae, Tami L; Chenevert, Thomas L; Rehemtulla, Alnawaz; Ross, Brian D

    2013-04-01

    The inherent treatment resistance of glioblastoma (GBM) can involve multiple mechanisms including checkpoint kinase (Chk1/2)-mediated increased DNA repair capability, which can attenuate the effects of genotoxic chemotherapies and radiation. The goal of this study was to evaluate diffusion-weighted magnetic resonance imaging (DW-MRI) as a biomarker for Chk1/2 inhibitors in combination with radiation for enhancement of treatment efficacy in GBM. We evaluated a specific small molecule inhibitor of Chk1/2, AZD7762, in combination with radiation using in vitro human cell lines and in vivo using a genetically engineered GBM mouse model. DW-MRI and T1-contrast MRI were used to follow treatment effects on intracranial tumor cellularity and growth rates, respectively. AZD7762 inhibited clonal proliferation in a panel of GBM cell lines and increased radiosensitivity in p53-mutated GBM cell lines to a greater extent compared to p53 wild-type cells. In vivo efficacy of AZD7762 demonstrated a dose-dependent inhibitory effect on GBM tumor growth rate and a reduction in tumor cellularity based on DW-MRI scans along with enhancement of radiation efficacy. DW-MRI was found to be a useful imaging biomarker for the detection of radiosensitization through inhibition of checkpoint kinases. Chk1/2 inhibition resulted in antiproliferative activity, prevention of DNA damage-induced repair, and radiosensitization in preclinical GBM tumor models, both in vitro and in vivo. The effects were found to be maximal in p53-mutated GBM cells. These results provide the rationale for integration of DW-MRI in clinical translation of Chk1/2 inhibition with radiation for the treatment of GBM.

  10. Clinical implications of six inflammatory biomarkers as prognostic indicators in Ewing sarcoma

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    Li YJ

    2017-09-01

    Full Text Available Yong-Jiang Li, Xi Yang, Wen-Biao Zhang, Cheng Yi, Feng Wang, Ping Li Department of Oncology, West China Hospital, Sichuan University, Chengdu, People’s Republic of China Abstract: Cancer-related systemic inflammation responses have been correlated with cancer development and progression. The prognostic significance of several inflammatory indicators, including neutrophil–lymphocyte ratio (NLR, platelet–lymphocyte ratio (PLR, Glasgow Prognostic Score (GPS, C-reactive protein to albumin ratio (CRP/Alb ratio, lymphocyte–monocyte ratio (LMR, and neutrophil–platelet score (NPS, were found to be correlated with prognosis in several cancers. However, the prognostic role of these inflammatory biomarkers in Ewing sarcoma has not been evaluated. This study enrolled 122 Ewing patients. Receiver operating characteristic (ROC analysis was generated to determine optimal cutoff values; areas under the curves (AUCs were assessed to show the discriminatory ability of the biomarkers; Kaplan–Meier analysis was conducted to plot the survival curves; and Cox multivariate survival analysis was performed to identify independent prognostic factors. The optimal cutoff values of CRP/Alb ratio, NLR, PLR, and LMR were 0.225, 2.38, 131, and 4.41, respectively. CRP/Alb ratio had a significantly larger AUC than NLR, PLR, LMR, and NPS. Higher levels of CRP/Alb ratio (hazard ratio [HR] 2.41, P=0.005, GPS (HR 2.27, P=0.006, NLR (HR 2.07, P=0.013, and PLR (HR 1.85, P=0.032 were significantly correlated with poor prognosis. As the biomarkers had internal correlations, only the CRP/Alb ratio was involved in the multivariate Cox analysis and remained an independent prognostic indicator. The study demonstrated that CRP/Alb ratio, GPS, and NLR were effective prognostic indicators for patients with Ewing sarcoma, and the CRP/Alb ratio was the most robust prognostic indicator with a discriminatory ability superior to that of the other indicators; however, PLR, LMR, and

  11. Prediction of the filter no-reflow phenomenon in patients with angina pectoris by using multimodality: Magnetic resonance imaging, optical coherence tomography, and serum biomarkers.

