WorldWideScience

Sample records for cancer biomarker discovery

  1. Biological Networks for Cancer Candidate Biomarkers Discovery

    Science.gov (United States)

    Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

    2016-01-01

    Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field.

  2. Biological Networks for Cancer Candidate Biomarkers Discovery.

    Science.gov (United States)

    Yan, Wenying; Xue, Wenjin; Chen, Jiajia; Hu, Guang

    2016-01-01

    Due to its extraordinary heterogeneity and complexity, cancer is often proposed as a model case of a systems biology disease or network disease. There is a critical need of effective biomarkers for cancer diagnosis and/or outcome prediction from system level analyses. Methods based on integrating omics data into networks have the potential to revolutionize the identification of cancer biomarkers. Deciphering the biological networks underlying cancer is undoubtedly important for understanding the molecular mechanisms of the disease and identifying effective biomarkers. In this review, the networks constructed for cancer biomarker discovery based on different omics level data are described and illustrated from recent advances in the field. PMID:27625573

  3. The proteomics in prostate cancer biomarker discovery

    Directory of Open Access Journals (Sweden)

    V. E. Shevchenko

    2015-06-01

    Full Text Available Prostate cancer (PC represents the second most frequent type of tumor in men worldwide. Proteomics represents a promising approach for the discovery of new biomarkers able to improve the management of PC patients. Markers more specific and sensitive than prostate-specific antigen are needed for PC diagnosis, prognosis and response to treatment. Moreover, proteomics could represent an important tool to identify new molecular targets for PC tailored therapy. Now several possible PC biomarkers sources, each with advantages and limitations, are under investigation, including tissues, urine, serum, plasma and prostatic fluids. Innovative high-throughput proteomic platforms are now identifying and quantifying new specific and sensitive biomarkers for PC detection, stratification and treatment. Nevertheless, many putative biomarkers are still far from being applied in clinical practice.This review aims to discuss the recent advances in PC proteomics, emphasizing biomarker discovery and their application to clinical utility for diagnosis and patient stratification.

  4. Using Aptamers for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Yun Min Chang

    2013-01-01

    Full Text Available Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment SELEX and cell-based SELEX (cell-SELEX. Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics.

  5. Cancer Biomarker Discovery: Lectin-Based Strategies Targeting Glycoproteins

    Directory of Open Access Journals (Sweden)

    David Clark

    2012-01-01

    Full Text Available Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state.

  6. Cancer biomarker discovery in saliva by mass spectrometry

    Directory of Open Access Journals (Sweden)

    Kiran S. Ambatipudi

    2014-05-01

    Full Text Available The quest for biomarkers has been much pursued to aid in the early diagnosis, monitor post-treatment progress and development of targeted therapies. Nevertheless, the translation of biomarker discovery to clinical use has been limited due to multiple reasons such as the long path from discovery to clinical assays, limitation of samples and incoherent pipeline for biomarker development. To date, diagnosis of cancer has been based on biopsies and histological examinations and often becomes difficult to get repeated sampling from patients for confirmation. Consequently, it is important for clinical researchers to look at multiple body fluids and different molecular techniques to identify biomarkers. One such bodyfluid is saliva, which is easily and non-invasively collected and contains thousands of potential protein biomarkers. Moreover, recent advances in the sensitivity and specificity of mass spectrometry based proteomics hold great promise to identify potential biomarkers. This review presents an overview of the potential use of saliva and mass spectrometry for global discovery and validation of biomarkers.

  7. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    Directory of Open Access Journals (Sweden)

    Shin Nishiumi

    2014-07-01

    Full Text Available The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis.

  8. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...... levels show random distribution in a given cohort. However, gene expression levels may also be affected by technical bias when the actual measurement technology or sample handling may introduce a systematic error. If the distribution of systematic errors correlates with the biological phenotype then the...

  9. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Ming Lu

    2007-01-01

    Full Text Available Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.Abbreviations: 2DE: two-dimensional gel electrophoresis; ABPP: activity-based protein profiling; CEA: carcinoembryonic antigen; CI: confidence interval; ESI: electrospray ionization; FP: fluorophosphonate; HPLC: high performance liquid chromatography; ICAT: isotope coded affi nitytags; IEF: isoelectric focusing; iTRAQ: isobaric tags for relative and absolute quantification; LCMS: combined liquid chromatography-mass spectrometry; LCMSMS: liquid chromatography tandem mass spectrometry; LOD: limit of detection; m/z: mass to charge ratio; MALDI: matrix-assisted laser desorption ionization; MS: mass spectrometry; MUDPIT: multidimensional protein identification technology; NAF: nipple aspirate fluid; PMF: peptide mass fingerprinting; PSA: prostate specifi c antigen; PTMs: post-translational modifications; RPMA: reverse phase protein microarray; SELDI: surface enhanced laser desorption ionization; TOF: time-of-flight.

  10. Predictive biomarkers for personalised anti-cancer drug use: discovery to clinical implementation.

    Science.gov (United States)

    Alymani, Nayef A; Smith, Murray D; Williams, David J; Petty, Russell D

    2010-03-01

    A priority translational research objective in cancer medicine is the discovery of novel therapeutic targets for solid tumours. Ideally, co-discovery of predictive biomarkers occurs in parallel to facilitate clinical development of agents and ultimately personalise clinical use. However, the identification of clinically useful predictive biomarkers for solid tumours has proven challenging with many initially promising biomarkers failing to translate into clinically useful applications. In particular, the 'failure' of a predictive biomarker has often only become apparent at a relatively late stage in investigation. Recently, the field has recognised the need to develop a robust clinical biomarker development methodology to facilitate the process. This review discusses the recent progress in this area focusing on the key stages in the biomarker development process: discovery, validation, qualification and implementation. Concentrating on predictive biomarkers for selecting systemic therapies for individual patients in the clinic, the advances and progress in each of these stages in biomarker development are outlined and the key remaining challenges are discussed. Specific examples are discussed to illustrate the challenges identified and how they have been addressed. Overall, we find that significant progress has been made towards a formalised biomarker developmental process. This holds considerable promise for facilitating the translation of predictive biomarkers from discovery to clinical implementation. Further enhancements could eventually be found through alignment with regulatory processes. PMID:20138504

  11. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    OpenAIRE

    Debasish Paul; Avinash Kumar; Akshada Gajbhiye; Santra, Manas K.; Rapole Srikanth

    2013-01-01

    Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE,...

  12. 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, Weijun; Liu, Tao; Kagan, Jacob; Srivastava, Sudhir; Smith, Richard D.; Rodland, Karin D.; Camp, David G.

    2016-01-01

    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.

  13. Mass Spectrometry-Based Proteomics in Molecular Diagnostics: Discovery of Cancer Biomarkers Using Tissue Culture

    Directory of Open Access Journals (Sweden)

    Debasish Paul

    2013-01-01

    Full Text Available Accurate diagnosis and proper monitoring of cancer patients remain a key obstacle for successful cancer treatment and prevention. Therein comes the need for biomarker discovery, which is crucial to the current oncological and other clinical practices having the potential to impact the diagnosis and prognosis. In fact, most of the biomarkers have been discovered utilizing the proteomics-based approaches. Although high-throughput mass spectrometry-based proteomic approaches like SILAC, 2D-DIGE, and iTRAQ are filling up the pitfalls of the conventional techniques, still serum proteomics importunately poses hurdle in overcoming a wide range of protein concentrations, and also the availability of patient tissue samples is a limitation for the biomarker discovery. Thus, researchers have looked for alternatives, and profiling of candidate biomarkers through tissue culture of tumor cell lines comes up as a promising option. It is a rich source of tumor cell-derived proteins, thereby, representing a wide array of potential biomarkers. Interestingly, most of the clinical biomarkers in use today (CA 125, CA 15.3, CA 19.9, and PSA were discovered through tissue culture-based system and tissue extracts. This paper tries to emphasize the tissue culture-based discovery of candidate biomarkers through various mass spectrometry-based proteomic approaches.

  14. Proteomics in Cancer Biomarkers Discovery: Challenges and Applications

    Directory of Open Access Journals (Sweden)

    Reem M. Sallam

    2015-01-01

    Full Text Available With the introduction of recent high-throughput technologies to various fields of science and medicine, it is becoming clear that obtaining large amounts of data is no longer a problem in modern research laboratories. However, coherent study designs, optimal conditions for obtaining high-quality data, and compelling interpretation, in accordance with the evidence-based systems biology, are critical factors in ensuring the emergence of good science out of these recent technologies. This review focuses on the proteomics field and its new perspectives on cancer research. Cornerstone publications that have tremendously helped scientists and clinicians to better understand cancer pathogenesis; to discover novel diagnostic and/or prognostic biomarkers; and to suggest novel therapeutic targets will be presented. The author of this review aims at presenting some of the relevant literature data that helped as a step forward in bridging the gap between bench work results and bedside potentials. Undeniably, this review cannot include all the work that is being produced by expert research groups all over the world.

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

    Science.gov (United States)

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

    2016-01-01

    Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives. PMID:26581546

  16. New trends in molecular and cellular biomarker discovery for colorectal cancer

    Science.gov (United States)

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-01-01

    Colorectal cancer (CRC) is the third leading cause of cancer death worldwide, which is consequence of multistep tumorigenesis of several genetic and epigenetic events. Since CRC is mostly asymptomatic until it progresses to advanced stages, the early detection using effective screening approaches, selection of appropriate therapeutic strategies and efficient follow-up programs are essential to reduce CRC mortalities. Biomarker discovery for CRC based on the personalized genotype and clinical information could facilitate the classification of patients with certain types and stages of cancer to tailor preventive and therapeutic approaches. These cancer-related biomarkers should be highly sensitive and specific in a wide range of specimen(s) (including tumor tissues, patients’ fluids or stool). Reliable biomarkers which enable the early detection of CRC, can improve early diagnosis, prognosis, treatment response prediction, and recurrence risk. Advances in our understanding of the natural history of CRC have led to the development of different CRC associated molecular and cellular biomarkers. This review highlights the new trends and approaches in CRC biomarker discovery, which could be potentially used for early diagnosis, development of new therapeutic approaches and follow-up of patients. PMID:27433083

  17. Quantitative proteomics in resected renal cancer tissue for biomarker discovery and profiling

    OpenAIRE

    Atrih, A; Mudaliar, M A V; Zakikhani, P; Lamont, D J; Huang, J T-J; Bray, S.E.; Barton, G.; Fleming, S; Nabi, G.

    2014-01-01

    Background: Proteomics-based approaches for biomarker discovery are promising strategies used in cancer research. We present state-of-art label-free quantitative proteomics method to assess proteome of renal cell carcinoma (RCC) compared with noncancer renal tissues. Methods: Fresh frozen tissue samples from eight primary RCC lesions and autologous adjacent normal renal tissues were obtained from surgically resected tumour-bearing kidneys. Proteins were extracted by complete solubilisation of...

  18. A Combined Shotgun and Targeted Mass Spectrometry Strategy for Breast Cancer Biomarker Discovery.

    Science.gov (United States)

    Sjöström, Martin; Ossola, Reto; Breslin, Thomas; Rinner, Oliver; Malmström, Lars; Schmidt, Alexander; Aebersold, Ruedi; Malmström, Johan; Niméus, Emma

    2015-07-01

    It is of highest importance to find proteins responsible for breast cancer dissemination, for use as biomarkers or treatment targets. We established and performed a combined nontargeted LC-MS/MS and a targeted LC-SRM workflow for discovery and validation of protein biomarkers. Eighty breast tumors, stratified for estrogen receptor status and development of distant recurrence (DR ± ), were collected. After enrichment of N-glycosylated peptides, label-free LC-MS/MS was performed on each individual tumor in triplicate. In total, 1515 glycopeptides from 778 proteins were identified and used to create a map of the breast cancer N-glycosylated proteome. Based on this specific proteome map, we constructed a 92-plex targeted label-free LC-SRM panel. These proteins were quantified across samples by LC-SRM, resulting in 10 proteins consistently differentially regulated between DR+/DR- tumors. Five proteins were further validated in a separate cohort as prognostic biomarkers at the gene expression level. We also compared the LC-SRM results to clinically reported HER2 status, demonstrating its clinical accuracy. In conclusion, we demonstrate a combined mass spectrometry strategy, at large scale on clinical samples, leading to the identification and validation of five proteins as potential biomarkers for breast cancer recurrence. All MS data are available via ProteomeXchange and PASSEL with identifiers PXD001685 and PASS00643. PMID:25944384

  19. Mass spectrometry based translational proteomics for biomarker discovery and application in colorectal cancer.

    Science.gov (United States)

    Ma, Hong; Chen, Guilin; Guo, Mingquan

    2016-04-01

    Colorectal cancer (CRC) is a leading cause of cancer-related death in the world. Clinically, early detection of the disease is the most effective approach to tackle this tough challenge. Discovery and development of reliable and effective diagnostic tools for the assessment of prognosis and prediction of response to drug therapy are urgently needed for personalized therapies and better treatment outcomes. Among many ongoing efforts in search for potential CRC biomarkers, MS-based translational proteomics provides a unique opportunity for the discovery and application of protein biomarkers toward better CRC early detection and treatment. This review updates most recent studies that use preclinical models and clinical materials for the identification of CRC-related protein markers. Some new advances in the development of CRC protein markers such as CRC stem cell related protein markers, SRM/MRM-MS and MS cytometry approaches are also discussed in order to address future directions and challenges from bench translational research to bedside clinical application of CRC biomarkers. PMID:26616366

  20. Recent patents and advances in genomic biomarker discovery for colorectal cancers.

    Science.gov (United States)

    Quyun, Chen; Ye, Zhiyun; Lin, Sheng-Cai; Lin, Biaoyang

    2010-06-01

    Colorectal cancer (CRC) is the third most common cancer in the world. Early diagnosis of colorectal cancer is the key to reducing the death rate of CRC patients. Predicting the response to current therapeutic modalities of CRC will also have a great impact on patient care. This review summarizes recent advances and patents in biomarker discovery in CRC under five major categories; including genomic changes, expression changes, mutations, epigenetic changes and microRNAs. The interesting patents include: 1) a patent for a method to differentiate normal exfoliated cells from cancer cells based on whether they were subjected to apoptosis and DNA degradation; 2) A model (PM-33 multiple molecular marker model) based on expression changes of up-regulation of the MDM2, DUSP6, and NFl genes down-regulation of the RNF4, MMD and EIF2S3 genes, which achieved an 88% sensitivity, and an 82% specificity for CRC diagnosis; 3) gene mutations in PTEN, KRAS, PIK3CA for predicting the response to anti-EGFR therapies, a common drug used for CRC treatment; 4) patents on epigenetic changes of ITGA4, SEPT9, ALX4, TFAP2E FOXL2, SARM1, ID4 etc. and many key miRNAs. Finally, future directions in the fields were commented on or suggested, including the combination of multiple categories of biomarkers and pathway central or network-based biomarker panels. PMID:20426761

  1. Prostate cancer serum biomarker discovery through proteomic analysis of alpha-2 macroglobulin protein complexes

    Science.gov (United States)

    Burgess, Earle F.; Ham, Amy-Joan L.; Tabb, David L.; Billheimer, Dean; Roth, Bruce J.; Chang, Sam S.; Cookson, Michael S.; Hinton, Timothy J.; Cheek, Kristin L.; Hill, Salisha; Pietenpol, Jennifer A.

    2010-01-01

    Alpha-2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen-independent, metastatic prostate cancer and six control patients without malignancy were analyzed by immunoaffinity enrichment of A2M protein complexes and MS identification of associated proteins. Known A2M substrates were reproducibly identified from patient serum in both cohorts, as well as proteins previously undetected in human serum. One example is heat shock protein 90 alpha (HSP90α), which was identified only in the serum of cancer patients in this study. Using an ELISA, the presence of HSP90α in human serum was validated on expanded test cohorts and found to exist in higher median serum concentrations in prostate cancer (n = 18) relative to control (n = 13) patients (median concentrations 50.7 versus 27.6 ng/mL, respectively, p = 0.001). Our results demonstrate the technical feasibility of this approach and support the analysis of A2M protein complexes for proteomic-based serum biomarker discovery. PMID:20107526

  2. Reproducible cancer biomarker discovery in SELDI-TOF MS using different pre-processing algorithms.

    Directory of Open Access Journals (Sweden)

    Jinfeng Zou

    Full Text Available BACKGROUND: There has been much interest in differentiating diseased and normal samples using biomarkers derived from mass spectrometry (MS studies. However, biomarker identification for specific diseases has been hindered by irreproducibility. Specifically, a peak profile extracted from a dataset for biomarker identification depends on a data pre-processing algorithm. Until now, no widely accepted agreement has been reached. RESULTS: In this paper, we investigated the consistency of biomarker identification using differentially expressed (DE peaks from peak profiles produced by three widely used average spectrum-dependent pre-processing algorithms based on SELDI-TOF MS data for prostate and breast cancers. Our results revealed two important factors that affect the consistency of DE peak identification using different algorithms. One factor is that some DE peaks selected from one peak profile were not detected as peaks in other profiles, and the second factor is that the statistical power of identifying DE peaks in large peak profiles with many peaks may be low due to the large scale of the tests and small number of samples. Furthermore, we demonstrated that the DE peak detection power in large profiles could be improved by the stratified false discovery rate (FDR control approach and that the reproducibility of DE peak detection could thereby be increased. CONCLUSIONS: Comparing and evaluating pre-processing algorithms in terms of reproducibility can elucidate the relationship among different algorithms and also help in selecting a pre-processing algorithm. The DE peaks selected from small peak profiles with few peaks for a dataset tend to be reproducibly detected in large peak profiles, which suggests that a suitable pre-processing algorithm should be able to produce peaks sufficient for identifying useful and reproducible biomarkers.

  3. Probing the O-glycoproteome of Gastric Cancer Cell Lines for Biomarker Discovery

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana; Magalhães, Ana; Steentoft, Catharina; Gomes, Catarina; Vester-Christensen, Malene B; Ferreira, José Alexandre; Afonso, Luis P; Santos, Lúcio L; de Sousa, João Pinto; Mandel, Ulla; Clausen, Henrik; Vakhrushev, Sergey Y; Reis, Celso A

    2015-01-01

    Circulating O-glycoproteins shed from cancer cells represent important serum biomarkers for diagnostic and prognostic purposes. We have recently shown that selective detection of cancer-associated aberrant glycoforms of circulating O-glycoprotein biomarkers can increase specificity of cancer biom...

  4. Discovery of dachshund 2 protein as a novel biomarker of poor prognosis in epithelial ovarian cancer

    Directory of Open Access Journals (Sweden)

    Nodin Björn

    2012-01-01

    Full Text Available Abstract Background The Dachshund homolog 2 (DACH2 gene has been implicated in development of the female genital tract in mouse models and premature ovarian failure syndrome, but to date, its expression in human normal and cancerous tissue remains unexplored. Using the Human Protein Atlas as a tool for cancer biomarker discovery, DACH2 protein was found to be differentially expressed in epithelial ovarian cancer (EOC. Here, the expression and prognostic significance of DACH2 was further evaluated in ovarian cancer cell lines and human EOC samples. Methods Immunohistochemical expression of DACH2 was examined in tissue microarrays with 143 incident EOC cases from two prospective, population-based cohorts, including a subset of benign-appearing fallopian tubes (n = 32. A nuclear score (NS, i.e. multiplier of staining fraction and intensity, was calculated. For survival analyses, cases were dichotomized into low (NS 3 using classification and regression tree analysis. Kaplan Meier analysis and Cox proportional hazards modelling were used to assess the impact of DACH2 expression on survival. DACH2 expression was analysed in the cisplatin sensitive ovarian cancer cell line A2780 and its cisplatin resistant derivative A2780-Cp70. The specificity of the DACH2 antibody was tested using siRNA-mediated silencing of DACH2 in A2780-Cp70 cells. Results DACH2 expression was considerably higher in the cisplatin resistant A2780-Cp70 cells compared to the cisplatin-sensitive A2780 cells. While present in all sampled fallopian tubes, DACH2 expression ranged from negative to strong in EOC. In EOC, DACH2 expression correlated with several proteins involved in DNA integrity and repair, and proliferation. DACH2 expression was significantly higher in carcinoma of the serous subtype compared to non-serous carcinoma. In the full cohort, high DACH2 expression was significantly associated with poor prognosis in univariable analysis, and in carcinoma of the serous subtype

  5. Prostate cancer serum biomarker discovery through proteomic analysis of alpha-2 macroglobulin protein complexes

    OpenAIRE

    Burgess, Earle F.; Ham, Amy-Joan L.; Tabb, David L.; Billheimer, Dean; Roth, Bruce J.; Chang, Sam S.; Cookson, Michael S.; Hinton, Timothy J.; Cheek, Kristin L.; Hill, Salisha; Jennifer A Pietenpol

    2008-01-01

    Alpha-2 macroglobulin (A2M) functions as a universal protease inhibitor in serum and is capable of binding various cytokines and growth factors. In this study, we investigated if immunoaffinity enrichment and proteomic analysis of A2M protein complexes from human serum could improve detection of biologically relevant and novel candidate protein biomarkers in prostate cancer. Serum samples from six patients with androgen-independent, metastatic prostate cancer and six control patients without ...

  6. In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer

    KAUST Repository

    Kaur, Mandeep

    2011-09-19

    Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors. 2011 Kaur et al; licensee BioMed Central Ltd.

  7. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    Directory of Open Access Journals (Sweden)

    Jianwen She

    2013-09-01

    Full Text Available Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC, reversed-phase liquid chromatography (RP–LC, and gas chromatography (GC. All three techniques are coupled to a mass spectrometer (MS in the full scan acquisition mode, and both unsupervised and supervised methods are used for data mining. The univariate and multivariate feature selection are used to determine subsets of potentially discriminative predictors. These predictors are further identified by obtaining accurate masses and isotopic ratios using selected ion monitoring (SIM and data-dependent MS/MS and/or accurate mass MSn ion tree scans utilizing high resolution MS. A list combining all of the identified potential biomarkers generated from different platforms and algorithms is used for pathway analysis. Such a workflow combining comprehensive metabolic profiling and advanced data mining techniques may provide a powerful approach for metabolic pathway analysis and biomarker discovery in cancer research. Two case studies with previous published data are adapted and included in the context to elucidate the application of the workflow.

  8. MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

    Directory of Open Access Journals (Sweden)

    Lazar Iulia M

    2009-03-01

    Full Text Available Abstract Background The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM, have been implemented. Methods MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX/reversed phase liquid chromatography (RPLC separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron. In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. Results In this work, we report on the generation of a library of 9,677 peptides (p a, b, y ions in the spectrum, the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW Conclusion Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter

  9. MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

    International Nuclear Information System (INIS)

    The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented. MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide. In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing ~1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000. Preliminary experiments have

  10. Glycoscience aids in biomarker discovery

    Directory of Open Access Journals (Sweden)

    Serenus Hua1,2 & Hyun Joo An1,2,*

    2012-06-01

    Full Text Available The glycome consists of all glycans (or carbohydrates within abiological system, and modulates a wide range of important biologicalactivities, from protein folding to cellular communications.The mining of the glycome for disease markers representsa new paradigm for biomarker discovery; however, this effortis severely complicated by the vast complexity and structuraldiversity of glycans. This review summarizes recent developmentsin analytical technology and methodology as applied tothe fields of glycomics and glycoproteomics. Mass spectrometricstrategies for glycan compositional profiling are described, as arepotential refinements which allow structure-specific profiling.Analytical methods that can discern protein glycosylation at aspecific site of modification are also discussed in detail.Biomarker discovery applications are shown at each level ofanalysis, highlighting the key role that glycoscience can play inhelping scientists understand disease biology.

  11. Biomarkers for Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Rikako Ishigamori

    2010-09-01

    Full Text Available Colorectal cancer (CRC is the third most common epithelial malignancy in the world. Since CRC develops slowly from removable precancerous lesions, detection of the lesion at an early stage by regular health examinations can reduce the incidence and mortality of this malignancy. Colonoscopy significantly improves the detection rate of CRC, but the examination is expensive and inconvenient. Therefore, we need novel biomarkers that are non-invasive to enable us to detect CRC quite early. A number of validation studies have been conducted to evaluate genetic, epigenetic or protein markers for identification in the stool and/or serum. Currently, the fecal occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics will lead to the discovery of novel non-invasive biomarkers.

  12. Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery

    Directory of Open Access Journals (Sweden)

    Kooren Joel A

    2011-09-01

    Full Text Available Abstract Introduction Early diagnosis of Oral Squamous Cell Carcinoma (OSCC increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs would be ideal. Methods In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery. Results Our evaluation focused on three core issues. First, using an "on-strip" processing method, we found that protein can be isolated from exudate samples in amounts compatible with large-scale mass spectrometry-based proteomic analysis. Second, we found that the OPML exudate proteome was distinct from that of whole saliva, while being similar to the OPML epithelial cell proteome, demonstrating the fidelity of our exudate collection method. Third, in a proof-of-principle study, we identified numerous, inflammation-associated proteins showing an expected increase in abundance in OPML exudates compared to healthy oral tissue exudates. These results demonstrate the feasibility of identifying differentially abundant proteins from exudate samples, which is essential for biomarker discovery studies. Conclusions Collectively, our findings demonstrate that our exudate collection method coupled with mass spectrometry-based proteomics has great potential for transforming OSCC biomarker discovery and clinical diagnostics assay development.

  13. Profiling of circulating microRNAs for prostate cancer biomarker discovery

    DEFF Research Database (Denmark)

    Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro;

    2014-01-01

    and T-stage of the primary PC. Better tools to assess PC aggressiveness could aid in treatment decisions. Recently, circulating miRNAs have been suggested as potential new biomarkers for PC with diagnostic and prognostic potential. Here, to identify new serum miRNA biomarker candidates for PC, we...... well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100 %) miRNA candidate marker panels able to identify 84 % of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80 % of...

  14. Molecular biomarker discovery and physiological assessment of skeletal muscle in cancer cachexia

    OpenAIRE

    Stephens, Nathan Andrew

    2014-01-01

    Cachexia affects up to two thirds of all cancer patients with progressive disease. It is a syndrome characterised by weight-loss, anorexia, fatigue, asthenia, peripheral oedema, and is responsible for around 20% of cancer deaths. Cachectic patients suffer loss of both muscle mass and adipose tissue (with comparative sparing of visceral protein) and the lean tissue loss appears resistant to nutritional support. Progress in the treatment of cancer cachexia has been hampered due t...

  15. Combined blood/tissue analysis for cancer biomarker discovery: application to renal cell carcinoma.

    Science.gov (United States)

    Johann, Donald J; Wei, Bih-Rong; Prieto, DaRue A; Chan, King C; Ye, Xiaying; Valera, Vladimir A; Simpson, R Mark; Rudnick, Paul A; Xiao, Zhen; Issaq, Haleem J; Linehan, W Marston; Stein, Stephen E; Veenstra, Timothy D; Blonder, Josip

    2010-03-01

    A method that relies on subtractive tissue-directed shot-gun proteomics to identify tumor proteins in the blood of a patient newly diagnosed with cancer is described. To avoid analytical and statistical biases caused by physiologic variability of protein expression in the human population, this method was applied on clinical specimens obtained from a single patient diagnosed with nonmetastatic renal cell carcinoma (RCC). The proteomes extracted from tumor, normal adjacent tissue and preoperative plasma were analyzed using 2D-liquid chromatography-mass spectrometry (LC-MS). The lists of identified proteins were filtered to discover proteins that (i) were found in the tumor but not normal tissue, (ii) were identified in matching plasma, and (iii) whose spectral count was higher in tumor tissue than plasma. These filtering criteria resulted in identification of eight tumor proteins in the blood. Subsequent Western-blot analysis confirmed the presence of cadherin-5, cadherin-11, DEAD-box protein-23, and pyruvate kinase in the blood of the patient in the study as well as in the blood of four other patients diagnosed with RCC. These results demonstrate the utility of a combined blood/tissue analysis strategy that permits the detection of tumor proteins in the blood of a patient diagnosed with RCC. PMID:20121140

  16. Biomarkers in precision therapy in colorectal cancer

    OpenAIRE

    Reimers, Marlies S.; Zeestraten, Eliane C.M.; Kuppen, Peter J.K.; Liefers, Gerrit Jan; van de Velde, Cornelis J. H.

    2013-01-01

    Colorectal cancer (CRC) is the most commonly diagnosed cancer in Europe. Because CRC is also a major cause of cancer-related deaths worldwide, a lot of research has been focused on the discovery and development of biomarkers to improve the diagnostic process and to predict treatment outcomes. Up till now only a few biomarkers are recommended by expert panels. Current TNM criteria, however, cause substantial under- and overtreatment of CRC patients. Consequently, there is a growing need for ne...

  17. A Comprehensive Workflow of Mass Spectrometry-Based Untargeted Metabolomics in Cancer Metabolic Biomarker Discovery Using Human Plasma and Urine

    OpenAIRE

    Jianwen She; Wei Zou; Vladimir V. Tolstikov

    2013-01-01

    Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC), reversed-phase liquid chromatography (RP–LC), and gas chromatography (GC). All three techniques are coupled to a mass spectro...

  18. Deglycosylation and label-free quantitative LC-MALDI MS applied to efficient serum biomarker discovery of lung cancer

    Directory of Open Access Journals (Sweden)

    Kohno Nobuoki

    2011-04-01

    Full Text Available Abstract Background Serum is an ideal source of biomarker discovery and proteomic profiling studies are continuously pursued on serum samples. However, serum is featured by high level of protein glycosylations that often cause ionization suppression and confound accurate quantification analysis by mass spectrometry. Here we investigated the effect of N-glycan and sialic acid removal from serum proteins on the performance of label-free quantification results. Results Serum tryptic digests with or without deglycosylation treatment were analyzed by LC-MALDI MS and quantitatively compared on the Expressionist Refiner MS module. As a result, 345 out of 2,984 peaks (11.6% showed the specific detection or the significantly improved intensities in deglycosylated serum samples (P P Conclusions We demonstrated here that sample deglycosylation improves the quantitative performance of shotgun proteomics, which can be effectively applied to any samples with high glycoprotein contents.

  19. Proteomic Approaches for Biomarker Panels in Cancer.

    Science.gov (United States)

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

    Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery. PMID:26565430

  20. Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium

    OpenAIRE

    Birse, Charles E; Lagier, Robert J.; Fitzhugh, William; Harvey I Pass; Rom, William N.; Eric S. Edell; Aaron O. Bungum; Maldonado, Fabien; Jett, James R.; Mesri, Mehdi; Sult, Erin; Joseloff, Elizabeth; Li, Aiqun; Heidbrink, Jenny; Dhariwal, Gulshan

    2015-01-01

    Background Support for early detection of lung cancer has emerged from the National Lung Screening Trial (NLST), in which low-dose computed tomography (LDCT) screening reduced lung cancer mortality by 20 % relative to chest x-ray. The US Preventive Services Task Force (USPSTF) recently recommended annual screening for the high-risk population, concluding that the benefits (life years gained) outweighed harms (false positive findings, abortive biopsy/surgery, radiation exposure). In making the...

  1. Stable Feature Selection for Biomarker Discovery

    CERN Document Server

    He, Zengyou

    2010-01-01

    Feature selection techniques have been used as the workhorse in biomarker discovery applications for a long time. Surprisingly, the stability of feature selection with respect to sampling variations has long been under-considered. It is only until recently that this issue has received more and more attention. In this article, we review existing stable feature selection methods for biomarker discovery using a generic hierarchal framework. We have two objectives: (1) providing an overview on this new yet fast growing topic for a convenient reference; (2) categorizing existing methods under an expandable framework for future research and development.

  2. Aberrant glycosylation associated with enzymes as cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Meany Danni L

    2011-06-01

    Full Text Available Abstract Background One of the new roles for enzymes in personalized medicine builds on a rational approach to cancer biomarker discovery using enzyme-associated aberrant glycosylation. A hallmark of cancer, aberrant glycosylation is associated with differential expressions of enzymes such as glycosyltransferase and glycosidases. The aberrant expressions of the enzymes in turn cause cancer cells to produce glycoproteins with specific cancer-associated aberrations in glycan structures. Content In this review we provide examples of cancer biomarker discovery using aberrant glycosylation in three areas. First, changes in glycosylation machinery such as glycosyltransferases/glycosidases could be used as cancer biomarkers. Second, most of the clinically useful cancer biomarkers are glycoproteins. Discovery of specific cancer-associated aberrations in glycan structures of these existing biomarkers could improve their cancer specificity, such as the discovery of AFP-L3, fucosylated glycoforms of AFP. Third, cancer-associated aberrations in glycan structures provide a compelling rationale for discovering new biomarkers using glycomic and glycoproteomic technologies. Summary As a hallmark of cancer, aberrant glycosylation allows for the rational design of biomarker discovery efforts. But more important, we need to translate these biomarkers from discovery to clinical diagnostics using good strategies, such as the lessons learned from translating the biomarkers discovered using proteomic technologies to OVA 1, the first FDA-cleared In Vitro Diagnostic Multivariate Index Assay (IVDMIA. These lessons, providing important guidance in current efforts in biomarker discovery and translation, are applicable to the discovery of aberrant glycosylation associated with enzymes as cancer biomarkers as well.

  3. Novel diagnostic biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Chikezie O. Madu, Yi Lu

    2010-01-01

    Full Text Available Prostate cancer is the most frequently diagnosed malignancy in American men, and a more aggressive form of the disease is particularly prevalent among African Americans. The therapeutic success rate for prostate cancer can be tremendously improved if the disease is diagnosed early. Thus, a successful therapy for this disease depends heavily on the clinical indicators (biomarkers for early detection of the presence and progression of the disease, as well as the prediction after the clinical intervention. However, the current clinical biomarkers for prostate cancer are not ideal as there remains a lack of reliable biomarkers that can specifically distinguish between those patients who should be treated adequately to stop the aggressive form of the disease and those who should avoid overtreatment of the indolent form.A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. A biomarker reveals further information to presently existing clinical and pathological analysis. It facilitates screening and detecting the cancer, monitoring the progression of the disease, and predicting the prognosis and survival after clinical intervention. A biomarker can also be used to evaluate the process of drug development, and, optimally, to improve the efficacy and safety of cancer treatment by enabling physicians to tailor treatment for individual patients. The form of the prostate cancer biomarkers can vary from metabolites and chemical products present in body fluid to genes and proteins in the prostate tissues.Current advances in molecular techniques have provided new tools facilitating the discovery of new biomarkers for prostate cancer. These emerging biomarkers will be beneficial and critical in developing new and clinically reliable indicators that will have a high specificity for the diagnosis and prognosis of

  4. Discovery of potential prognostic long non-coding RNA biomarkers for predicting the risk of tumor recurrence of breast cancer patients.

    Science.gov (United States)

    Zhou, Meng; Zhong, Lei; Xu, Wanying; Sun, Yifan; Zhang, Zhaoyue; Zhao, Hengqiang; Yang, Lei; Sun, Jie

    2016-01-01

    Deregulation of long non-coding RNAs (lncRNAs) expression has been proven to be involved in the development and progression of cancer. However, expression pattern and prognostic value of lncRNAs in breast cancer recurrence remain unclear. Here, we analyzed lncRNA expression profiles of breast cancer patients who did or did not develop recurrence by repurposing existing microarray datasets from the Gene Expression Omnibus database, and identified 12 differentially expressed lncRNAs that were closely associated with tumor recurrence of breast cancer patients. We constructed a lncRNA-focus molecular signature by the risk scoring method based on the expression levels of 12 relapse-related lncRNAs from the discovery cohort, which classified patients into high-risk and low-risk groups with significantly different recurrence-free survival (HR = 2.72, 95% confidence interval 2.07-3.57; p = 4.8e-13). The 12-lncRNA signature also represented similar prognostic value in two out of three independent validation cohorts. Furthermore, the prognostic power of the 12-lncRNA signature was independent of known clinical prognostic factors in at least two cohorts. Functional analysis suggested that the predicted relapse-related lncRNAs may be involved in known breast cancer-related biological processes and pathways. Our results highlighted the potential of lncRNAs as novel candidate biomarkers to identify breast cancer patients at high risk of tumor recurrence. PMID:27503456

  5. Proteomics Discovery of Disease Biomarkers

    OpenAIRE

    Mamoun Ahram; Petricoin, Emanuel F.

    2008-01-01

    Recent technological developments in proteomics have shown promising initiatives in identifying novel biomarkers of various diseases. Such technologies are capable of investigating multiple samples and generating large amount of data end-points. Examples of two promising proteomics technologies are mass spectrometry, including an instrument based on surface enhanced laser desorption/ionization, and protein microarrays. Proteomics data must, however, undergo analytical processing using bioinfo...

  6. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    Science.gov (United States)

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  7. In-depth cDNA Library Sequencing Provides Quantitative Gene Expression Profiling in Cancer Biomarker Discovery

    Institute of Scientific and Technical Information of China (English)

    Wanling Yang; Dingge Ying; Yu-Lung Lau

    2009-01-01

    procedures may allow detection of many expres-sion features for less abundant gene variants. With the reduction of sequencing cost and the emerging of new generation sequencing technology, in-depth sequencing of cDNA pools or libraries may represent a better and powerful tool in gene expression profiling and cancer biomarker detection. We also propose using sequence-specific subtraction to remove hundreds of the most abundant housekeeping genes to in-crease sequencing depth without affecting relative expression ratio of other genes, as transcripts from as few as 300 most abundantly expressed genes constitute about 20% of the total transcriptome. In-depth sequencing also represents a unique ad-vantage of detecting unknown forms of transcripts, such as alternative splicing variants, fusion genes, and regulatory RNAs, as well as detecting mutations and polymorphisms that may play important roles in disease pathogenesis.

  8. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg; Barak, Vivian; Molina, Rafael; Hayes, Daniel F; Diamandis, Eleftherios P; Bossuyt, Patrick

    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...

  9. State of the Art in Tumor Antigen and Biomarker Discovery

    International Nuclear Information System (INIS)

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology

  10. State of the Art in Tumor Antigen and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Patrick Chames

    2011-06-01

    Full Text Available Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

  11. State of the Art in Tumor Antigen and Biomarker Discovery

    Energy Technology Data Exchange (ETDEWEB)

    Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick, E-mail: patrick.chames@inserm.fr [INSERM U624, 163 avenue de Luminy, 13288 Marseille Cedex 09 (France)

    2011-06-09

    Our knowledge of tumor immunology has resulted in multiple approaches for the treatment of cancer. However, a gap between research of new tumors markers and development of immunotherapy has been established and very few markers exist that can be used for treatment. The challenge is now to discover new targets for active and passive immunotherapy. This review aims at describing recent advances in biomarkers and tumor antigen discovery in terms of antigen nature and localization, and is highlighting the most recent approaches used for their discovery including “omics” technology.

  12. Biomarkers in Prostate Cancer Epidemiology

    Directory of Open Access Journals (Sweden)

    Mudit Verma

    2011-09-01

    Full Text Available Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high risk for developing prostate cancer. In cancer epidemiology, epigenetic biomarkers offer advantages over other types of biomarkers because they are expressed against a person’s genetic background and environmental exposure, and because abnormal events occur early in cancer development, which includes several epigenetic alterations in cancer cells. This article describes different biomarkers that have potential use in studying the epidemiology of prostate cancer. We also discuss the characteristics of an ideal biomarker for prostate cancer, and technologies utilized for biomarker assays. Among epigenetic biomarkers, most reports indicate GSTP1 hypermethylation as the diagnostic marker for prostate cancer; however, NKX2-5, CLSTN1, SPOCK2, SLC16A12, DPYS, and NSE1 also have been reported to be regulated by methylation mechanisms in prostate cancer. Current challenges in utilization of biomarkers in prostate cancer diagnosis and epidemiologic studies and potential solutions also are discussed.

  13. 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.

  14. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

    OpenAIRE

    Vilém Guryča; Daniel Roeder; Paolo Piraino; Jens Lamerz; Axel Ducret; Hanno Langen; Paul Cutler

    2014-01-01

    The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by t...

  15. Network-Based Protein Biomarker Discovery Platforms.

    Science.gov (United States)

    Kim, Minhyung; Hwang, Daehee

    2016-03-01

    The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms. PMID:27103885

  16. Proteomics in Discovery of Hepatocellular Carcinoma Biomarkers

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Objective: To discover new proteomic biomarkers of hepatocellular carcinoma. Methods: Surface enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry was used to discover biomarkers for differentiating hepatocellular carcinoma and chronic liver disease. A population of 50 patients with hepatocellular carcinoma and 33 patients with chronic liver disease was studied. Results: Twelve proteomic biomarkers of hepatocellular carcinoma were detected in this study. Three proteomic biomarkers were highly expressed in hepatocellular carcinoma and nine proteomic biomarkers were highly expressed in chronic liver disease. The most valuable proteomic biomarker with m/z=11498 had no similar diagnostic value as α-fetoprotein. Conclusion:Some of the twelve proteomic biomarkers may become new biomarkers of hepatocellular carcinoma.

  17. Evaluating the potential of a novel oral lesion exudate collection method coupled with mass spectrometry-based proteomics for oral cancer biomarker discovery

    OpenAIRE

    Kooren Joel A; Rhodus Nelson L; Tang Chuanning; Jagtap Pratik D; Horrigan Bryan J; Griffin Timothy J

    2011-01-01

    Abstract Introduction Early diagnosis of Oral Squamous Cell Carcinoma (OSCC) increases the survival rate of oral cancer. For early diagnosis, molecular biomarkers contained in samples collected non-invasively and directly from at-risk oral premalignant lesions (OPMLs) would be ideal. Methods In this pilot study we evaluated the potential of a novel method using commercial PerioPaper absorbent strips for non-invasive collection of oral lesion exudate material coupled with mass spectrometry-bas...

  18. Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. PMID:26703953

  19. Evaluation of reverse phase protein array (RPPA)-based pathway-activation profiling in 84 non-small cell lung cancer (NSCLC) cell lines as platform for cancer proteomics and biomarker discovery.

    Science.gov (United States)

    Ummanni, Ramesh; Mannsperger, Heiko A; Sonntag, Johanna; Oswald, Marcus; Sharma, Ashwini K; König, Rainer; Korf, Ulrike

    2014-05-01

    The reverse phase protein array (RPPA) approach was employed for a quantitative analysis of 71 cancer-relevant proteins and phosphoproteins in 84 non-small cell lung cancer (NSCLC) cell lines and by monitoring the activation state of selected receptor tyrosine kinases, PI3K/AKT and MEK/ERK1/2 signaling, cell cycle control, apoptosis, and DNA damage. Additional information on NSCLC cell lines such as that of transcriptomic data, genomic aberrations, and drug sensitivity was analyzed in the context of proteomic data using supervised and non-supervised approaches for data analysis. First, the unsupervised analysis of proteomic data indicated that proteins clustering closely together reflect well-known signaling modules, e.g. PI3K/AKT- and RAS/RAF/ERK-signaling, cell cycle regulation, and apoptosis. However, mutations of EGFR, ERBB2, RAF, RAS, TP53, and PI3K were found dispersed across different signaling pathway clusters. Merely cell lines with an amplification of EGFR and/or ERBB2 clustered closely together on the proteomic, but not on the transcriptomic level. Secondly, supervised data analysis revealed that sensitivity towards anti-EGFR drugs generally correlated better with high level EGFR phosphorylation than with EGFR abundance itself. High level phosphorylation of RB and high abundance of AURKA were identified as candidates that can potentially predict sensitivity towards the aurora kinase inhibitor VX680. Examples shown demonstrate that the RPPA approach presents a useful platform for targeted proteomics with high potential for biomarker discovery. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:24361481

  20. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

    Full Text Available Abstract Background The use of gene signatures can potentially be of considerable value in the field of clinical diagnosis. However, gene signatures defined with different methods can be quite various even when applied the same disease and the same endpoint. Previous studies have shown that the correct selection of subsets of genes from microarray data is key for the accurate classification of disease phenotypes, and a number of methods have been proposed for the purpose. However, these methods refine the subsets by only considering each single feature, and they do not confirm the association between the genes identified in each gene signature and the phenotype of the disease. We proposed an innovative new method termed Minimize Feature's Size (MFS based on multiple level similarity analyses and association between the genes and disease for breast cancer endpoints by comparing classifier models generated from the second phase of MicroArray Quality Control (MAQC-II, trying to develop effective meta-analysis strategies to transform the MAQC-II signatures into a robust and reliable set of biomarker for clinical applications. Results We analyzed the similarity of the multiple gene signatures in an endpoint and between the two endpoints of breast cancer at probe and gene levels, the results indicate that disease-related genes can be preferably selected as the components of gene signature, and that the gene signatures for the two endpoints could be interchangeable. The minimized signatures were built at probe level by using MFS for each endpoint. By applying the approach, we generated a much smaller set of gene signature with the similar predictive power compared with those gene signatures from MAQC-II. Conclusions Our results indicate that gene signatures of both large and small sizes could perform equally well in clinical applications. Besides, consistency and biological significances can be detected among different gene signatures, reflecting the

  1. Multi-dimensional discovery of biomarker and phenotype complexes

    Directory of Open Access Journals (Sweden)

    Huang Kun

    2010-10-01

    Full Text Available Abstract Background Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity in order to diagnose, stage and plan treatments for disease states is highly desirable. Numerous techniques exist that can be used to develop networks of co-expressed or otherwise related genes and clinical features. Such techniques can also be used to create formalized knowledge collections based upon the information incumbent to ontologies and domain literature. However, reports of integrative approaches that bridge such networks to create systems-level models of disease or wellness are notably lacking in the contemporary literature. Results In response to the preceding gap in knowledge and practice, we report upon a prototypical series of experiments that utilize multi-modal approaches to network induction. These experiments are intended to elicit meaningful and significant biomarker-phenotype complexes spanning multiple levels of granularity. This work has been performed in the experimental context of a large-scale clinical and basic science data repository maintained by the National Cancer Institute (NCI funded Chronic Lymphocytic Leukemia Research Consortium. Conclusions Our results indicate that it is computationally tractable to link orthogonal networks of genes, clinical features, and conceptual knowledge to create multi-dimensional models of interrelated biomarkers and phenotypes. Further, our results indicate that such systems-level models contain interrelated bio-molecular and clinical markers capable of supporting hypothesis discovery and testing. Based on such findings, we propose a conceptual model intended to inform the cross-linkage of the results of such methods. This model has as its aim the identification of novel and knowledge-anchored biomarker-phenotype complexes.

  2. Bioinformatics and biomarker discovery "Omic" data analysis for personalized medicine

    CERN Document Server

    Azuaje, Francisco

    2010-01-01

    This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided w

  3. Potential Approaches and Recent Advances in Biomarker Discovery in Clear-Cell Renal Cell Carcinoma

    Science.gov (United States)

    Majer, Weronika; Kluzek, Katarzyna; Bluyssen, Hans; Wesoły, Joanna

    2015-01-01

    The early diagnosis and monitoring of clear-cell Renal Cell Carcinoma (ccRCC), which is the most common renal malignancy, remains challenging. The late diagnosis and lack of tools that can be used to assess the progression of the disease and metastasis significantly influence the chance of survival of ccRCC patients. Molecular biomarkers have been shown to aid the diagnosis and disease monitoring for other cancers, but such markers are not currently available for ccRCC. Recently, plasma and serum circulating nucleic acids, nucleic acids present in urine, and plasma and urine proteins gained interest in the field of cancer biomarker discovery. Here, we describe the applicability of plasma and urine nucleic acids as cancer biomarkers with a particular focus on DNA, small RNA, and protein markers for ccRCC. PMID:26516358

  4. Secreted proteins as a fundamental source for biomarker discovery

    Czech Academy of Sciences Publication Activity Database

    Šťastná, Miroslava; Van Eyk, J.E.

    2012-01-01

    Roč. 12, 4-5 (2012), s. 722-735. ISSN 1615-9853 Institutional research plan: CEZ:AV0Z40310501 Keywords : conditioned media * secreted proteins * proteomics * biomarker discovery Subject RIV: CB - Analytical Chemistry, Separation Impact factor: 4.132, year: 2012

  5. Biomarkers of HIV-associated Cancer

    OpenAIRE

    Brian Thabile Flepisi; Patrick Bouic; Gerhard Sissolak; Bernd Rosenkranz

    2014-01-01

    Cancer biomarkers have provided great opportunities for improving the management of cancer patients by enhancing the efficiency of early detection, diagnosis, and efficacy of treatment. Every cell type has a unique molecular signature, referred to as biomarkers, which are identifiable characteristics such as levels or activities of a myriad of genes, proteins, or other molecular features. Biomarkers can facilitate the molecular definition of cancer, provide information about the course of can...

  6. Epigenetic biomarkers in esophageal cancer.

    Science.gov (United States)

    Kaz, Andrew M; Grady, William M

    2014-01-28

    The aberrant DNA methylation of tumor suppressor genes is well documented in esophageal cancer, including adenocarcinoma (EAC) and squamous cell carcinoma (ESCC) as well as in Barrett's esophagus (BE), a pre-malignant condition that is associated with chronic acid reflux. BE is a well-recognized risk factor for the development of EAC, and consequently the standard of care is for individuals with BE to be placed in endoscopic surveillance programs aimed at detecting early histologic changes that associate with an increased risk of developing EAC. Yet because the absolute risk of EAC in individuals with BE is minimal, a clinical need in the management of BE is the identification of additional risk markers that will indicate individuals who are at a significant absolute risk of EAC so that they may be subjected to more intensive surveillance. The best currently available risk marker is the degree of dysplasia in endoscopic biopsies from the esophagus; however, this marker is suboptimal for a variety of reasons. To date, there are no molecular biomarkers that have been translated to widespread clinical practice. The search for biomarkers, including hypermethylated genes, for either the diagnosis of BE, EAC, or ESCC or for risk stratification for the development of EAC in those with BE is currently an area of active research. In this review, we summarize the status of identified candidate epigenetic biomarkers for BE, EAC, and ESCC. Most of these aberrantly methylated genes have been described in the context of early detection or diagnostic markers; others might prove useful for estimating prognosis or predicting response to treatment. Finally, special attention will be paid to some of the challenges that must be overcome in order to develop clinically useful esophageal cancer biomarkers. PMID:22406828

  7. Statistical considerations of optimal study design for human plasma proteomics and biomarker discovery.

    Science.gov (United States)

    Zhou, Cong; Simpson, Kathryn L; Lancashire, Lee J; Walker, Michael J; Dawson, Martin J; Unwin, Richard D; Rembielak, Agata; Price, Patricia; West, Catharine; Dive, Caroline; Whetton, Anthony D

    2012-04-01

    A mass spectrometry-based plasma biomarker discovery workflow was developed to facilitate biomarker discovery. Plasma from either healthy volunteers or patients with pancreatic cancer was 8-plex iTRAQ labeled, fractionated by 2-dimensional reversed phase chromatography and subjected to MALDI ToF/ToF mass spectrometry. Data were processed using a q-value based statistical approach to maximize protein quantification and identification. Technical (between duplicate samples) and biological variance (between and within individuals) were calculated and power analysis was thereby enabled. An a priori power analysis was carried out using samples from healthy volunteers to define sample sizes required for robust biomarker identification. The result was subsequently validated with a post hoc power analysis using a real clinical setting involving pancreatic cancer patients. This demonstrated that six samples per group (e.g., pre- vs post-treatment) may provide sufficient statistical power for most proteins with changes>2 fold. A reference standard allowed direct comparison of protein expression changes between multiple experiments. Analysis of patient plasma prior to treatment identified 29 proteins with significant changes within individual patient. Changes in Peroxiredoxin II levels were confirmed by Western blot. This q-value based statistical approach in combination with reference standard samples can be applied with confidence in the design and execution of clinical studies for predictive, prognostic, and/or pharmacodynamic biomarker discovery. The power analysis provides information required prior to study initiation. PMID:22338609

  8. Emerging concepts in biomarker discovery; The US-Japan workshop on immunological molecular markers in oncology

    Directory of Open Access Journals (Sweden)

    Rivoltini Licia

    2009-06-01

    Full Text Available Abstract Supported by the Office of International Affairs, National Cancer Institute (NCI, the "US-Japan Workshop on Immunological Biomarkers in Oncology" was held in March 2009. The workshop was related to a task force launched by the International Society for the Biological Therapy of Cancer (iSBTc and the United States Food and Drug Administration (FDA to identify strategies for biomarker discovery and validation in the field of biotherapy. The effort will culminate on October 28th 2009 in the "iSBTc-FDA-NCI Workshop on Prognostic and Predictive Immunologic Biomarkers in Cancer", which will be held in Washington DC in association with the Annual Meeting. The purposes of the US-Japan workshop were a to discuss novel approaches to enhance the discovery of predictive and/or prognostic markers in cancer immunotherapy; b to define the state of the science in biomarker discovery and validation. The participation of Japanese and US scientists provided the opportunity to identify shared or discordant themes across the distinct immune genetic background and the diverse prevalence of disease between the two Nations. Converging concepts were identified: enhanced knowledge of interferon-related pathways was found to be central to the understanding of immune-mediated tissue-specific destruction (TSD of which tumor rejection is a representative facet. Although the expression of interferon-stimulated genes (ISGs likely mediates the inflammatory process leading to tumor rejection, it is insufficient by itself and the associated mechanisms need to be identified. It is likely that adaptive immune responses play a broader role in tumor rejection than those strictly related to their antigen-specificity; likely, their primary role is to trigger an acute and tissue-specific inflammatory response at the tumor site that leads to rejection upon recruitment of additional innate and adaptive immune mechanisms. Other candidate systemic and/or tissue-specific biomarkers

  9. MicroRNA signatures as clinical biomarkers in lung cancer

    Directory of Open Access Journals (Sweden)

    Markou A

    2015-05-01

    Full Text Available Athina Markou, Martha Zavridou, Evi S Lianidou Analysis of Circulating Tumor Cells, Lab of Analytical Chemistry, Department of Chemistry, University of Athens, Athens, Greece Abstract: Even if early lung cancer detection has been recently significantly improved, the invasive nature of current diagnostic procedures, and a relatively high percentage of false positives, is limiting the application of modern detection tools. The discovery and clinical evaluation of novel specific and robust non-invasive biomarkers for diagnosis of lung cancer at an early stage, as well as for better prognosis and prediction of therapy response, is very challenging. MicroRNAs (miRNAs can play an important role in the diagnosis and management of lung cancer patients, as important and reliable biomarkers for cancer detection and prognostic prediction, and even as promising as novel targets for cancer therapy. miRNAs are important in cancer pathogenesis, and deregulation of their expression levels has been detected not only in lung cancer but in many other human tumor types. Numerous studies strongly support the potential of miRNAs as biomarkers in non-small-cell lung cancer, and there is increasing evidence that altered miRNA expression is associated with tumor progression and survival. It is worth mentioning also that detection of miRNAs circulating in plasma or serum has enormous potential, because miRNAs serve as non-invasive biomarkers not only for the diagnosis and prognosis of the disease, but also as novel response and sensitivity predictors for cancer treatment. In this review, we summarize the current findings on the critical role of miRNAs in lung cancer tumorigenesis and highlight their potential as circulating biomarkers in lung cancer. Our review is based on papers that have been published after 2011, and includes the key words “miRNAs” and “lung cancer”. Keywords: non-small-cell lung carcinoma, miRNAs, tumor biomarkers, circulating miRNAs, liquid

  10. Application of “omics” to Prion Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Rhiannon L. C. H. Huzarewich

    2010-01-01

    Full Text Available The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases.

  11. Searching for a system: The quest for ovarian cancer biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.; Maihle, Nita J.

    2011-11-01

    The stark difference in clinical outcome for patients with ovarian cancer diagnosed at early stages (95% at 5 years) versus late stages (27.6% at 5 years) has driven a decades-long quest for effective biomarkers that will enable earlier detection of ovarian cancer. Yet despite intense efforts, including the application of modern high throughput technologies such as transcriptomics and proteomics, there has been little improvement in performance compared to the gold standard of quantifying serum CA125 immunoreactivity paired with transvaginal ultrasound. This review describes the strategies that have been used for identification of ovarian cancer biomarkers, including the recent introduction of novel bioinformatic approaches. Results obtained using high throughput-based vs. biologically rational approaches for the discovery of diagnostic early detection biomarkers are compared and analyzed for functional enrichment.

  12. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery.

    Science.gov (United States)

    Maher, Toby M

    2013-06-01

    Despite major advances in the understanding of the pathogenesis of idiopathic pulmonary fibrosis (IPF), diagnosis and management of the condition continue to pose significant challenges. Clinical management of IPF remains unsatisfactory due to limited availability of effective drug therapies, a lack of accurate indicators of disease progression, and an absence of simple short-term measures of therapeutic response. The identification of more accurate predictors of prognosis and survival in IPF would facilitate counseling of patients and their families, aid communication among clinicians, and would guide optimal timing of referral for transplantation. Improvements in molecular techniques have led to the identification of new disease pathways and a more targeted approach to the development of novel anti-fibrotic agents. However, despite an increased interest in biomarkers of IPF disease progression there are a lack of measures that can be used in early phase clinical trials. Careful longitudinal phenotyping of individuals with IPF together with the application of novel omics-based technology should provide important insights into disease pathogenesis and should address some of the major issues holding back drug development in IPF. The PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints) study is a currently enrolling, prospective cohort study designed to tackle these issues. PMID:23728868

  13. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery

    Directory of Open Access Journals (Sweden)

    Toby M. Maher

    2013-06-01

    Full Text Available Despite major advances in the understanding of the pathogenesis of idiopathic pulmonary fibrosis (IPF, diagnosis and management of the condition continue to pose significant challenges. Clinical management of IPF remains unsatisfactory due to limited availability of effective drug therapies, a lack of accurate indicators of disease progression, and an absence of simple short-term measures of therapeutic response. The identification of more accurate predictors of prognosis and survival in IPF would facilitate counseling of patients and their families, aid communication among clinicians, and would guide optimal timing of referral for transplantation. Improvements in molecular techniques have led to the identification of new disease pathways and a more targeted approach to the development of novel anti-fibrotic agents. However, despite an increased interest in biomarkers of IPF disease progression there are a lack of measures that can be used in early phase clinical trials. Careful longitudinal phenotyping of individuals with IPF together with the application of novel omics-based technology should provide important insights into disease pathogenesis and should address some of the major issues holding back drug development in IPF. The PROFILE (Prospective Observation of Fibrosis in the Lung Clinical Endpoints study is a currently enrolling, prospective cohort study designed to tackle these issues.

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

    Science.gov (United States)

    Swanton, Charles; Larkin, James M; Gerlinger, Marco; Eklund, Aron C; Howell, Michael; Stamp, Gordon; Downward, Julian; Gore, Martin; Futreal, P Andrew; Escudier, Bernard; Andre, Fabrice; Albiges, Laurence; Beuselinck, Benoit; Oudard, Stephane; Hoffmann, Jens; Gyorffy, Balázs; Torrance, Chris J; Boehme, Karen A; Volkmer, Hansjuergen; Toschi, Luisella; Nicke, Barbara; Beck, Marlene; Szallasi, Zoltan

    2010-01-01

    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-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 inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding

  15. Integrative analysis to select cancer candidate biomarkers to targeted validation

    Science.gov (United States)

    Heberle, Henry; Domingues, Romênia R.; Granato, Daniela C.; Yokoo, Sami; Canevarolo, Rafael R.; Winck, Flavia V.; Ribeiro, Ana Carolina P.; Brandão, Thaís Bianca; Filgueiras, Paulo R.; Cruz, Karen S. P.; Barbuto, José Alexandre; Poppi, Ronei J.; Minghim, Rosane; Telles, Guilherme P.; Fonseca, Felipe Paiva; Fox, Jay W.; Santos-Silva, Alan R.; Coletta, Ricardo D.; Sherman, Nicholas E.; Paes Leme, Adriana F.

    2015-01-01

    Targeted proteomics has flourished as the method of choice for prospecting for and validating potential candidate biomarkers in many diseases. However, challenges still remain due to the lack of standardized routines that can prioritize a limited number of proteins to be further validated in human samples. To help researchers identify candidate biomarkers that best characterize their samples under study, a well-designed integrative analysis pipeline, comprising MS-based discovery, feature selection methods, clustering techniques, bioinformatic analyses and targeted approaches was performed using discovery-based proteomic data from the secretomes of three classes of human cell lines (carcinoma, melanoma and non-cancerous). Three feature selection algorithms, namely, Beta-binomial, Nearest Shrunken Centroids (NSC), and Support Vector Machine-Recursive Features Elimination (SVM-RFE), indicated a panel of 137 candidate biomarkers for carcinoma and 271 for melanoma, which were differentially abundant between the tumor classes. We further tested the strength of the pipeline in selecting candidate biomarkers by immunoblotting, human tissue microarrays, label-free targeted MS and functional experiments. In conclusion, the proposed integrative analysis was able to pre-qualify and prioritize candidate biomarkers from discovery-based proteomics to targeted MS. PMID:26540631

  16. Resolving breast cancer heterogeneity by searching reliable protein cancer biomarkers in the breast fluid secretome

    International Nuclear Information System (INIS)

    One of the major goals in cancer research is to find and evaluate the early presence of biomarkers in human fluids and tissues. To resolve the complex cell heterogeneity of a tumor mass, it will be useful to characterize the intricate biomolecular composition of tumor microenvironment (the so called cancer secretome), validating secreted proteins as early biomarkers of cancer initiation and progression. This approach is not broadly applicable because of the paucity of well validated and FDA-approved biomarkers and because most of the candidate biomarkers are mainly organ-specific rather than tumor-specific. For these reasons, there is an urgent need to identify and validate a panel of biomarker combinations for early detection of human tumors. This is especially important for breast cancer, the cancer spread most worldwide among women. It is well known that patients with early diagnosed breast cancer live longer, require less extensive treatment and fare better than patients with more aggressive and/or advanced disease. In the frame of searching breast cancer biomarkers (especially using nipple aspirate fluid mirroring breast microenvironment), studies have highlighted an optimal combination of well-known biomarkers: uPA + PAI-1 + TF. When individually investigated they did not show perfect accuracy in predicting the presence of breast cancer, whereas the triple combination has been demonstrated to be highly predictive of pre-cancer and/or cancerous conditions, approaching 97-100% accuracy. Despite the heterogeneous composition of breast cancer and the difficulties to find specific breast cancer biomolecules, the noninvasive analysis of the nipple aspirate fluid secretome may significantly improve the discovery of promising biomarkers, helping also the differentiation among benign and invasive breast diseases, opening new frontiers in early oncoproteomics

  17. Data mining of spectroscopic data for biomarker discovery.

    Science.gov (United States)

    Norton, S M; Huyn, P; Hastings, C A; Heller, J C

    2001-05-01

    The goals of precise diagnosis, prevention and treatment of disease can be realized through the discovery of biological markers. Spectroscopic tools can simultaneously detect and quantify multiple small molecule and macromolecular components of biological samples, and are therefore ideal methods for the discovery of previously uncharacterized markers. However, the identification of meaningful spectral features is complicated by the lack of foreknowledge of the molecular nature of a disease, spectral noise and biological variability that is uncorrelated with the disease state. Pattern recognition techniques, both statistical and machine-learning, have been increasingly used in recent years with spectroscopic data to identify markers and classify patients into disease subsets. This review summarizes recent developments, limitations and future prospects in the use of data mining techniques with magnetic resonance spectroscopy, mass spectrometry and optical spectroscopy for the discovery of biomarkers. PMID:11560066

  18. New serum biomarkers for prostate cancer diagnosis

    OpenAIRE

    Chadha, Kailash C.; Austin Miller; Nair, Bindukumar B.; Schwartz, Stanley A.; Trump, Donald L.; Willie Underwood

    2014-01-01

    Background: Prostate-specific antigen (PSA) is currently used as a biomarker for diagnosis and management of prostate cancer (CaP). However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker. Objective: The goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP. Methods: Concurrent meas...

  19. Proteomic profiling of exosomes leads to the identification of novel biomarkers for prostate cancer

    NARCIS (Netherlands)

    D. Duijvesz (Diederick); K.E. Burnum-Johnson (Kristin); M.A. Gritsenko (Marina); A.M. Hoogland (Marije); M.S. Vredenbregt-van den Berg (Mirella); R. Willemsen (Rob); T.M. Luider (Theo); L. Paša-Tolić (Ljiljana); G.W. Jenster (Guido)

    2013-01-01

    textabstractBackground: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼10

  20. Proteomics and Its Application in Biomarker Discovery and Drug Development

    Institute of Scientific and Technical Information of China (English)

    He Qing-Yu; Chiu Jen-Fu

    2004-01-01

    Proteomics is a research field aiming to characterize molecular and cellular dynamics in protein expression and function on a global level. The introduction of proteomics has been greatly broadening our view and accelerating our path in various medical researches. The most significant advantage of proteomics is its ability to examine a whole proteome or sub-proteome in a single experiment so that the protein alterations corresponding to a pathological or biochemical condition at a given time can be considered in an integrated way. Proteomic technology has been extensively used to tackle a wide variety of medical subjects including biomarker discovery and drug development. By complement with other new technique advance in genomics and bioinformatics,proteomics has a great potential to make considerable contribution to biomarker identification and revolutionize drug development process. A brief overview of the proteomic technologies will be provided and the application of proteomics in biomarker discovery and drug development will be discussed using our current research projects as examples.

  1. Sputum-Based Molecular Biomarkers for the Early Detection of Lung Cancer: Limitations and Promise

    International Nuclear Information System (INIS)

    Lung cancer is the leading cause of cancer deaths, with an overall survival of 15% at five years. Biomarkers that can sensitively and specifically detect lung cancer at early stage are crucial for improving this poor survival rate. Sputum has been the target for the discovery of non-invasive biomarkers for lung cancer because it contains airway epithelial cells, and molecular alterations identified in sputum are most likely to reflect tumor-associated changes or field cancerization caused by smoking in the lung. Sputum-based molecular biomarkers include morphology, allelic imbalance, promoter hypermethylation, gene mutations and, recently, differential miRNA expression. To improve the sensitivity and reproducibility of sputum-based biomarkers, we recommend standardization of processing protocols, bronchial epithelial cell enrichment, and identification of field cancerization biomarkers

  2. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

    The epidemiology of autism is continuously increasing all over the world with social, behavioural and economical burdens. Autism is considered as a multi-factorial disorder, influenced by genetic, neurological, environmental and immunological aspects. Autism is still believed to be incurable disorder with little information about the role of proteins patterns in the diagnosis of the disease. Knowing the applications of proteomic tools, it is possible to identify quantitative and qualitative protein patterns in a wide variety of tissues and body fluids such as blood, urine, saliva and cerebrospinal fluid in order to establish specific diagnostic and prognostic biomarkers. The aim of this review is to provide an overview of the various protocols available for proteomics by using mass spectrometry analysis, discuss reports in which these techniques have been previously applied in biomarker discovery for the diagnosis of autism, and consider the future development of this area of research. (author)

  3. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

    Balog, Crina I.; Hensbergen, Paul J.; Derks, Rico; Verweij, Jaco J.; Dam, Govert J. van; Vennervald, Birgitte J; Deelder, André M.; Mayboroda, Oleg A.

    2009-01-01

    Urine is potentially a rich source of peptide biomarkers, but reproducible, high-throughput peptidomic analysis is often hampered by the inherent variability in factors such as pH and salt concentration. Our goal was to develop a generally applicable, rapid, and robust method for screening large...... numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. METHODS: Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed...... samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high...

  4. Metabolomics-based discovery of diagnostic biomarkers for onchocerciasis.

    Directory of Open Access Journals (Sweden)

    Judith R Denery

    Full Text Available BACKGROUND: Development of robust, sensitive, and reproducible diagnostic tests for understanding the epidemiology of neglected tropical diseases is an integral aspect of the success of worldwide control and elimination programs. In the treatment of onchocerciasis, clinical diagnostics that can function in an elimination scenario are non-existent and desperately needed. Due to its sensitivity and quantitative reproducibility, liquid chromatography-mass spectrometry (LC-MS based metabolomics is a powerful approach to this problem. METHODOLOGY/PRINCIPAL FINDINGS: Analysis of an African sample set comprised of 73 serum and plasma samples revealed a set of 14 biomarkers that showed excellent discrimination between Onchocerca volvulus-positive and negative individuals by multivariate statistical analysis. Application of this biomarker set to an additional sample set from onchocerciasis endemic areas where long-term ivermectin treatment has been successful revealed that the biomarker set may also distinguish individuals with worms of compromised viability from those with active infection. Machine learning extended the utility of the biomarker set from a complex multivariate analysis to a binary format applicable for adaptation to a field-based diagnostic, validating the use of complex data mining tools applied to infectious disease biomarker discovery and diagnostic development. CONCLUSIONS/SIGNIFICANCE: An LC-MS metabolomics-based diagnostic has the potential to monitor the progression of onchocerciasis in both endemic and non-endemic geographic areas, as well as provide an essential tool to multinational programs in the ongoing fight against this neglected tropical disease. Ultimately this technology can be expanded for the diagnosis of other filarial and/or neglected tropical diseases.

  5. Nanomaterials based biosensors for cancer biomarker detection

    Science.gov (United States)

    Malhotra, Bansi D.; Kumar, Saurabh; Mouli Pandey, Chandra

    2016-04-01

    Biosensors have enormous potential to contribute to the evolution of new molecular diagnostic techniques for patients suffering with cancerous diseases. A major obstacle preventing faster development of biosensors pertains to the fact that cancer is a highly complex set of diseases. The oncologists currently rely on a few biomarkers and histological characterization of tumors. Some of the signatures include epigenetic and genetic markers, protein profiles, changes in gene expression, and post-translational modifications of proteins. These molecular signatures offer new opportunities for development of biosensors for cancer detection. In this context, conducting paper has recently been found to play an important role towards the fabrication of a biosensor for cancer biomarker detection. In this paper we will focus on results of some of the recent studies obtained in our laboratories relating to fabrication and application of nanomaterial modified paper based biosensors for cancer biomarker detection.

  6. The Use of Proteomics in Biomarker Discovery in Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Pia Davidsson

    2005-01-01

    Full Text Available Biomarkers for neurodegenerative diseases should reflect the central pathogenic processes of the diseases. The field of clinical proteomics is especially well suited for discovery of biomarkers in cerebrospinal fluid (CSF, which reflects the proteins in the brain under healthy conditions as well as in several neurodegenerative diseases. Known proteins involved in the pathology of neurodegenerative diseases are, respectively, normal tau protein, β-amyloid (1-42, synaptic proteins, amyloid precursor protein (APP, apolipoprotein E (apoE, which previously have been studied by protein immunoassays. The objective of this paper was to summarize results from proteomic studies of differential protein patterns in neurodegenerative diseases with focus on Alzheimer's disease (AD. Today, discrimination of AD from controls and from other neurological diseases has been improved by simultaneous analysis of both β-amyloid (1-42, total-tau, and phosphorylated tau, where a combination of low levels of CSF-β-amyloid 1-42 and high levels of CSF-tau and CSF-phospho-tau is associated with an AD diagnosis. Detection of new biomarkers will further strengthen diagnosis and provide useful information in drug trials. The combination of immunoassays and proteomic methods show that the CSF proteins express differential protein patterns in AD, FTD, and PD patients, which reflect divergent underlying pathophysiological mechanisms and neuropathological changes in these diseases.

  7. Genomic Biomarkers for Breast Cancer Risk.

    Science.gov (United States)

    Walsh, Michael F; Nathanson, Katherine L; Couch, Fergus J; Offit, Kenneth

    2016-01-01

    Clinical risk assessment for cancer predisposition includes a three-generation pedigree and physical examination to identify inherited syndromes. Additionally genetic and genomic biomarkers may identify individuals with a constitutional basis for their disease that may not be evident clinically. Genomic biomarker testing may detect molecular variations in single genes, panels of genes, or entire genomes. The strength of evidence for the association of a genomic biomarker with disease risk may be weak or strong. The factors contributing to clinical validity and utility of genomic biomarkers include functional laboratory analyses and genetic epidemiologic evidence. Genomic biomarkers may be further classified as low, moderate or highly penetrant based on the likelihood of disease. Genomic biomarkers for breast cancer are comprised of rare highly penetrant mutations of genes such as BRCA1 or BRCA2, moderately penetrant mutations of genes such as CHEK2, as well as more common genomic variants, including single nucleotide polymorphisms, associated with modest effect sizes. When applied in the context of appropriate counseling and interpretation, identification of genomic biomarkers of inherited risk for breast cancer may decrease morbidity and mortality, allow for definitive prevention through assisted reproduction, and serve as a guide to targeted therapy . PMID:26987529

  8. Drug discovery in ovarian cancer.

    Science.gov (United States)

    Chase, Dana M; Mathur, Nidhee; Tewari, Krishnansu S

    2010-11-01

    Drug discovery in the ovarian cancer arena has led to the activation of several important clinical trials. Many biologic agents have come down the pipeline and are being studied in phase II trials for recurrent disease. These agents include antivascular compounds that disrupt angiogenesis through a variety of mechanisms (e.g., prevention of ligand-binding to the vascular endothelial growth factor receptor-2 (VEGF-R2), high-affinity VEGF blockade, oral inhibitors of tyrosine kinases stimulated by VEGF, inhibition of alpha5beta1 integrin, neutralization of angioproteins, etc.). Other novel drugs include oral platinum compounds as well as those that antagonize the tumor proliferation genes in the Hedgehog pathway, and that target folic acid receptors which are expressed by ovarian cancer cells. In addition, studies are underway with oral agents that inhibit the tyrosine kinase activity associated with two oncogenes (epidermal growth factor receptor (EGFR) and HER-2/neu). Finally, emerging technologies in clinical trials include nanotechnology to enhance delivery of chemotherapy to ovarian tumors, drug resistance/sensitivity assays to guide therapy, and agents that mobilize and induce proliferation of hematopoetic progenitor cells to aid in red blood cell, white blood cell, and platelet recovery following chemotherapy. The relevant patents in drug discovery of ovarian cancer are discussed. PMID:20524931

  9. DETECTION OF CANCER BIOMARKERS WITH NANOTECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2013-01-01

    Full Text Available Early detection of cancer biomarkers with high precision is critically important for cancer therapy. A variety of sensors based on different nanostructured materials have attracted intensive research interest due to their potential for highly sensitive and selective detection of cancer biomarkers. This review covers the use of a variety of nanostructured materials, including carbon nanotubes, silicon nanowires, gold nanoparticles and quantum dots, in the fabrication of sensors. Emphases are placed on how the detection systems work and what detection limits can be achieved. Some assays described in this review outperform established methods for cancer biomarker detection. It is highly promising that these sensors would soon move into commercial-scale production and find routine use in hospitals.

  10. Molecular Imaging of Biomarkers in Breast Cancer

    Science.gov (United States)

    Ulaner, Gary A.; Riedl, Chris C.; Dickler, Maura N.; Jhaveri, Komal; Pandit-Taskar, Neeta; Weber, Wolfgang

    2016-01-01

    The success of breast cancer therapy is ultimately defined by clinical endpoints such as survival. It is valuable to have biomarkers that can predict the most efficacious therapies or measure response to therapy early in the course of treatment. Molecular imaging has a promising role in complementing and overcoming some of the limitations of traditional biomarkers by providing the ability to perform noninvasive, repeatable whole-body assessments. The potential advantages of imaging biomarkers are obvious and initial clinical studies have been promising, but proof of clinical utility still requires prospective multicenter clinical trials. PMID:26834103

  11. The National Cancer Program: Driving Discovery

    Science.gov (United States)

    An overview of NCI’s role in driving cancer research discoveries: conducting and funding research in challenging areas and providing resources and leadership to national infrastructures for cancer research.

  12. Mass Spectrometry-Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

    Science.gov (United States)

    Hawkridge, Adam M.; Muddiman, David C.

    2009-07-01

    Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry-based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed.

  13. Methylated genes as new cancer biomarkers.

    LENUS (Irish Health Repository)

    Duffy, M J

    2012-02-01

    Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested that measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2 for predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene methylation need to be standardised, simplified and evaluated in external quality assurance programmes. It is concluded that methylated genes have the potential to provide a new generation of cancer biomarkers.

  14. Discovery – Methotrexate: Chemotherapy Treatment for Cancer

    Science.gov (United States)

    Prior to the 1950s, treatment for the majority of cancers was limited to either surgery or the use of radiation. The discovery of the use of methotrexate in curing a rare cancer marked the first time a cancer had been cured. This led to the development of many of today’s common cancer treatments.

  15. Hypermethylated DNA, a Biomarker for colorectal cancer

    DEFF Research Database (Denmark)

    Rasmussen, Simon Ladefoged; Krarup, Henrik Bygum; Sunesen, Kåre Gotschalck;

    2016-01-01

    AIM: In colorectal cancer (CRC), improved methods for early detection are essential for increasing survival. Hypermethylated DNA in blood or stool has been proposed as a biomarker for CRC. In recent years, biochemical methods have improved, and several hypermethylated genes that are sensitive and...

  16. Identification of Biomarkers for Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Anna Meiliana

    2014-12-01

    Full Text Available BACKGROUND: Prostate cancer (PCa was the second most common type of cancer and the fifth leading cause of cancer-related death in men. The great challenge for physicians is being able to accurately predict PCa prognosis and treatment response in order to reduce PCa-speciic mortality while avoiding overtreatment by identifying of when to intervene, and in which patients. CONTENT: Currently, PCa prognosis and treatment decision of PCa involved digital rectal examination, Prostate-Speciic Antigens (PSA, and subsequent biopsies for histopathological staging, known as Gleason score. However, each procedure has its shortcomings. Efforts to find a better clinically meaningful and non-invasive biomarkers still developed involving proteins, circulating tumor cells, nucleic acids, and the ‘omics' approaches. SUMMARY: Biomarkers for PCa will most likely be an assay employing multiple biomarkers in combination using protein and gene microarrays, containing markers that are differentially expressed in PCa. KEYWORDS: prostate cancer, PSA, biomarkers, nomograms, miRNA, proteomic, genomic, metabolomic.