    Science.gov (United States)

    Matsumoto, Kenji; Ehara, Shoichi; Hasegawa, Takao; Otsuka, Kenichiro; Yoshikawa, Junichi; Shimada, Kenei

    2016-05-01

    Although the occurrence of no-reflow during percutaneous coronary intervention (PCI) has been shown to be associated with worse short- and long-term clinical outcomes, the clinical relevance of preventing flow deterioration by using the filter-based distal protection devices (DPDs) is controversial. We investigated predictors of the filter no-reflow (FNR) phenomenon during PCI by using multimodality, such as hyperintense plaques (HIPs) in the coronary artery on T1-weighted imaging (T1WI) non-contrast magnetic resonance, plaque composition by using optical coherence tomography (OCT), and serum biomarkers, in patients with angina pectoris. Fifty lesions from 50 patients with angina were examined. All patients underwent T1WI within 24 h before invasive coronary angiography was performed, and preinterventional OCT was performed on a native atherosclerotic culprit lesion. The signal intensity of coronary plaque to cardiac muscle ratio (PMR) was calculated on a standard console of the magnetic resonance system. Of the 50 lesions, 20 lesions showed FNR during PCI, while non-FNR was observed in 30 lesions. A cut-off value >1.85 of PMR had a sensitivity of 65%, a specificity of 93%, a positive predictive value of 87%, and a negative predictive value of 80% for identifying lesions with FNR. Multivariate analysis revealed that the presence of HIPs with PMR >1.85 (p=0.008) was the only independent predictor of the FNR phenomenon during PCI. This study shows that the presence of HIPs with PMR >1.85 on T1WI was a novel independent predictor of the FNR phenomenon during PCI in angina patients. This result may help in identifying high-risk lesions for no-reflow to deploy filter-based DPDs. Copyright © 2015 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

  12. Imbalanced target prediction with pattern discovery on clinical data repositories.

    Science.gov (United States)

    Chan, Tak-Ming; Li, Yuxi; Chiau, Choo-Chiap; Zhu, Jane; Jiang, Jie; Huo, Yong

    2017-04-20

    Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice. We propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed. We compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

  13. Predictive Biomarkers in Colorectal Cancer: From the Single Therapeutic Target to a Plethora of Options

    Directory of Open Access Journals (Sweden)

    Daniela Rodrigues

    2016-01-01

    Full Text Available Colorectal cancer (CRC is one of the most frequent cancers and is a leading cause of cancer death worldwide. Treatments used for CRC may include some combination of surgery, radiation therapy, chemotherapy, and targeted therapy. The current standard drugs used in chemotherapy are 5-fluorouracil and leucovorin in combination with irinotecan and/or oxaliplatin. Most recently, biologic agents have been proven to have therapeutic benefits in metastatic CRC alone or in association with standard chemotherapy. However, patients present different treatment responses, in terms of efficacy and toxicity; therefore, it is important to identify biological markers that can predict the response to therapy and help select patients that would benefit from specific regimens. In this paper, authors review CRC genetic markers that could be useful in predicting the sensitivity/resistance to chemotherapy.

  14. Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies

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    Fedele Vita

    2006-06-01

    Full Text Available Abstract Background Recent studies indicate that microRNAs (miRNAs are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Results Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81; and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ER-positive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03; as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2-positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index. Conclusion In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast

  15. A urinary peptide biomarker set predicts worsening of albuminuria in type 2 diabetes mellitus

    NARCIS (Netherlands)

    Roscioni, S. S.; de Zeeuw, D.; Hellemons, M. E.; Mischak, H.; Zuerbig, P.; Bakker, S. J. L.; Gansevoort, R. T.; Reinhard, H.; Persson, F.; Lajer, M.; Rossing, P.; Lambers Heerspink, H. J.

    Microalbuminuria is considered the first clinical sign of kidney dysfunction and is associated with a poor renal and cardiovascular prognosis in type 2 diabetes. Detection of patients who are prone to develop micro- or macroalbuminuria may represent an effective strategy to start or optimise

  16. The Wide and Complex Field of NAFLD Biomarker Research: Trends.

    Science.gov (United States)

    Wichro, Erika; Macheiner, Tanja; Schmid, Jasmin; Kavsek, Barbara; Sargsyan, Karine

    2014-01-01

    Background. Nonalcoholic fatty liver disease is now acknowledged as a complex public health issue linked to sedentary lifestyle, obesity, and related disorders like type 2 diabetes and metabolic syndrome. Aims. We aimed to retrieve its trends out of the huge amount of published data. Therefore, we conducted an extensive literature search to identify possible biomarker and/or biomarker combinations by retrospectively assessing and evaluating common and novel biomarkers to predict progression and prognosis of obesity related liver diseases. Methodology. We analyzed finally 62 articles accounting for 157 cohorts and 45,288 subjects. Results. Despite the various approaches, most cohorts were considerably small and rarely comparable. Also, we found that the same standard parameters were measured rather than novel biomarkers. Diagnostics approaches appeared incomparable. Conclusions. Further collaborative investigations on harmonizing ways of data acquisition and identifying such biomarkers for clinical use are necessary to yield sufficient significant results of potential biomarkers.