  17. 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

    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of...... European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and...... how the PREDICT consortium will endeavour to identify a new generation of predictive biomarkers....

  18. Current Stem Cell Biomarkers and Their Functional Mechanisms in Prostate Cancer

    Science.gov (United States)

    Zhang, Kaile; Zhou, Shukui; Wang, Leilei; Wang, Jianlong; Zou, Qingsong; Zhao, Weixin; Fu, Qiang; Fang, Xiaolan

    2016-01-01

    Currently there is little effective treatment available for castration resistant prostate cancer, which is responsible for the majority of prostate cancer related deaths. Emerging evidence suggested that cancer stem cells might play an important role in resistance to traditional cancer therapies, and the studies of cancer stem cells (including specific isolation and targeting on those cells) might benefit the discovery of novel treatment of prostate cancer, especially castration resistant disease. In this review, we summarized major biomarkers for prostate cancer stem cells, as well as their functional mechanisms and potential application in clinical diagnosis and treatment of patients. PMID:27447616

  19. Ovarian cancer biomarkers as diagnostic triage tests

    Directory of Open Access Journals (Sweden)

    Jordan SM

    2013-02-01

    Full Text Available Sara M Jordan, Robert E BristowDivision of Gynecologic Oncology, University of California, Irvine Medical Center, Orange, CA, USAAbstract: Ovarian cancer survival improves with accurate surgical staging, maximal tumor removal, and appropriate adjuvant chemotherapy. Therefore, survival is higher among patients managed by a gynecologic oncologist trained in these surgical techniques. Unfortunately, identifying patients preoperatively for referral to a gynecologic oncologist is often challenging, given that there are no definitive noninvasive diagnostic tests to triage patients with an adnexal mass to a surgical subspecialist. Inaccurate preoperative diagnosis of an adnexal mass frequently results in either unnecessary surgery for a benign mass or inadequate surgical staging for a malignant mass, with a subsequent negative effect on overall survival. Several recent tests have been investigated to improve the preoperative diagnosis of women presenting with adnexal masses. Cancer antigen 125 is the most commonly used serum marker for screening and monitoring of ovarian cancer, but is elevated in many benign conditions and falsely normal in 50% of early-stage epithelial ovarian cancers. The relatively low sensitivity and specificity of CA125 has driven researchers to identify new biomarkers and algorithms to assist with triaging adnexal masses. A promising new biomarker, human epididymis protein 4, has been developed to monitor for recurrence of ovarian cancer. Three algorithms have also been developed, ie, risk of malignancy index, risk of ovarian malignancy algorithm, and OVA-1, which is the first diagnostic algorithm that combines multiple biomarkers for the purpose of triaging adnexal masses to be approved by the US Food and Drug Administration.Keywords: ovarian cancer, biomarkers, CA125, RMI, ROMA, HE4, OVA-1

  20. Methylated genes as new cancer biomarkers

    DEFF Research Database (Denmark)

    Brunner, Nils; Duffy, M.J; Napieralski, R.;

    2009-01-01

    measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2 for...... predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene...

  1. Integration of Proteomics, Bioinformatics and Systems biology in Brain Injury Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    JoyGuingab-Cagmat

    2013-05-01

    Full Text Available Traumatic brain injury (TBI is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed.

  2. Integration of proteomics, bioinformatics, and systems biology in traumatic brain injury biomarker discovery.

    Science.gov (United States)

    Guingab-Cagmat, J D; Cagmat, E B; Hayes, R L; Anagli, J

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their efficacy as TBI biomarkers. However, several hurdles have to be overcome even during the discovery phase which is only the first step in the long process of biomarker development. The high-throughput nature of MS-based proteomic experiments generates a massive amount of mass spectral data presenting great challenges in downstream interpretation. Currently, different bioinformatics platforms are available for functional analysis and data mining of MS-generated proteomic data. These tools provide a way to convert data sets to biologically interpretable results and functional outcomes. A strategy that has promise in advancing biomarker development involves the triad of proteomics, bioinformatics, and systems biology. In this review, a brief overview of how bioinformatics and systems biology tools analyze, transform, and interpret complex MS datasets into biologically relevant results is discussed. In addition, challenges and limitations of proteomics, bioinformatics, and systems biology in TBI biomarker discovery are presented. A brief survey of researches that utilized these three overlapping disciplines in TBI biomarker discovery is also presented. Finally, examples of TBI biomarkers and their applications are discussed. PMID:23750150

  3. Clinical proteomics for liver disease: a promising approach for discovery of novel biomarkers

    Directory of Open Access Journals (Sweden)

    Tsubouchi Hirohito

    2010-12-01

    Full Text Available Abstract Hepatocellular carcinoma (HCC is the fifth most common cancer and advanced hepatic fibrosis is a major risk factor for HCC. Hepatic fibrosis including liver cirrhosis and HCC are mainly induced by persistent hepatitis B or C virus infection, with approximately 500 million people infected with hepatitis B or C virus worldwide. Furthermore, the number of patients with non-alcoholic fatty liver disease (NAFLD has recently increased and NAFLD can progress to cirrhosis and HCC. These chronic liver diseases are major causes of morbidity and mortality, and the identification of non-invasive biomarkers is important for early diagnosis. Recent advancements in quantitative and large-scale proteomic methods could be used to optimize the clinical application of biomarkers. Early diagnosis of HCC and assessment of the stage of hepatic fibrosis or NAFLD can also contribute to more effective therapeutic interventions and an improve prognosis. Furthermore, advancements of proteomic techniques contribute not only to the discovery of clinically useful biomarkers, but also in clarifying the molecular mechanisms of disease pathogenesis by using body fluids, such as serum, and tissue samples and cultured cells. In this review, we report recent advances in quantitative proteomics and several findings focused on liver diseases, including HCC, NAFLD, hepatic fibrosis and hepatitis B or C virus infections.

  4. Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

    Full Text Available The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility.

  5. Using Aptamers for Cancer Biomarker Discovery

    OpenAIRE

    Yun Min Chang; Donovan, Michael J; Weihong Tan

    2013-01-01

    Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment) SELEX and cell-based SELEX (cell-SELEX). Aptamers can be paired with recent advances in nanotechnology, microarray...

  6. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

    Fagö-Olsen, Carsten Lindberg; Ottesen, Bent; Christensen, Ib Jarle; Høgdall, Estrid; Lundvall, Lene; Nedergaard, Lotte; Engelholm, Svend-Aage; Antonsen, Sofie Leisby; Lydolph, Magnus; Høgdall, Claus

    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.......64. CONCLUSION: Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer....

  7. Cancer Hallmarks, Biomarkers and Breast Cancer Molecular Subtypes.

    Science.gov (United States)

    Dai, Xiaofeng; Xiang, Liangjian; Li, Ting; Bai, Zhonghu

    2016-01-01

    Breast cancer is a complex disease encompassing multiple tumor entities, each characterized by distinct morphology, behavior and clinical implications. Besides estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2, novel biomarkers have shown their prognostic and predictive values, complicating our understanding towards to the heterogeneity of such cancers. Ten cancer hallmarks have been proposed by Weinberg to characterize cancer and its carcinogenesis. By reviewing biomarkers and breast cancer molecular subtypes, we propose that the divergent outcome observed from patients stratified by hormone status are driven by different cancer hallmarks. 'Sustaining proliferative signaling' further differentiates cancers with positive hormone receptors. 'Activating invasion and metastasis' and 'evading immune destruction' drive the differentiation of triple negative breast cancers. 'Resisting cell death', 'genome instability and mutation' and 'deregulating cellular energetics' refine breast cancer classification with their predictive values. 'Evading growth suppressors', 'enabling replicative immortality', 'inducing angiogenesis' and 'tumor-promoting inflammation' have not been involved in breast cancer classification which need more focus in the future biomarker-related research. This review novels in its global view on breast cancer heterogeneity, which clarifies many confusions in this field and contributes to precision medicine. PMID:27390604

  8. Approach to Cerebrospinal Fluid (CSF) Biomarker Discovery and Evaluation in HIV Infection

    Energy Technology Data Exchange (ETDEWEB)

    Price, Richard W.; Peterson, Julia; Fuchs, Dietmar; Angel, Thomas E.; Zetterberg, Henrik; Hagberg, Lars; Spudich, Serena S.; Smith, Richard D.; Jacobs, Jon M.; Brown, Joseph N.; Gisslen, Magnus

    2013-12-13

    Central nervous system (CNS) infection is a nearly universal facet of systemic HIV infection that varies in character and neurological consequences. While clinical staging and neuropsychological test performance have been helpful in evaluating patients, cerebrospinal fluid (CSF) biomarkers present a valuable and objective approach to more accurate diagnosis, assessment of treatment effects and understanding of evolving pathobiology. We review some lessons from our recent experience with CSF biomarker studies. We have used two approaches to biomarker analysis: targeted, hypothesis-driven and non-targeted exploratory discovery methods. We illustrate the first with data from a cross-sectional study of defined subject groups across the spectrum of systemic and CNS disease progression and the second with a longitudinal study of the CSF proteome in subjects initiating antiretroviral treatment. Both approaches can be useful and, indeed, complementary. The first is helpful in assessing known or hypothesized biomarkers while the second can identify novel biomarkers and point to broad interactions in pathogenesis. Common to both is the need for well-defined samples and subjects that span a spectrum of biological activity and biomarker concentrations. Previouslydefined guide biomarkers of CNS infection, inflammation and neural injury are useful in categorizing samples for analysis and providing critical biological context for biomarker discovery studies. CSF biomarkers represent an underutilized but valuable approach to understanding the interactions of HIV and the CNS and to more objective diagnosis and assessment of disease activity. Both hypothesis-based and discovery methods can be useful in advancing the definition and use of these biomarkers.

  9. Research status and funding trends of lung cancer biomarkers

    OpenAIRE

    Li, Cui; Hong, Wei

    2013-01-01

    Lung cancer is one of malignant tumors with the highest morbidity and mortality in the world. At present, research of early diagnosis, treatment, prognosis, and metastasis associated biomarkers is most active. This article reviewed the research status of lung cancer biomarkers and analyzed the funding situation in the field of lung cancer markers in recent 10 years in China and abroad, to provide a reference for the future basic and clinical translational research of lung cancer biomarkers.

  10. Risk Factors and Biomarkers of Ischemic Stroke in Cancer Patients

    OpenAIRE

    Kim, Kwangsoo; Lee, Ji-Hun

    2014-01-01

    Background and Purpose Stroke is common among cancer patients. However, risk factors and biomarkers of stroke in cancer patients are not well established. This study aimed to investigate risk factors and biomarkers as well as etiology of ischemic stroke in cancer patients. Methods A retrospective review was conducted in cancer patients with ischemic stroke who were admitted to a general hospital in Busan, Korea, between January 2003 and December 2012. The risk factors and biomarkers for strok...

  11. Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies

    Directory of Open Access Journals (Sweden)

    Rowan E. Moore

    2007-01-01

    Full Text Available The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.

  12. Integration of Proteomics, Bioinformatics, and Systems Biology in Traumatic Brain Injury Biomarker Discovery

    OpenAIRE

    Guingab-Cagmat, J.D.; Cagmat, E.B.; Hayes, R. L.; Anagli, J.

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for their...

  13. Integration of Proteomics, Bioinformatics and Systems biology in Brain Injury Biomarker Discovery

    OpenAIRE

    JoyGuingab-Cagmat

    2013-01-01

    Traumatic brain injury (TBI) is a major medical crisis without any FDA-approved pharmacological therapies that have been demonstrated to improve functional outcomes. It has been argued that discovery of disease-relevant biomarkers might help to guide successful clinical trials for TBI. Major advances in mass spectrometry (MS) have revolutionized the field of proteomic biomarker discovery and facilitated the identification of several candidate markers that are being further evaluated for thei...

  14. Mitochondrial DNA as a Cancer Biomarker

    OpenAIRE

    Jakupciak, John P.; Wang, Wendy; Markowitz, Maura E; Ally, Delphine; Coble, Michael; Srivastava, Sudhir; Maitra, Anirban; Barker, Peter E.; Sidransky, David; O’Connell, Catherine D.

    2005-01-01

    As part of a national effort to identify biomarkers for the early detection of cancer, we developed a rapid and high-throughput sequencing protocol for the detection of sequence variants in mitochondrial DNA. Here, we describe the development and implementation of this protocol for clinical samples. Heteroplasmic and homoplasmic sequence variants occur in the mitochondrial genome in patient tumors. We identified these changes by sequencing mitochondrial DNA obtained from tumors and blood from...

  15. Discovery – Preventing Skin Cancer

    Science.gov (United States)

    Cancer research includes stopping cancer before it spreads. NCI funded the development of the Melanoma Risk Assessment Tool and the ABC method. Both help to diagnose high-risk patients and prevent melanoma earlier in the fight against skin cancer.

  16. Biomarkers and Pharmacogenetics in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Xunhai Xu

    2011-07-01

    Full Text Available Appropriate identification and validation of biomarkers as well as pharmacogenetics are important in formulating patient-oriented, individualized chemotherapy or biological therapy in cancer patients. These markers can be especially valuable in pancreatic cancer, where high mortality and complex disease biology are frequently encountered. Recently, several advances have been made to further our knowledge in this specific area of pancreatic cancer. In the 2011 American Society of Clinical Oncology (ASCO Annual Meeting, researchers have presented several interesting results in biomarkers development: the identifications of 9 single nucleotide polymorphisms (SNPs that is associated with positive efficacy of gemcitabine (Abstract #4022; the introduction of circulating tumor cells as a prognostic markers in pancreatic adenocarcinoma (Abstract #e14657; the re-affirmation of plasma cytidine deaminase (CDA as a positive predictive markers for gemcitabine efficacy, as well as the postulations that CDA*3 as a potential genotype marker to predict gemcitabine responses (Abstract #e14645; and finally the retrospective tumor tissues analysis in the Arbeitsgemeinschaft Internistische Onkologie (AIO trial in an attempt for epidermal growth factor receptor (EGFR pathway biomarker identifications (Abstract #4047

  17. Integrating biomarkers in colorectal cancer trials in the West and China.

    Science.gov (United States)

    Tejpar, Sabine; Shen, Lin; Wang, Xicheng; Schilsky, Richard L

    2015-09-01

    The discovery of biomarkers that provide information on drug efficacy is recognized as essential for successful and cost-effective treatment of cancer. However, biomarker discovery is difficult, and requires multiple independent studies to identify a target that serves as a suitable predictor of efficacy and to ensure appropriate biomarker validation. Clinical trials that are performed, sometimes sequentially, in Europe, the USA or Asia, are often similar in their design, in part owing to regulatory, marketing, or safety considerations. We believe some of these trials offer additional unique opportunities for biomarker discovery or validation. There are multiple hurdles to overcome, such as homogenous tissue acquisition and analysis, defining and aligning biomarker hypotheses across trials, and the need to adapt sample sizes and trial designs. Nevertheless, we believe that a collaborative engagement of the academic, regulatory and pharmaceutical community can go a long way in addressing these issues and producing more-rapid results in the field of personalized medicine. In this Perspectives, we describe our views on the current fragmented approach to biomarker discovery and validation in relevant trials run within our own regions-that is, Europe, China, and the USA-and hope this article serves as a base for further reflection. PMID:25963094

  18. Milestones in Cancer Research and Discovery

    Science.gov (United States)

    During the past 250 years, we have witnessed many landmark discoveries in our efforts to make progress against cancer, an affliction known to humanity for thousands of years. This timeline shows a few key milestones in the history of cancer research.

  19. MicroRNA biomarkers in whole blood for detection of pancreatic cancer

    DEFF Research Database (Denmark)

    Schultz, Nicolai A; Dehlendorff, Christian; Jensen, Benny V;

    2014-01-01

    IMPORTANCE Biomarkers for the early diagnosis of patients with pancreatic cancer are needed to improve prognosis. OBJECTIVES To describe differences in microRNA expression in whole blood between patients with pancreatic cancer, chronic pancreatitis, and healthy participants and to identify panels...... of microRNAs for use in diagnosis of pancreatic cancer compared with the cancer antigen 19-9 (CA19-9). DESIGN, SETTING, AND PARTICIPANTS A case-control study that included 409 patients with pancreatic cancer and 25 with chronic pancreatitis who had been included prospectively in the Danish BIOPAC...... (Biomarkers in Patients with Pancreatic Cancer) study (July 2008-October 2012) plus 312 blood donors as healthy participants. The microRNA expressions in pretreatment whole blood RNA samples were collected and analyzed in 3 randomly determined subcohorts: discovery cohort (143 patients with pancreatic cancer...

  20. Proteomics of pediatric heart failure: from traditional biomarkers to new discovery strategies.

    Science.gov (United States)

    Xu, Mingguo; Ramirez-Correa, Genaro A; Murphy, Anne M

    2015-08-01

    Heart failure in children is a complex clinical syndrome with multiple aetiologies. The underlying disorders that lead to heart failure in children differ significantly from those in adults. Some clinical biomarkers for heart failure status and prognosis appear to be useful in both age groups. This review outlines the use and the present status of biomarkers for heart failure in paediatric cardiology. Furthermore, clinical scenarios in which development of new biomarkers might address management or prognosis are discussed. Finally, strategies for proteomic discovery of novel biomarkers and application to practice are described. PMID:26377710

  1. Translating colorectal cancer genetics into clinically useful biomarkers.

    Science.gov (United States)

    Morley-Bunker, A; Walker, L C; Currie, M J; Pearson, J; Eglinton, T

    2016-08-01

    Colorectal cancer (CRC) is a major health problem worldwide accounting for over a million deaths annually. While many patients with Stage II and III CRC can be cured with combinations of surgery, radiotherapy and chemotherapy, this is morbid costly treatment and a significant proportion will suffer recurrence and eventually die of CRC. Increased understanding of the molecular pathogenesis of CRC has the potential to identify high risk patients and target therapy more appropriately. Despite increased understanding of the molecular events underlying CRC development, established molecular techniques have only produced a limited number of biomarkers suitable for use in routine clinical practice to predict risk, prognosis and response to treatment. Recent rapid technological developments, however, have made genomic sequencing of CRC more economical and efficient, creating potential for the discovery of genetic biomarkers that have greater diagnostic, prognostic and therapeutic capabilities for the management of CRC. This paper reviews the current understanding of the molecular pathogenesis of CRC, and summarizes molecular biomarkers that surgeons will encounter in current clinical use as well as those under development in clinical and preclinical trials. New molecular technologies are reviewed together with their potential impact on the understanding of the molecular pathogenesis of CRC and their potential clinical utility in classification, diagnosis, prognosis and targeting of therapy. PMID:26990814

  2. Tumor interstitial fluid - a treasure trove of cancer biomarkers.

    Science.gov (United States)

    Gromov, Pavel; Gromova, Irina; Olsen, Charlotta J; Timmermans-Wielenga, Vera; Talman, Mai-Lis; Serizawa, Reza R; Moreira, José M A

    2013-11-01

    Tumor interstitial fluid (TIF) is a proximal fluid that, in addition to the set of blood soluble phase-borne proteins, holds a subset of aberrantly externalized components, mainly proteins, released by tumor cells and tumor microenvironment through various mechanisms, which include classical secretion, non-classical secretion, secretion via exosomes and membrane protein shedding. Consequently, the interstitial aqueous phase of solid tumors is a highly promising resource for the discovery of molecules associated with pathological changes in tissues. Firstly, it allows one to delve deeper into the regulatory mechanisms and functions of secretion-related processes in tumor development. Secondly, the anomalous secretion of molecules that is innate to tumors and the tumor microenvironment, being associated with cancer progression, offers a valuable source for biomarker discovery and possible targets for therapeutic intervention. Here we provide an overview of the features of tumor-associated interstitial fluids, based on recent and updated information obtained mainly from our studies of breast cancer. Data from the study of interstitial fluids recovered from several other types of cancer are also discussed. This article is a part of a Special Issue entitled: The Updated Secretome. PMID:23416532

  3. New serum biomarkers for prostate cancer diagnosis

    Science.gov (United States)

    Chadha, Kailash C.; Miller, Austin; Nair, Bindukumar B.; Schwartz, Stanley A.; Trump, Donald L.; Underwood, Willie

    2014-01-01

    Background Prostate-specific antigen (PSA) is currently used as a biomarker for diagnosis and management of prostate cancer (CaP). However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker. Objective The goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP. Methods Concurrent measurements of circulating interleukin-8 (IL-8), Tumor necrosis factor-α (TNF-α) and soluble tumor necrosis factor-α receptors 1 (sTNFR1) were obtained from four groups of men: (1) Controls (2) with elevated prostate-specific antigen with a negative prostate biopsy (elPSA_negBx) (3) with clinically localized CaP and (4) with castration resistant prostate cancer. Results TNF-α Area under the receiver operating characteristic curve (AUC = 0.93) and sTNFR1 (AUC = 0.97) were strong predictors of elPSA_negBx (vs. CaP). The best predictor of elPSA_negBx vs CaP was sTNFR1 and IL-8 combined (AUC = 0.997). The strongest single predictors of localized versus metastatic CaP were TNF-α (AUC = 0.992) and PSA (AUC = 0.963) levels. Conclusions The specificity and sensitivity of a PSA-based CaP diagnosis can be significantly enhanced by concurrent serum measurements of IL-8, TNF-α and sTNFR1. In view of the concerns about the ability of PSA to distinguish clinically relevant CaP from indolent disease, assessment of these biomarkers in the larger cohort is warranted. PMID:25593898

  4. New serum biomarkers for prostate cancer diagnosis

    Directory of Open Access Journals (Sweden)

    Kailash C Chadha

    2014-01-01

    Full Text Available Background: Prostate-specific antigen (PSA is currently used as a biomarker for diagnosis and management of prostate cancer (CaP. However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker. Objective: The goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP. Methods: Concurrent measurements of circulating interleukin-8 (IL-8, Tumor necrosis factor-α (TNF-α and soluble tumor necrosis factor-α receptors 1 (sTNFR1 were obtained from four groups of men: (1 Controls (2 with elevated prostate-specific antigen with a negative prostate biopsy (elPSA_negBx (3 with clinically localized CaP and (4 with castration resistant prostate cancer. Results: TNF-α Area under the receiver operating characteristic curve (AUC = 0.93 and sTNFR1 (AUC = 0.97 were strong predictors of elPSA_negBx (vs. CaP. The best predictor of elPSA_negBx vs CaP was sTNFR1 and IL-8 combined (AUC = 0.997. The strongest single predictors of localized versus metastatic CaP were TNF-α (AUC = 0.992 and PSA (AUC = 0.963 levels. Conclusions: The specificity and sensitivity of a PSA-based CaP diagnosis can be significantly enhanced by concurrent serum measurements of IL-8, TNF-α and sTNFR1. In view of the concerns about the ability of PSA to distinguish clinically relevant CaP from indolent disease, assessment of these biomarkers in the larger cohort is warranted.

  5. Testicular cancer: biology and biomarkers.

    Science.gov (United States)

    Looijenga, Leendert H J; Stoop, Hans; Biermann, Katharina

    2014-03-01

    The term "human germ cell tumors" (GCTs) refers to a heterogeneous group of neoplasms, all with a defined histological appearance. They have specific epidemiological characteristics, clinical behavior, and pathogenesis. Histologically, GCTs contain various tissue elements, which are homologs of normal embryogenesis. We have proposed a subclassification of GCTs in five subtypes, three of which preferentially occur in the testis. These include teratomas and yolk sac tumors of neonates and infants (type I), seminomas and nonseminomas of (predominantly) adolescents and adults (type II), and spermatocytic seminomas of the elderly (type III). Both spontaneous and induced animal models have been reported, of which the relevance for human GCTs is still to be clarified. Multidisciplinary studies have recently shed new light on the (earliest steps in the) pathogenesis of GCTs, mainly in regard of malignant type II GCTs (germ cell cancer (GCC)). This review discusses novel understanding of the pathogenesis of (mainly) GCC, focusing on identification of informative diagnostic markers suitable for application in a clinical setting. These include OCT3/4, SOX9/FOXL2, SOX17/SOX2, as well as embryonic microRNAs. These markers have been identified through studies on normal embryogenesis, specifically related to the gonads, including the germ cell lineage. Their strengths and limitations are discussed as well as the expected future approach to identify the group of individuals at highest risk for development of a GCC. The latter would allow screening of defined populations, early diagnosis, optimal follow-up, and potentially early treatment, preventing long-term side effects of systemic treatment. PMID:24487784

  6. Discovery of Novel Biomarkers for Alzheimer's Disease from Blood

    Science.gov (United States)

    Long, Jintao; Pan, Genhua; Ifeachor, Emmanuel; Belshaw, Robert; Li, Xinzhong

    2016-01-01

    Blood-based biomarkers for Alzheimer's disease would be very valuable because blood is a more accessible biofluid and is suitable for repeated sampling. However, currently there are no robust and reliable blood-based biomarkers for practical diagnosis. In this study we used a knowledge-based protein feature pool and two novel support vector machine embedded feature selection methods to find panels consisting of two and three biomarkers. We validated these biomarker sets using another serum cohort and an RNA profile cohort from the brain. Our panels included the proteins ECH1, NHLRC2, HOXB7, FN1, ERBB2, and SLC6A13 and demonstrated promising sensitivity (>87%), specificity (>91%), and accuracy (>89%). PMID:27418712

  7. Development and evaluation of statistical approaches in proteomic biomarker discovery

    OpenAIRE

    Patel, Amit

    2011-01-01

    A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacological responses to a therapeutic intervention. The aim of this project was to deal with the identification of potential biomarker candidates from experimental data comparing samples displaying divergent physiological traits. Chapter 1 introduces the topic and the aims of the project. The primary aim was to identify the ideal statistical a...

  8. Sparse discriminant analysis for breast cancer biomarker identification and classification

    Institute of Scientific and Technical Information of China (English)

    Yu Shi; Daoqing Dai; Chaochun Liu; Hong Yan

    2009-01-01

    Biomarker identification and cancer classification are two important procedures in microarray data analysis. We propose a novel uni-fied method to carry out both tasks. We first preselect biomarker candidates by eliminating unrelated genes through the BSS/WSS ratio filter to reduce computational cost, and then use a sparse discriminant analysis method for simultaneous biomarker identification and cancer classification. Moreover, we give a mathematical justification about automatic biomarker identification. Experimental results show that the proposed method can identify key genes that have been verified in biochemical or biomedical research and classify the breast cancer type correctly.

  9. Colorectal Cancer Biomarkers: Where Are We Now?

    Directory of Open Access Journals (Sweden)

    Maria Gonzalez-Pons

    2015-01-01

    Full Text Available Colorectal cancer is one of the major causes of cancer-related death in the Western world. Patient survival is highly dependent on the tumor stage at the time of diagnosis. Reduced sensitivity to chemotherapy is still a major obstacle in effective treatment of advanced disease. Due to the fact that colorectal cancer is mostly asymptomatic until it progresses to advanced stages, the implementation of screening programs aimed at early detection is essential to reduce incidence and mortality rates. Current screening and diagnostic methods range from semi-invasive procedures such as colonoscopy to noninvasive stool-based tests. The combination of the absence of symptoms, the semi-invasive nature of currently used methods, and the suboptimal accuracy of fecal blood tests results in colorectal cancer diagnosis at advanced stages in a significant number of individuals. Alterations in gene expression leading to colorectal carcinogenesis are reflected in dysregulated levels of nucleic acids and proteins, which can be used for the development of novel, minimally invasive molecular biomarkers. The purpose of this review is to discuss the commercially available colorectal cancer molecular diagnostic methods as well as to highlight some of the new candidate predictive and prognostic molecular markers for tumor, stool, and blood samples.

  10. Cell-free microRNAs in blood and other body fluids, as cancer biomarkers.

    Science.gov (United States)

    Ortiz-Quintero, Blanca

    2016-06-01

    The discovery of cell-free microRNAs (miRNAs) in serum, plasma and other body fluids has yielded an invaluable potential source of non-invasive biomarkers for cancer and other non-malignant diseases. miRNAs in the blood and other body fluids are highly stable in biological samples and are resistant to environmental conditions, such as freezing, thawing or enzymatic degradation, which makes them convenient as potential biomarkers. In addition, they are more easily sampled than tissue miRNAs. Altered levels of cell-free miRNAs have been found in every type of cancer analysed, and increasing evidence indicates that they may participate in carcinogenesis by acting as cell-to-cell signalling molecules. This review summarizes the biological characteristics and mechanisms of release of cell-free miRNAs that make them promising candidates as non-invasive biomarkers of cancer. PMID:27218664

  11. Circulating microRNAs as minimally invasive biomarkers for cancer theragnosis and prognosis

    Directory of Open Access Journals (Sweden)

    William C. S. Cho

    2011-02-01

    Full Text Available Novel cancer biomarker discovery is urgently needed for cancer theragnosis and prognosis, and among the many possible types of samples, blood is regarded to be ideal for this discovery as it can be collected easily in a minimally invasive manner. Results of the last few years have ascertained the quantification of microRNA (miRNA as a promising approach for the detection and prognostication of cancer. Indeed, an increasing number of studies have shown that circulating cancer-associated miRNAs are readily measured in plasma or serum and they can robustly discriminate cancer patients from healthy controls, as well as distinguishing between good-prognosis and poor-prognosis patients. Furthermore, recent findings also suggest the potential of circulating miRNAs in the screening, monitoring, and treatment of cancer. This article summarizes the most significant and latest discoveries of original researches on circulating miRNAs involvement in cancer, focusing on the potential of circulating miRNAs as minimally invasive biomarkers for cancer theragnosis and prognosis.

  12. Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.

    OpenAIRE

    Barbara Di Camillo; Tiziana Sanavia; Matteo Martini; Giuseppe Jurman; Francesco Sambo; Annalisa Barla; Margherita Squillario; Cesare Furlanello; Gianna Toffolo; Claudio Cobelli

    2012-01-01

    MOTIVATION: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1) dataset size (few subjects with respect to the number of features); 2) heterogeneity of the disease; 3) heterogeneity of experimental protocols and computational pipelines employed in the a...

  13. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...... conditions tested. Jack-knife PLSR, however, was to some extent improved by modifying the variable selection criterion, and was much less time-consuming to run. Sparse PLSR may therefore be the method of choice when dealing with spectroscopic data, where the level of noise is relatively low, while for...... model for humans. By Sparse MBPLSR, potential biomarkers from LC-MS and NMR data could be detected and the relationships among the measurement variables of both analytical methods could be studied. Detection of potential biomarkers is followed up by an identification process through online metabolite...

  14. Including network knowledge into Cox regression models for biomarker signature discovery.

    Science.gov (United States)

    Fröhlich, Holger

    2014-03-01

    Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step toward a better personalized medicine. During the last decade various methods have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Most of these methods focus on classification problems, that is learn a model from data that discriminates patients into distinct clinical groups. Far less has been published on approaches that predict a patient's event risk. In this paper, we investigate eight methods that integrate network information into multivariable Cox proportional hazard models for risk prediction in breast cancer. We compare the prediction performance of our tested algorithms via cross-validation as well as across different datasets. In addition, we highlight the stability and interpretability of obtained gene signatures. In conclusion, we find GeneRank-based filtering to be a simple, computationally cheap and highly predictive technique to integrate network information into event time prediction models. Signatures derived via this method are highly reproducible. PMID:24430933

  15. Emerging Therapeutic Biomarkers in Endometrial Cancer

    Directory of Open Access Journals (Sweden)

    Peixin Dong

    2013-01-01

    Full Text Available Although clinical trials of molecular therapies targeting critical biomarkers (mTOR, epidermal growth factor receptor/epidermal growth factor receptor 2, and vascular endothelial growth factor in endometrial cancer show modest effects, there are still challenges that might remain regarding primary/acquired drug resistance and unexpected side effects on normal tissues. New studies that aim to target both genetic and epigenetic alterations (noncoding microRNA underlying malignant properties of tumor cells and to specifically attack tumor cells using cell surface markers overexpressed in tumor tissue are emerging. More importantly, strategies that disrupt the cancer stem cell/epithelial-mesenchymal transition-dependent signals and reactivate antitumor immune responses would bring new hope for complete elimination of all cell compartments in endometrial cancer. We briefly review the current status of molecular therapies tested in clinical trials and mainly discuss the potential therapeutic candidates that are possibly used to develop more effective and specific therapies against endometrial cancer progression and metastasis.

  16. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mor, Gil G; Ward, David C; Bray-Ward, Patricia

    2015-03-10

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  17. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

    Mor, Gil G. (Cheshire, CT); Ward, David C. (Las Vegas, NV); Bray-Ward, Patricia (Las Vegas, NV)

    2010-02-23

    The claimed invention describes methods to diagnose or aid in the diagnosis of cancer. The claimed methods are based on the identification of biomarkers which are particularly well suited to discriminate between cancer subjects and healthy subjects. These biomarkers were identified using a unique and novel screening method described herein. The biomarkers identified herein can also be used in the prognosis and monitoring of cancer. The invention comprises the use of leptin, prolactin, OPN and IGF-II for diagnosing, prognosis and monitoring of ovarian cancer.

  18. Biomarker discovery in systemic sclerosis: state of the art

    Directory of Open Access Journals (Sweden)

    Bonella F

    2015-07-01

    Full Text Available Francesco Bonella,1 Giuseppe Patuzzo,2 Claudio Lunardi2 1Interstitial and Rare Lung Disease Unit, Ruhrlandklinik University Hospital, University of Duisburg-Essen, Essen, Germany; 2Department of Medicine, University of Verona, Verona, Italy Abstract: Systemic sclerosis (SSc is an autoimmune disease characterized by immune dysfunction and by abnormalities of the microvasculature with vascular obliteration, eventually leading to fibrosis of the skin, gastrointestinal tract, lungs, heart, and kidney. The etiology and pathogenesis of SSc remain unclear, despite recent significant progress in the field. Immune activation and microangiopathy are followed by widespread organ fibrosis, leading to organ failure and increased mortality. The production of inflammatory cytokines and growth factors after tissue injury, as well as the presence of circulating autoantibodies, provide a source of biomarkers with potential diagnostic and prognostic applications in the clinical routine. Two principal approaches exist to discover and characterize biomarkers. The proof-of-concept approach verifies the ability of known proteins, generally involved in the pathogenesis, to correlate with disease phenotype and outcome. A proteomic approach does not need prior knowledge of the proteins or of their function, but it requires high-performance and time-consuming techniques. In this review, we highlight the most recent findings in biomarkers used to characterize SSc organ involvement, to stratify the patients, and to assess the response to treatment. Keywords: systemic sclerosis, biomarkers, proteomics, gene expression profiling

  19. Biomarker discovery in asthma and COPD: Application of proteomics techniques in human and mice

    Directory of Open Access Journals (Sweden)

    Steven Haenen

    2014-09-01

    Full Text Available The use of advanced proteomics approaches in the search for biomarkers in chronic lung diseases, such as asthma and COPD, is rather limited. Asthma and COPD are complex disorders, which can be subdivided into several phenotypes. This results in a heterogeneity of differential expressed biological molecules. Furthermore, genetic differences between animals and humans make ‘translation’ of possible biomarkers challenging. Yet, the improved sensitivity and high throughput of proteomic techniques could be an important asset for (new protein biomarker discovery in either human or animal models. We have reviewed the literature that reported the use of different proteomics approaches performed on samples obtained from humans and murine models in asthma and COPD research for the discovery of new biomarkers of diseases, biomarkers of sensitization or for the refinement of treatment. There is an increasing trend in the use of proteomics to explore new biomarkers of asthma or COPD. Although several murine models have been developed to study these lung diseases, and proteomics studies have been performed, ‘translation’ of identified candidate biomarkers into clinical studies is often lacking.

  20. Immunodiagnosis of tuberculosis: a dynamic view of biomarker discovery

    OpenAIRE

    Kunnath-Velayudhan, S.; Gennaro, M L

    2011-01-01

    Summary: Infection with Mycobacterium tuberculosis causes a variety of clinical conditions ranging from life-long asymptomatic infection to overt disease with increasingly severe tissue damage and a heavy bacillary burden. Immune biomarkers should follow the evolution of infection and disease because the host immune response is at the core of protection against disease and tissue damage in M. tuberculosis infection. Moreover, levels of immune markers are often affected by the antigen load. We...

  1. Manifold Learning for Biomarker Discovery in MR Imaging

    Science.gov (United States)

    Wolz, Robin; Aljabar, Paul; Hajnal, Joseph V.; Rueckert, Daniel

    We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of each image in such a low-dimensional space captures information about structural shape and appearance and, when a phenotype exists, about the subject's clinical state. A key contribution is that we propose a method for incorporating longitudinal image information in the learned manifold. In particular, we compare simultaneously embedding baseline and follow-up scans into a single manifold with the combination of separate manifold representations for inter-subject and intra-subject variation. We apply the proposed methods to 362 subjects enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI) and classify healthy controls, subjects with Alzheimer's disease (AD) and subjects with mild cognitive impairment (MCI). Learning manifolds based on both the appearance and temporal change of the hippocampus, leads to correct classification rates comparable with those provided by state-of-the-art automatic segmentation estimates of hippocampal volume and atrophy. The biomarkers identified with the proposed method are data-driven and represent a potential alternative to a-priori defined biomarkers derived from manual or automated segmentations.

  2. Clinical Use of Cancer Biomarkers in Epithelial Ovarian Cancer

    DEFF Research Database (Denmark)

    Söletormos, Georg; Duffy, Michael J; Othman Abu Hassan, Suher; Verheijen, René H M; Tholander, Bengt; Bast, Robert C; Gaarenstroom, Katja N; Sturgeon, Catharine M; Bonfrer, Johannes M; Petersen, Per Hyltoft; Troonen, Hugo; CarloTorre, Gian; Kanty Kulpa, Jan; Tuxen, Malgorzata K; Molina, Raphael

    2016-01-01

    OBJECTIVE: To present an update of the European Group on Tumor Markers guidelines for serum markers in epithelial ovarian cancer. METHODS: Systematic literature survey from 2008 to 2013. The articles were evaluated by level of evidence and strength of recommendation. RESULTS: Because of its low...... sensitivity (50-62% for early stage epithelial ovarian cancer) and limited specificity (94-98.5%), cancer antigen (CA) 125 (CA125) is not recommended as a screening test in asymptomatic women. The Risk of Malignancy Index, which includes CA125, transvaginal ultrasound, and menopausal status, is recommended...... candidate for secondary cytoreductive surgery. CONCLUSIONS: At present, CA125 remains the most important biomarker for epithelial ovarian cancer, excluding tumors of mucinous origin.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives...

  3. Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

    OpenAIRE

    Li, Gerald; Bankhead, Peter; Dunne, Philip D.; O'Reilly, Paul G; James, Jacqueline A.; Salto-Tellez, Manuel; Hamilton, Peter; McArt, Darragh G.

    2016-01-01

    Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative anal...

  4. A New Serum Biomarker for Lung Cancer - Transthyretin

    Directory of Open Access Journals (Sweden)

    Liyun LIU

    2009-04-01

    Full Text Available Background and objective Lung cancer is the leading cause of cancer death worldwide and very few specific biomarkers could be used in clinical diagnosis at present. The aim of this study is to find novel potential serum biomarkers for lung cancer using Surface Enhanced Laser Desorption/Ionization (SELDI technique. Methods Serumsample of 227 cases including 146 lung cancer, 13 pneumonia, 28 tuberculous pleurisy and 40 normal individuals were analyzed by CM10 chips. The candidate biomarkers were identified by ESI/MS-MS and database searching, and further confirmed by immunoprecipitation. The same sets of serum sample from all groups were re-measured by ELISA assay. Results Three protein peaks with the molecular weight 13.78 kDa, 13.90 kDa and 14.07 kDa were found significantlydecreased in lung cancer serum compared to the other groups and were all automatically selected as specific biomarkers by Biomarker Wizard software. The candidate biomarkers obtained from 1-D SDS gel bands by matching the molecular weight with peaks on CM10 chips were identified by Mass spectrometry as the native transthyretin (nativeTTR, cysTTR and glutTTR, and the identity was further validated by immunoprecipitation using commercial TTR antibodies. Downregulated of TTR was found in both ELISA and SELDI analysis. Conclusion TTRs acted as the potentially useful biomarkers for lung cancer by SELDI technique.

  5. Functional genomics and cancer drug target discovery.

    Science.gov (United States)

    Moody, Susan E; Boehm, Jesse S; Barbie, David A; Hahn, William C

    2010-06-01

    The recent development of technologies for whole-genome sequencing, copy number analysis and expression profiling enables the generation of comprehensive descriptions of cancer genomes. However, although the structural analysis and expression profiling of tumors and cancer cell lines can allow the identification of candidate molecules that are altered in the malignant state, functional analyses are necessary to confirm such genes as oncogenes or tumor suppressors. Moreover, recent research suggests that tumor cells also depend on synthetic lethal targets, which are not mutated or amplified in cancer genomes; functional genomics screening can facilitate the discovery of such targets. This review provides an overview of the tools available for the study of functional genomics, and discusses recent research involving the use of these tools to identify potential novel drug targets in cancer. PMID:20521217

  6. Inconvenient truth: cancer biomarker development by using proteomics.

    Science.gov (United States)

    Kondo, Tadashi

    2014-05-01

    A biomarker is a crucial tool for measuring the progress of disease and the effects of treatment for better clinical outcomes in cancer patients. Diagnostic, predictive, and prognostic biomarkers are required in various clinical settings. The proteome, a functional translation of the genome, is considered a rich source of biomarkers; therefore, sizable time and funding have been spent in proteomics to develop biomarkers. Although significant progress has been made in technologies toward comprehensive protein expression profiling, and many biomarker candidates published, none of the reported biomarkers have proven to be beneficial for cancer patients. The present deceleration in biomarker research can be attributed to technical limitations. Additional efforts are required to further technical progress; however, there are many examples demonstrating that problems in biomarker research are not so much with the technology but in the study design. In the study of biomarkers for early diagnosis, candidates are screened and validated by comparing cases and controls of similar sample size, and the low prevalence of disease is often ignored. Although it is reasonable to take advantage of multiple rather than single biomarkers when studying diverse disease mechanisms, the annotation of individual components of reported multiple biomarkers does not often explain the variety of molecular events underlying the clinical observations. In tissue biomarker studies, the heterogeneity of disease tissues and pathological observations are often not considered, and tissues are homogenized as a whole for protein extraction. In addition to the challenge of technical limitations, the fundamental aspects of biomarker development in a disease study need to be addressed. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:23896458

  7. Biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy: a novel strategy in drug development

    Directory of Open Access Journals (Sweden)

    Jan eStenvang

    2013-12-01

    Full Text Available Cancer is a leading cause of mortality worldwide and matters are only set to worsen as its incidence continues to rise. Traditional approaches to combat cancer include improved prevention, early diagnosis, optimized surgery, development of novel drugs and honing regimens of existing anti-cancer drugs. Although discovery and development of novel and effective anti-cancer drugs is a major research area, it is well known that oncology drug development is a lengthy process, extremely costly and with high attrition rates. Furthermore, those drugs that do make it through the drug development mill are often quite expensive, laden with severe side-effects and, unfortunately, to date, have only demonstrated minimal increases in overall survival. Therefore, a strong interest has emerged to identify approved non-cancer drugs that possess anti-cancer activity, thus shortcutting the development process. This research strategy is commonly known as drug repurposing or drug repositioning and provides a faster path to the clinics. We have developed and implemented a modification of the standard drug repurposing strategy that we review here; rather than investigating target-promiscuous non-cancer drugs for possible anti-cancer activity, we focus on the discovery of novel cancer indications for already approved chemotherapeutic anti-cancer drugs. Clinical implementation of this strategy is normally commenced at clinical phase II trials and includes pre-treated patients. As the response rates to any non-standard chemotherapeutic drug will be relatively low in such a patient cohort it is a pre-requisite that such testing is based on predictive biomarkers. This review describes our strategy of biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy, taking the repurposing of topoisomerase I inhibitors and topoisomerase I as a potential predictive biomarker as case in point.

  8. AKAP4 is a circulating biomarker for non-small cell lung cancer

    Science.gov (United States)

    Gumireddy, Kiranmai; Li, Anping; Chang, David H.; Liu, Qin; Kossenkov, Andrew V.; Yan, Jinchun; Korst, Robert J.; Nam, Brian T.; Xu, Hua; Zhang, Lin; Ganepola, Ganepola A.P.; Showe, Louise C.; Huang, Qihong

    2015-01-01

    Cancer testis antigens (CTAs) are widely expressed in tumor tissues, circulating tumor cells (CTCs) and in cancer derived exosomes that are frequently engulfed by lymphoid cells. To determine whether tumor derived CTA mRNAs could be detected in RNA from purified peripheral blood mononuclear cells (PBMC) of non-small cell lung cancer (NSCLC) patients, we assayed for the expression of 116 CTAs in PBMC RNA in a discovery set and identified AKAP4 as a potential NSCLC biomarker. We validated AKAP4 as a highly accurate biomarker in a cohort of 264 NSCLCs and 135 controls from 2 different sites including a subset of controls with high risk lung nodules. When all (264) lung cancers were compared with all (135) controls the area under the ROC curve (AUC) was 0.9714. When 136 stage I NSCLC lung cancers are compared with all controls the AUC is 0.9795 and when all lung cancer patients were compared to 27 controls with histologically confirmed benign lung nodules, a comparison of significant clinical importance, the AUC was 0.9825. AKAP4 expression increases significantly with tumor stage, but independent of age, gender, smoking history or cancer subtype. Follow-up studies in a small number of resected NSCLC patients revealed a decrease of AKAP4 expression post-surgical resection that remained low in patients in remission and increased with tumor recurrence. AKAP4 is a highly accurate biomarker for the detection of early stage lung cancer. PMID:26160834

  9. High-Sensitivity and Low-Toxicity Fucose Probe for Glycan Imaging and Biomarker Discovery.

    Science.gov (United States)

    Kizuka, Yasuhiko; Funayama, Sho; Shogomori, Hidehiko; Nakano, Miyako; Nakajima, Kazuki; Oka, Ritsuko; Kitazume, Shinobu; Yamaguchi, Yoshiki; Sano, Masahiro; Korekane, Hiroaki; Hsu, Tsui-Ling; Lee, Hsiu-Yu; Wong, Chi-Huey; Taniguchi, Naoyuki

    2016-07-21

    Fucose, a terminal sugar in glycoconjugates, critically regulates various physiological and pathological phenomena, including cancer development and inflammation. However, there are currently no probes for efficient labeling and detection of this sugar. We chemically synthesized a novel series of alkynyl-fucose analogs as probe candidates and found that 7-alkynyl-fucose gave the highest labeling efficiency and low cytotoxicity. Among the fucose analogs, 7-alkynyl-fucose was the best substrate against all five fucosyltransferases examined. We confirmed its conversion to the corresponding guanosine diphosphate derivative in cells and found that cellular glycoproteins were labeled much more efficiently with 7-alkynyl-fucose than with an existing probe. 7-Alkynyl-fucose was detected in the N-glycan core by mass spectrometry, and 7-alkynyl-fucose-modified proteins mostly disappeared in core-fucose-deficient mouse embryonic fibroblasts, suggesting that this analog mainly labeled core fucose in these cells. These results indicate that 7-alkynyl-fucose is a highly sensitive and powerful tool for basic glycobiology research and clinical application for biomarker discovery. PMID:27447047

  10. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

    Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

  11. Towards Personalized Cancer Therapy : New Diagnostic Biomarkers and Radiosensitization Strategies

    OpenAIRE

    Spiegelberg, Diana

    2015-01-01

    This thesis focuses on the evaluation of biomarkers for radio-immunodiagnostics and radio-immunotherapy and on radiosensitization strategies after HSP90 inhibition, as a step towards more personalized cancer medicine. There is a need to develop new tracers that target cancer-specific biomarkers to improve diagnostic imaging, as well as to combine treatment strategies to potentiate synergistic effects. Special focus has been on the cell surface molecule CD44 and its oncogenic variants, which w...

  12. Immune responses to cancer: are they potential biomarkers of prognosis?

    Directory of Open Access Journals (Sweden)

    Theresa L Whiteside

    2013-05-01

    Full Text Available Recent technical improvements in evaluations of immune cells in situ and immune monitoring of patients with cancer have provided a wealth of new data confirming that immune cells play a key role in human cancer progression. This, in turn, has revived the expectation that immune endpoints might serve as reliable biomarkers of outcome or response to therapy in cancer. The recent successes in linking the T-cell signature in human colorectal carcinoma (CRC with prognosis have provided a strong motive for searching for additional immune biomarkers that could serve as intermediate endpoints of response to therapy and outcome in human cancers. A number of potentially promising immune biomarkers have emerged, but most remain to be validated. Among them, the B-cell signature, as exemplified by expression of the immunoglobulin G kappa chain (IGKC in tumor-infiltrating lymphocytes (TIL, has been validated as a biomarker of response to adjuvant therapy and better survival in patients with breast carcinoma and several other types of human solid tumors. Additional immune endpoints are being currently tested as potentially promising biomarkers in cancer. In view of currently growing use of immune cancer therapies, the search for immune biomarkers of prognosis are critically important for identifying patients who would benefit the most from adjuvant immunotherapy.

  13. Isolation and Quantification of MicroRNAs from Urinary Exosomes/Microvesicles for Biomarker Discovery

    OpenAIRE

    Lv, Lin-Li; Cao, Yuhan; Liu, Dan; Xu, Min; Liu, Hong; Tang, Ri-Ning; Ma, Kun-Ling; Liu, Bi-Cheng

    2013-01-01

    Recent studies indicate that microRNA (miRNA) is contained within exosome. Here we sought to optimize the methodologies for the isolation and quantification of urinary exosomal microRNA as a prelude to biomarker discovery studies. Exosomes were isolated through ultracentrifugation and characterized by immunoelectron microscopy. To determine the RNA was confined inside exosomes, the pellet was treated with RNase before RNA isolation. The minimum urine volume, storage conditions for exosomes an...

  14. The impact of sample storage time on estimates of association in biomarker discovery studies

    OpenAIRE

    Kugler, Karl G; Hackl, Werner O; Mueller, Laurin AJ; Fiegl, Heidi; Graber, Armin; Ruth M Pfeiffer

    2011-01-01

    Background Using serum, plasma or tumor tissue specimens from biobanks for biomarker discovery studies is attractive as samples are often readily available. However, storage over longer periods of time can alter concentrations of proteins in those specimens. We therefore assessed the bias in estimates of association from case-control studies conducted using banked specimens when maker levels changed over time for single markers and also for multiple correlated markers in simulations. Data fro...

  15. Urinary proteomics as a novel tool for biomarker discovery in kidney diseases*

    OpenAIRE

    Wu, Jing; Chen, Yi-ding; Gu, Wei

    2010-01-01

    Urine has become one of the most attractive biofluids in clinical proteomics, for its procurement is easy and noninvasive and it contains sufficient proteins and peptides. Urinary proteomics has thus rapidly developed and has been extensively applied to biomarker discovery in clinical diseases, especially kidney diseases. In this review, we discuss two important aspects of urinary proteomics in detail, namely, sample preparation and proteomic technologies. In addition, data mining in urinary ...

  16. Two-dimensional SDS-PAGE fractionation of biological samples for biomarker discovery

    OpenAIRE

    Rabilloud, Thierry; Triboulet, Sarah

    2013-01-01

    Two-dimensional electrophoresis is still a very valuable tool in proteomics, due to its reproducibility and its ability to analyze complete proteins. However, due to its sensitivity to dynamic range issues, its most suitable use in the frame of biomarker discovery is not on very complex fluids such as plasma, but rather on more proximal, simpler fluids such as CSF, urine, or secretome samples. Here, we describe the complete workflow for the analysis of such dilute samples by two-dimensional e...

  17. Application of mass spectrometry-based proteomics for biomarker discovery in neurological disorders

    OpenAIRE

    Venugopal Abhilash; Chaerkady Raghothama; Pandey Akhilesh

    2009-01-01

    Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Quantitative proteomic approaches have already been applied to investigate various neurological disorders, espe...

  18. Glycoprotein Biomarkers for the Early Detection of Aggressive Prostate Cancer — EDRN Public Portal

    Science.gov (United States)

    The Early Detection Research Network of the NCI is charged with the discovery, development and validation of biomarkers for early detection and prognosis related to neoplastic disease. Our laboratory is an NCI EDRN (U01CA152813) working on "Glycoprotein biomarkers for the early detection of aggressive prostate cancer". This EDRN administratiVE! supplement is a collaboration with Robert Veltri on his project to identify men with very low risk (indolent) prostate cancer (CaP) at the diagnostic biopsy at selection for active surveillance (AS). We will assess biopsy tissue using quantitative nuclear histomorphometric measurements and molecular biomarkers to predict an unexpected catastrophic CaP in such men with indolent CaP. At Johns Hopkins Hospital w1e use the Epstein criteria that includes; PSA density (PSAD) aggressive disease from a AS diagnostic biopsy. Our approach will combine nuclear morphometry measured by digital microscopy with a unique biopsy tissue biomarker profile (DNA content, Ki67, Her2neu, CACND1 and periostin). Fc•r the molecular targets we will us•e a multiplex tissue blot (MTB) immunohistochemistry method. The Aims o'f our work include 1) to utilize retrospective archival biopsy material from 70 AS cases where the outcome was unexpected and disastrous and collect an equal number of AS cases (n=140) and perform assays for morphology and biomarker targi ts proposed, 2) and predict failure using Cox proportional hazards statistical modeling.

  19. A review of molecular biomarkers for bladder cancer

    Directory of Open Access Journals (Sweden)

    Miakhil I

    2013-01-01

    Full Text Available Background: Numerous molecular markers for bladder cancer have been identified and investigated with various laboratory techniques. Molecular markers are isolated from tissue, serum and urine. They fall into proteomic, genetic and epigenetic categories. Some of molecular markers show promising results in terms of facilitating early diagnosis and guiding treatment. Molecular markers or the so- called biomarkers can provide additional information alongside staging, grading and lymphovascular invasion, for better prognostication.Aim:This studyprovides an up-to-date review of the frequently studied and most important biomarkers that have shown consistent relevance in relation to bladder cancer. Methods: The key words were searched on the PubMed, Google scholar and NHS library search engines. Results: More than twenty biomarkers as per our methodology were identified but only half of them have shown consistence relevance in bladder cancer. Conclusion: It is envisaged that a combination of a few biomarkers, which are investigated frequently and have shown clinical relevance, could possibly provide useful information in predicting recurrence and provide useful prognostic information. So far none of the biomarkers for bladder cancer are adopted in the UK standard practice. Despite that the Food and Drug Administration (FDA had approved some of these biomarkers, none of the urology associations incorporated them in to their guidelines as yet. However, it won’t be long before a final consensus is reached to integrate molecular staging in to the current TNM staging system.

  20. Integrating proteomic and functional genomic technologies in discovery-driven translational breast cancer research

    DEFF Research Database (Denmark)

    Celis, Julio E; Gromov, Pavel; Gromova, Irina;

    2003-01-01

    . Here we describe the essence of a long-term initiative undertaken by The Danish Centre for Translational Breast Cancer Research and currently underway for cancer biomarker discovery using fresh tissue biopsies and bio-fluids. The Centre is a virtual hub that brings together scientists working......The application of state-of-the-art proteomics and functional genomics technologies to the study of cancer is rapidly shifting toward the analysis of clinically relevant samples derived from patients, as the ultimate aim of translational research is to bring basic discoveries closer to the bedside...... in various areas of basic cancer research such as cell cycle control, invasion and micro-environmental alterations, apoptosis, cell signaling, and immunology, with clinicians (oncologists, surgeons), pathologists, and epidemiologists, with the aim of understanding the molecular mechanisms underlying breast...

  1. Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems.

    Science.gov (United States)

    Rodrigues, Daniela; Jerónimo, Carmen; Henrique, Rui; Belo, Luís; de Lourdes Bastos, Maria; de Pinho, Paula Guedes; Carvalho, Márcia

    2016-07-15

    Metabolomics has recently proved to be useful in the area of biomarker discovery for cancers in which early diagnostic and prognostic biomarkers are urgently needed, as is the case of bladder cancer (BC). This article presents a comprehensive review of the literature on the metabolomic studies on BC, highlighting metabolic pathways perturbed in this disease and the altered metabolites as potential biomarkers for BC detection. Current disease model systems used in the study of BC metabolome include in vitro-cultured cancer cells, ex vivo neoplastic bladder tissues and biological fluids, mainly urine but also blood serum/plasma, from BC patients. The major advantages and drawbacks of each model system are discussed. Based on available data, it seems that BC metabolic signature is mainly characterized by alterations in metabolites related to energy metabolic pathways, particularly glycolysis, amino acid and fatty acid metabolism, known to be crucial for cell proliferation, as well as glutathione metabolism, known to be determinant in maintaining cellular redox balance. In addition, purine and pyrimidine metabolism as well as carnitine species were found to be altered in BC. Finally, it is emphasized that, despite the progress made in respect to novel biomarkers for BC diagnosis, there are still some challenges and limitations that should be addressed in future metabolomic studies to ensure their translatability to clinical practice. PMID:26804544

  2. Urinary PGE-M: a promising cancer biomarker.

    Science.gov (United States)

    Wang, Dingzhi; DuBois, Raymond N

    2013-06-01

    Cancer prevention, early diagnosis, and targeted therapies are the keys to success in better cancer control and treatment. A big challenge remains to identify biomarkers for predicting who may have higher cancer risk and are able to respond to certain chemopreventive agents as well as for assessing a patient's response during treatment. Although a large body of evidence indicates that chronic inflammation is a risk factor for cancer, it is unclear whether inflammatory biomarkers can be used to predict cancer risk, progression, and death. Considering the importance of the proinflammatory COX-2-derived prostaglandin E2 (PGE2) in inflammation and cancer, Morris and colleagues found that urinary PGE-M is positively associated with obesity, smoking, and lung metastases in patients with breast cancer (4). Along the same lines, Kim and colleagues showed a potential association between urinary PGE-M and breast cancer risk in postmenopausal women (beginning on page 511). In agreement with previous reports, their findings indicate that urinary PGE-M may serve as a promising biomarker for prognosticating cancer risk and disease progression. PMID:23636051

  3. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Science.gov (United States)

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  4. Biomarkers, Bundled Payments, and Colorectal Cancer Care

    OpenAIRE

    Ross, William; Lynch, Patrick; Raju, Gottumukkala; Rodriguez, Alma; Burke, Thomas; Hafemeister, Lisa; Hawk, Ernest; Wu, Xifeng; Raymond N. DuBois; MISHRA, LOPA

    2012-01-01

    Changes in the management of cancers such as colorectal cancer (CRC) are urgently needed, as such cancers continue to be one of the most commonly diagnosed cancers; CRC accounts for 21% of all cancers and is responsible for mortalities second only to lung cancer in the United States. A comprehensive science-driven approach towards markedly improved early detection/screening to efficacious targeted therapeutics with clear diagnostic and prognostic markers is essential. In addition, further cha...

  5. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    International Nuclear Information System (INIS)

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  6. Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.

    Directory of Open Access Journals (Sweden)

    Barbara Di Camillo

    Full Text Available MOTIVATION: The identification of robust lists of molecular biomarkers related to a disease is a fundamental step for early diagnosis and treatment. However, methodologies for the discovery of biomarkers using microarray data often provide results with limited overlap. These differences are imputable to 1 dataset size (few subjects with respect to the number of features; 2 heterogeneity of the disease; 3 heterogeneity of experimental protocols and computational pipelines employed in the analysis. In this paper, we focus on the first two issues and assess, both on simulated (through an in silico regulation network model and real clinical datasets, the consistency of candidate biomarkers provided by a number of different methods. METHODS: We extensively simulated the effect of heterogeneity characteristic of complex diseases on different sets of microarray data. Heterogeneity was reproduced by simulating both intrinsic variability of the population and the alteration of regulatory mechanisms. Population variability was simulated by modeling evolution of a pool of subjects; then, a subset of them underwent alterations in regulatory mechanisms so as to mimic the disease state. RESULTS: The simulated data allowed us to outline advantages and drawbacks of different methods across multiple studies and varying number of samples and to evaluate precision of feature selection on a benchmark with known biomarkers. Although comparable classification accuracy was reached by different methods, the use of external cross-validation loops is helpful in finding features with a higher degree of precision and stability. Application to real data confirmed these results.

  7. Exosomal miRNAs as biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Nina Pettersen Hessvik

    2013-03-01

    Full Text Available miRNAs are small non-coding RNAs that finely regulate gene expression in cells. Alterations in miRNA expression have been associated with development of cancer, and miRNAs are now being investigated as biomarkers for cancer as well as other diseases. Recently, miRNAs have been found outside cells in body fluids. Extracellular miRNAs exist in different forms - associated with Ago2 proteins, loaded into extracellular vesicles (exosomes, microvesicles or apoptotic bodies or into high density lipoprotein particles. These extracellular miRNAs are probably products of distinct cellular processes, and might therefore play different roles. However, their functions in vivo are currently unknown. In spite of this, they are considered as promising, noninvasive diagnostic and prognostic tools. Prostate cancer is the most common cancer in men in the Western world, but the currently used biomarker (prostate specific antigen has low specificity. Therefore, novel biomarkers are highly needed. In this review we will discuss possible biological functions of extracellular miRNAs, as well as the potential use of miRNAs from extracellular vesicles as biomarkers for prostate cancer.

  8. Warehousing re-annotated cancer genes for biomarker meta-analysis.

    Science.gov (United States)

    Orsini, M; Travaglione, A; Capobianco, E

    2013-07-01

    Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects. PMID:23639751

  9. Urinary Proteomics Pilot Study for Biomarker Discovery and Diagnosis in Heart Failure with Reduced Ejection Fraction.

    Directory of Open Access Journals (Sweden)

    Kasper Rossing

    Full Text Available Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF.Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 HFrEF patients and 29 age- and sex-matched individuals without HFrEF resulted in identification of 103 peptides that were significantly differentially excreted in HFrEF. These 103 peptides were used to establish the support vector machine-based HFrEF classifier HFrEF103. In a subsequent validation cohort, HFrEF103 very accurately (area under the curve, AUC = 0.972 discriminated between HFrEF patients (N = 94, sensitivity = 93.6% and control individuals with and without impaired renal function and hypertension (N = 552, specificity = 92.9%. Interestingly, HFrEF103 showed low sensitivity (12.6% in individuals with diastolic left ventricular dysfunction (N = 176. The HFrEF-related peptide biomarkers mainly included fragments of fibrillar type I and III collagen but also, e.g., of fibrinogen beta and alpha-1-antitrypsin.CE-MS based urine proteome analysis served as a sensitive tool to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.

  10. Transcriptional responses to radiation exposure facilitate the discovery of biomarkers functioning as radiation biodosimeters

    International Nuclear Information System (INIS)

    The development of new methods for a retrospective quantification of the radiation dose of exposed individuals is of widespread interest. To this end, I developed a computational framework for biomarker discovery and radiation dose prediction and successfully identified gene signatures with which low and medium to high radiation doses can be accurately quantified. To enhance our understanding of the radiation-induced transcriptional response, I additionally analyzed microarray data of human PBLs after ex vivo gamma-irradiation and characterized affected functional processes and pathways.

  11. Transcriptional responses to radiation exposure facilitate the discovery of biomarkers functioning as radiation biodosimeters

    Energy Technology Data Exchange (ETDEWEB)

    Strunz, Sonja

    2014-05-13

    The development of new methods for a retrospective quantification of the radiation dose of exposed individuals is of widespread interest. To this end, I developed a computational framework for biomarker discovery and radiation dose prediction and successfully identified gene signatures with which low and medium to high radiation doses can be accurately quantified. To enhance our understanding of the radiation-induced transcriptional response, I additionally analyzed microarray data of human PBLs after ex vivo gamma-irradiation and characterized affected functional processes and pathways.

  12. Inside back cover: Biomarker discovery in mass spectrometry-based urinary proteomics.

    Science.gov (United States)

    Thomas, Samuel; Hao, Ling; Ricke, William A; Li, Lingjun

    2016-04-01

    DOI: 10.1002/prca.201500102 Urine is among the most valuable sample materials for studies of human diseases. These urine solutes are shown with increasing approximate diameter from metabolite at 1 nm to protein at 5 nm to a group of exosomes at 100 nm each to a cell at 10 000 nm. This article highlights promising technologies and strategies in the mass spectrometry-based urine proteomics and its application to disease biomarker discovery. Further details can be found in the article by Samuel Thomas et al. on page 358. PMID:27061328

  13. Targeted proteomics for biomarker discovery and validation of hepatocellular carcinoma in hepatitis C infected patients

    OpenAIRE

    Mustafa, Gul M; Larry, Denner; John R. Petersen; Elferink, Cornelis J.

    2015-01-01

    Hepatocellular carcinoma (HCC)-related mortality is high because early detection modalities are hampered by inaccuracy, expense and inherent procedural risks. Thus there is an urgent need for minimally invasive, highly specific and sensitive biomarkers that enable early disease detection when therapeutic intervention remains practical. Successful therapeutic intervention is predicated on the ability to detect the cancer early. Similar unmet medical needs abound in most fields of medicine and ...

  14. Enabling Metabolomics Based Biomarker Discovery Studies Using Molecular Phenotyping of Exosome-Like Vesicles

    OpenAIRE

    Altadill, Tatiana; Campoy, Irene; Lanau, Lucia; Gill, Kirandeep; Rigau, Marina; Gil-Moreno, Antonio; Reventos, Jaume; Byers, Stephen; Colas, Eva; Cheema, Amrita K.

    2016-01-01

    Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported us...

  15. Lung cancer screening: from imaging to biomarker

    OpenAIRE

    Xiang, Dong; Zhang, Bicheng; Doll, Donald; Shen, Kui; Kloecker, Goetz; Freter, Carl

    2013-01-01

    Despite several decades of intensive effort to improve the imaging techniques for lung cancer diagnosis and treatment, primary lung cancer is still the number one cause of cancer death in the United States and worldwide. The major causes of this high mortality rate are distant metastasis evident at diagnosis and ineffective treatment for locally advanced disease. Indeed, approximately forty percent of newly diagnosed lung cancer patients have distant metastasis. Currently, the only potential ...

  16. Risk factors and novel biomarkers in breast cancer

    OpenAIRE

    Fourkala, E.-O.

    2011-01-01

    Efforts continue to identify and validate novel risk factors / biomarkers for breast cancer and improve current risk prediction models in the general population due to ongoing issues with sensitivity and specificity. The overall goal of this PhD study is to add to this effort. Specific aims are to (1) examine which is the best source of getting notified for breast cancer diagnosis in the general population since accurate data is crucial for risk assessment studies (2) investigate the assoc...

  17. Prostate cancer biomarker profiles in urinary sediments and exosomes

    NARCIS (Netherlands)

    Dijkstra, S.; Birker, I.L.; Smit, F.P.; Leyten, G.H.J.M.; Reijke, T.M. de; Oort, I.M. van; Mulders, P.F.A.; Jannink, S.A.; Schalken, J.A.

    2014-01-01

    PURPOSE: Urinary biomarker tests for diagnosing prostate cancer have gained considerable interest. Urine is a complex mixture that can be subfractionated. We evaluated 2 urinary fractions that contain nucleic acids, ie cell pellets and exosomes. The influence of digital rectal examination before uri

  18. Identification of candidate epigenetic biomarkers for ovarian cancer detection

    NARCIS (Netherlands)

    Huang, Yi-Wen; Jansen, Rachel A.; Fabbri, Enrica; Potter, Dustin; Liyanarachchi, Sandya; Chan, Michael W. Y.; Liu, Joseph C.; Crijns, Anne P. G.; Brown, Robert; Nephew, Kenneth P.; Van Der Zee, Ate G. J.; Cohn, David E.; Yan, Pearlly S.; Huang, Tim H. -M.; Lin, Huey-Jen L.

    2009-01-01

    Ovarian cancer ranks the most lethal among gynecologic neoplasms in women. To develop potential biomarkers for diagnosis, we have identified five novel genes (CYP39A1, GTF2A1, FOXD4L4, EBP, and HAAO) that are hypermethylated in ovarian tumors, compared with the non-malignant normal ovarian surface e

  19. 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.

  20. Effects of synbiotics on cancer risk biomarkers

    OpenAIRE

    Clune, Yvonne E.

    2005-01-01

    Colorectal cancer (CRC) is the fourth most common cause of death from cancer in the world and second most common (behind lung cancer) in developed countries. In recent years there has been much interest in the potential use of prebiotics, probiotics and synbiotics in the prevention and treatment of CRC. We have previously shown that synbiotic consumption in Azoxymethane treated rats modulates the immune system, influences the genotoxic potential of caecal contents and reduces the number of co...

  1. Biomarkers of Angiogenesis in Colorectal Cancer

    OpenAIRE

    Luay Mousa; Salem, Mohamed E.; Sameh Mikhail

    2015-01-01

    Colorectal cancer (CRC) is the third most common cancer worldwide and accounts for 10% of all new cancer diagnoses. Angiogenesis is a tightly regulated process that is mediated by a group of angiogenic factors such as vascular endothelial growth factor and its receptors. Given the widespread use of antiangiogenic agents in CRC, there has been considerable interest in the development of methods to identify novel markers that can predict outcome in the treatment of this disease with angiogenesi...

  2. Evaluating biomarkers to model cancer risk post cosmic ray exposure

    Science.gov (United States)

    Sridharan, Deepa M.; Asaithamby, Aroumougame; Blattnig, Steve R.; Costes, Sylvain V.; Doetsch, Paul W.; Dynan, William S.; Hahnfeldt, Philip; Hlatky, Lynn; Kidane, Yared; Kronenberg, Amy; Naidu, Mamta D.; Peterson, Leif E.; Plante, Ianik; Ponomarev, Artem L.; Saha, Janapriya; Snijders, Antoine M.; Srinivasan, Kalayarasan; Tang, Jonathan; Werner, Erica; Pluth, Janice M.

    2016-06-01

    Robust predictive models are essential to manage the risk of radiation-induced carcinogenesis. Chronic exposure to cosmic rays in the context of the complex deep space environment may place astronauts at high cancer risk. To estimate this risk, it is critical to understand how radiation-induced cellular stress impacts cell fate decisions and how this in turn alters the risk of carcinogenesis. Exposure to the heavy ion component of cosmic rays triggers a multitude of cellular changes, depending on the rate of exposure, the type of damage incurred and individual susceptibility. Heterogeneity in dose, dose rate, radiation quality, energy and particle flux contribute to the complexity of risk assessment. To unravel the impact of each of these factors, it is critical to identify sensitive biomarkers that can serve as inputs for robust modeling of individual risk of cancer or other long-term health consequences of exposure. Limitations in sensitivity of biomarkers to dose and dose rate, and the complexity of longitudinal monitoring, are some of the factors that increase uncertainties in the output from risk prediction models. Here, we critically evaluate candidate early and late biomarkers of radiation exposure and discuss their usefulness in predicting cell fate decisions. Some of the biomarkers we have reviewed include complex clustered DNA damage, persistent DNA repair foci, reactive oxygen species, chromosome aberrations and inflammation. Other biomarkers discussed, often assayed for at longer points post exposure, include mutations, chromosome aberrations, reactive oxygen species and telomere length changes. We discuss the relationship of biomarkers to different potential cell fates, including proliferation, apoptosis, senescence, and loss of stemness, which can propagate genomic instability and alter tissue composition and the underlying mRNA signatures that contribute to cell fate decisions. Our goal is to highlight factors that are important in choosing

  3. Application of a high throughput method of biomarker discovery to improvement of the EarlyCDT(®-Lung Test.

    Directory of Open Access Journals (Sweden)

    Isabel K Macdonald

    Full Text Available BACKGROUND: The National Lung Screening Trial showed that CT screening for lung cancer led to a 20% reduction in mortality. However, CT screening has a number of disadvantages including low specificity. A validated autoantibody assay is available commercially (EarlyCDT®-Lung to aid in the early detection of lung cancer and risk stratification in patients with pulmonary nodules detected by CT. Recent advances in high throughput (HTP cloning and expression methods have been developed into a discovery pipeline to identify biomarkers that detect autoantibodies. The aim of this study was to demonstrate the successful clinical application of this strategy to add to the EarlyCDT-Lung panel in order to improve its sensitivity and specificity (and hence positive predictive value, (PPV. METHODS AND FINDINGS: Serum from two matched independent cohorts of lung cancer patients were used (n = 100 and n = 165. Sixty nine proteins were initially screened on an abridged HTP version of the autoantibody ELISA using protein prepared on small scale by a HTP expression and purification screen. Promising leads were produced in shake flask culture and tested on the full assay. These results were analyzed in combination with those from the EarlyCDT-Lung panel in order to provide a set of re-optimized cut-offs. Five proteins that still displayed cancer/normal differentiation were tested for reproducibility and validation on a second batch of protein and a separate patient cohort. Addition of these proteins resulted in an improvement in the sensitivity and specificity of the test from 38% and 86% to 49% and 93% respectively (PPV improvement from 1 in 16 to 1 in 7. CONCLUSION: This is a practical example of the value of investing resources to develop a HTP technology. Such technology may lead to improvement in the clinical utility of the EarlyCDT--Lung test, and so further aid the early detection of lung cancer.

  4. ProfileDB: a resource for proteomics and cross-omics biomarker discovery.

    Science.gov (United States)

    Bauer, Chris; Glintschert, Alexander; Schuchhardt, Johannes

    2014-05-01

    The increasing size and complexity of high-throughput datasets pose a growing challenge for researchers. Often very different (cross-omics) techniques with individual data analysis pipelines are employed making a unified biomarker discovery strategy and a direct comparison of different experiments difficult and time consuming. Here we present the comprehensive web-based application ProfileDB. The application is designed to integrate data from different high-throughput 'omics' data types (Transcriptomics, Proteomics, Metabolomics) with clinical parameters and prior knowledge on pathways and ontologies. Beyond data storage, ProfileDB provides a set of dedicated tools for study inspection and data visualization. The user can gain insights into a complex experiment with just a few mouse clicks. We will demonstrate the application by presenting typical use cases for the identification of proteomics biomarkers. All presented analyses can be reproduced using the public ProfileDB web server. The ProfileDB application is available by standard browser (Firefox 18+, Internet Explorer Version 9+) technology via http://profileDB.-microdiscovery.de/ (login and pass-word: profileDB). The installation contains several public datasets including different cross-'omics' experiments. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. PMID:24270047

  5. Schizophrenia genomics and proteomics: are we any closer to biomarker discovery?

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

    Full Text Available Abstract The field of proteomics has made leaps and bounds in the last 10 years particularly in the fields of oncology and cardiovascular medicine. In comparison, neuroproteomics is still playing catch up mainly due to the relative complexity of neurological disorders. Schizophrenia is one such disorder, believed to be the results of multiple factors both genetic and environmental. Affecting over 2 million people in the US alone, it has become a major clinical and public health concern worldwide. This paper gives an update of schizophrenia biomarker research as reviewed by Lakhan in 2006 and gives us a rundown of the progress made during the last two years. Several studies demonstrate the potential of cerebrospinal fluid as a source of neuro-specific biomarkers. Genetic association studies are making headway in identifying candidate genes for schizophrenia. In addition, metabonomics, bioinformatics, and neuroimaging techniques are aiming to complete the picture by filling in knowledge gaps. International cooperation in the form of genomics and protein databases and brain banks is facilitating research efforts. While none of the recent developments described here in qualifies as biomarker discovery, many are likely to be stepping stones towards that goal.

  6. Proteomic-driven biomarker discovery in gestational diabetes mellitus: a review.

    Science.gov (United States)

    Singh, Apoorva; Subramani, Elavarasan; Datta Ray, Chaitali; Rapole, Srikanth; Chaudhury, Koel

    2015-09-01

    Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy and it affects 18% of pregnant women worldwide. GDM is considered a high-risk state which may lead to type II diabetes which is associated with an increase in a number of interrelated adverse perinatal outcomes. Given the fact that the progress of a successful pregnancy is dependent on the intricate communication between several biological molecules, identification of the proteomic profile perturbations in women with GDM is expected to help in understanding the disease pathogenesis and also discovery of clinical biomarker(s). In recent years, both gel-free and gel-based proteomics have been extensively investigated for improving maternal and child health. Although there are several reports integrating various aspects of proteomics in pregnancy related diseases such as preeclampsia, extensive Pubmed search shows no review so far on the application of proteomics in gestational diabetes. In this review, we focus on various high-throughput proteomic technologies for the identification of unique biosignatures and biomarkers responsible for the early prediction of GDM. Further, different analytical strategies and biological samples involved in proteomic analysis of this pregnancy-related disease are discussed.This article is part of a Special Issue entitled: Proteomics in India. PMID:26216595

  7. Biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy

    DEFF Research Database (Denmark)

    Stenvang, Jan; Kümler, Iben; Nygård, Sune Boris;

    2013-01-01

    process. This research strategy is commonly known as drug repurposing or drug repositioning and provides a faster path to the clinics. We have developed and implemented a modification of the standard drug repurposing strategy that we review here; rather than investigating target-promiscuous non...... any non-standard chemotherapeutic drug will be relatively low in such a patient cohort it is a pre-requisite that such testing is based on predictive biomarkers. This review describes our strategy of biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy, taking the repurposing of......Cancer is a leading cause of mortality worldwide and matters are only set to worsen as its incidence continues to rise. Traditional approaches to combat cancer include improved prevention, early diagnosis, optimized surgery, development of novel drugs, and honing regimens of existing anti...