  17. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs: a report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U

    1998-01-01

    cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each...... as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed...... country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers...

  18. Fluorescence-based Western blotting for quantitation of protein biomarkers in clinical samples.

    Science.gov (United States)

    Zellner, Maria; Babeluk, Rita; Diestinger, Michael; Pirchegger, Petra; Skeledzic, Senada; Oehler, Rudolf

    2008-09-01

    Since most high throughput techniques used in biomarker discovery are very time and cost intensive, highly specific and quantitative analytical alternative application methods are needed for the routine analysis. Conventional Western blotting allows detection of specific proteins to the level of single isotypes while its quantitative accuracy is rather limited. We report a novel and improved quantitative Western blotting method. The use of fluorescently labelled secondary antibodies strongly extends the dynamic range of the quantitation and improves the correlation with the protein amount (r=0.997). By an additional fluorescent staining of all proteins immediately after their transfer to the blot membrane, it is possible to visualise simultaneously the antibody binding and the total protein profile. This allows for an accurate correction for protein load. Applying this normalisation it could be demonstrated that fluorescence-based Western blotting is able to reproduce a quantitative analysis of two specific proteins in blood platelet samples from 44 subjects with different diseases as initially conducted by 2D-DIGE. These results show that the proposed fluorescence-based Western blotting is an adequate application technique for biomarker quantitation and suggest possibilities of employment that go far beyond.

  19. High-Sensitivity Troponin: A Clinical Blood Biomarker for Staging Cardiomyopathy in Fabry Disease.

    Science.gov (United States)

    Seydelmann, Nora; Liu, Dan; Krämer, Johannes; Drechsler, Christiane; Hu, Kai; Nordbeck, Peter; Schneider, Andreas; Störk, Stefan; Bijnens, Bart; Ertl, Georg; Wanner, Christoph; Weidemann, Frank

    2016-05-31

    High-sensitivity troponin (hs-TNT), a biomarker of myocardial damage, might be useful for assessing fibrosis in Fabry cardiomyopathy. We performed a prospective analysis of hs-TNT as a biomarker for myocardial changes in Fabry patients and a retrospective longitudinal follow-up study to assess longitudinal hs-TNT changes relative to fibrosis and cardiomyopathy progression. For the prospective analysis, hs-TNT from 75 consecutive patients with genetically confirmed Fabry disease was analyzed relative to typical Fabry-associated echocardiographic findings and total myocardial fibrosis as measured by late gadolinium enhancement (LE) on magnetic resonance imaging. Longitudinal data (3.9±2.0 years), including hs-TNT, LE, and echocardiographic findings from 58 Fabry patients, were retrospectively collected. Hs-TNT level positively correlated with LE (linear correlation coefficient, 0.72; odds ratio, 32.81 [95% CI, 3.56-302.59]; P=0.002); patients with elevated baseline hs-TNT (>14 ng/L) showed significantly increased LE (median: baseline, 1.9 [1.1-3.3] %; follow-up, 3.2 [2.3-4.9] %; PFabry disease and a qualified predictor of cardiomyopathy progression. Thus, hs-TNT could be helpful for staging and follow-up of Fabry patients. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

  20. Utility of combinations of biomarkers, cognitive markers, and risk factors to predict conversion from mild cognitive impairment to Alzheimer disease in patients in the Alzheimer's disease neuroimaging initiative.