  8. B-Cell Activating Factor as a Cancer Biomarker and Its Implications in Cancer-Related Cachexia

    Directory of Open Access Journals (Sweden)

    Michal Rihacek

    2015-01-01

    Full Text Available B-cell activating factor (BAFF is a cytokine and adipokine of the TNF ligand superfamily. The main biological function of BAFF in maintaining the maturation of B-cells to plasma cells has recently made it a target of the first FDA-approved selective BAFF antibody, belimumab, for the therapy of systemic lupus erythematosus. Concomitantly, the role of BAFF in cancer has been a subject of research since its discovery. Here we review BAFF as a biomarker of malignant disease activity and prognostic factor in B-cell derived malignancies such as multiple myeloma. Moreover, anti-BAFF therapy seems to be a promising approach in treatment of B-cell derived leukemias/lymphomas. In nonhematologic solid tumors, BAFF may contribute to cancer progression by mechanisms both dependent on and independent of BAFF’s proinflammatory role. We also describe ongoing research into the pathophysiological link between BAFF and cancer-related cachexia. BAFF has been shown to contribute to inflammation and insulin resistance which are known to worsen cancer cachexia syndrome. Taking all the above together, BAFF is emerging as a biomarker of several malignancies and a possible hallmark of cancer cachexia.

  9. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    Energy Technology Data Exchange (ETDEWEB)

    Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

    2012-10-31

    Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  10. Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

    Directory of Open Access Journals (Sweden)

    Meng-Hua Tao

    2010-04-01

    Full Text Available In spite of its public health importance, our understanding of the mechanisms of breast carcinogenesis and progress is still evolving. The metabolic syndrome (MS is a constellation of biochemical abnormalities including visceral adiposity, hyperglycemia, hyperinsulinemia, dyslipidemia and high blood pressure. The components of the MS have all been related to late-stage disease and even to a poor prognosis of breast cancer through multiple interacting mechanisms. In this review, we aim to present a summary of recent advances in the understanding of the contribution of the MS to breast cancer with the emphasis on the role of biomarkers of the MS in the prognosis of breast cancer.

  11. Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

    Energy Technology Data Exchange (ETDEWEB)

    Zhu, Qiu-Li; Xu, Wang-Hong, E-mail: mtao@buffalo.edu [Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032 (China); Tao, Meng-Hua, E-mail: mtao@buffalo.edu [Department of Social and Preventive Medicine, School of Public Health and Health Professions, University at Buffalo, Buffalo, NY 14214 (United States)

    2010-04-28

    In spite of its public health importance, our understanding of the mechanisms of breast carcinogenesis and progress is still evolving. The metabolic syndrome (MS) is a constellation of biochemical abnormalities including visceral adiposity, hyperglycemia, hyperinsulinemia, dyslipidemia and high blood pressure. The components of the MS have all been related to late-stage disease and even to a poor prognosis of breast cancer through multiple interacting mechanisms. In this review, we aim to present a summary of recent advances in the understanding of the contribution of the MS to breast cancer with the emphasis on the role of biomarkers of the MS in the prognosis of breast cancer.

  12. Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

    International Nuclear Information System (INIS)

    In spite of its public health importance, our understanding of the mechanisms of breast carcinogenesis and progress is still evolving. The metabolic syndrome (MS) is a constellation of biochemical abnormalities including visceral adiposity, hyperglycemia, hyperinsulinemia, dyslipidemia and high blood pressure. The components of the MS have all been related to late-stage disease and even to a poor prognosis of breast cancer through multiple interacting mechanisms. In this review, we aim to present a summary of recent advances in the understanding of the contribution of the MS to breast cancer with the emphasis on the role of biomarkers of the MS in the prognosis of breast cancer

  13. Epigenetic biomarkers in prostate cancer: Current and future uses.

    Science.gov (United States)

    Chiam, Karen; Ricciardelli, Carmela; Bianco-Miotto, Tina

    2014-01-28

    Epigenome alterations are characteristic of nearly all human malignancies and include changes in DNA methylation, histone modifications and microRNAs (miRNAs). However, what induces these epigenetic alterations in cancer is largely unknown and their mechanistic role in prostate tumorigenesis is just beginning to be evaluated. Identification of the epigenetic modifications involved in the development and progression of prostate cancer will not only identify novel therapeutic targets but also prognostic and diagnostic markers. This review will focus on the use of epigenetic modifications as biomarkers for prostate cancer. PMID:22391123

  14. Exosomal miRNAs as cancer biomarkers and therapeutic targets

    OpenAIRE

    Arron Thind; Clive Wilson

    2016-01-01

    Intercommunication between cancer cells and with their surrounding and distant environments is key to the survival, progression and metastasis of the tumour. Exosomes play a role in this communication process. MicroRNA (miRNA) expression is frequently dysregulated in tumour cells and can be reflected by distinct exosomal miRNA (ex-miRNA) profiles isolated from the bodily fluids of cancer patients. Here, the potential of ex-miRNA as a cancer biomarker and therapeutic target is critically analy...

  15. Chromosomal aberrations and SCEs as biomarkers of cancer risk

    DEFF Research Database (Denmark)

    Norppa, H; Bonassi, S; Hansteen, I-L; Hagmar, L; Strömberg, U; Rössner, P; Boffetta, P; Lindholm, C; Gundy, S; Lazutka, J; Cebulska-Wasilewska, A; Fabiánová, E; Srám, R J; Knudsen, Lisbeth E.; Barale, R; Fucic, A

    Previous studies have suggested that the frequency of chromosomal aberrations (CAs), but not of sister chromatid exchanges (SCEs), predicts cancer risk. We have further examined this relationship in European cohorts comprising altogether almost 22,000 subjects, in the framework of a European...... collaborative project (CancerRiskBiomarkers). The present paper gives an overview of some of the results of the project, especially as regards CAs and SCEs. The results confirm that a high level of CAs is associated with an increased risk of cancer and indicate that this association does not depend on the time...... between CA analysis and cancer detection, i.e., is obviously not explained by undetected cancer. The present evidence indicates that both chromatid-type and chromosome-type CAs predict cancer, even though some data suggest that chromosome-type CAs may have a more pronounced predictive value than chromatid...

  16. Aberrantly methylated DNA as a biomarker in breast cancer

    DEFF Research Database (Denmark)

    Kristiansen, Søren; Jørgensen, Lars Mønster; Guldberg, Per;

    2013-01-01

    hypermethylation events, their use as tumor biomarkers is usually not hampered by analytical signals from normal cells, which is a general problem for existing protein tumor markers used for clinical assessment of breast cancer. There is accumulating evidence that DNA-methylation changes in breast cancer patients......Aberrant DNA hypermethylation at gene promoters is a frequent event in human breast cancer. Recent genome-wide studies have identified hundreds of genes that exhibit differential methylation between breast cancer cells and normal breast tissue. Due to the tumor-specific nature of DNA...... occur early during tumorigenesis. This may open up for effective screening, and analysis of blood or nipple aspirate may later help in diagnosing breast cancer. As a more detailed molecular characterization of different types of breast cancer becomes available, the ability to divide patients into...

  17. Glycomic Approaches for the Discovery of Targets in Gastrointestinal Cancer

    Directory of Open Access Journals (Sweden)

    Stefan eMereiter

    2016-03-01

    Full Text Available Gastrointestinal (GI cancer is the most common group of malignancies and many of its types are among the most deadly. Various glycoconjugates have been used in clinical practice as serum biomarker for several GI tumors, however with limited diagnose application. Despite the good accessibility by endoscopy of many GI organs, the lack of reliable serum biomarkers often leads to late diagnosis of malignancy and consequently low 5-year survival rates. Recent advances in analytical techniques have provided novel glycoproteomic and glycomic data and generated functional information and putative biomarker targets in oncology. Glycosylation alterations have been demonstrated in a series of glycoconjugates (glycoproteins, proteoglycans and glycosphingolipids that are involved in cancer cell adhesion, signaling, invasion and metastasis formation. In this review, we present an overview on the major glycosylation alterations in GI cancer and the current serological biomarkers used in the clinical oncology setting. We further describe recent glycomic studies in GI cancer, namely gastric, colorectal and pancreatic cancer. Moreover, we discuss the role of glycosylation as a modulator of the function of several key players in cancer cell biology. Finally, we address several state-of-the-art techniques currently applied in this field, such as glycomic and glycoproteomic analyses, the application of glycoengineered cell line models, microarray and proximity ligation assay, as well as imaging mass spectrometry and provide an outlook to future perspectives and clinical applications.

  18. The discovery and development of proteomic safety biomarkers for the detection of drug-induced liver toxicity

    International Nuclear Information System (INIS)

    Biomarkers are biometric measurements that provide critical quantitative information about the biological condition of the animal or individual being tested. In drug safety studies, established toxicity biomarkers are used along with other conventional study data to determine dose-limiting organ toxicity, and to define species sensitivity for new chemical entities intended for possible use as human medicines. A continuing goal of drug safety scientists in the pharmaceutical industry is to discover and develop better trans-species biomarkers that can be used to determine target organ toxicities for preclinical species in short-term studies at dose levels that are some multiple of the intended human dose and again later in full development for monitoring clinical trials at lower therapeutic doses. Of particular value are early, predictive, noninvasive biomarkers that have in vitro, in vivo, and clinical transferability. Such translational biomarkers bridge animal testing used in preclinical science and human studies that are part of subsequent clinical testing. Although suitable for in vivo preclinical regulatory studies, conventional hepatic safety biomarkers are basically confirmatory markers because they signal organ toxicity after some pathological damage has occurred, and are therefore not well-suited for short-term, predictive screening assays early in the discovery-to-development progression of new chemical entities (NCEs) available in limited quantities. Efforts between regulatory agencies and the pharmaceutical industry are underway for the coordinated discovery, qualification, verification and validation of early predictive toxicity biomarkers. Early predictive safety biomarkers are those that are detectable and quantifiable prior to the onset of irreversible tissue injury and which are associated with a mechanism of action relevant to a specific type of potential hepatic injury. Potential drug toxicity biomarkers are typically endogenous macromolecules in

  19. Identification and validation of oncologic miRNA biomarkers for luminal A-like breast cancer.

    Directory of Open Access Journals (Sweden)

    Ailbhe M McDermott

    Full Text Available INTRODUCTION: Breast cancer is a common disease with distinct tumor subtypes phenotypically characterized by ER and HER2/neu receptor status. MiRNAs play regulatory roles in tumor initiation and progression, and altered miRNA expression has been demonstrated in a variety of cancer states presenting the potential for exploitation as cancer biomarkers. Blood provides an excellent medium for biomarker discovery. This study investigated systemic miRNAs differentially expressed in Luminal A-like (ER+PR+HER2/neu- breast cancer and their effectiveness as oncologic biomarkers in the clinical setting. METHODS: Blood samples were prospectively collected from patients with Luminal A-like breast cancer (n = 54 and controls (n = 56. RNA was extracted, reverse transcribed and subjected to microarray analysis (n = 10 Luminal A-like; n = 10 Control. Differentially expressed miRNAs were identified by artificial neural network (ANN data-mining algorithms. Expression of specific miRNAs was validated by RQ-PCR (n = 44 Luminal A; n = 46 Control and potential relationships between circulating miRNA levels and clinicopathological features of breast cancer were investigated. RESULTS: Microarray analysis identified 76 differentially expressed miRNAs. ANN revealed 10 miRNAs for further analysis (miR-19b, miR-29a, miR-93, miR-181a, miR-182, miR-223, miR-301a, miR-423-5p, miR-486-5 and miR-652. The biomarker potential of 4 miRNAs (miR-29a, miR-181a, miR-223 and miR-652 was confirmed by RQ-PCR, with significantly reduced expression in blood of women with Luminal A-like breast tumors compared to healthy controls (p = 0.001, 0.004, 0.009 and 0.004 respectively. Binary logistic regression confirmed that combination of 3 of these miRNAs (miR-29a, miR-181a and miR-652 could reliably differentiate between cancers and controls with an AUC of 0.80. CONCLUSION: This study provides insight into the underlying molecular portrait of Luminal A-like breast

  20. Cantilever with immobilized antibody for liver cancer biomarker detection

    International Nuclear Information System (INIS)

    A novel cantilever array-based bio-sensor was batch-fabricated with IC compatible MEMS technology for precise liver cancer bio-marker detection. A micro-cavity was designed in the free end of the cantilever for local antibody-immobilization, thus the adsorption of the cancer biomarker takes place only in the local region of the cantilever instead of the whole lever, and the effect of adsorption-induced k variation can be dramatically reduced. These structural features offer several advantages: high sensitivity, high throughput, high mass detection accuracy, and a portable system. In addition, an analytical model has been established to eliminate the effect of the adsorption-induced lever stiffness change and has been applied to the precise mass detection of the cancer biomarker AFP; the experimentally detected AFP antigen mass by the sensor (7.6 pg/mL) is quite close to the calculated one (5.5 pg/mL), two orders of magnitude better than those of the fully antibody-immobilized cantilever sensor. These approaches can promote real applications of the cantilever sensors in cancer diagnosis. (semiconductor devices)

  1. Cantilever with immobilized antibody for liver cancer biomarker detection

    Science.gov (United States)

    Shuaipeng, Wang; Jingjing, Wang; Yinfang, Zhu; Jinling, Yang; Fuhua, Yang

    2014-10-01

    A novel cantilever array-based bio-sensor was batch-fabricated with IC compatible MEMS technology for precise liver cancer bio-marker detection. A micro-cavity was designed in the free end of the cantilever for local antibody-immobilization, thus the adsorption of the cancer biomarker takes place only in the local region of the cantilever instead of the whole lever, and the effect of adsorption-induced k variation can be dramatically reduced. These structural features offer several advantages: high sensitivity, high throughput, high mass detection accuracy, and a portable system. In addition, an analytical model has been established to eliminate the effect of the adsorption-induced lever stiffness change and has been applied to the precise mass detection of the cancer biomarker AFP; the experimentally detected AFP antigen mass by the sensor (7.6 pg/mL) is quite close to the calculated one (5.5 pg/mL), two orders of magnitude better than those of the fully antibody-immobilized cantilever sensor. These approaches can promote real applications of the cantilever sensors in cancer diagnosis.

  2. A semiparametric modeling framework for potential biomarker discovery and the development of metabonomic profiles

    Directory of Open Access Journals (Sweden)

    Dey Dipak K

    2008-01-01

    Full Text Available Abstract Background The discovery of biomarkers is an important step towards the development of criteria for early diagnosis of disease status. Recently electrospray ionization (ESI and matrix assisted laser desorption (MALDI time-of-flight (TOF mass spectrometry have been used to identify biomarkers both in proteomics and metabonomics studies. Data sets generated from such studies are generally very large in size and thus require the use of sophisticated statistical techniques to glean useful information. Most recent attempts to process these types of data model each compound's intensity either discretely by positional (mass to charge ratio clustering or through each compounds' own intensity distribution. Traditionally data processing steps such as noise removal, background elimination and m/z alignment, are generally carried out separately resulting in unsatisfactory propagation of signals in the final model. Results In the present study a novel semi-parametric approach has been developed to distinguish urinary metabolic profiles in a group of traumatic patients from those of a control group consisting of normal individuals. Data sets obtained from the replicates of a single subject were used to develop a functional profile through Dirichlet mixture of beta distribution. This functional profile is flexible enough to accommodate variability of the instrument and the inherent variability of each individual, thus simultaneously addressing different sources of systematic error. To address instrument variability, all data sets were analyzed in replicate, an important issue ignored by most studies in the past. Different model comparisons were performed to select the best model for each subject. The m/z values in the window of the irregular pattern are then further recommended for possible biomarker discovery. Conclusion To the best of our knowledge this is the very first attempt to model the physical process behind the time-of flight mass

  3. Chemoresistive Gas Sensors for the Detection of Colorectal Cancer Biomarkers

    Directory of Open Access Journals (Sweden)

    Cesare Malagù

    2014-10-01

    Full Text Available Numerous medical studies show that tumor growth is accompanied by protein changes that may lead to the peroxidation of the cell membrane with consequent emission of volatile organic compounds (VOCs by breath or intestinal gases that should be seen as biomarkers for colorectal cancer (CRC. The analysis of VOCs represents a non-invasive and potentially inexpensive preliminary screening technique. An array of chemoresistive gas sensors based on screen-printed metal oxide semiconducting films has been selected to discriminate gases of oncological interest, e.g., 1-iodononane and benzene, widely assumed to be biomarkers of colorectal cancer, from those of interference in the gut, such as methane and nitric oxide.

  4. Nano and Microparticle-Enhanced Immunosensor Approaches for the Detection of Cancer Biomarker Proteins

    Science.gov (United States)

    Mani, Vigneshwaran

    Accurate, sensitive, point-of-care multiplexed protein measurements are critical for early disease detection and monitoring, impacting biomarker and drug discovery, and personalized medicine. Significant application involves monitoring panels of proteins in the blood that are biomarkers for diagnosing cancer. However, measurements of biomarker panels in blood or other bodily fluids have been slow to integrate into current practice of cancer diagnostics partly due to the lack of technically simple, low-cost, sensitive, point-of-care multiplexed measurement devices, as well as the lack of rigorously validated protein panels. The present thesis in part addresses these limitations by the development of electrochemical and surface plasmon resonance (SPR) immunosensors utilizing 1mum superparamagnetic labels for accurate detection of prostate cancer biomarker proteins in patient serum samples. Electrochemical discrete immunosensors featuring nanostructured surface with densely packed 5 nm glutathione-coated gold nanoparticles coupled with multi-enzyme magnetic particle (MP) labels enabled measurement of prostate specific antigen (PSA) with a detection limit (DL) of 0.5 pg mL-1 in undiluted serum. Such low DLs are attributed to high surface area, conductivity of nanostructured surface, and multi-enzyme signal amplification. DLs are further improved by utilizing MP bioconjugated with more than 100,000 antibody labels to offline capture proteins from the serum sample matrix, minimizing nonspecific binding of interfering proteins on sensor surface before detection. This approach provided an unprecedented 10 fg DL mL-1 for PSA in undiluted serum using a flow SPR biosensor. Finally electrochemical microfluidic immunoarrays featuring nanostructured surface and offline protein capture by multi-label MPs enabled multiplexed detection of prostate cancer biomarkers PSA and interleukin-6 (IL-6). These approaches provided up to 1000-fold lower DLs compared to commercial bead based

  5. Clinical Utility of Biomarkers in Localized Prostate Cancer.

    OpenAIRE

    Leapman, MS; Nguyen, HG; Cooperberg, MR

    2016-01-01

    A new generation of prostate cancer (PCa) biomarkers has emerged, including diagnostic serum and urine markers aimed at refining the identification high-grade tumors and tissue-based gene expression assays offering prognostic and predictive clinical information. Such tests seek to improve treatment-related decisions at multiple decision points, including initial diagnosis and following initial primary therapy. In this review, we aim to contextualize the body of evidence surrounding these emer...

  6. Characterisation of novel biomarkers for cancer therapy monitoring

    Czech Academy of Sciences Publication Activity Database

    Hrabáková, Rita; Kollareddy, M.; Tylečková, Jiřina; Halada, Petr; Hajdúch, M.; Kovářová, Hana

    Brixen: Max-Planck-Institute for Biophysical Chemistry, 2011. s. 1-1. [5th European Summer School „Proteomic basics“. 31.07.2011-06.08.2011, Brixen] R&D Projects: GA MŠk LC07017; GA MŠk MSM6198959216 Institutional research plan: CEZ:AV0Z50450515; CEZ:AV0Z50200510 Keywords : drug resistance * anti-cancer therapy * proteomics * biomarker Subject RIV: CE - Biochemistry

  7. Plasma alkylresorcinols, biomarkers of whole-grain wheat and rye intake, and incidence of colorectal cancer

    DEFF Research Database (Denmark)

    Kyrø, Cecilie; Olsen, Anja; Landberg, Rikard;

    2014-01-01

    between alkylresorcinols, biomarkers of whole-grain rye and wheat intake, and colorectal cancer incidence were investigated using prediagnostic plasma samples from colorectal cancer case patients and matched control subjects nested within the European Prospective Investigation into Cancer and Nutrition...

  8. Isolation and quantification of microRNAs from urinary exosomes/microvesicles for biomarker discovery.

    Science.gov (United States)

    Lv, Lin-Li; Cao, Yuhan; Liu, Dan; Xu, Min; Liu, Hong; Tang, Ri-Ning; Ma, Kun-Ling; Liu, Bi-Cheng

    2013-01-01

    Recent studies indicate that microRNA (miRNA) is contained within exosome. Here we sought to optimize the methodologies for the isolation and quantification of urinary exosomal microRNA as a prelude to biomarker discovery studies. Exosomes were isolated through ultracentrifugation and characterized by immunoelectron microscopy. To determine the RNA was confined inside exosomes, the pellet was treated with RNase before RNA isolation. The minimum urine volume, storage conditions for exosomes and exosomal miRNA was evaluated. The presence of miRNAs in patients with various kidney diseases was validated with real-time PCR. The result shows that miRNAs extracted from the exosomal fraction were resistant to RNase digestion and with high quality confirmed by agarose electrophoresis. 16 ml of urine was sufficient for miRNA isolation by absolute quantification with 4.15×10(5) copies/ul for miR-200c. Exosomes was stable at 4℃ 24h for shipping before stored at -80℃ and was stable in urine when stored at -80°C for 12 months. Exosomal miRNA was detectable despite 5 repeat freeze-thaw cycles. The detection of miRNA by quantitative PCR showed high reproducibility (>94% for intra-assay and >76% for inter-assay), high sensitivity (positive call 100% for CKD patients), broad dynamic range (8-log wide) and good linearity for quantification (R(2)>0.99). miR-29c and miR-200c showed different expression in different types of kidney disease. In summary, the presence of urinary exosomal miRNA was confirmed for patients with a diversity of chronic kidney disease. The conditions of urine collection, storage and miRNA detection determined in this study may be useful for future biomarker discovery efforts. PMID:24250247

  9. Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Astrid Wachter

    2015-11-01

    Full Text Available Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article.

  10. Candidate List of yoUr Biomarker (CLUB: A Web-based Platform to Aid Cancer Biomarker Research

    Directory of Open Access Journals (Sweden)

    N. Leigh Anderson

    2008-01-01

    Full Text Available CLUB (“Candidate List of yoUr Biomarkers” is a freely available, web-based resource designed to support Cancer biomarker research. It is targeted to provide a comprehensive list of candidate biomarkers for various cancers that have been reported by the research community. CLUB provides tools for comparison of marker candidates from different experimental platforms, with the ability to filter, search, query and explore, molecular interaction networks associated with cancer biomarkers from the published literature and from data uploaded by the community. This complex and ambitious project is implemented in phases. As a first step, we have compiled from the literature an initial set of differentially expressed human candidate cancer biomarkers. Each candidate is annotated with information from publicly available databases such as Gene Ontology, Swiss-Prot database, National Center for Biotechnology Information’s reference sequences, Biomolecular Interaction Network Database and IntAct interaction. The user has the option to maintain private lists of biomarker candidates or share and export these for use by the community. Furthermore, users may customize and combine commonly used sets of selection procedures and apply them as a stored workflow using selected candidate lists. To enable an assessment by the user before taking a candidate biomarker to the experimental validation stage, the platform contains the functionality to identify pathways associated with cancer risk, staging, prognosis, outcome in cancer and other clinically associated phenotypes. The system is available at http://club.bii.a-star.edu.sg.

  11. Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification

    Science.gov (United States)

    Book Chapter 18, titled Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification, will be published in the book titled High Performance Liquid Chromatography in Pesticide Residue Analysis (Part of the C...

  12. Potentiometric Sensors Based on Surface Molecular Imprinting: Detection of Cancer Biomarkers and Viruses

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y.; Zhang, Z; Jain, V; Yi, J; Mueller, S; Sokolov, J; Liu, Z; Levon, K; Rigas, B; Rafailovich, M

    2010-01-01

    The continuing discovery of cancer biomarkers necessitates improved methods for their detection. Molecular imprinting using artificial materials provides an alternative to the detection of a wide range of substances. We applied surface molecular imprinting using self-assembled monolayers to design sensing elements for the detection of cancer biomarkers and other proteins. These elements consist of a gold-coated silicon chip onto which hydroxyl-terminated alkanethiol molecules and template biomolecule are co-adsorbed, where the thiol molecules are chemically bound to the metal substrate and self-assembled into highly ordered monolayers, the biomolecules can be removed, creating the foot-print cavities in the monolayer matrix for this kind of template molecules. Re-adsorption of the biomolecules to the sensing chip changes its potential, which can be measured potentiometrically. We applied this method to the detection of carcinoembryonic antigen (CEA) in both solutions of purified CEA and in the culture medium of a CEA-producing human colon cancer cell line. The CEA assay, validated also against a standard immunoassay, was both sensitive (detection range 2.5-250 ng/mL) and specific (no cross-reactivity with hemoglobin; no response by a non-imprinted sensor). Similar results were obtained for human amylase. In addition, we detected virions of poliovirus in a specific manner (no cross-reactivity to adenovirus, no response by a non-imprinted sensor). Our findings demonstrate the application of the principles of molecular imprinting to the development of a new method for the detection of protein cancer biomarkers and to protein-based macromolecular structures such as the capsid of a virion. This approach has the potential of generating a general assay methodology that could be highly sensitive, specific, simple and likely inexpensive.

  13. Discovery and development of sulforaphane as a cancer chemopreventive phytochemical

    Institute of Scientific and Technical Information of China (English)

    Yuesheng ZHANG; Li TANG

    2007-01-01

    Sulforaphane (SF) is a phytochemical that displays both anticarcinogenic and anticancer activity. SF modulates many cancer-related events, including suscep-tibility to carcinogens, cell death, cell cycle, angiogenesis, invasion and metastasis.We review its discovery and development as a cancer chemopreventive agent with the intention of encouraging further research on this important compound and facilitating the identification and development of new phytochemicals for cancer prevention.

  14. MiRNAs and LincRNAs: Could They Be Considered as Biomarkers in Colorectal Cancer?

    Directory of Open Access Journals (Sweden)

    Jesús Garcia-Foncillas

    2012-01-01

    Full Text Available Recent advances in the field of RNA research have provided compelling evidence implicating microRNA (miRNA and long non-coding RNA molecules in many diverse and substantial biological processes, including transcriptional and post-transcriptional regulation of gene expression, genomic imprinting, and modulation of protein activity. Thus, studies of non-coding RNA (ncRNA may contribute to the discovery of possible biomarkers in human cancers. Considering that the response to chemotherapy can differ amongst individuals, researchers have begun to isolate and identify the genes responsible. Identification of targets of this ncRNA associated with cancer can suggest that networks of these linked to oncogenes or tumor suppressors play pivotal roles in cancer development. Moreover, these ncRNA are attractive drug targets since they may be differentially expressed in malignant versus normal cells and regulate expression of critical proteins in the cell. This review focuses on ncRNAs that are differently expressed in malignant tissue, and discusses some of challenges derived from their use as potential biomarkers of tumor properties.

  15. miRNAs and Other Epigenetic Changes as Biomarkers in Triple Negative Breast Cancer

    Directory of Open Access Journals (Sweden)

    Andrea Mathe

    2015-11-01

    Full Text Available Triple negative breast cancer (TNBC is characterised by the lack of receptors for estrogen (ER, progesterone (PR, and human epidermal growth factor 2 (HER2. Since it cannot be treated by current endocrine therapies which target these receptors and due to its aggressive nature, it has one of the worst prognoses of all breast cancer subtypes. The only treatments remain chemo- and/or radio-therapy and surgery and because of this, novel biomarkers or treatment targets are urgently required to improve disease outcomes. MicroRNAs represent an attractive candidate for targeted therapies against TNBC, due to their natural ability to act as antisense interactors and regulators of entire gene sets involved in malignancy and their superiority over mRNA profiling to accurately classify disease. Here we review the current knowledge regarding miRNAs as biomarkers in TNBC and their potential use as therapeutic targets in this disease. Further, we review other epigenetic changes and interactions of these changes with microRNAs in this breast cancer subtype, which may lead to the discovery of new treatment targets for TNBC.

  16. Feature Selection Methods for Early Predictive Biomarker Discovery Using Untargeted Metabolomic Data.

    Science.gov (United States)

    Grissa, Dhouha; Pétéra, Mélanie; Brandolini, Marion; Napoli, Amedeo; Comte, Blandine; Pujos-Guillot, Estelle

    2016-01-01

    Untargeted metabolomics is a powerful phenotyping tool for better understanding biological mechanisms involved in human pathology development and identifying early predictive biomarkers. This approach, based on multiple analytical platforms, such as mass spectrometry (MS), chemometrics and bioinformatics, generates massive and complex data that need appropriate analyses to extract the biologically meaningful information. Despite various tools available, it is still a challenge to handle such large and noisy datasets with limited number of individuals without risking overfitting. Moreover, when the objective is focused on the identification of early predictive markers of clinical outcome, few years before occurrence, it becomes essential to use the appropriate algorithms and workflow to be able to discover subtle effects among this large amount of data. In this context, this work consists in studying a workflow describing the general feature selection process, using knowledge discovery and data mining methodologies to propose advanced solutions for predictive biomarker discovery. The strategy was focused on evaluating a combination of numeric-symbolic approaches for feature selection with the objective of obtaining the best combination of metabolites producing an effective and accurate predictive model. Relying first on numerical approaches, and especially on machine learning methods (SVM-RFE, RF, RF-RFE) and on univariate statistical analyses (ANOVA), a comparative study was performed on an original metabolomic dataset and reduced subsets. As resampling method, LOOCV was applied to minimize the risk of overfitting. The best k-features obtained with different scores of importance from the combination of these different approaches were compared and allowed determining the variable stabilities using Formal Concept Analysis. The results revealed the interest of RF-Gini combined with ANOVA for feature selection as these two complementary methods allowed selecting the 48

  17. Biomarkers for pancreatic carcinogenesis

    OpenAIRE

    Hustinx, S.R.

    2007-01-01

    Pancreatic cancer is a devastating disease. Most pancreatic cancers (approximately 85%) are diagnosed at a late, incurable stage. The poor prognosis and late presentation of pancreatic cancer patients underscore the importance of early detection, which is the sine qua non for the fight against pancreatic cancer. It is hoped for the future that the understanding of genetic alterations will lead to the rapid discovery of an effective biomarker of pancreatic carcinogenesis. In this thesis we vis...

  18. Biomarkers for Response to Neoadjuvant Chemoradiation for Rectal Cancer

    International Nuclear Information System (INIS)

    Locally advanced rectal cancer (LARC) is currently treated with neoadjuvant chemoradiation. Although approximately 45% of patients respond to neoadjuvant therapy with T-level downstaging, there is no effective method of predicting which patients will respond. Molecular biomarkers have been investigated for their ability to predict outcome in LARC treated with neoadjuvant chemotherapy and radiation. A literature search using PubMed resulted in the initial assessment of 1,204 articles. Articles addressing the ability of a biomarker to predict outcome for LARC treated with neoadjuvant chemotherapy and radiation were included. Six biomarkers met the criteria for review: p53, epidermal growth factor receptor (EGFR), thymidylate synthase, Ki-67, p21, and bcl-2/bax. On the basis of composite data, p53 is unlikely to have utility as a predictor of response. Epidermal growth factor receptor has shown promise as a predictor when quantitatively evaluated in pretreatment biopsies or when EGFR polymorphisms are evaluated in germline DNA. Thymidylate synthase, when evaluated for polymorphisms in germline DNA, is promising as a predictive biomarker. Ki-67 and bcl-2 are not useful in predicting outcome. p21 needs to be further evaluated to determine its usefulness in predicting outcome. Bax requires more investigation to determine its usefulness. Epidermal growth factor receptor, thymidylate synthase, and p21 should be evaluated in larger prospective clinical trials for their ability to guide preoperative therapy choices in LARC.

  19. The path forward to biomarker discovery in psoriatic disease: a report from the GRAPPA 2010 annual meeting.

    Science.gov (United States)

    Gladman, Dafna D; Ritchlin, Christopher T; Fitzgerald, Oliver

    2012-02-01

    At the 2010 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), wide-ranging discussions were held regarding biomarker research in psoriatic disease. Consensus was reached on 2 areas of priority: (1) the study of soluble biomarkers of radiographic progression in psoriatic arthritis (PsA); and (2) the analysis of comorbidity biomarkers, specifically cardiovascular and articular, in a psoriasis inception cohort. For each of these areas, rigorous definition of the clinical phenotype of PsA will be essential. To date, 2 instruments have been identified to define the phenotype: the ClASsification of Psoriatic ARthritis criteria and various screening questionnaires. In this overview, we discuss the challenges of the clinical phenotype of PsA and review GRAPPA plans for developing a research program for biomarker discovery. PMID:22298275

  20. Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.; Hoogland, Marije; Vredenbregt-van den Berg, Mirella S.; Willemsen, Rob; Luider, Theo N.; Pasa-Tolic, Ljiljana; Jenster, Guido

    2013-12-31

    Introduction: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, biomarker discovery from body fluids is often hampered by the high abundance of many proteins unrelated to disease. An attractive alternative biomarker discovery approach is the isolation of small vesicles (exosomes, ~100 nm). They contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific marker discovery. Profiling prostate cancer-derived exosomes could reveal new markers for this malignancy. Materials and Methods: Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. Proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode, followed by the Accurate Mass and Time (AMT) tag approach. Exosomal proteins were validated by Western blotting. A Tissue Micro Array, containing 481 different PCa samples (radical prostatectomy), was used to correlate candidate markers with several clinical-pathological parameters such as PSA, Gleason score, biochemical recurrence, and (PCa-related) death. Results: Proteomic characterization resulted in the identification of 263 proteins by at least 2 peptides. Specifically analysis of exosomes from PNT2C2, RWPE-1, PC346C, and VCaP identified 248, 233, 169, and 216 proteins, respectively. Statistical analyses revealed 52 proteins differently expressed between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. The Tissue Micro 4 Array showed strong correlation of higher Gleason scores and local recurrence with increased cytoplasmic XPO1 (P<0.001). Conclusions: Differentially abundant proteins of cell line-derived exosomes make a clear subdivision between

  1. Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer.

    Science.gov (United States)

    Kim, Kyoungmi; Taylor, Sandra L; Ganti, Sheila; Guo, Lining; Osier, Michael V; Weiss, Robert H

    2011-05-01

    Kidney cancer is the seventh most common cancer in the Western world, its incidence is increasing, and it is frequently metastatic at presentation, at which stage patient survival statistics are grim. In addition, there are no useful biofluid markers for this disease, such that diagnosis is dependent on imaging techniques that are not generally used for screening. In the present study, we use metabolomics techniques to identify metabolites in kidney cancer patients' urine, which appear at different levels (when normalized to account for urine volume and concentration) from the same metabolites in nonkidney cancer patients. We found that quinolinate, 4-hydroxybenzoate, and gentisate are differentially expressed at a false discovery rate of 0.26, and these metabolites are involved in common pathways of specific amino acid and energetic metabolism, consistent with high tumor protein breakdown and utilization, and the Warburg effect. When added to four different (three kidney cancer-derived and one "normal") cell lines, several of the significantly altered metabolites, quinolinate, α-ketoglutarate, and gentisate, showed increased or unchanged cell proliferation that was cell line-dependent. Further evaluation of the global metabolomics analysis, as well as confirmation of the specific potential biomarkers using a larger sample size, will lead to new avenues of kidney cancer diagnosis and therapy. PMID:21348635

  2. Identification of a novel prostate cancer biomarker, caveolin-1: Implications and potential clinical benefit

    International Nuclear Information System (INIS)

    While prostate cancer is a common disease in men, it is uncommonly life-threatening. To better understand this phenomenon, tumor biologists have sought to elucidate the mechanisms that contribute to the development of virulent prostate cancer. The recent discovery that caveolin-1 (Cav-1) functions as an important oncogene involved in prostate cancer progression reflects the success of this effort. Cav-1 is a major structural coat protein of caveolae, specialized plasma membrane invaginations involved in multiple cellular functions, including molecular transport, cell adhesion, and signal transduction. Cav-1 is aberrantly overexpressed in human prostate cancer, with higher levels evident in metastatic versus primary sites. Intracellular Cav-1 promotes cell survival through activation of Akt and enhancement of additional growth factor pro-survival pathways. Cav-1 is also secreted as a biologically active molecule that promotes cell survival and angiogenesis within the tumor microenvironment. Secreted Cav-1 can be reproducibly detected in peripheral blood using a sensitive and specific immunoassay. Cav-1 levels distinguish men with prostate cancer from normal controls, and preoperative Cav-1 levels predict which patients are at highest risk for relapse following radical prostatectomy for localized disease. Thus, secreted Cav-1 is a promising biomarker in identifying clinically significant prostate cancer

  3. Identifying Cancer Biomarkers Via Node Classification within a Mapreduce Framework

    Directory of Open Access Journals (Sweden)

    Taysir Hassan A. Soliman

    2015-12-01

    Full Text Available Big data are giving new research challenges in the life sciences domain because of their variety, volume, veracity, velocity, and value. Predicting gene biomarkers is one of the vital research issues in bioinformatics field, where microarray gene expression and network based methods can be used. These datasets suffer from the huge data voluminous, causing main memory problems. In this paper, a Random Committee Node Classifier algorithm (RCNC is proposed for identifying cancer biomarkers, which is based on microarray gene expression data and Protein-Protein Interaction (PPI data. Data are enriched from other public databases, such as IntACT1 and UniProt2 and Gene Ontology3 (GO. Cancer Biomarkers are identified when applied to different datasets with an accuracy rate an accuracy rate 99.16%, 99.96% precision, 99.24% recall, 99.16% F1-measure and 99.6 ROC. To speed up the performance, it is run within a MapReduce framework, where RCNC MapReduce algorithm is much faster than RCNC sequential algorithm when having large datasets.

  4. Midkine: A Novel Prognostic Biomarker for Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Jono, Hirofumi, E-mail: hjono@fc.kuh.kumamoto-u.ac.jp; Ando, Yukio [Department of Diagnostic Medicine, Graduate School of Medical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto, 860-8556 (Japan)

    2010-04-20

    Since diagnosis at an early stage still remains a key issue for modern oncology and is crucial for successful cancer therapy, development of sensitive, specific, and non-invasive tumor markers, especially, in serum, is urgently needed. Midkine (MK), a plasma secreted protein, was initially identified in embryonal carcinoma cells at early stages of retinoic acid-induced differentiation. Multiple studies have reported that MK plays important roles in tumor progression, and is highly expressed in various malignant tumors. Because increased serum MK concentrations also have been reported in patients with various tumors, serum MK may have the potential to become a very useful tumor marker. Here, we review and discuss the possibility and usefulness of MK as a novel tumor marker.