    Science.gov (United States)

    Gomar, Jesus J; Bobes-Bascaran, Maria T; Conejero-Goldberg, Concepcion; Davies, Peter; Goldberg, Terry E

    2011-09-01

    Biomarkers have become increasingly important in understanding neurodegenerative processes associated with Alzheimer disease. Markers include regional brain volumes, cerebrospinal fluid measures of pathological Aβ1-42 and total tau, cognitive measures, and individual risk factors. To determine the discriminative utility of different classes of biomarkers and cognitive markers by examining their ability to predict a change in diagnostic status from mild cognitive impairment to Alzheimer disease. Longitudinal study. We analyzed the Alzheimer's Disease Neuroimaging Initiative database to study patients with mild cognitive impairment who converted to Alzheimer disease (n = 116) and those who did not convert (n = 204) within a 2-year period. We determined the predictive utility of 25 variables from all classes of markers, biomarkers, and risk factors in a series of logistic regression models and effect size analyses. The Alzheimer's Disease Neuroimaging Initiative public database. Primary outcome measures were odds ratios, pseudo- R(2)s, and effect sizes. In comprehensive stepwise logistic regression models that thus included variables from all classes of markers, the following baseline variables predicted conversion within a 2-year period: 2 measures of delayed verbal memory and middle temporal lobe cortical thickness. In an effect size analysis that examined rates of decline, change scores for biomarkers were modest for 2 years, but a change in an everyday functional activities measure (Functional Assessment Questionnaire) was considerably larger. Decline in scores on the Functional Assessment Questionnaire and Trail Making Test, part B, accounted for approximately 50% of the predictive variance in conversion from mild cognitive impairment to Alzheimer disease. Cognitive markers at baseline were more robust predictors of conversion than most biomarkers. Longitudinal analyses suggested that conversion appeared to be driven less by changes in the neurobiologic

  1. Connecting clinical and actuarial prediction with rule-based methods.

    Science.gov (United States)

    Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

    2015-06-01

    Meta-analyses comparing the accuracy of clinical versus actuarial prediction have shown actuarial methods to outperform clinical methods, on average. However, actuarial methods are still not widely used in clinical practice, and there has been a call for the development of actuarial prediction methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

  2. Interleukin-6 and procalcitonin as biomarkers in mortality prediction of hospitalized patients with community acquired pneumonia

    Directory of Open Access Journals (Sweden)

    Ilija Andrijevic

    2014-01-01

    Full Text Available Introduction: Community acquired pneumonia (CAP may present as life-threatening infection with uncertain progression and outcome of treatment. Primary aim of the trial was determination of the cut-off value of serum interleukin-6 (IL-6 and procalcitonin (PCT above which, 30-day mortality in hospitalized patients with CAP, could be predicted with high sensitivity and specificity. We investigated correlation between serum levels of IL-6 and PCT at admission and available scoring systems of CAP (pneumonia severity index-PSI, modified early warning score-MEWS and (Confusion, Urea nitrogen, respiratory rate, Blood pressure, ≥65 years of age-CURB65. Methods: This was prospective, non-randomized trial which included 101 patients with diagnosed CAP. PSI, MEWS and CURB65 were assessed on first day of hospitalization. IL-6 and PCT were also sampled on the first day of hospitalization. Results: Based on ROC curve analysis (AUC ± SE = 0.934 ± 0.035; 95%CI(0.864-1.0; P = 0.000 hospitalized CAP patients with elevated IL-6 level have 93.4% higher risk level for lethal outcome. Cut-off value of 20.2 pg/ml IL-6 shows sensitivity of 84% and specificity of 87% in mortality prediction. ROC curve analysis confirmed significant role of procalcitonin as a mortality predictor in CAP patients (AUC ± SE = 0.667 ± 0.062; 95%CI(0.546-0.789; P = 0.012. Patients with elevated PCT level have 66.7% higher risk level for lethal outcome. As a predictor of mortality at the cut-off value of 2.56 ng/ml PCT shows sensitivity of 76% and specificity of 61.8%. Conclusions: Both IL-6 and PCI are significant for prediction of 30-day mortality in hospitalized patients with CAP. Serum levels of IL6 correlate with major CAP scoring systems.

  3. Biomarkers in Vasculitis

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    Monach, Paul A.

    2014-01-01

    Purpose of review Better biomarkers are needed for guiding management of patients with vasculitis. Large cohorts and technological advances had led to an increase in pre-clinical studies of potential biomarkers. Recent findings The most interesting markers described recently include a gene expression signature in CD8+ T cells that predicts tendency to relapse or remain relapse-free in ANCA-associated vasculitis, and a pair of urinary proteins that are elevated in Kawasaki disease but not other febrile illnesses. Both of these studies used “omics” technologies to generate and then test hypotheses. More conventional hypothesis-based studies have indicated that the following circulating proteins have potential to improve upon clinically available tests: pentraxin-3 in giant cell arteritis and Takayasu’s arteritis; von Willebrand factor antigen in childhood central nervous system vasculitis; eotaxin-3 and other markers related to eosinophils or Th2 immune responses in eosinophilic granulomatosis with polyangiitis (Churg-Strauss syndrome); and MMP-3, TIMP-1, and CXCL13 in ANCA-associated vasculitis. Summary New markers testable in blood and urine have the potential to assist with diagnosis, staging, assessment of current disease activity, and prognosis. However, the standards for clinical usefulness, in particular the demonstration of either very high sensitivity or very high specificity, have yet to be met for clinically relevant outcomes. PMID:24257367