  5. Biomarkers for diet and cancer prevention research: potentials and challenges

    Institute of Scientific and Technical Information of China (English)

    Cindy D DAVIS; John A MILNER

    2007-01-01

    As cancer incidence is projected to increase for decades there is a need for effec-tive preventive strategies. Fortunately, evidence continues to mount that altering dietary habits is an effective and cost-efficient approach for reducing cancer risk and for modifying the biological behavior of tumors. Predictive, validated and sensitive biomarkers, including those that reliably evaluate "intake" or exposure to a specific food or bioactive component, that assess one or more specific bio-logical "effects" that are linked to cancer, and that effectively predict individual "susceptibility" as a function of nutrient-nutrient interactions and genetics, are fundamental to evaluating who will benefit most from dietary interventions. These biomarkers must be readily accessible, easily and reliably assayed, and predictive of a key process(es) involved in cancer. The response to a food is determined not only by the effective concentration of the bioactive food component(s) reaching the target tissue, but also by the amount of the target requiring modification.Thus, this threshold response to foods and their components will vary from indi-vidual to individual. The key to understanding a personalized response is a greater knowledge of nutrigenomics, proteomics and metabolomics.

  6. E-Cadherin as a diagnostic biomarker in breast cancer

    Directory of Open Access Journals (Sweden)

    Rajeev Singhai

    2011-01-01

    Full Text Available Background: E-cadherin is expressed in most normal epithelial tissues. Selective loss of E-cadherin can cause dedifferentiation and invasiveness in human carcinomas, leading E-cadherin to be classified as a tumor suppressor. Loss of E-cadherin has been demonstrated in invasive lobular carcinoma of the breast, but the relationship between E-cadherin expression and breast cancer histopathology and prognosis is less clear. Aim: Our objective was to assess loss of E-cadherin as a diagnostic breast cancer biomarker and as an aid to the sub-classification of invasive breast cancer. We also correlated the loss of expression of E-cadherin with various clinical and pathologic prognostic factors. Material and Methods: Breast cancer specimens after modified radical mastectomy were obtained from women who underwent surgery at Grant Medical College and Sir J.J Group of Hospitals, Mumbai, India between May 2007 and October 2010. We stained 276 breast cancers specimens with monoclonal antibodies to E-cadherin. The breast cancers were classified by histopathological type. Results: A statistical correlation of E-cadherin loss with a positive diagnosis of invasive lobular carcinoma was found, but there was no correlation with any prognostic tumor variables. A negative E-cadherin stain was a sensitive and specific biomarker to confirm the diagnosis of invasive lobular carcinoma (specificity 97.7%; negative predictive value 96.8%; sensitivity 88.1%; and positive predictive value 91.2%. Positive E-cadherin expression was also associated with tubulolobular carcinomas. Conclusions: E-cadherin immunohistochemistry is helpful in classifying breast cancer cases with indeterminate histopathologic features. E-cadherin loss is uncommon in non-lobular carcinomas but shows no correlation to currently established prognostic variables.

  7. Targeting cancer testis antigens for biomarkers and immunotherapy in colorectal cancer: Current status and challenges

    Institute of Scientific and Technical Information of China (English)

    Anil; Suri; Nirmala; Jagadish; Shikha; Saini; Namita; Gupta

    2015-01-01

    Colorectal cancer ranks third among the estimatedcancer cases and cancer related mortalities in United States in 2014. Early detection and efficient therapy remains a significant clinical challenge for this disease. Therefore, there is a need to identify novel tumor asso-ciated molecules to target for biomarker development and immunotherapy. In this regard, cancer testis antigens have emerged as a potential targets for developing novel clinical biomarkers and immunotherapy for various malignancies. These germ cell specific proteins exhibit aberrant expression in cancer cells and contribute in tumorigenesis. Owing to their unique expression profile and immunogenicity in cancer patients, cancer testis antigens are clinically referred as the most promising tumor associated antigens. Several cancer testis antigens have been studied in colorectal cancer but none of them could be used in clinical practice. This review is an attempt to address the promising cancer testis antigens in colorectal cancer and their possible clinical implications as biomarkers and immunotherapeutic targets with particular focus on challenges and future interventions.

  8. Scaffold Repurposing of Old Drugs Towards New Cancer Drug Discovery.

    Science.gov (United States)

    Chen, Haijun; Wu, Jianlei; Gao, Yu; Chen, Haiying; Zhou, Jia

    2016-01-01

    As commented by the Nobelist James Black that "The most fruitful basis of the discovery of a new drug is to start with an old drug", drug repurposing represents an attractive drug discovery strategy. Despite the success of several repurposed drugs on the market, the ultimate therapeutic potential of a large number of non-cancer drugs is hindered during their repositioning due to various issues including the limited efficacy and intellectual property. With the increasing knowledge about the pharmacological properties and newly identified targets, the scaffolds of the old drugs emerge as a great treasure-trove towards new cancer drug discovery. In this review, we summarize the recent advances in the development of novel small molecules for cancer therapy by scaffold repurposing with highlighted examples. The relevant strategies, advantages, challenges and future research directions associated with this approach are also discussed. PMID:26881709

  9. A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery : SiViT

    OpenAIRE

    Brown, James L; Shovman, Mark; Robertson, Paul; Boiko, Andrei; Goltsov, Alexey; Mullen, Peter; Harrison, David James

    2016-01-01

    Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model in...

  10. Exosomal Proteins as a Diagnostic Biomarkers in Lung Cancer

    DEFF Research Database (Denmark)

    Sandfeld-Paulsen, B; Jakobsen, K R; Bæk, R;

    2016-01-01

    BACKGROUND: Exosomes have been suggested as promising biomarkers in non-small cell lung cancer (NSCLC), since they contain proteins from their originating cells and are readily available in plasma. In this study, we explore the potential of exosome protein profiling in diagnosing lung cancer...... patients of all stages and various histological subtypes. METHODS: Plasma was isolated from 581 patients (431 with lung cancer, 150 controls). The Extracellular Vesicle (EV) Array was used to phenotype exosomes. The EV Array contained 49 antibodies for capturing exosomes. Subsequently, a cocktail of biotin......-conjugated CD9, CD81 and CD63 antibodies was used to detect and visualize captured exosomes. Multi-marker models were made combining two or more markers. The optimal multi-marker model was evaluated by Area under the curve (AUC) and Random Forests analysis. RESULTS: The markers CD151, CD171 and Tspan8 were...

  11. Circulating DNA as Potential Biomarker for Cancer Individualized Therapy

    Institute of Scientific and Technical Information of China (English)

    Yu Shaorong; Liu Baorui; Lu Jianwei; Feng Jifeng

    2013-01-01

    Cancer individualized therapy often requires for gene mutation analysis of tumor tissue. However, tumor tissue is not always available in clinical practice, particularly from patients with refractory and recurrence disease. Even if patients have sufifcient tumor tissue for detection, as development of cancer, the gene status and drug sensitivity of tumor tissues could also change. Hence, screening mutations from primary tumor tissues becomes useless, it’s necessary to ifnd a surrogate tumor tissue for individualized gene screening. Circulating DNA is digested rapidly from blood, which could provide real-time information of the released fragment and make the real-time detection possible. Therefore, it’s expected that circulating DNA could be a potential tumor biomarker for cancer individualized therapy. This review focuses on the biology and clinical utility of circulating DNA mainly on gene mutation detection. Besides, its current status and possible direction in this research area is summarized and discussed objectively.

  12. Microscopy Opening Up New Cancer Discovery Avenues

    Science.gov (United States)

    Today’s high-powered microscopes are allowing researchers to study the fine details of individual cells and to peer into cells, opening up new avenues of discovery about the inner workings of cells, including the events that can cause healthy cells to tra

  13. Comparison of proteomic biomarker panels in urine and serum for ovarian cancer diagnosis

    DEFF Research Database (Denmark)

    Petri, Anette Lykke; Simonsen, Anja Hviid; Høgdall, Estrid; Christensen, Ib Jarle; Kjaer, Susanne Krüger; Yip, Christine; Risum, Signe Normann; Pedersen, Anette Tønnes; Hartwell, Dorte; Fung, Eric T; Høgdall, Claus

    2010-01-01

    The purposes of this study were to confirm previously found candidate epithelial ovarian cancer biomarkers in urine and to compare a paired serum biomarker panel and a urine biomarker panel from the same study cohort with regard to the receiver operating characteristic curve (ROC) area under the ...

  14. 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.

  15. Application of multiple statistical tests to enhance mass spectrometry-based biomarker discovery

    Directory of Open Access Journals (Sweden)

    Garner Harold R

    2009-05-01

    Full Text Available Abstract Background Mass spectrometry-based biomarker discovery has long been hampered by the difficulty in reconciling lists of discriminatory peaks identified by different laboratories for the same diseases studied. We describe a multi-statistical analysis procedure that combines several independent computational methods. This approach capitalizes on the strengths of each to analyze the same high-resolution mass spectral data set to discover consensus differential mass peaks that should be robust biomarkers for distinguishing between disease states. Results The proposed methodology was applied to a pilot narcolepsy study using logistic regression, hierarchical clustering, t-test, and CART. Consensus, differential mass peaks with high predictive power were identified across three of the four statistical platforms. Based on the diagnostic accuracy measures investigated, the performance of the consensus-peak model was a compromise between logistic regression and CART, which produced better models than hierarchical clustering and t-test. However, consensus peaks confer a higher level of confidence in their ability to distinguish between disease states since they do not represent peaks that are a result of biases to a particular statistical algorithm. Instead, they were selected as differential across differing data distribution assumptions, demonstrating their true discriminatory potential. Conclusion The methodology described here is applicable to any high-resolution MALDI mass spectrometry-derived data set with minimal mass drift which is essential for peak-to-peak comparison studies. Four statistical approaches with differing data distribution assumptions were applied to the same raw data set to obtain consensus peaks that were found to be statistically differential between the two groups compared. These consensus peaks demonstrated high diagnostic accuracy when used to form a predictive model as evaluated by receiver operating characteristics

  16. Towards discovery-driven translational research in breast cancer

    DEFF Research Database (Denmark)

    Celis, Julio E; Moreira, José M A; Gromova, Irina;

    2005-01-01

    , promise to have a major impact on the way breast cancer will be diagnosed, treated and monitored in the future. Here we present a brief report on long-term ongoing strategies at the Danish Centre for Translational Breast Cancer Research to search for markers for early detection and targets for therapeutic......Discovery-driven translational research in breast cancer is moving steadily from the study of cell lines to the analysis of clinically relevant samples that, together with the ever increasing number of novel and powerful technologies available within genomics, proteomics and functional genomics...... biology approach to fight breast cancer....

  17. Ki-67 biomarker in breast cancer of Indian women

    Directory of Open Access Journals (Sweden)

    Amit V. Patil

    2011-03-01

    Full Text Available Background: Biological markers that reliably predict clinical or pathological response to primary systemic therapy early during a course of chemotherapy may have considerable clinical potential. Aims: Aims of study to evaluated changes in Ki-67 (MIB-1 labeling index and apoptotic index (AI before, during, and after neoadjuvant anthracycline chemotherapy in breast cancer in Indian women. Materials and Methods: Breast cancer tissues were collected from Grant Medical College and Sir J.J. Group of Hospitals, Mumbai, India. Twenty-seven patients receiving neoadjuvant FEC (5-fluorouracil, epirubicin, and cyclophosphamide chemotherapy for operable breast cancer underwent repeat core biopsy after 21 days of treatment. Results: The objective clinical response rate was 56%. Eight patients (31% achieved a pathological response by histopathological criteria; two patients had a near-complete pathological response. Increased day-21 AI was a statistically significant predictor of pathological response (p = 0.049. A strong trend for predicting pathological response was seen with higher Ki-67 indices at day 21 and AI at surgery (p = 0.06 and 0.06, respectively. Conclusion: The clinical utility of early changes in biological marker expression during chemotherapy remains unclear. Until further prospectively validated evidence confirming the reliability of predictive biomarkers is available, clinical decision-making should not be based upon individual biological tumor biomarker profiles.

  18. 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

  19. Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection

    CERN Document Server

    Chung, Audrey G; Kumar, Devinder; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

    2015-01-01

    Prostate cancer is the most diagnosed form of cancer in Canadian men, and is the third leading cause of cancer death. Despite these statistics, prognosis is relatively good with a sufficiently early diagnosis, making fast and reliable prostate cancer detection crucial. As imaging-based prostate cancer screening, such as magnetic resonance imaging (MRI), requires an experienced medical professional to extensively review the data and perform a diagnosis, radiomics-driven methods help streamline the process and has the potential to significantly improve diagnostic accuracy and efficiency, and thus improving patient survival rates. These radiomics-driven methods currently rely on hand-crafted sets of quantitative imaging-based features, which are selected manually and can limit their ability to fully characterize unique prostate cancer tumour phenotype. In this study, we propose a novel \\textit{discovery radiomics} framework for generating custom radiomic sequences tailored for prostate cancer detection. Discover...

  20. Circulating exosomal microRNAs as biomarkers of colon cancer.

    Directory of Open Access Journals (Sweden)

    Hiroko Ogata-Kawata

    Full Text Available PURPOSE: Exosomal microRNAs (miRNAs have been attracting major interest as potential diagnostic biomarkers of cancer. The aim of this study was to characterize the miRNA profiles of serum exosomes and to identify those that are altered in colorectal cancer (CRC. To evaluate their use as diagnostic biomarkers, the relationship between specific exosomal miRNA levels and pathological changes of patients, including disease stage and tumor resection, was examined. EXPERIMENTAL DESIGN: Microarray analyses of miRNAs in exosome-enriched fractions of serum samples from 88 primary CRC patients and 11 healthy controls were performed. The expression levels of miRNAs in the culture medium of five colon cancer cell lines were also compared with those in the culture medium of a normal colon-derived cell line. The expression profiles of miRNAs that were differentially expressed between CRC and control sample sets were verified using 29 paired samples from post-tumor resection patients. The sensitivities of selected miRNAs as biomarkers of CRC were evaluated and compared with those of known tumor markers (CA19-9 and CEA using a receiver operating characteristic analysis. The expression levels of selected miRNAs were also validated by quantitative real-time RT-PCR analyses of an independent set of 13 CRC patients. RESULTS: The serum exosomal levels of seven miRNAs (let-7a, miR-1229, miR-1246, miR-150, miR-21, miR-223, and miR-23a were significantly higher in primary CRC patients, even those with early stage disease, than in healthy controls, and were significantly down-regulated after surgical resection of tumors. These miRNAs were also secreted at significantly higher levels by colon cancer cell lines than by a normal colon-derived cell line. The high sensitivities of the seven selected exosomal miRNAs were confirmed by a receiver operating characteristic analysis. CONCLUSION: Exosomal miRNA signatures appear to mirror pathological changes of CRC patients and

  1. Pathological examination of breast cancer biomarkers: current status in Japan.

    Science.gov (United States)

    Masuda, Shinobu

    2016-07-01

    This article reviews the current status of pathological evaluation for biomarkers in Japan. The introduced issues are the international trends for estimation of biomarkers considering diagnosis and treatment decision, and pathological issues under discussion, and how Japanese Breast Cancer Society (JBCS) members have addressed issues related to pathology and biomarkers evaluation. As topics of immunohistochemical study, (1) ASCO/CAP guidelines, (2) Ki67 and other markers, (3) quantification and image analysis, (4) application of cytologic samples, (5) pre-analytical process, and (6) Japan Pathology Quality Assurance System are introduced. Various phases of concepts, guidelines, and methodologies are co-existed in today's clinical practice. It is expected in near future that conventional methods and molecular procedures will be emerged, and Japanese Quality assurance/Quality control (QA/QC) system will work practically. What we have to do in the next generation are to validate novel procedures, to evaluate the relationship between traditional concepts and newly proposed ideas, to establish a well organized QA/QC system, and to standardize pre-analytical process that are the basis of all procedures using pathological tissues. PMID:25239167

  2. MetaBoot: a machine learning framework of taxonomical biomarker discovery for different microbial communities based on metagenomic data.

    Science.gov (United States)

    Wang, Xiaojun; Su, Xiaoquan; Cui, Xinping; Ning, Kang

    2015-01-01

    As more than 90% of species in a microbial community could not be isolated and cultivated, the metagenomic methods have become one of the most important methods to analyze microbial community as a whole. With the fast accumulation of metagenomic samples and the advance of next-generation sequencing techniques, it is now possible to qualitatively and quantitatively assess all taxa (features) in a microbial community. A set of taxa with presence/absence or their different abundances could potentially be used as taxonomical biomarkers for identification of the corresponding microbial community's phenotype. Though there exist some bioinformatics methods for metagenomic biomarker discovery, current methods are not robust, accurate and fast enough at selection of non-redundant biomarkers for prediction of microbial community's phenotype. In this study, we have proposed a novel method, MetaBoot, that combines the techniques of mRMR (minimal redundancy maximal relevance) and bootstrapping, for discover of non-redundant biomarkers for microbial communities through mining of metagenomic data. MetaBoot has been tested and compared with other methods on well-designed simulated datasets considering normal and gamma distribution as well as publicly available metagenomic datasets. Results have shown that MetaBoot was robust across datasets of varied complexity and taxonomical distribution patterns and could also select discriminative biomarkers with quite high accuracy and biological consistency. Thus, MetaBoot is suitable for robustly and accurately discover taxonomical biomarkers for different microbial communities. PMID:26213658

  3. Cancer patient flows discovery in DRG databases

    OpenAIRE

    Jay, Nicolas; Napoli, Amedeo; Kohler, François

    2006-01-01

    In France, cancer care is evolving to the design of regional networks, so as to coordinate expertise, services and resources allocation. Existing information systems along with data-mining tools can provide better knowledge on the distribution of patient flows. We used one year data of the French Diagnosis Related Groups (DRGs) based system to perform our analysis. Formal Concept Analysis has been used to build Iceberg Lattices of cancer patient flows in the French region of Lorraine. This un...

  4. Reverse phase protein array based tumor profiling identifies a biomarker signature for risk classification of hormone receptor-positive breast cancer

    Directory of Open Access Journals (Sweden)

    Johanna Sonntag

    2014-03-01

    Full Text Available A robust subclassification of luminal breast cancer, the most common molecular subtype of human breast cancer, is crucial for therapy decisions. While a part of patients is at higher risk of recurrence and requires chemo-endocrine treatment, the other part is at lower risk and also poorly responds to chemotherapeutic regimens. To approximate the risk of cancer recurrence, clinical guidelines recommend determining histologic grading and abundance of a cell proliferation marker in tumor specimens. However, this approach assigns an intermediate risk to a substantial number of patients and in addition suffers from a high interobserver variability. Therefore, the aim of our study was to identify a quantitative protein biomarker signature to facilitate risk classification. Reverse phase protein arrays (RPPA were used to obtain quantitative expression data for 128 breast cancer relevant proteins in a set of hormone receptor-positive tumors (n = 109. Proteomic data for the subset of histologic G1 (n = 14 and G3 (n = 22 samples were used for biomarker discovery serving as surrogates of low and high recurrence risk, respectively. A novel biomarker selection workflow based on combining three different classification methods identified caveolin-1, NDKA, RPS6, and Ki-67 as top candidates. NDKA, RPS6, and Ki-67 were expressed at elevated levels in high risk tumors whereas caveolin-1 was observed as downregulated. The identified biomarker signature was subsequently analyzed using an independent test set (AUC = 0.78. Further evaluation of the identified biomarker panel by Western blot and mRNA profiling confirmed the proteomic signature obtained by RPPA. In conclusion, the biomarker signature introduced supports RPPA as a tool for cancer biomarker discovery.

  5. Circulating microRNAs as Prognostic and Predictive Biomarkers in Patients with Colorectal Cancer

    OpenAIRE

    Jakob Vasehus Schou; Julia Sidenius Johansen; Dorte Nielsen; Simona Rossi

    2016-01-01

    MiRNAs are suggested as promising cancer biomarkers. They are stable and extractable from a variety of clinical tissue specimens (fresh frozen or formalin fixed paraffin embedded tissue) and a variety of body fluids (e.g., blood, urine, saliva). However, there are several challenges that need to be solved, considering their potential as biomarkers in cancer, such as lack of consistency between biomarker panels in independent studies due to lack of standardized sample handling and processing, ...

  6. New discoveries in prostate cancer pathogenesis

    International Nuclear Information System (INIS)

    Background. Through PSA screening the rate of prostate cancers detected at an early stage has increased significantly; thus a decrease in mortality can be expected in the near future. Despite all scientific efforts, however, the molecular mechanisms underlying the development and progression of prostate cancer remain poorly understood. Prostate cancer is a disease of aging men and epidemiological evidence supports a major contribution to its development through diet, lifestyle and environmental factors. Genetic instability is the basic phenomenon of tissue cell cancerisation. This instability can be hereditary or due to mutations and other chromosomal aberrations acquired during life. In recent years a large number of interesting data have been collected which show the relationships between focal atrophy and genetic instability of the prostate epithelia. Atrophy can be the result of prostatitis, ischemia as well as of oxidative stress (diet). Several chromosomal aberrations typical for prostate cancer (loss of 8p22; gain of 8q24 and X) can be already detected in the epithelia of the atrophic areas. Moreover also the deactivation of a gene (GSTP1) which encodes a carcinogene-detoxification enzyme has been found in such epithelia. Conclusions. Molecular pathology is slowly revealing the links which exist among age, atherosclerosis and oxidative stress (diet), inflammation and the pathogenesis of prostate cancer. In the near future perhaps this knowledge will enable us to actively prevent this most common malignancy of elderly men. (author)

  7. Validation of Candidate Serum Ovarian Cancer Biomarkers for Early Detection

    Directory of Open Access Journals (Sweden)

    Feng Su

    2007-01-01

    Full Text Available Objective: We have previously analyzed protein profi les using Surface Enhanced Laser Desorption and Ionization Time-Of-Flight Mass Spectroscopy (SELDI-TOF-MS [Kozak et al. 2003, Proc. Natl. Acad. Sci. U.S.A. 100:12343–8] and identified 3 differentially expressed serum proteins for the diagnosis of ovarian cancer (OC [Kozak et al. 2005, Proteomics, 5:4589–96], namely, apolipoprotein A-I (apoA-I, transthyretin (TTR and transferin (TF. The objective of the present study is to determine the efficacy of the three OC biomarkers for the detection of early stage (ES OC, in direct comparison to CA125.Methods: The levels of CA125, apoA-I, TTR and TF were measured in 392 serum samples [82 women with normal ovaries (N, 24 women with benign ovarian tumors (B, 85 women with ovarian tumors of low malignant potential (LMP, 126 women with early stage ovarian cancer (ESOC, and 75 women with late stage ovarian cancer (LSOC], obtained through the GOG and Cooperative Human Tissue Network. Following statistical analysis, multivariate regression models were built to evaluate the utility of the three OC markers in early detection.Results: Multiple logistic regression models (MLRM utilizing all biomarker values (CA125, TTR, TF and apoA-I from all histological subtypes (serous, mucinous, and endometrioid adenocarcinoma distinguished normal samples from LMP with 91% sensitivity (specifi city 92%, and normal samples from ESOC with a sensitivity of 89% (specifi city 92%. MLRM, utilizing values of all four markers from only the mucinous histological subtype showed that collectively, CA125, TTR, TF and apoA-I, were able to distinguish normal samples from mucinous LMP with 90% sensitivity, and further distinguished normal samples from early stage mucinous ovarian cancer with a sensitivity of 95%. In contrast, in serum samples from patients with mucinous tumors, CA125 alone was able to distinguish normal samples from LMP and early stage ovarian cancer with a sensitivity of

  8. The Janus serum bank and biomarkers of cancer

    Directory of Open Access Journals (Sweden)

    Randi Gislefoss

    2009-10-01

    Full Text Available The Janus serum bank, established in 1973, contains sera stored at –25 degrees collected from 330,000 originally healthy individuals. The number of cancer cases have increased from zero in 1973 to more than 50,000 in 2005, including invasive and non-invasive cancers. Information on cases have been obtained by coupling the Janus file against the Norwegian Cancer Registry. The sera have been used in over 70 different cancers research projects, usually in case-control studies and in collaboration with national and international research groups. The type of biomarker analysed include antibodies against Chlamydia, CMV, Epstein Barr virus, HPV and Helicobacter pylori. Leptin, long chain fatty acids, androgens and other hormones, vitamins as well as environmental toxins such as organochlorines are other types of cancer biomarkers investigated. Mutation analyses (BRCA-1 etc have been possible using PCR and the trace amounts of DNA remaining in the sera.Janus serum bank ble etablert i 1973 og inneholder sera lagret ved –25 grader, innsamlet fra 330.000 opprinnelig friske personer. Antall krefttilfeller har steget fra null i 1973 til over 50.000 i år 2005, inkludert både invasiv og ikke-invasiv kreft. Informasjon om kasus er tilgjengelig ved å koble Janus-filene mot Kreftregisterets databaser. Serumprøvene er blitt benyttet i over 70 forskjellige kreftforskningsprosjekter, som oftest i kasus-kontroll studier og i samarbeide med en rekke nasjonale og internasjonale forskningsgrupper. Mange ulike biomarkører på kreft er blitt analysert, bl.a. antistoffer mot Chlamydia, CMV, Epstein Barr virus, HPV og Helicobacter pylori. Leptin, lange fettsyrer, androgener og andre hormoner, vitaminer såvel som miljøgifter av typen organiske klorforbindelser er eksempler på andre kreftbiomarkører som er undersøkt. Det har også vært mulig å gjøre mutasjonsanalyser (BRCA-1 etc ved å bruke PCR til å amplifisere opp den spormengden DNA som finnes i serum.

  9. Urinary metalloproteinases: noninvasive biomarkers for breast cancer risk assessment

    DEFF Research Database (Denmark)

    Pories, Susan E; Zurakowski, David; Roy, Roopali;

    2008-01-01

    Matrix metalloproteinases (MMP) and a disintegrin and metalloprotease 12 (ADAM 12) can be detected in the urine of breast cancer patients and provide independent prediction of disease status. To evaluate the potential of urinary metalloproteinases as biomarkers to predict breast cancer risk status......, urine samples from women with known risk marker lesions, atypical hyperplasia and lobular carcinoma in situ (LCIS), were analyzed. Urine samples were obtained from 148 women: 44 women with atypical hyperplasia, 24 women with LCIS, and 80 healthy controls. MMP analysis was done using gelatin zymography...... and ADAM 12 analysis was done via immunoblotting with monospecific antibodies and subsequent densitometric measurement. Positive urinary MMP-9 levels indicated a 5-fold risk of atypical hyperplasia and >13-fold risk of LCIS compared with normal controls. Urinary ADAM 12 levels were significantly...

  10. Exosomal miRNAs as cancer biomarkers and therapeutic targets.

    Science.gov (United States)

    Thind, Arron; Wilson, Clive

    2016-01-01

    Intercommunication between cancer cells and with their surrounding and distant environments is key to the survival, progression and metastasis of the tumour. Exosomes play a role in this communication process. MicroRNA (miRNA) expression is frequently dysregulated in tumour cells and can be reflected by distinct exosomal miRNA (ex-miRNA) profiles isolated from the bodily fluids of cancer patients. Here, the potential of ex-miRNA as a cancer biomarker and therapeutic target is critically analysed. Exosomes are a stable source of miRNA in bodily fluids but, despite a number of methods for exosome extraction and miRNA quantification, their suitability for diagnostics in a clinical setting is questionable. Furthermore, exosomally transferred miRNAs can alter the behaviour of recipient tumour and stromal cells to promote oncogenesis, highlighting a role in cell communication in cancer. However, our incomplete understanding of exosome biogenesis and miRNA loading mechanisms means that strategies to target exosomes or their transferred miRNAs are limited and not specific to tumour cells. Therefore, if ex-miRNA is to be employed in novel non-invasive diagnostic approaches and as a therapeutic target in cancer, two further advances are necessary: in methods to isolate and detect ex-miRNA, and a better understanding of their biogenesis and functions in tumour-cell communication. PMID:27440105

  11. PBX3 is a putative biomarker of aggressive prostate cancer.

    Science.gov (United States)

    Ramberg, Håkon; Grytli, Helene Hartvedt; Nygård, Ståle; Wang, Wanzhong; Ögren, Olov; Zhao, Sen; Løvf, Marthe; Katz, Betina; Skotheim, Rolf I; Bjartell, Anders; Eri, Lars Magne; Berge, Viktor; Svindland, Aud; Taskén, Kristin Austlid

    2016-10-15

    There is a great need to identify new and better prognostic and predictive biomarkers to stratify prostate cancer patients for optimal treatment. The aims of this study were to characterize the expression profile of pre-B cell leukemia homeobox (PBX) transcription factors in prostate cancer with an emphasis on investigating whether PBX3 harbours any prognostic value. The expression profile of PBX3 and PBX1 in prostate tissue was determined by immunohistochemical and immunoblot analysis. Furthermore, the expression of PBX3 transcript variants was analyzed by RT-PCR, NanoString Technologies®, and by analyzing RNA sequence data. The potential of PBX3 to predict prognosis, either at mRNA or protein level, was studied in four independent cohorts. PBX3 was mainly expressed in the nucleus of normal prostate basal cells, while it showed cytosolic expression in prostatic intraepithelial neoplasia and cancer cells. We detected four PBX3 transcript variants in prostate tissue. Competing risk regression analysis revealed that high PBX3 expression was associated with slower progression to castration resistant prostate cancer (sub-hazard ratio (SHR) 0.18, 95% CI: 0.081-0.42, p values aggressive prostate cancer. PMID:27273830

  12. Significant cancer prevention factor extraction: an association rule discovery approach.

    Science.gov (United States)

    Nahar, Jesmin; Tickle, Kevin S; Ali, A B M Shawkat; Chen, Yi-Ping Phoebe

    2011-06-01

    Cancer is increasing the total number of unexpected deaths around the world. Until now, cancer research could not significantly contribute to a proper solution for the cancer patient, and as a result, the high death rate is uncontrolled. The present research aim is to extract the significant prevention factors for particular types of cancer. To find out the prevention factors, we first constructed a prevention factor data set with an extensive literature review on bladder, breast, cervical, lung, prostate and skin cancer. We subsequently employed three association rule mining algorithms, Apriori, Predictive apriori and Tertius algorithms in order to discover most of the significant prevention factors against these specific types of cancer. Experimental results illustrate that Apriori is the most useful association rule-mining algorithm to be used in the discovery of prevention factors. PMID:20703554

  13. Circulating microRNAs: Novel biomarkers for esophageal cancer

    Directory of Open Access Journals (Sweden)

    Sheng-Li Zhou, Li-Dong Wang

    2010-05-01

    Full Text Available Esophageal carcinogenesis is a multi-stage process, involving a variety of changes in gene expression and physiological structure change. MicroRNAs (miRNAs are a class of small non-coding endogenous RNA molecules. Recent innovation in miRNAs profiling technology have shed new light on the pathology of esophageal carcinoma (EC, and also heralded great potential for exploring novel biomarkers for both EC diagnosis and treatment. Frequent dysregulation of miRNA in malignancy highlights the study of molecular factors upstream of gene expression following the extensive investigation on elucidating the important role of miRNA in carcinogenesis. We herein present a thorough review of the role of miRNAs in EC, addressing miRNA functions, their putative role as oncogenes or tumor suppressors and their potential target genes. The recent progresses in discovering the quantifiable circulating cancer-associated miRNAs indicate the potential clinical use of miRNAs as novel minimally invasive biomarkers for EC and other cancers. We also discuss the potential role of miRNAs in detection, screening and surveillance of EC as miRNAs can be a potential target in personalized treatment of EC.

  14. Challenges in Using Circulating miRNAs as Cancer Biomarkers

    Directory of Open Access Journals (Sweden)

    Paola Tiberio

    2015-01-01

    Full Text Available In the last years, circulating miRNAs have emerged as a new class of promising cancer biomarkers. Independent studies have shown the feasibility of using these small RNAs as tools for the diagnosis and prognosis of different types of malignancies as well as for predicting and possibly monitoring treatment response. However, despite an initial enthusiasm for their possible clinical application, widespread inconsistencies have been observed among the studies, and miRNA-based tools still represent the object of research within clinical diagnostic or treatment protocols. The poor overlap of results could be explained, at least in part, by preanalytical and analytical variables and donor-related factors that could generate artefacts, impairing an accurate quantification of circulating miRNAs. In fact, critical issues are represented by nonuniform sample choice, handling, and processing, as well as by blood cell contamination in sample preparation and lack of consensus for data normalization. In this review, we address the potential technical biases and individual-related parameters that can influence circulating miRNA studies’ outcome. The exciting potential of circulating miRNAs as cancer biomarkers could confer an important advance in the disease management, but their clinical significance might not be proven without a global consensus of procedures and standardized protocols for their accurate detection.

  15. A Preliminary Analysis of Non-small Cell Lung Cancer Biomarkers in Serum

    Institute of Scientific and Technical Information of China (English)

    XUE-YUAN XIAO; YING TANG; XIU-PING WEI; DA-CHENG HE

    2003-01-01

    Objective To identify potential serum biomarkers that could be used to discriminate lungcancers from normal. Methods Proteomic spectra of twenty-eight serum samples from patientswith non-small cell lung cancer and twelve from normal individuals were generated by SELDI(Surfaced Enhanced Laser Desorption/Ionization) Mass Spectrometry. Anion-exchange columns wereused to fractionate the sera into 6 designated pH groups. Two different types of protein chip arrays,IMAC-Cu and WCX2, were employed. Samples were examined in PBSII Protein Chip Reader(Ciphergen Biosystem Inc) and the discriminatory profiling between cancer and normal samples wasanalyzed with Biomarker Pattern software. Results Five distinct potential lung cancer biomarkerswith higher sensitivity and specificity were found, with four common biomarkers in both IMAC-Cuand WCX2 chip; the remaining biomarker occurred only in WCX2 chip. Two biomarkers wereup-regulated while three biomarkers were down-regulated in the serum samples from patients withnon-small cell lung cancer. The sensitivities provided by the individual biomarkers were 75%-96.43%and specificities were 75%-100%. Conclusions The preliminary results suggest that serum is acapable resource for detecting specific non-small cell lung cancer biomarkers. SELDI massspectrometry is a useful tool for the detection and identification of new potential biomarker ofnon-small cell lung cancer in serum.

  16. Discovery and validation of breast cancer subtypes

    OpenAIRE

    Bukholm Ida RK; Noh Dong-Young; Han Wonshik; Børresen-Dale Anne-Lise; Langerød Anita; Jeffrey Stefanie S; Kapp Amy V; Nicolau Monica; Brown Patrick O; Tibshirani Robert

    2006-01-01

    Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets) using a ...

  17. Differential profiling of breast cancer plasma proteome by isotope-coded affinity tagging method reveals biotinidase as a breast cancer biomarker

    International Nuclear Information System (INIS)

    Breast cancer is one of the leading causes of women's death worldwide. It is important to discover a reliable biomarker for the detection of breast cancer. Plasma is the most ideal source for cancer biomarker discovery since many cells cross-communicate through the secretion of soluble proteins into blood. Plasma proteomes obtained from 6 breast cancer patients and 6 normal healthy women were analyzed by using the isotope-coded affinity tag (ICAT) labeling approach and tandem mass spectrometry. All the plasma samples used were depleted of highly abundant 6 plasma proteins by immune-affinity column chromatography before ICAT labeling. Several proteins showing differential abundance level were selected based on literature searches and their specificity to the commercially available antibodies, and then verified by immunoblot assays. A total of 155 proteins were identified and quantified by ICAT method. Among them, 33 proteins showed abundance changes by more than 1.5-fold between the plasmas of breast cancer patients and healthy women. We chose 5 proteins for the follow-up confirmation in the individual plasma samples using immunoblot assay. Four proteins, α1-acid glycoprotein 2, monocyte differentiation antigen CD14, biotinidase (BTD), and glutathione peroxidase 3, showed similar abundance ratio to ICAT result. Using a blind set of plasmas obtained from 21 breast cancer patients and 21 normal healthy controls, we confirmed that BTD was significantly down-regulated in breast cancer plasma (Wilcoxon rank-sum test, p = 0.002). BTD levels were lowered in all cancer grades (I-IV) except cancer grade zero. The area under the receiver operating characteristic curve of BTD was 0.78. Estrogen receptor status (p = 0.940) and progesterone receptor status (p = 0.440) were not associated with the plasma BTD levels. Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer

  18. Biomarkers for cancer-related fatigue and adverse reactions to chemotherapy in lung cancer patients

    OpenAIRE

    Sha, Fei; ZHUANG, SHANSHAN; Zhou, Li; Zhang, Liqun; YANG, YUXIAN; ZHANG, SHENGQI; Jiang, Yi; QIU, GUODONG; Chen, Chen; ZHENG, JIETING; ZHANG, SHUYAO

    2014-01-01

    This study was conducted to investigate the biomarkers that appear to be correlated with cancer-related fatigue (CRF) and the adverse reactions (ADRs) to chemotherapy. A total of 100 lung cancer patients were selected and CRF prior to and following chemotherapy was evaluated. The plasma levels of tumor necrosis factor (TNF)-α and interleukin (IL)-1 and the level of 17-hydroxycorticosteroid (17-OHCS) in the urine were analyzed and correlated with CRF and the ADRs associated with chemotherapy. ...

  19. Bioinformatics for cancer immunotherapy target discovery

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Campos, Benito; Barnkob, Mike Stein;

    2014-01-01

    cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline......The mechanisms of immune response to cancer have been studied extensively and great effort has been invested into harnessing the therapeutic potential of the immune system. Immunotherapies have seen significant advances in the past 20 years, but the full potential of protective and therapeutic...... and co-targets for single-epitope and multi-epitope strategies. We provide examples of application to the well-known tumor antigen HER2 and suggest bioinformatics methods to ameliorate therapy resistance and ensure efficient and lasting control of tumors....

  20. Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

    Directory of Open Access Journals (Sweden)

    Yingrong Chen

    2015-01-01

    Full Text Available Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.

  1. Circular RNAs as potential biomarkers for cancer diagnosis and therapy.

    Science.gov (United States)

    Wang, Fengling; Nazarali, Adil J; Ji, Shaoping

    2016-01-01

    Circular RNAs (circRNAs) are a naturally occurring type of universal and diverse endogenous noncoding RNAs which unlike linear RNAs, have covalently linked ends. They are usually stable, abundant, conserved RNA molecules and often exhibit tissue/developmental-stage specific expression. Functional circRNAs have been identified to act as microRNA sponges and RNA-binding protein (RBP) sequestering agents as well as transcriptional regulators. These multiple functional roles elicit a great potential for circRNAs in biological applications. Emerging evidence shows that circRNAs play important roles in several diseases, particularly in cancer where they act through regulating protein expression of the pivotal genes that are critical for carcinogenesis. The presence of abundant circRNAs in saliva, exosomes and clinical standard blood samples will make them potential diagnostic or predictive biomarkers for diseases, particularly for cancer development, progression and prognosis. Here, we review the current literature and provide evidence for the impact of circRNAs in cancers and their potential significance in cancer prognosis and clinical treatment. PMID:27429839

  2. Many accurate small-discriminatory feature subsets exist in microarray transcript data: biomarker discovery

    Directory of Open Access Journals (Sweden)

    Grate Leslie R

    2005-04-01

    Full Text Available Abstract Background Molecular profiling generates abundance measurements for thousands of gene transcripts in biological samples such as normal and tumor tissues (data points. Given such two-class high-dimensional data, many methods have been proposed for classifying data points into one of the two classes. However, finding very small sets of features able to correctly classify the data is problematic as the fundamental mathematical proposition is hard. Existing methods can find "small" feature sets, but give no hint how close this is to the true minimum size. Without fundamental mathematical advances, finding true minimum-size sets will remain elusive, and more importantly for the microarray community there will be no methods for finding them. Results We use the brute force approach of exhaustive search through all genes, gene pairs (and for some data sets gene triples. Each unique gene combination is analyzed with a few-parameter linear-hyperplane classification method looking for those combinations that form training error-free classifiers. All 10 published data sets studied are found to contain predictive small feature sets. Four contain thousands of gene pairs and 6 have single genes that perfectly discriminate. Conclusion This technique discovered small sets of genes (3 or less in published data that form accurate classifiers, yet were not reported in the prior publications. This could be a common characteristic of microarray data, thus making looking for them worth the computational cost. Such small gene sets could indicate biomarkers and portend simple medical diagnostic tests. We recommend checking for small gene sets routinely. We find 4 gene pairs and many gene triples in the large hepatocellular carcinoma (HCC, Liver cancer data set of Chen et al. The key component of these is the "placental gene of unknown function", PLAC8. Our HMM modeling indicates PLAC8 might have a domain like part of lP59's crystal structure (a Non

  3. A TMA de-arraying method for high throughput biomarker discovery in tissue research.

    Directory of Open Access Journals (Sweden)

    Yinhai Wang

    Full Text Available BACKGROUND: Tissue MicroArrays (TMAs represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide. METHODOLOGY: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap. CONCLUSION: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores, 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.

  4. Discovery and validation of breast cancer subtypes

    Directory of Open Access Journals (Sweden)

    Bukholm Ida RK

    2006-09-01

    Full Text Available Abstract Background Previous studies demonstrated breast cancer tumor tissue samples could be classified into different subtypes based upon DNA microarray profiles. The most recent study presented evidence for the existence of five different subtypes: normal breast-like, basal, luminal A, luminal B, and ERBB2+. Results Based upon the analysis of 599 microarrays (five separate cDNA microarray datasets using a novel approach, we present evidence in support of the most consistently identifiable subtypes of breast cancer tumor tissue microarrays being: ESR1+/ERBB2-, ESR1-/ERBB2-, and ERBB2+ (collectively called the ESR1/ERBB2 subtypes. We validate all three subtypes statistically and show the subtype to which a sample belongs is a significant predictor of overall survival and distant-metastasis free probability. Conclusion As a consequence of the statistical validation procedure we have a set of centroids which can be applied to any microarray (indexed by UniGene Cluster ID to classify it to one of the ESR1/ERBB2 subtypes. Moreover, the method used to define the ESR1/ERBB2 subtypes is not specific to the disease. The method can be used to identify subtypes in any disease for which there are at least two independent microarray datasets of disease samples.

  5. Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

    OpenAIRE

    2015-01-01

    Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top...

  6. Circulating MicroRNAs as Biomarkers in Biliary Tract Cancers

    Science.gov (United States)

    Letelier, Pablo; Riquelme, Ismael; Hernández, Alfonso H.; Guzmán, Neftalí; Farías, Jorge G.; Roa, Juan Carlos

    2016-01-01

    Biliary tract cancers (BTCs) are a group of highly aggressive malignant tumors with a poor prognosis. The current diagnosis is based mainly on imaging and intraoperative exploration due to brush cytology havinga low sensitivity and the standard markers, such as carcinoembryonic antigen (CEA) and carbohydrate 19-9 (CA19-9), not having enough sensitivity nor specificity to be used in a differential diagnosis and early stage detection. Thus, better non-invasive methods that can distinguish between normal and pathological tissue are needed. MicroRNAs (miRNAs) are small, single-stranded non-coding RNA molecules of ~20–22 nucleotides that regulate relevant physiological mechanisms and can also be involved in carcinogenesis. Recent studies have demonstrated that miRNAs are detectable in multiple body fluids, showing great stability, either free or trapped in circulating microvesicles, such as exosomes. miRNAs are ideal biomarkers that may be used in screening and prognosis in biliary tract cancers, aiding also in the clinical decisions at different stages of cancer treatment. This review highlights the progress in the analysis of circulating miRNAs in serum, plasma and bile as potential diagnostic and prognostic markers of BTCs. PMID:27223281

  7. Role of MGMT as biomarker in colorectal cancer

    Science.gov (United States)

    Inno, Alessandro; Fanetti, Giuseppe; Di Bartolomeo, Maria; Gori, Stefania; Maggi, Claudia; Cirillo, Massimo; Iacovelli, Roberto; Nichetti, Federico; Martinetti, Antonia; de Braud, Filippo; Bossi, Ilaria; Pietrantonio, Filippo

    2014-01-01

    O6-methylguanine DNA methyltransferase (MGMT) gene promoter methylation plays an important role in colorectal carcinogenesis, occurring in about 30%-40% of metastatic colorectal cancer. Its prognostic role has not been defined yet, but loss of expression of MGMT, which is secondary to gene promoter methylation, results in an interesting high response to alkylating agents such as dacarbazine and temozolomide. In a phase 2 study on heavily pre-treated patients with MGMT methylated metastatic colorectal cancer, temozolomide achieved about 30% of disease control rate. Activating mutations of RAS or BRAF genes as well as mismatch repair deficiency may represent mechanisms of resistance to alkylating agents, but a dose-dense schedule of temozolomide may potentially restore sensitivity in RAS-mutant patients. Further development of temozolomide in MGMT methylated colorectal cancer includes investigation of synergic combinations with other agents such as fluoropyrimidines and research for additional biomarkers, in order to better define the role of temozolomide in the treatment of individual patients. PMID:25516857

  8. Digital image analysis outperforms manual biomarker assessment in breast cancer.

    Science.gov (United States)

    Stålhammar, Gustav; Fuentes Martinez, Nelson; Lippert, Michael; Tobin, Nicholas P; Mølholm, Ida; Kis, Lorand; Rosin, Gustaf; Rantalainen, Mattias; Pedersen, Lars; Bergh, Jonas; Grunkin, Michael; Hartman, Johan

    2016-04-01

    In the spectrum of breast cancers, categorization according to the four gene expression-based subtypes 'Luminal A,' 'Luminal B,' 'HER2-enriched,' and 'Basal-like' is the method of choice for prognostic and predictive value. As gene expression assays are not yet universally available, routine immunohistochemical stains act as surrogate markers for these subtypes. Thus, congruence of surrogate markers and gene expression tests is of utmost importance. In this study, 3 cohorts of primary breast cancer specimens (total n=436) with up to 28 years of survival data were scored for Ki67, ER, PR, and HER2 status manually and by digital image analysis (DIA). The results were then compared for sensitivity and specificity for the Luminal B subtype, concordance to PAM50 assays in subtype classification and prognostic power. The DIA system used was the Visiopharm Integrator System. DIA outperformed manual scoring in terms of sensitivity and specificity for the Luminal B subtype, widely considered the most challenging distinction in surrogate subclassification, and produced slightly better concordance and Cohen's κ agreement with PAM50 gene expression assays. Manual biomarker scores and DIA essentially matched each other for Cox regression hazard ratios for all-cause mortality. When the Nottingham combined histologic grade (Elston-Ellis) was used as a prognostic surrogate, stronger Spearman's rank-order correlations were produced by DIA. Prognostic value of Ki67 scores in terms of likelihood ratio χ(2) (LR χ(2)) was higher for DIA that also added significantly more prognostic information to the manual scores (LR-Δχ(2)). In conclusion, the system for DIA evaluated here was in most aspects a superior alternative to manual biomarker scoring. It also has the potential to reduce time consumption for pathologists, as many of the steps in the workflow are either automatic or feasible to manage without pathological expertise. PMID:26916072

  9. Cell Line Modeling to Study Biomarker Panel in Prostate Cancer

    Science.gov (United States)

    NickKholgh, Bita; Fang, Xiaolan; Winters, Shira M.; Raina, Anvi; Pandya, Komal S.; Gyabaah, Kenneth; Fino, Nora; Balaji, K.C.

    2016-01-01

    BACKGROUND African–American men with prostate cancer (PCa) present with higher-grade and -stage tumors compared to Caucasians. While the disparity may result from multiple factors, a biological basis is often strongly suspected. Currently, few well-characterized experimental model systems are available to study the biological basis of racial disparity in PCa. We report a validated in vitro cell line model system that could be used for the purpose. METHODS We assembled a PCa cell line model that included currently available African–American PCa cell lines and LNCaP (androgen-dependent) and C4-2 (castration-resistant) Caucasian PCa cells. The utility of the cell lines in studying the biological basis of variance in a malignant phenotype was explored using a multiplex biomarker panel consisting of proteins that have been proven to play a role in the progression of PCa. The panel expression was evaluated by Western blot and RT-PCR in cell lines and validated in human PCa tissues by RT-PCR. As proof-of-principle to demonstrate the utility of our model in functional studies, we performed MTS viability assays and molecular studies. RESULTS The dysregulation of the multiplex biomarker panel in primary African–American cell line (E006AA) was similar to metastatic Caucasian cell lines, which would suggest that the cell line model could be used to study an inherent aggressive phenotype in African–American men with PCa. We had previously demonstrated that Protein kinase D1 (PKD1) is a novel kinase that is down regulated in advanced prostate cancer. We established the functional relevance by over expressing PKD1, which resulted in decreased proliferation and epithelial mesenchymal transition (EMT) in PCa cells. Moreover, we established the feasibility of studying the expression of the multiplex biomarker panel in archived human PCa tissue from African–Americans and Caucasians as a prelude to future translational studies. CONCLUSION We have characterized a novel in

  10. Putative Biomarkers and Targets of Estrogen Receptor Negative Human Breast Cancer

    Directory of Open Access Journals (Sweden)

    Stephen W. Byers

    2011-07-01

    Full Text Available Breast cancer is a progressive and potentially fatal disease that affects women of all ages. Like all progressive diseases, early and reliable diagnosis is the key for successful treatment and annihilation. Biomarkers serve as indicators of pathological, physiological, or pharmacological processes. Her2/neu, CA15.3, estrogen receptor (ER, progesterone receptor (PR, and cytokeratins are biomarkers that have been approved by the Food and Drug Administration for disease diagnosis, prognosis, and therapy selection. The structural and functional complexity of protein biomarkers and the heterogeneity of the breast cancer pathology present challenges to the scientific community. Here we review estrogen receptor-related putative breast cancer biomarkers, including those of putative breast cancer stem cells, a minor population of estrogen receptor negative tumor cells that retain the stem cell property of self renewal. We also review a few promising cytoskeleton targets for ER alpha negative breast cancer.

  11. Intratumour variation of biomarker expression by immunohistochemistry in resectable non-small cell lung cancer

    DEFF Research Database (Denmark)

    Jakobsen, Jan Nyrop; Santoni-Rugiu, Eric; Ravn, Jesper;

    2013-01-01

    truly reflect the pattern of biomarker expression. It may also be an important factor in chemo resistance, as tumours with heterogeneous biomarker expression may potentially harbour chemo resistant tumour clones. MATERIALS AND METHODS: Immunohistochemical evaluation of the expression of excision repair...... intratumour heterogeneity in 33-87% of tumours examined. This heterogeneity may influence results in studies investigating the therapeutic impact of predictive biomarkers in non-small cell lung cancer (NSCLC)....

  12. Investigating Multi-cancer Biomarkers and Their Cross-predictability in the Expression Profiles of Multiple Cancer Types

    Directory of Open Access Journals (Sweden)

    George C. Tseng

    2009-01-01

    Full Text Available Microarray technology has been widely applied to the analysis of many malignancies, however, integrative analyses across multiple studies are rarely investigated. In this study we performed a meta-analysis on the expression profiles of four published studies analyzing organ donor, benign tissues adjacent to tumor and tumor tissues from liver, prostate, lung and bladder samples. We identified 99 distinct multi-cancer biomarkers in the comparison of all three tissues in liver and prostate and 44 in the comparison of normal versus tumor in liver, prostate and lung. The bladder samples appeared to have a different list of biomarkers from the other three cancer types. The identified multi-cancer biomarkers achieved high accuracy similar to using whole genome in the within-cancer-type prediction. They also performed superior than the one using whole genome in inter-cancer-type prediction. To test the validity of the multi-cancer biomarkers, 23 independent prostate cancer samples were evaluated and 96% accuracy was achieved in inter-study prediction from the original prostate, liver and lung cancer data sets respectively. The result suggests that the compact lists of multi-cancer biomarkers are important in cancer development and represent the common signatures of malignancies of multiple cancer types. Pathway analysis revealed important tumorogenesis functional categories.

  13. Circulating microRNAs as Prognostic and Predictive Biomarkers in Patients with Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Jakob Vasehus Schou

    2016-06-01

    Full Text Available MiRNAs are suggested as promising cancer biomarkers. They are stable and extractable from a variety of clinical tissue specimens (fresh frozen or formalin fixed paraffin embedded tissue and a variety of body fluids (e.g., blood, urine, saliva. However, there are several challenges that need to be solved, considering their potential as biomarkers in cancer, such as lack of consistency between biomarker panels in independent studies due to lack of standardized sample handling and processing, use of inconsistent normalization approaches, and differences in patients populations. Focusing on colorectal cancer (CRC, divergent results regarding circulating miRNAs as prognostic or predictive biomarkers are reported in the literature. In the present review, we summarize the current data on circulating miRNAs as prognostic/predictive biomarkers in patients with localized and metastatic CRC (mCRC.

  14. Mass cytometry as a platform for the discovery of cellular biomarkers to guide effective rheumatic disease therapy.

    Science.gov (United States)

    Nair, Nitya; Mei, Henrik E; Chen, Shih-Yu; Hale, Matthew; Nolan, Garry P; Maecker, Holden T; Genovese, Mark; Fathman, C Garrison; Whiting, Chan C

    2015-01-01

    The development of biomarkers for autoimmune diseases has been hampered by a lack of understanding of disease etiopathogenesis and of the mechanisms underlying the induction and maintenance of inflammation, which involves complex activation dynamics of diverse cell types. The heterogeneous nature and suboptimal clinical response to treatment observed in many autoimmune syndromes highlight the need to develop improved strategies to predict patient outcome to therapy and personalize patient care. Mass cytometry, using CyTOF®, is an advanced technology that facilitates multiparametric, phenotypic analysis of immune cells at single-cell resolution. In this review, we outline the capabilities of mass cytometry and illustrate the potential of this technology to enhance the discovery of cellular biomarkers for rheumatoid arthritis, a prototypical autoimmune disease. PMID:25981462

  15. Biomarkers of ambient air pollution and lung cancer

    DEFF Research Database (Denmark)

    Demetriou, Christiana A; Raaschou-Nielsen, Ole; Loft, Steffen;

    2012-01-01

    these studies, causality assessment can benefit from biomarker research. In the present systematic review, we assess the contribution of intermediate biomarkers in epidemiological studies, to ascertain whether their measurement reinforces causal reasoning. We have reviewed 524 papers which described the...

  16. Pairwise protein expression classifier for candidate biomarker discovery for early detection of human disease prognosis

    Directory of Open Access Journals (Sweden)

    Kaur Parminder

    2012-08-01

    Full Text Available Abstract Background An approach to molecular classification based on the comparative expression of protein pairs is presented. The method overcomes some of the present limitations in using peptide intensity data for class prediction for problems such as the detection of a disease, disease prognosis, or for predicting treatment response. Data analysis is particularly challenging in these situations due to sample size (typically tens being much smaller than the large number of peptides (typically thousands. Methods based upon high dimensional statistical models, machine learning or other complex classifiers generate decisions which may be very accurate but can be complex and difficult to interpret in simple or biologically meaningful terms. A classification scheme, called ProtPair, is presented that generates simple decision rules leading to accurate classification which is based on measurement of very few proteins and requires only relative expression values, providing specific targeted hypotheses suitable for straightforward validation. Results ProtPair has been tested against clinical data from 21 patients following a bone marrow transplant, 13 of which progress to idiopathic pneumonia syndrome (IPS. The approach combines multiple peptide pairs originating from the same set of proteins, with each unique peptide pair providing an independent measure of discriminatory power. The prediction rate of the ProtPair for IPS study as measured by leave-one-out CV is 69.1%, which can be very beneficial for clinical diagnosis as it may flag patients in need of closer monitoring. The “top ranked” proteins provided by ProtPair are known to be associated with the biological processes and pathways intimately associated with known IPS biology based on mouse models. Conclusions An approach to biomarker discovery, called ProtPair, is presented. ProtPair is based on the differential expression of pairs of peptides and the associated proteins. Using mass

  17. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.

    Directory of Open Access Journals (Sweden)

    Paul R West

    Full Text Available The diagnosis of autism spectrum disorder (ASD at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age.To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment.Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD.A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set.This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1 determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2 gaining new insight into the biochemical mechanisms of various subtypes of ASD 3 identifying biomolecular targets for new modes of therapy, and 4 providing the basis for individualized treatment recommendations.

  18. Discovery of the cancer stem cell related determinants of radioresistance

    International Nuclear Information System (INIS)

    Tumors are known to be heterogeneous containing a dynamic mixture of phenotypically and functionally different tumor cells. The two concepts attempting to explain the origin of intratumor heterogeneity are the cancer stem cell hypothesis and the clonal evolution model. The stochastic model argues that tumors are biologically homogenous and all cancer cells within the tumor have equal ability to propagate the tumor growth depending on continuing mutations and selective pressure. By contrast, the stem cells model suggests that cancer heterogeneity is due to the hierarchy that originates from a small population of cancer stem cells (CSCs) which are biologically distinct from the bulk tumor and possesses self-renewal, tumorigenic and multilineage potential. Although these two hypotheses have been discussed for a long time as mutually exclusive explanations of tumor heterogeneity, they are easily reconciled serving as a driving force of cancer evolution and diversity. Recent discovery of the cancer cell plasticity and heterogeneity makes the CSC population a moving target that could be hard to track and eradicate. Understanding the signaling mechanisms regulating CSCs during the course of cancer treatment can be indispensable for the optimization of current treatment strategies

  19. HNRNPC as a candidate biomarker for chemoresistance in gastric cancer.

    Science.gov (United States)

    Huang, Hao; Han, Yong; Zhang, Cheng; Wu, Jian; Feng, Junnan; Qu, Like; Shou, Chengchao

    2016-03-01

    Chemoresistance is a major cause of treatment failure and high mortality in advanced gastric cancer (AGC). Currently, the mechanism of chemoresistance remains unclear, and there is no biomarker to accurately predict the efficacy of chemotherapy. In the present study, we established human gastric cancer (GC) cell lines resistant to 5-fluorouracil (5FU), paclitaxel (TA), or cisplatin (DDP) by gradient drug treatment and generated a novel monoclonal antibody 5B2 targeting heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC) overexpressed in chemoresistant GC cells. Overexpressing HNRNPC in GC cells promoted chemoresistance, and knockdown of HNRNPC by small interfering RNA (siRNA) reversed chemoresistance. By utilizing available datasets, we demonstrated that high level of HNRNPC transcript indicated poor overall survival (OS) and free of progression (FP). HNRNPC expression was negatively correlated with OS of GC patients treated with 5FU-based drugs and with time to progression (TTP) of GC patients treated with CF regimen. These data suggest the potential usefulness of HNRNPC as a prognostic and therapeutic marker of GC. PMID:26453116

  20. Early detection of recurrence after curative resection for colorectal cancer - obstacles when using soluble biomarkers?

    DEFF Research Database (Denmark)

    Nielsen, Hans Jørgen; Jess, Per; Aldulaymi, Bahir Hadi Mohammed;

    2013-01-01

    Abstract Objective. Results from monitoring studies using biomarkers in blood samples aiming at early detection of recurrent colorectal cancer (CRC) are presently evaluated. However, some serological biomarker levels are influenced by the surgical trauma, which may complicate translation of the l...

  1. Environmental effects on molecular biomarkers expression in pancreatic and brain cancer

    Science.gov (United States)

    Mensah, Lawrence; Mallidi, Srivalleesha; Massodi, Iqbal; Anbil, Sriram; Mai, Zhiming; Hasan, Tayyaba

    2013-03-01

    A complete understanding of the biological mechanisms regulating devastating disease such as cancer remains elusive. Pancreatic and brain cancers are primary among the cancer types with poor prognosis. Molecular biomarkers have emerged as group of proteins that are preferentially overexpressed in cancers and with a key role in driving disease progression and resistance to chemotherapy. The epidermal growth factor receptor (EGFR), a cell proliferative biomarker is particularly highly expressed in most cancers including brain and pancreatic cancers. The ability of EGFR to sustain prolong cell proliferation is augmented by biomarkers such as Bax, Bcl-XL and Bcl-2, proteins regulating the apoptotic process. To better understand the role and effect of the microenvironment on these biomarkers in pancreatic cancer (PaCa); we analysed two pancreatic tumor lines (AsPc-1 and MiaPaCa-2) in 2D, 3D in-vitro cultures and in orthotopic tumors at different growth stages. We also investigated in patient derived glioblastoma (GBM) tumor cultures, the ability to utilize the EGFR expression to specifically deliver photosensitizer to the cells for photodynamic therapy. Overall, our results suggest that (1) microenvironment changes affect biomarker expression; thereby it is critical to understand these effects prior to designing combination therapies and (2) EGFR expression in tumor cells indeed could serve as a reliable and a robust biomarker that could be used to design targeted and image-guided photodynamic therapy.

  2. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, Bhowmik Salil [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of); Lee, Young-Joo; Yi, Hong Jae [College of Pharmacy, Kyung Hee University, Hoegi-dong, Dongdaemun-gu, Seoul 130-791 (Korea, Republic of); Chung, Bong Chul [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); Jung, Byung Hwa, E-mail: jbhluck@kist.re.kr [Bioanalysis and Biotransformation Research Center, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650 (Korea, Republic of); University of Science and Technology, (305-333) 113 Gwahangno, Yuseong-gu, Daejeon (Korea, Republic of)

    2010-02-19

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg{sup -1} day{sup -1} or 250 mg kg{sup -1} day{sup -1} for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  3. Discovery of safety biomarkers for atorvastatin in rat urine using mass spectrometry based metabolomics combined with global and targeted approach

    International Nuclear Information System (INIS)

    In order to develop a safety biomarker for atorvastatin, this drug was orally administrated to hyperlipidemic rats, and a metabolomic study was performed. Atorvastatin was given in doses of either 70 mg kg-1 day-1 or 250 mg kg-1 day-1 for a period of 7 days (n = 4 for each group). To evaluate any abnormal effects of the drug, physiological and plasma biochemical parameters were measured and histopathological tests were carried out. Safety biomarkers were derived by comparing these parameters and using both global and targeted metabolic profiling. Global metabolic profiling was performed using liquid chromatography/time of flight/mass spectrometry (LC/TOF/MS) with multivariate data analysis. Several safety biomarker candidates that included various steroids and amino acids were discovered as a result of global metabolic profiling, and they were also confirmed by targeted metabolic profiling using gas chromatography/mass spectrometry (GC/MS) and capillary electrophoresis/mass spectrometry (CE/MS). Serum biochemical and histopathological tests were used to detect abnormal drug reactions in the liver after repeating oral administration of atorvastatin. The metabolic differences between control and the drug-treated groups were compared using PLS-DA score plots. These results were compared with the physiological and plasma biochemical parameters and the results of a histopathological test. Estrone, cortisone, proline, cystine, 3-ureidopropionic acid and histidine were proposed as potential safety biomarkers related with the liver toxicity of atorvastatin. These results indicate that the combined application of global and targeted metabolic profiling could be a useful tool for the discovery of drug safety biomarkers.

  4. Nanomechanical sandwich assay for multiple cancer biomarkers in breast cancer cell-derived exosomes.

    Science.gov (United States)

    Etayash, H; McGee, A R; Kaur, K; Thundat, T

    2016-08-18

    The use of exosomes as cancer diagnostic biomarkers is technically limited by their size, heterogeneity and the need for extensive purification and labelling. We report the use of cantilever arrays for simultaneous detection of multiple exosomal surface-antigens with high sensitivity and selectivity. Exosomes from breast cancer were selectively identified by detecting over-expressed membrane-proteins CD24, CD63, and EGFR. Excellent selectivity however, was achieved when targeting the cell-surface proteoglycan, Glypican-1 at extraordinary limits (∼200 exosomes per mL, ∼0.1 pg mL(-1)). PMID:27492928

  5. Use of biomarkers in the discovery of novel anti-schizophrenia drugs

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D.; Thomsen, Morten S.; Hansen, Henrik; Lichota, Jacek

    anti-schizophrenic drug candidates targeting single receptors will be based on biomarker assays that measure signalling pathways, transcriptional factors, epigenetic mechanisms and synaptic function and translate these effects to behavioural effects in animals and humans. This review discusses current...

  6. High-throughput profiling for discovery of non-coding RNA biomarkers of lung disease.

    OpenAIRE

    McKiernan, Paul J; Catherine M. Greene

    2016-01-01

    In respiratory medicine there is a need for clinical biomarkers for diagnosis, prognosis and assessment of response to therapy. Noncoding RNA (ncRNA) is expressed in all human cells; two major classes - long ncRNA and microRNA - are detectable extracellularly in the circulation and other biofluids. Altered ncRNA expression is associated with lung disease; collectively this indicates that ncRNA represents a potential biomarker class. This article presents and compares existing platforms for de...

  7. Biomarker screening of oral cancer cell lines revealed sub-populations of CD133-, CD44-, CD24- and ALDH1- positive cancer stem cells

    Directory of Open Access Journals (Sweden)

    Kendall K

    2013-05-01

    Full Text Available Head and neck squamous cell carcinoma (HNSCC ranks sixth worldwide for cancer-related mortality. For the past several decades the mainstay of treatment for HNSCC has been surgery and external beam radiation, although more recent trials combining chemotherapy and radiation have demonstrated improvements. However, cancer recurrence and treatment failures continue to occur in a significant percentage of patients. Recent advances in tumor biology have led to the discovery that many cancers, including HNSCC, may contain subpopulations of cells with stem cell-like properties that may explain relapse and recurrence. The objective of this study was to screen existing oral cancer cell lines for biomarkers specific for cells with stem cell-like properties. RNA was isolated for RT-PCR screening using primers for specific mRNA of the biomarkers: CD44, CD24, CD133, NANOG, Nestin, ALDH1, and ABCG2 in CAL27, SCC25 and SCC15 cells. This analysis revealed that some oral cancer cell lines (CAL27 and SCC25 may contain small subpopulations of adhesion- and contact-independent cells (AiDC that also express tumor stem cell markers, including CD44, CD133, and CD24. In addition, CAL27 cells also expressed the intracellular tumor stem cell markers, ALDH1 and ABCG2. Isolation and culture of the adhesion- and contact-independent cells from CAL27 and SCC25 populations revealed differential proliferation rates and more robust inhibition by the MEK inhibitor PD98059, as well as the chemotherapeutic agents Cisplatin and Paclitaxel, within the AiDC CAL27 cells. At least one oral cancer cell line (CAL27 contained subpopulations of cells that express specific biomarkers associated with tumor stem cells which were morphologically and phenotypically distinct from other cells within this cell line.

  8. Serum uPAR as Biomarker in Breast Cancer Recurrence: A Mathematical Model

    Science.gov (United States)

    Hao, Wenrui; Friedman, Avner

    2016-01-01

    There are currently over 2.5 million breast cancer survivors in the United States and, according to the American Cancer Society, 10 to 20 percent of these women will develop recurrent breast cancer. Early detection of recurrence can avoid unnecessary radical treatment. However, self-examination or mammography screening may not discover a recurring cancer if the number of surviving cancer cells is small, while biopsy is too invasive and cannot be frequently repeated. It is therefore important to identify non-invasive biomarkers that can detect early recurrence. The present paper develops a mathematical model of cancer recurrence. The model, based on a system of partial differential equations, focuses on tissue biomarkers that include the plasminogen system. Among them, only uPAR is known to have significant correlation to its concentration in serum and could therefore be a good candidate for serum biomarker. The model includes uPAR and other associated cytokines and cells. It is assumed that the residual cancer cells that survived primary cancer therapy are concentrated in the same location within a region with a very small diameter. Model simulations establish a quantitative relation between the diameter of the growing cancer and the total uPAR mass in the cancer. This relation is used to identify uPAR as a potential serum biomarker for breast cancer recurrence. PMID:27078836

  9. Serum uPAR as Biomarker in Breast Cancer Recurrence: A Mathematical Model.

    Science.gov (United States)

    Hao, Wenrui; Friedman, Avner

    2016-01-01

    There are currently over 2.5 million breast cancer survivors in the United States and, according to the American Cancer Society, 10 to 20 percent of these women will develop recurrent breast cancer. Early detection of recurrence can avoid unnecessary radical treatment. However, self-examination or mammography screening may not discover a recurring cancer if the number of surviving cancer cells is small, while biopsy is too invasive and cannot be frequently repeated. It is therefore important to identify non-invasive biomarkers that can detect early recurrence. The present paper develops a mathematical model of cancer recurrence. The model, based on a system of partial differential equations, focuses on tissue biomarkers that include the plasminogen system. Among them, only uPAR is known to have significant correlation to its concentration in serum and could therefore be a good candidate for serum biomarker. The model includes uPAR and other associated cytokines and cells. It is assumed that the residual cancer cells that survived primary cancer therapy are concentrated in the same location within a region with a very small diameter. Model simulations establish a quantitative relation between the diameter of the growing cancer and the total uPAR mass in the cancer. This relation is used to identify uPAR as a potential serum biomarker for breast cancer recurrence. PMID:27078836

  10. Biomarkers for early detection of colorectal cancer and polyps: systematic review.

    Science.gov (United States)

    Shah, Reena; Jones, Emma; Vidart, Victoire; Kuppen, Peter J K; Conti, John A; Francis, Nader K

    2014-09-01

    There is growing interest in early detection of colorectal cancer as current screening modalities lack compliance and specificity. This study systematically reviewed the literature to identify biomarkers for early detection of colorectal cancer and polyps. Literature searches were conducted for relevant papers since 2007. Human studies reporting on early detection of colorectal cancer and polyps using biomarkers were included. Methodologic quality was evaluated, and sensitivity, specificity, and the positive predictive value (PPV) were reported. The search strategy identified 3,348 abstracts. A total of 44 papers, examining 67 different tumor markers, were included. Overall sensitivities for colorectal cancer detection by fecal DNA markers ranged from 53% to 87%. Combining fecal DNA markers increased the sensitivity of colorectal cancer and adenoma detection. Canine scent detection had a sensitivity of detecting colorectal cancer of 99% and specificity of 97%. The PPV of immunochemical fecal occult blood test (iFOBT) is 1.26%, compared with 0.31% for the current screening method of guaiac fecal occult blood test (gFOBT). A panel of serum protein biomarkers provides a sensitivity and specificity above 85% for all stages of colorectal cancer, and a PPV of 0.72%. Combinations of fecal and serum biomarkers produce higher sensitivities, specificities, and PPVs for early detection of colorectal cancer and adenomas. Further research is required to validate these biomarkers in a well-structured population-based study. PMID:25004920

  11. TRPM7 and TRPM8 Ion Channels in Pancreatic Adenocarcinoma: Potential Roles as Cancer Biomarkers and Targets

    Directory of Open Access Journals (Sweden)

    Nelson S. Yee

    2012-01-01

    Full Text Available Transient receptor potential (TRP ion channels are essential for normal functions and health by acting as molecular sensors and transducing various stimuli into cellular and physiological responses. Growing evidence has revealed that TRP ion channels play important roles in a wide range of human diseases, including malignancies. In light of recent discoveries, it has been found that TRP melastatin-subfamily members, TRPM7 and TRPM8, are required for normal and cancerous development of exocrine pancreas. We are currently investigating the mechanisms which mediate the functional roles of TRPM7 and TRPM8 and attempting to develop these ion channels as clinical biomarkers and therapeutic targets for achieving the goal of personalized therapy in pancreatic cancer.

  12. Biomarker Validation for Aging: Lessons from mtDNA Heteroplasmy Analyses in Early Cancer Detection

    Directory of Open Access Journals (Sweden)

    Peter E. Barker

    2009-11-01

    Full Text Available The anticipated biological and clinical utility of biomarkers has attracted significant interest recently. Aging and early cancer detection represent areas active in the search for predictive and prognostic biomarkers. While applications differ, overlapping biological features, analytical technologies and specific biomarker analytes bear comparison. Mitochondrial DNA (mtDNA as a biomarker in both biological models has been evaluated. However, it remains unclear whether mtDNA changes in aging and cancer represent biological relationships that are causal, incidental, or a combination of both. This article focuses on evaluation of mtDNA-based biomarkers, emerging strategies for quantitating mtDNA admixtures, and how current understanding of mtDNA in aging and cancer evolves with introduction of new technologies. Whether for cancer or aging, lessons from mtDNA based biomarker evaluations are several. Biological systems are inherently dynamic and heterogeneous. Detection limits for mtDNA sequencing technologies differ among methods for low-level DNA sequence admixtures in healthy and diseased states. Performance metrics of analytical mtDNA technology should be validated prior to application in heterogeneous biologically-based systems. Critical in evaluating biomarker performance is the ability to distinguish measurement system variance from inherent biological variance, because it is within the latter that background healthy variability as well as high-value, disease-specific information reside.

  13. Considering Exosomal miR-21 as a Biomarker for Cancer

    Directory of Open Access Journals (Sweden)

    Jian Shi

    2016-03-01

    Full Text Available Cancer is a fatal human disease. Early diagnosis of cancer is the most effective method to prevent cancer development and to achieve higher survival rates for patients. Many traditional diagnostic methods for cancer are still not sufficient for early, more convenient and accurate, and noninvasive diagnosis. Recently, the use of microRNAs (miRNAs, such as exosomal microRNA-21(miR-21, as potential biomarkers was widely reported. This initial systematic review analyzes the potential role of exosomal miR-21 as a general biomarker for cancers. A total of 10 studies involving 318 patients and 215 healthy controls have covered 10 types of cancers. The sensitivity and specificity of pooled studies were 75% (0.70–0.80 and 85% (0.81–0.91, with their 95% confidence intervals (CIs, while the area under the summary receiver operating characteristic curve (AUC was 0.93. Additionally, we examined and evaluated almost all other issues about biomarkers, including cutoff points, internal controls and detection methods, from the literature. This initial meta-analysis indicates that exosomal miR-21 has a strong potential to be used as a universal biomarker to identify cancers, although as a general biomarker the case number for each cancer type is small. Based on the literature, a combination of miRNA panels and other cancer antigens, as well as a selection of appropriate internal controls, has the potential to serve as a more sensitive and accurate cancer diagnosis tool. Additional information on miR-21 would further support its use as a biomarker in cancer.

  14. Considering Exosomal miR-21 as a Biomarker for Cancer.

    Science.gov (United States)

    Shi, Jian

    2016-01-01

    Cancer is a fatal human disease. Early diagnosis of cancer is the most effective method to prevent cancer development and to achieve higher survival rates for patients. Many traditional diagnostic methods for cancer are still not sufficient for early, more convenient and accurate, and noninvasive diagnosis. Recently, the use of microRNAs (miRNAs), such as exosomal microRNA-21(miR-21), as potential biomarkers was widely reported. This initial systematic review analyzes the potential role of exosomal miR-21 as a general biomarker for cancers. A total of 10 studies involving 318 patients and 215 healthy controls have covered 10 types of cancers. The sensitivity and specificity of pooled studies were 75% (0.70-0.80) and 85% (0.81-0.91), with their 95% confidence intervals (CIs), while the area under the summary receiver operating characteristic curve (AUC) was 0.93. Additionally, we examined and evaluated almost all other issues about biomarkers, including cutoff points, internal controls and detection methods, from the literature. This initial meta-analysis indicates that exosomal miR-21 has a strong potential to be used as a universal biomarker to identify cancers, although as a general biomarker the case number for each cancer type is small. Based on the literature, a combination of miRNA panels and other cancer antigens, as well as a selection of appropriate internal controls, has the potential to serve as a more sensitive and accurate cancer diagnosis tool. Additional information on miR-21 would further support its use as a biomarker in cancer. PMID:27043643

  15. RNA-Seq accurately identifies cancer biomarker signatures to distinguish tissue of origin.

    Science.gov (United States)

    Wei, Iris H; Shi, Yang; Jiang, Hui; Kumar-Sinha, Chandan; Chinnaiyan, Arul M

    2014-11-01

    Metastatic cancer of unknown primary (CUP) accounts for up to 5% of all new cancer cases, with a 5-year survival rate of only 10%. Accurate identification of tissue of origin would allow for directed, personalized therapies to improve clinical outcomes. Our objective was to use transcriptome sequencing (RNA-Seq) to identify lineage-specific biomarker signatures for the cancer types that most commonly metastasize as CUP (colorectum, kidney, liver, lung, ovary, pancreas, prostate, and stomach). RNA-Seq data of 17,471 transcripts from a total of 3,244 cancer samples across 26 different tissue types were compiled from in-house sequencing data and publically available International Cancer Genome Consortium and The Cancer Genome Atlas datasets. Robust cancer biomarker signatures were extracted using a 10-fold cross-validation method of log transformation, quantile normalization, transcript ranking by area under the receiver operating characteristic curve, and stepwise logistic regression. The entire algorithm was then repeated with a new set of randomly generated training and test sets, yielding highly concordant biomarker signatures. External validation of the cancer-specific signatures yielded high sensitivity (92.0% ± 3.15%; mean ± standard deviation) and specificity (97.7% ± 2.99%) for each cancer biomarker signature. The overall performance of this RNA-Seq biomarker-generating algorithm yielded an accuracy of 90.5%. In conclusion, we demonstrate a computational model for producing highly sensitive and specific cancer biomarker signatures from RNA-Seq data, generating signatures for the top eight cancer types responsible for CUP to accurately identify tumor origin. PMID:25425966

  16. Biomarkers that currently effect clinical practice in lung cancer: EGFR, ALK, MET, ROS-1 and KRAS

    Directory of Open Access Journals (Sweden)

    GrzegorzJanuszKorpanty

    2014-08-01

    Full Text Available Lung cancer remains the most lethal malignancy in the world. Despite improvements in surgical treatment, systemic therapy and radiotherapy, the 5-year survival rate for all patients diagnosed with lung cancer remains between 15-20%. Newer therapeutic strategies rely on specific molecular alterations, or biomarkers, that provide opportunities for a personalized approach to specific patient populations. Classification of lung cancer is becoming increasingly focused on these biomarkers, which renders the term “non-small cell lung” cancer less clinically useful. Non-small cell lung cancer is now recognized as a complex malignancy and its molecular and genomic diversity allows for patient-centered treatment options. Here we review advances in targeted treatment of lung adenocarcinoma with respect to five clinically relevant biomarkers - EGFR, ALK, MET, ROS-1 and KRAS.