  4. Biomarkers in acute heart failure.

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    Mallick, Aditi; Januzzi, James L

    2015-06-01

    The care of patients with acutely decompensated heart failure is being reshaped by the availability and understanding of several novel and emerging heart failure biomarkers. The gold standard biomarkers in heart failure are B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide, which play an important role in the diagnosis, prognosis, and management of acute decompensated heart failure. Novel biomarkers that are increasingly involved in the processes of myocardial injury, neurohormonal activation, and ventricular remodeling are showing promise in improving diagnosis and prognosis among patients with acute decompensated heart failure. These include midregional proatrial natriuretic peptide, soluble ST2, galectin-3, highly-sensitive troponin, and midregional proadrenomedullin. There has also been an emergence of biomarkers for evaluation of acute decompensated heart failure that assist in the differential diagnosis of dyspnea, such as procalcitonin (for identification of acute pneumonia), as well as markers that predict complications of acute decompensated heart failure, such as renal injury markers. In this article, we will review the pathophysiology and usefulness of established and emerging biomarkers for the clinical diagnosis, prognosis, and management of acute decompensated heart failure. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

  5. A Culture-Brain Link: Negative Age Stereotypes Predict Alzheimer’s-disease Biomarkers

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    Levy, Becca R.; Ferrucci, Luigi; Zonderman, Alan B.; Slade, Martin D.; Troncoso, Juan; Resnick, Susan M.

    2016-01-01

    Although negative age stereotypes have been found to predict adverse outcomes among older individuals, it was unknown whether the influence of stereotypes extends to brain changes associated with Alzheimer’s disease. To consider this possibility, we drew on the age stereotypes of dementia-free participants in the Baltimore Longitudinal Study of Aging that had been measured decades before yearly MRIs and brain autopsies were performed. Those with more negative age stereotypes earlier in life had significantly steeper hippocampal-volume loss, and significantly greater accumulation of neurofibrillary tangles and amyloid plaques at autopsy, adjusting for relevant covariates. These findings suggest a new pathway to identifying mechanisms and potential interventions related to the neuropathology of Alzheimer’s disease. PMID:26641877

  6. A culture-brain link: Negative age stereotypes predict Alzheimer's disease biomarkers.

    Science.gov (United States)

    Levy, Becca R; Ferrucci, Luigi; Zonderman, Alan B; Slade, Martin D; Troncoso, Juan; Resnick, Susan M

    2016-02-01

    Although negative age stereotypes have been found to predict adverse outcomes among older individuals, it was unknown whether the influence of stereotypes extends to brain changes associated with Alzheimer's disease. To consider this possibility, we drew on dementia-free participants, in the Baltimore Longitudinal Study of Aging, whose age stereotypes were assessed decades before yearly magnetic resonance images and brain autopsies were performed. Those holding more-negative age stereotypes earlier in life had significantly steeper hippocampal-volume loss and significantly greater accumulation of neurofibrillary tangles and amyloid plaques, adjusting for relevant covariates. These findings suggest a new pathway to identifying mechanisms and potential interventions related to the pathology of Alzheimer's disease. (c) 2016 APA, all rights reserved).

  7. Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics.

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    Collins, Dearbhaile C; Sundar, Raghav; Lim, Joline S J; Yap, Timothy A

    2017-01-01

    Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Sweat chloride as a biomarker of CFTR activity: proof of concept and ivacaftor clinical trial data.

    Science.gov (United States)

    Accurso, Frank J; Van Goor, Fredrick; Zha, Jiuhong; Stone, Anne J; Dong, Qunming; Ordonez, Claudia L; Rowe, Steven M; Clancy, John Paul; Konstan, Michael W; Hoch, Heather E; Heltshe, Sonya L; Ramsey, Bonnie W; Campbell, Preston W; Ashlock, Melissa A

    2014-03-01

    We examined data from a Phase 2 trial {NCT00457821} of ivacaftor, a CFTR potentiator, in cystic fibrosis (CF) patients with aG551D mutation to evaluate standardized approaches to sweat chloride measurement and to explore the use of sweat chloride and nasal potential difference (NPD) to estimate CFTR activity. Sweat chloride and NPD were secondary endpoints in this placebo-controlled, multicenter trial. Standardization of sweat collection, processing,and analysis was employed for the first time. Sweat chloride and chloride ion transport (NPD) were integrated into a model of CFTR activity. Within-patient sweat chloride determinations showed sufficient precision to detect differences between dose-groups and assess ivacaftor treatment effects. Analysis of changes in sweat chloride and NPD demonstrated that patients treated with ivacaftor achieved CFTR activity equivalent to approximately 35%–40% of normal. Sweat chloride is useful in multicenter trials as a biomarker of CFTR activity and to test the effect of CFTR potentiators.

  9. Clinical gestalt and the prediction of massive transfusion after trauma.

    Science.gov (United States)

    Pommerening, Matthew J; Goodman, Michael D; Holcomb, John B; Wade, Charles E; Fox, Erin E; Del Junco, Deborah J; Brasel, Karen J; Bulger, Eileen M; Cohen, Mitch J; Alarcon, Louis H; Schreiber, Martin A; Myers, John G; Phelan, Herb A; Muskat, Peter; Rahbar, Mohammad; Cotton, Bryan A

    2015-05-01

    Early recognition and treatment of trauma patients requiring massive transfusion (MT) has been shown to reduce mortality. While many risk factors predicting MT have been demonstrated, there is no universally accepted method or algorithm to identify these patients. We hypothesised that even among experienced trauma surgeons, the clinical gestalt of identifying patients who will require MT is unreliable. Transfusion and mortality outcomes after trauma were observed at 10 U.S. Level-1 trauma centres in patients who survived ≥ 30 min after admission and received ≥ 1 unit of RBC within 6h of arrival. Subjects who received ≥ 10 units within 24h of admission were classified as MT patients. Trauma surgeons were asked the clinical gestalt question "Is the patient likely to be massively transfused?" 10 min after the patients arrival. The performance of clinical gestalt to predict MT was assessed using chi-square tests and ROC analysis to compare gestalt to previously described scoring systems. Of the 1245 patients enrolled, 966 met inclusion criteria and 221 (23%) patients received MT. 415 (43%) were predicted to have a MT and 551(57%) were predicted to not have MT. Patients predicted to have MT were younger, more often sustained penetrating trauma, had higher ISS scores, higher heart rates, and lower systolic blood pressures (all pGestalt sensitivity was 65.6% and specificity was 63.8%. PPV and NPV were 34.9% and 86.2% respectively. Data from this large multicenter trial demonstrates that predicting the need for MT continues to be a challenge. Because of the increased mortality associated with delayed therapy, a more reliable algorithm is needed to identify and treat these severely injured patients earlier. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

    Directory of Open Access Journals (Sweden)

    Elena Nikolayevna Aleksandrova

    2014-03-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost of therapy using these drugs in future.

  11. Role of laboratory biomarkers in monitoring and prediction of the effectiveness of treatment of rheumatic diseases using genetically engineered drugs

    Directory of Open Access Journals (Sweden)

    Elena Nikolayevna Aleksandrova

    2014-01-01

    Full Text Available Significant progress in treating immunoinflammatory rheumatic diseases (RD is related to the design of a novel family of drugs, genetically engineered (GE drugs. Molecular and cellular biomarkers (antibodies, indicators of acute inflammation, cytokines, chemokines, growth factors, endothelial activation markers, immunoglobulins, cryoglobulins, T- and B-cell subpopulations, products of bone and cartilage metabolism, genetic and metabolic markers that allow one to conduct immunological monitoring and prediction of the effectiveness of RD therapy using tumor necrosis factor α inhibitors (infliximab, adalimumab, golimumab, etanercept, anti-B-cell drugs (rituximab, belimumab, interleukin-6 receptor antagonist (tocilizumab, and T-cell costimulation blocker (abatacept have been detected in blood, synovial fluid, urine, and bioptates of the affected tissues. In addition to the conventional uniplex immunodiagnostics techniques, multiplex analysis of marker, which is based on genetic, transcriptomic and proteomic technologies using DNA and protein microarrays, polymerase chain reaction, and flow cytometry, is becoming increasingly widespread. The search for and validation of immunological predictors of the effective response to GE drug therapy make it possible to optimize and reduce the cost