  17. A prospective evaluation of early detection biomarkers for ovarian cancer in the European EPIC cohort

    DEFF Research Database (Denmark)

    Terry, Kathryn L; Schock, Helena; Fortner, Renée T; Hüsing, Anika; Fichorova, Raina N; Yamamoto, Hidemi S; Vitonis, Allison F; Johnson, Theron; Overvad, Kim; Tjønneland, Anne; Boutron-Ruault, Marie-Christine; Mesrine, Sylvie; Severi, Gianluca; Dossus, Laure; Rinaldi, Sabina; Boeing, Heiner; Benetou, Vassiliki; Lagiou, Pagona; Trichopoulou, Antonia; Krogh, Vittorio; Kuhn, Elisabetta; Panico, Salvatore; Bueno-de-Mesquita, H Bas; Onland-Moret, N Charlotte; Peeters, Petra H; Gram, Inger Torhild; Weiderpass, Elisabete; Duell, Eric J; Sanchez, Maria-Jose; Ardanaz, Eva; Etxezarreta, Nerea; Navarro, Carmen; Idahl, Annika; Lundin, Eva; Jirström, Karin; Manjer, Jonas; Wareham, Nicholas J; Khaw, Kay-Tee; Smith Byrne, Karl; Travis, Ruth C; Gunter, Marc J; Merritt, Melissa A; Riboli, Elio; Cramer, Daniel; Kaaks, Rudolf

    2016-01-01

    source of information to evaluate early detection biomarkers. Here we evaluate the most promising ovarian cancer screening biomarkers in prospectively collected samples from the European Prospective Investigation into Cancer and Nutrition (EPIC) study. EXPERIMENTAL DESIGN: We measured CA125, HE4, CA72......PURPOSE: About 60% of ovarian cancers are diagnosed at late stage, when 5-year survival is less than 30% in contrast to 90% for local disease. This has prompted search for early detection biomarkers. For initial testing, specimens taken months or years before ovarian cancer diagnosis are the best.......4 and CA15.3 in 810 invasive epithelial ovarian cancer cases and 1,939 controls. We calculated the sensitivity at 95% and 98% specificity as well as Area under the Receiver Operator Curve (C-statistic) for each marker individually and in combination. Additionally, we evaluated marker performance by...

  18. Current status of predictive biomarkers for neoadjuvant therapy in esophageal cancer

    Institute of Scientific and Technical Information of China (English)

    Norihisa; Uemura; Tadashi; Kondo

    2014-01-01

    Neoadjuvant therapy has been proven to be extremely valuable and is widely used for advanced esophageal cancer. However, a significant proportion of treated patients(60%-70%) does not respond well to neoadjuvant treatments and develop severe adverse effects. Therefore, predictive markers for individualization of multimodality treatments are urgently needed in esophageal cancer. Recently, molecular biomarkers that predict the response to neoadjuvant therapy have been explored in multimodal approaches in esophageal cancer and successful examples of biomarker identification have been reported. In this review, promising candidates for predictive molecular biomarkers developed by using multiple molecular approaches are reviewed. Moreover, treatment strategies based on the status of predicted biomarkers are discussed, while considering the international differences in the clinical background. However, in the absence of adequate treatment options related to the results of the biomarker test, the usefulness of these diagnostic tools is limited and new effective therapies for biomarker-identified nonresponders to cancer treatment should be concurrent with the progress of predictive technologies. Further improvement in the prognosis of esophageal cancer patients can be achieved through the introduction of novel therapeutic approaches in clinical practice.

  19. Current application of proteomics in biomarker discovery for inflammatory bowel disease.

    Science.gov (United States)

    Chan, Patrick Py; Wasinger, Valerie C; Leong, Rupert W

    2016-02-15

    Recently, the field of proteomics has rapidly expanded in its application towards clinical research with objectives ranging from elucidating disease pathogenesis to discovering clinical biomarkers. As proteins govern and/or reflect underlying cellular processes, the study of proteomics provides an attractive avenue for research as it allows for the rapid identification of protein profiles in a biological sample. Inflammatory bowel disease (IBD) encompasses several heterogeneous and chronic conditions of the gastrointestinal tract. Proteomic technology provides a powerful means of addressing major challenges in IBD today, especially for identifying biomarkers to improve its diagnosis and management. This review will examine the current state of IBD proteomics research and its use in biomarker research. Furthermore, we also discuss the challenges of translating proteomic research into clinically relevant tools. The potential application of this growing field is enormous and is likely to provide significant insights towards improving our future understanding and management of IBD. PMID:26909226

  20. Similar Source of Differential Blood mRNAs in Lung Cancer and Pulmonary Inflammatory Diseases: Calls for Improved Strategy for Identifying Cancer-Specific Biomarkers

    OpenAIRE

    Hong, Guini; Chen, Beibei; Li, Hongdong; Zhang, Wenjing; Zheng, Tingting; Li, Shan; Shi, Tongwei; Ao, Lu; Guo, Zheng

    2014-01-01

    Background Many studies try to identify cancer diagnostic biomarkers by comparing peripheral whole blood (PWB) of cancer samples and healthy controls, explicitly or implicitly assuming that such biomarkers are potential candidate biomarkers for distinguishing cancer from nonmalignant inflammation-associated diseases. Methods Multiple PWB gene expression profiles for lung cancer/inflammation-associated pulmonary diseases were used for differential mRNAs identification and comparison and for pr...

  1. Inflammatory biomarkers and risk of cancer in 84,000 individuals from the general population.

    Science.gov (United States)

    Allin, Kristine H; Bojesen, Stig E; Nordestgaard, Børge G

    2016-10-01

    Inflammation and cancer are tightly linked. This study tests the hypothesis that an inflammatory score based on plasma levels of C-reactive protein (CRP) and fibrinogen and whole blood leukocyte count is associated with risk of colorectal, lung, breast and prostate cancer. A score ranging from none through three elevated biomarkers was constructed in 84,000 individuals from the Danish general population. During a median follow-up time of 4.8 years, 4,081 incident cancers occurred. Cox proportional hazards regression models were used to estimate hazard ratios (HRs) of incident cancer. Multifactor-adjusted HRs for colorectal cancer were 1.28 (95% CI, 1.01 to 1.62), 1.79 (95% CI, 1.41 to 2.27) and 2.18 (95% CI, 1.67 to 2.86) for individuals with elevated levels of one, two and three inflammatory biomarkers compared to individuals with none elevated biomarkers. A similar stepwise increasing risk was observed for lung and breast cancer with HRs of 3.03 (95% CI, 2.25 to 4.08) and 1.42 (95% CI, 1.11 to 1.80) for three versus none elevated biomarkers. HRs were highest within the first years of follow-up. Absolute 5-year risk of lung cancer was 7.8 (95% CI, 6.1 to 10)% among older smokers with three elevated biomarkers compared to 3.8 (95% CI, 2.6 to 5.6)% among those with none elevated biomarkers. In conclusion, simultaneously elevated CRP, fibrinogen and leukocyte count are associated with an increased risk of colorectal, lung and breast cancer. Cancer as a promoter of inflammation may be more likely to account for our findings than low-grade inflammation promoting cancer development. PMID:27194008

  2. Mitochondrial DNA mutations—candidate biomarkers for breast cancer diagnosis in Bangladesh

    OpenAIRE

    Rowshan Ara Begum; Abu Din Ahmed Shahinuzzaman; Atiqur Rahman; Gazi Nurun Nahar Sultana; Chowdhury Faiz Hossain

    2012-01-01

    Breast cancer is a major health problem that affects more than 24% of women in Bangladesh. Further- more, among low-income countries including Bangladesh, individuals have a high risk for developing breast cancer. This study aimed to identify candidate mitochondrial DNA (mtDNA) biomarkers for breast cancer diagnosis in Bangladeshi women to be used as a preventive approach. We screened the blood samples from 24 breast cancer patients and 20 healthy controls to detect polymorphisms in the D-loo...

  3. Discovery and validation of methylation markers for endometrial cancer.

    Science.gov (United States)

    Wentzensen, Nicolas; Bakkum-Gamez, Jamie N; Killian, J Keith; Sampson, Joshua; Guido, Richard; Glass, Andrew; Adams, Lisa; Luhn, Patricia; Brinton, Louise A; Rush, Brenda; d'Ambrosio, Lori; Gunja, Munira; Yang, Hannah P; Garcia-Closas, Montserrat; Lacey, James V; Lissowska, Jolanta; Podratz, Karl; Meltzer, Paul; Shridhar, Viji; Sherman, Mark E

    2014-10-15

    The prognosis of endometrial cancer is strongly associated with stage at diagnosis, suggesting that early detection may reduce mortality. Women who are diagnosed with endometrial carcinoma often have a lengthy history of vaginal bleeding, which offers an opportunity for early diagnosis and curative treatment. We performed DNA methylation profiling on population-based endometrial cancers to identify early detection biomarkers and replicated top candidates in two independent studies. We compared DNA methylation values of 1,500 probes representing 807 genes in 148 population-based endometrial carcinoma samples and 23 benign endometrial tissues. Markers were replicated in another set of 69 carcinomas and 40 benign tissues profiled on the same platform. Further replication was conducted in The Cancer Genome Atlas and in prospectively collected endometrial brushings from women with and without endometrial carcinomas. We identified 114 CpG sites showing methylation differences with p values of ≤ 10(-7) between endometrial carcinoma and normal endometrium. Eight genes (ADCYAP1, ASCL2, HS3ST2, HTR1B, MME, NPY and SOX1) were selected for further replication. Age-adjusted odds ratios for endometrial cancer ranged from 3.44 (95%-CI: 1.33-8.91) for ASCL2 to 18.61 (95%-CI: 5.50-62.97) for HTR1B. An area under the curve (AUC) of 0.93 was achieved for discriminating carcinoma from benign endometrium. Replication in The Cancer Genome Atlas and in endometrial brushings from an independent study confirmed the candidate markers. This study demonstrates that methylation markers may be used to evaluate women with abnormal vaginal bleeding to distinguish women with endometrial carcinoma from the majority of women without malignancy. PMID:24623538

  4. The expression profile of phosphatidylinositol in high spatial resolution imaging mass spectrometry as a potential biomarker for prostate cancer.

    Directory of Open Access Journals (Sweden)

    Takayuki Goto

    Full Text Available High-resolution matrix-assisted laser desorption/ionization imaging mass spectrometry (HR-MALDI-IMS is an emerging application for the comprehensive and detailed analysis of the spatial distribution of ionized molecules in situ on tissue slides. HR-MALDI-IMS in negative mode in a mass range of m/z 500-1000 was performed on optimal cutting temperature (OCT compound-embedded human prostate tissue samples obtained from patients with prostate cancer at the time of radical prostatectomy. HR-MALDI-IMS analysis of the 14 samples in the discovery set identified 26 molecules as highly expressed in the prostate. Tandem mass spectrometry (MS/MS showed that these molecules included 14 phosphatidylinositols (PIs, 3 phosphatidylethanolamines (PEs and 3 phosphatidic acids (PAs. Among the PIs, the expression of PI(18:0/18:1, PI(18:0/20:3 and PI(18:0/20:2 were significantly higher in cancer tissue than in benign epithelium. A biomarker algorithm for prostate cancer was formulated by analyzing the expression profiles of PIs in cancer tissue and benign epithelium of the discovery set using orthogonal partial least squares discriminant analysis (OPLS-DA. The sensitivity and specificity of this algorithm for prostate cancer diagnosis in the 24 validation set samples were 87.5 and 91.7%, respectively. In conclusion, HR-MALDI-IMS identified several PIs as being more highly expressed in prostate cancer than benign prostate epithelium. These differences in PI expression profiles may serve as a novel diagnostic tool for prostate cancer.

  5. In Vitro Evaluation of Biofield Treatment on Cancer Biomarkers Involved in Endometrial and Prostate Cancer Cell Lines

    OpenAIRE

    Trivedi, Mahendra Kumar

    2015-01-01

    Increasing cancer rates particularly in the developed world are associated with related lifestyle and environmental exposures. Combined immunotherapy and targeted therapies are the main treatment approaches in advanced and recurrent cancer. An alternate approach, energy medicine is increasingly used in life threatening problems to promote human wellness. This study aimed to investigate the effect of biofield treatment on cancer biomarkers involved in human endometrium and prostate cancer cell...

  6. Discovery of a Metastatic Immune Escape Mechanism Initiated by the Loss of Expression of the Tumour Biomarker Interleukin-33.

    Science.gov (United States)

    Saranchova, Iryna; Han, Jeffrey; Huang, Hui; Fenninger, Franz; Choi, Kyung Bok; Munro, Lonna; Pfeifer, Cheryl; Welch, Ian; Wyatt, Alexander W; Fazli, Ladan; Gleave, Martin E; Jefferies, Wilfred A

    2016-01-01

    A new paradigm for understanding immune-surveillance and immune escape in cancer is described here. Metastatic carcinomas express reduced levels of IL-33 and diminished levels of antigen processing machinery (APM), compared to syngeneic primary tumours. Complementation of IL-33 expression in metastatic tumours upregulates APM expression and functionality of major histocompatibility complex (MHC)-molecules, resulting in reduced tumour growth rates and a lower frequency of circulating tumour cells. Parallel studies in humans demonstrate that low tumour expression of IL-33 is an immune biomarker associated with recurrent prostate and kidney renal clear cell carcinomas. Thus, IL-33 has a significant role in cancer immune-surveillance against primary tumours, which is lost during the metastatic transition that actuates immune escape in cancer. PMID:27619158

  7. Systematic discovery of complex insertions and deletions in human cancers.

    Science.gov (United States)

    Ye, Kai; Wang, Jiayin; Jayasinghe, Reyka; Lameijer, Eric-Wubbo; McMichael, Joshua F; Ning, Jie; McLellan, Michael D; Xie, Mingchao; Cao, Song; Yellapantula, Venkata; Huang, Kuan-lin; Scott, Adam; Foltz, Steven; Niu, Beifang; Johnson, Kimberly J; Moed, Matthijs; Slagboom, P Eline; Chen, Feng; Wendl, Michael C; Ding, Li

    2016-01-01

    Complex insertions and deletions (indels) are formed by simultaneously deleting and inserting DNA fragments of different sizes at a common genomic location. Here we present a systematic analysis of somatic complex indels in the coding sequences of samples from over 8,000 cancer cases using Pindel-C. We discovered 285 complex indels in cancer-associated genes (such as PIK3R1, TP53, ARID1A, GATA3 and KMT2D) in approximately 3.5% of cases analyzed; nearly all instances of complex indels were overlooked (81.1%) or misannotated (17.6%) in previous reports of 2,199 samples. In-frame complex indels are enriched in PIK3R1 and EGFR, whereas frameshifts are prevalent in VHL, GATA3, TP53, ARID1A, PTEN and ATRX. Furthermore, complex indels display strong tissue specificity (such as VHL in kidney cancer samples and GATA3 in breast cancer samples). Finally, structural analyses support findings of previously missed, but potentially druggable, mutations in the EGFR, MET and KIT oncogenes. This study indicates the critical importance of improving complex indel discovery and interpretation in medical research. PMID:26657142

  8. Systematic Discovery of Complex Indels in Human Cancers

    Science.gov (United States)

    Ye, Kai; Wang, Jiayin; Jayasinghe, Reyka; Lameijer, Eric-Wubbo; McMichael, Joshua F.; Ning, Jie; McLellan, Michael D.; Xie, Mingchao; Cao, Song; Yellapantula, Venkata; Huang, Kuan-lin; Scott, Adam; Foltz, Steven; Niu, Beifang; Johnson, Kimberly J.; Moed, Matthijs; Slagboom, P. Eline; Chen, Feng; Wendl, Michael C.; Ding, Li

    2016-01-01

    Complex indels are formed by simultaneously deleting and inserting DNA fragments of different sizes at a common genomic location. Here, we present a systematic analysis of somatic complex indels in the coding sequences of over 8,000 cancer cases using Pindel-C. We discovered 285 complex indels in cancer genes (e.g., PIK3R1, TP53, ARID1A, GATA3, and KMT2D) in approximately 3.5% of cases analyzed; nearly all instances of complex indels were overlooked (81.1%) or mis-annotated (17.6%) in 2,199 samples previously reported. In-frame complex indels are enriched in PIK3R1 and EGFR while frameshifts are prevalent in VHL, GATA3, TP53, ARID1A, PTEN, and ATRX. Further, complex indels display strong tissue specificity (e.g., VHL from kidney cancer and GATA3 from breast cancer). Finally, structural analyses support findings of previously missed, but potentially druggable mutations in EGFR, MET, and KIT oncogenes. This study indicates the critical importance of improving complex indel discovery and interpretation in medical research. PMID:26657142

  9. Introducing differential expression of human heat shock protein 27 in hepatocellular carcinoma: moving toward identification of cancer biomarker.

    Science.gov (United States)

    Khan, Rizma; Siddiqui, Nadir Naveed; Ul Haq, Ahtesham; Rahman, M Ataur

    2016-01-01

    Previously, it has to be acknowledged that overexpressed heat shock protein B27 (HSPB27) have been implicated in the etiology of wide range of human cancers. However, the molecular mechanism leading to the disease initiation to progression in liver cancer is still unknown. Present work was undertaken to investigate the differentially expressed HSPB27 in association with those damages that lead to liver cancer development. For the identification of liver cancer biomarker, samples were subjected to comparative proteomic analysis using two-dimensional gel electrophoresis (2-DE) and were further validated by Western blot and immunohistochemical analysis. After validation, in silico studies were applied to demonstrate the significantly induced phosphorylated and S-nitrosylated signals. The later included the interacting partner of HSPB27, i.e., mitogen-activated protein kinase-3 and 5 (MAPK3 and 5), ubiquitin C (UBC), v-akt murine thymoma viral oncogene homolog 1 (AKT1), mitogen-activated protein kinase 14 (MAPK14), and tumor protein p53 (TP53), which bestowed with critical capabilities, namely, apoptosis, cell cycling, stress activation, tumor suppression, cell survival, angiogenesis, proliferation, and stress resistance. Taking together, these results shed new light on the potential biomarker HSPB27 that overexpression of HSPB27 did lead to upregulation of their interacting partner that together demonstrate their possible role as a novel tumor progressive agent for the treatment of metastasis in liver cancer. HSPB27 is a promising diagnostic marker for liver cancer although further large-scale studies are required. Also, molecular profiling may help pave the road to the discovery of new therapies. PMID:26242269

  10. Simultaneous Imaging of Two Different Cancer Biomarkers Using Aptamer-Conjugated Quantum Dots

    Directory of Open Access Journals (Sweden)

    Jonghwan Lee

    2015-04-01

    Full Text Available Studying gene expression profile in a single cancer cell is important because multiple genes are associated with cancer development. Quantum dots (QDs have been utilized as biological probes for imaging and detection. QDs display specific optical and electrical properties that depend on their size that can be applied for imaging and sensing applications. In this study, simultaneous imaging of the cancer biomarkers, tenascin-C and nucleolin, was performed using two types of aptamer-conjugated QDs. The simultaneous imaging of these two different cancer markers in three cancer cell lines was reliable and cell line-specific. Current requirements for cancer imaging technologies include the need for simple preparation methods and the ability to detect multiple cancer biomarkers and evaluate their intracellular localizations. The method employed in this study is a feasible solution to these requirements.

  11. Exosome-encapsulated microRNAs as circulating biomarkers for breast cancer.

    Science.gov (United States)

    Joyce, Doireann P; Kerin, Michael J; Dwyer, Róisín M

    2016-10-01

    Breast cancer is a highly prevalent disease, accounting for 29% of invasive cancers in women. Survival from this disease depends on the stage at diagnosis, with patients who are detected earlier having more favourable outcomes. It is because of this that research groups are focusing on the development of a blood-based biomarker for breast cancer. Such biomarkers may facilitate the detection of breast cancer in its infancy before it has spread beyond the primary site. MicroRNAs (miRNAs) have shown immense potential in this setting. These short, non-coding RNA sequences have been shown to be dysregulated in breast cancer. Despite showing immense promise, miRNAs have not been successfully implemented in the clinical setting due to a lack of a standardised approach which has resulted in conflicting results. These challenges may be addressed at least in part through the study of exosomes. The biomarker potential for exosomes holds huge promise and may revolutionise the way in which we diagnose and manage breast cancer. These nanovesicles may be isolated from a variety of bodily fluids, including serum, and their miRNA content has been shown to reflect that of the parent breast cancer cell. This review will highlight the nomenclature and defining characteristics of exosomes, and current methods of isolation of serum-derived exosomes. Initial promising reports on the potential utility of exosomal miRNAs to be used as breast cancer biomarkers will also be addressed. PMID:27170104

  12. Prediagnostic serum levels of inflammatory biomarkers are correlated with future development of lung and esophageal cancer.

    Science.gov (United States)

    Keeley, Brieze R; Islami, Farhad; Pourshams, Akram; Poustchi, Hossein; Pak, Jamie S; Brennan, Paul; Khademi, Hooman; Genden, Eric M; Abnet, Christian C; Dawsey, Sanford M; Boffetta, Paolo; Malekzadeh, Reza; Sikora, Andrew G

    2014-09-01

    This study tests the hypothesis that prediagnostic serum levels of 20 cancer-associated inflammatory biomarkers correlate directly with future development of head and neck, esophageal, and lung cancers in a high-risk prospective cohort. This is a nested case-control pilot study of subjects enrolled in the Golestan Cohort Study, an ongoing epidemiologic project assessing cancer trends in Golestan, Iran. We measured a panel of 20 21 cytokines, chemokines, and inflammatory molecules using Luminex technology in serum samples collected 2 or more years before cancer diagnosis in 78 aerodigestive cancer cases and 81 controls. Data was analyzed using Wilcoxon rank sum test, odds ratios, receiver operating characteristic areas of discrimination, and multivariate analysis. Biomarkers were profoundly and globally elevated in future esophageal and lung cancer patients compared to controls. Odds ratios were significant for association between several biomarkers and future development of esophageal cancer, including interleukin-1Rα (IL-1Ra; 35.9), interferon α2 (IFN-a2; 34.0), fibroblast growth factor-2 (FGF-2; 17.4), and granulocyte/macrophage colony-stimulating factor (GM-CSF; 17.4). The same pattern was observed among future lung cancer cases for G-CSF (27.7), GM-CSF (13.3), and tumor necrosis factor-α (TNF-a; 8.6). By contrast, the majority of biomarkers studied showed no significant correlation with future head and neck cancer development. This study provides the first direct evidence that multiple inflammatory biomarkers are coordinately elevated in future lung and esophageal cancer patients 2 or more years before cancer diagnosis. PMID:25040886

  13. Molecular biomarkers of colorectal cancer: prognostic and predictive tools for clinical practice

    Institute of Scientific and Technical Information of China (English)

    Wei-qin JIANG; Fang-fang FU; Yang-xia LI; Wei-bin WANG; Hao-hao WANG; Hai-ping JIANG; Li-song TENG

    2012-01-01

    Colorectal cancer remains one of the most common types of cancer and leading causes of cancer death worldwide.Although we have made steady progress in chemotherapy and targeted therapy,evidence suggests that the majority of patients undergoing drug therapy experience severe,debilitating,and even lethal adverse drug events which considerably outweigh the benefits.The identification of suitable biomarkers will allow clinicians to deliver the most appropriate drugs to specific patients and spare them ineffective and expensive treatments.Prognostic and predictive biomarkers have been the subjects of many published papers,but few have been widely incorporated into clinical practice.Here,we want to review recent biomarker data related to colorectal cancer,which may have been ready for clinical use.

  14. The Discovery and Validation of Biomarkers for the Diagnosis of Esophageal Squamous Dysplasia and Squamous Cell Carcinoma.

    Science.gov (United States)

    Couch, George; Redman, James E; Wernisch, Lorenz; Newton, Richard; Malhotra, Shalini; Dawsey, Sanford M; Lao-Sirieix, Pierre; Fitzgerald, Rebecca C

    2016-07-01

    The 5-year survival rate of esophageal cancer is less than 10% in developing countries, where more than 90% of these cancers are esophageal squamous cell carcinomas (ESCC). Endoscopic screening is undertaken in high incidence areas. Biomarker analysis could reduce the subjectivity associated with histologic assessment of dysplasia and thus improve diagnostic accuracy. The aims of this study were therefore to identify biomarkers for esophageal squamous dysplasia and carcinoma. A publicly available dataset was used to identify genes with differential expression in ESCC compared with normal esophagus. Each gene was ranked by a support vector machine separation score. Expression profiles were examined, before validation by qPCR and IHC. We found that 800 genes were overexpressed in ESCC compared with normal esophagus (P < 10(-5)). Of the top 50 genes, 33 were expressed in ESCC epithelium and not in normal esophagus epithelium or stroma using the Protein Atlas website. These were taken to qPCR validation, and 20 genes were significantly overexpressed in ESCC compared with normal esophagus (P < 0.05). TNFAIP3 and CHN1 showed differential expression with IHC. TNFAIP3 expression increased gradually through normal esophagus, mild, moderate and severe dysplasia, and SCC (P < 0.0001). CHN1 staining was rarely present in the top third of normal esophagus epithelium and extended progressively towards the surface in mild, moderate, and severe dysplasia, and SCC (P < 0.0001). Two novel promising biomarkers for ESCC were identified, TNFAIP3 and CHN1. CHN1 and TNFAIP3 may improve diagnostic accuracy of screening methods for ESCC. Cancer Prev Res; 9(7); 558-66. ©2016 AACR. PMID:27072986

  15. Decade in Review-Kidney Cancer Kidney cancer's decade—discoveries, therapies and opportunities

    OpenAIRE

    Linehan, W. Marston; Ricketts, Christopher J.

    2014-01-01

    Advances in kidney cancer have occurred over the past decade, including the discovery of mutations in chromatin remodeling genes and genomic heterogeneity in clear cell renal cell carcinoma (ccRCC), altered metabolic patterns in ccRCC and papillary renal cell carcinoma and the approval of drugs for patients with ccRCC.

  16. Impacts of Exercise on Prognostic Biomarkers in Lung Cancer Patients

    Science.gov (United States)

    2016-02-18

    Extensive Stage Small Cell Lung Cancer; Healthy, no Evidence of Disease; Limited Stage Small Cell Lung Cancer; Recurrent Non-small Cell Lung Cancer; Recurrent Small Cell Lung Cancer; Stage IA Non-small Cell Lung Cancer; Stage IB Non-small Cell Lung Cancer; Stage IIA Non-small Cell Lung Cancer; Stage IIB Non-small Cell Lung Cancer; Stage IIIA Non-small Cell Lung Cancer; Stage IIIB Non-small Cell Lung Cancer; Stage IV Non-small Cell Lung Cancer

  17. Rapid point-of-care breath test for biomarkers of breast cancer and abnormal mammograms.

    Directory of Open Access Journals (Sweden)

    Michael Phillips

    Full Text Available BACKGROUND: Previous studies have reported volatile organic compounds (VOCs in breath as biomarkers of breast cancer and abnormal mammograms, apparently resulting from increased oxidative stress and cytochrome p450 induction. We evaluated a six-minute point-of-care breath test for VOC biomarkers in women screened for breast cancer at centers in the USA and the Netherlands. METHODS: 244 women had a screening mammogram (93/37 normal/abnormal or a breast biopsy (cancer/no cancer 35/79. A mobile point-of-care system collected and concentrated breath and air VOCs for analysis with gas chromatography and surface acoustic wave detection. Chromatograms were segmented into a time series of alveolar gradients (breath minus room air. Segmental alveolar gradients were ranked as candidate biomarkers by C-statistic value (area under curve [AUC] of receiver operating characteristic [ROC] curve. Multivariate predictive algorithms were constructed employing significant biomarkers identified with multiple Monte Carlo simulations and cross validated with a leave-one-out (LOO procedure. RESULTS: Performance of breath biomarker algorithms was determined in three groups: breast cancer on biopsy versus normal screening mammograms (81.8% sensitivity, 70.0% specificity, accuracy 79% (73% on LOO [C-statistic value], negative predictive value 99.9%; normal versus abnormal screening mammograms (86.5% sensitivity, 66.7% specificity, accuracy 83%, 62% on LOO; and cancer versus no cancer on breast biopsy (75.8% sensitivity, 74.0% specificity, accuracy 78%, 67% on LOO. CONCLUSIONS: A pilot study of a six-minute point-of-care breath test for volatile biomarkers accurately identified women with breast cancer and with abnormal mammograms. Breath testing could potentially reduce the number of needless mammograms without loss of diagnostic sensitivity.

  18. Biomarkers for Pancreatic Cancer: Is it Ready for Primetime?

    OpenAIRE

    Muhammad Wasif Saif; Minsig Choi; Richard Kim; Amit Mahipal

    2013-01-01

    Pancreatic cancer remains a lethal disease with brief survival especially in patients with advanced disease. Within this decade pancreatic cancer will become the second leading cause of cancer death in the Unites States after lung cancer. It is estimated that 45,220 people will be diagnosed with pancreatic cancer and about 38,460 people will die of pancreatic cancer [1].

  19. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Christopher J. Walsh

    2015-08-01

    Full Text Available The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization versus late stage data integration (meta-analysis. A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers.

  20. Microarray Meta-Analysis and Cross-Platform Normalization: Integrative Genomics for Robust Biomarker Discovery

    OpenAIRE

    Walsh, Christopher J.; Pingzhao Hu; Jane Batt; dos Santos, Claudia C.

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus ...

  1. Synovial tissue analysis for the discovery of diagnostic and prognostic biomarkers in patients with early arthritis.

    Science.gov (United States)

    de Hair, Maria J H; Harty, Leonard C; Gerlag, Danielle M; Pitzalis, Costantino; Veale, Douglas J; Tak, Paul P

    2011-09-01

    Rheumatoid arthritis (RA) is a chronic disease of unspecified etiology that is manifest by persistent inflammation of the synovium. Considerable efforts have been undertaken globally to study the microenvironment of the inflamed synovium, with many encouraging and enlightening results that bring us closer to unmasking the precise etiologies of RA. Subsequent to these efforts, it has been discovered that CD68-positive macrophages present in abundance in the synovial sublining of the inflamed synovium rescind with treatments that induce clinical improvement in RA. Examination of serial synovial biopsies is now commonly used for screening purposes during early drug development, and the number of centers able to perform synovial tissue biopsy sampling according to standardized methods is increasing. Having implemented the use of serial synovial tissue biopsies to evaluate the effects of new treatments on the group level in early proof of principle studies, it is the ambition of the OMERACT Synovial Tissue Group to identify synovial diagnostic and prognostic biomarkers that could be used in individual patients. Therefore, we started a prospective study termed the Synoviomics Project aimed at the identification of novel diagnostic and prognostic synovial biomarkers. We will use straightforward and powerful technologies to analyze patient material and assess clinical parameters to identify such biomarkers. These markers may be used in the future to identify patients who are at risk of having persistent and destructive disease and to start tailor-made targeted therapies in an early phase to prevent autonomous disease progression and irreversible joint damage. PMID:21885519

  2. A Serum Biomarker Model to Diagnose Pancreatic Cancer Using Proteomic Fingerprint Technology

    Institute of Scientific and Technical Information of China (English)

    Chunlin Ge; Ning Ma; Dianbo Yao; Fengming Luan; Chaojun Hu; Yongzhe Li; Yongfeng Liu

    2008-01-01

    OBJECTIVE To establish a serum protein pattern model for screening pancreatic cancer.METHODS Twenty-nine serum samples from patients with pancreatic cancer were collected before surgery,and an additional 57 serum samples from age and sex-matched individuals without cancer were used as controls.WCX magnetic beans and a PBS Ⅱ-C protein chip reader(Ciphergen Biosystems Inc)were employed to detect the protein fingerprint expression of all serum samples.The resulting profiles comparing serum from cancer and normal patients were analyzed with the Biomarker Wizard system,to establish a model using the Biomarker Pattern system software.A double-blind test was used to determine the sensitivity and specificity of the model.RESULTS A group of 4 biomarkers (relative molecular weights were 5,705 Da,4,935 Da,5,318 Da,3,243 Da)were selected to set up a decision tree to produce the classification model to effectively screen pancreatic cancer patients.The results yielded a sensitivitv of 100%(20/20),specificity of 97.4%(37/38).The ROC curve was 99.7%.A double-blind test used to challenge the model resulted in a sensitivity of 88.9% and a specifcity of 89.5%.CONCLUSION New serum biomarkers of pancreatic cancer have been identified.The pattern of combined markers provides a powerful and reliable diagnostic method for pancreatic cancer with high sensitivity and specificity.

  3. Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

    OpenAIRE

    Chung, Liping; Moore, Katrina; Phillips, Leo; Boyle, Frances M.; Marsh, Deborah J.; Baxter, Robert C.

    2014-01-01

    Introduction Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel. Methods Training set serum samples from 99 BC and 51 H...

  4. Personalized Medicine and Oncology Practice Guidelines: A Case Study of Contemporary Biomarkers in Colorectal Cancer

    OpenAIRE

    Kelley, Robin K; Van Bebber, Stephanie L; Phillips, Kathryn A; Venook, Alan P.

    2011-01-01

    Predictive and prognostic biomarkers offer a potential means to personalize cancer medicine, although many reach the marketplace before they have been validated, and their adoption is often hindered by variable clinical evidence. Because of this variability in supporting evidence, clinical practice guidelines formulated by panels of subspecialty experts may be particularly important in guiding stakeholders’ acceptance and use of new personalized medicine biomarker tests and other nascent tech...

  5. Systematic biomarker discovery and coordinative validation for different primary nephrotic syndromes using gas chromatography-mass spectrometry.

    Science.gov (United States)

    Lee, Jung-Eun; Lee, Yu Ho; Kim, Se-Yun; Kim, Yang Gyun; Moon, Ju-Young; Jeong, Kyung-Hwan; Lee, Tae Won; Ihm, Chun-Gyoo; Kim, Sooah; Kim, Kyoung Heon; Kim, Dong Ki; Kim, Yon Su; Kim, Chan-Duck; Park, Cheol Whee; Lee, Do Yup; Lee, Sang-Ho

    2016-07-01

    The goal of this study is to identify systematic biomarker panel for primary nephrotic syndromes from urine samples by applying a non-target metabolite profiling, and to validate their utility in independent sampling and analysis by multiplex statistical approaches. Nephrotic syndrome (NS) is a nonspecific kidney disorder, which is mostly represented by minimal change disease (MCD), focal segmental glomerulosclerosis (FSGS), and membranous glomerulonephritis (MGN). Since urine metabolites may mirror disease-specific functional perturbations in kidney injury, we examined urine samples for distinctive metabolic changes to identify biomarkers for clinical applications. We developed unbiased multi-component covarianced models from a discovery set with 48 samples (12 healthy controls, 12 MCD, 12 FSGS, and 12 MGN). To extensively validate their diagnostic potential, new batch from 54 patients with primary NS were independently examined a year after. In the independent validation set, the model including citric acid, pyruvic acid, fructose, ethanolamine, and cysteine effectively discriminated each NS using receiver operating characteristic (ROC) analysis except MCD-MGN comparison; nonetheless an additional metabolite multi-composite greatly improved the discrimination power between MCD and MGN. Finally, we proposed the re-constructed metabolic network distinctively dysregulated by the different NSs that may deepen comprehensive understanding of the disease mechanistic, and help the enhanced identification of NS and therapeutic plans for future. PMID:27247212

  6. REG4 Is Highly Expressed in Mucinous Ovarian Cancer: A Potential Novel Serum Biomarker.

    Science.gov (United States)

    Lehtinen, Laura; Vesterkvist, Pia; Roering, Pia; Korpela, Taina; Hattara, Liisa; Kaipio, Katja; Mpindi, John-Patrick; Hynninen, Johanna; Auranen, Annika; Davidson, Ben; Haglund, Caj; Iljin, Kristiina; Grenman, Seija; Siitari, Harri; Carpen, Olli

    2016-01-01

    Preoperative diagnostics of ovarian neoplasms rely on ultrasound imaging and the serum biomarkers CA125 and HE4. However, these markers may be elevated in non-neoplastic conditions and may fail to identify most non-serous epithelial cancer subtypes. The objective of this study was to identify histotype-specific serum biomarkers for mucinous ovarian cancer. The candidate genes with mucinous histotype specific expression profile were identified from publicly available gene-expression databases and further in silico data mining was performed utilizing the MediSapiens database. Candidate biomarker validation was done using qRT-PCR, western blotting and immunohistochemical staining of tumor tissue microarrays. The expression level of the candidate gene in serum was compared to the serum CA125 and HE4 levels in a patient cohort of prospectively collected advanced ovarian cancer. Database searches identified REG4 as a potential biomarker with specificity for the mucinous ovarian cancer subtype. The specific expression within epithelial ovarian tumors was further confirmed by mRNA analysis. Immunohistochemical staining of ovarian tumor tissue arrays showed distinctive cytoplasmic expression pattern only in mucinous carcinomas and suggested differential expression between benign and malignant mucinous neoplasms. Finally, an ELISA based serum biomarker assay demonstrated increased expression only in patients with mucinous ovarian cancer. This study identifies REG4 as a potential serum biomarker for histotype-specific detection of mucinous ovarian cancer and suggests serum REG4 measurement as a non-invasive diagnostic tool for postoperative follow-up of patients with mucinous ovarian cancer. PMID:26981633

  7. Evolving Role of Bone Biomarkers in Castration-Resistant Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Janet E. Brown

    2010-09-01

    Full Text Available The preferential metastasis of prostate cancer cells to bone disrupts the process of bone remodeling and results in lesions that cause significant pain and patient morbidity. Although prostate-specific antigen (PSA is an established biomarker in prostate cancer, it provides only limited information relating to bone metastases and the treatment of metastatic bone disease with bisphosphonates or novel noncytotoxic targeted or biological agents that may provide clinical benefits without affecting PSA levels. As bone metastases develop, factors derived from bone metabolism are released into blood and urine, including N- and C-terminal peptide fragments of type 1 collagen and bone-specific alkaline phosphatase, which represent potentially useful biomarkers for monitoring metastatic bone disease. A number of clinical trials have investigated these bone biomarkers with respect to their diagnostic, prognostic, and predictive values. Results suggest that higher levels of bone biomarkers are associated with an increased risk of skeletal-related events and/or death. As a result of these findings, bone biomarkers are now being increasingly used as study end points, particularly in studies investigating novel agents with putative bone effects. Data from prospective clinical trials are needed to validate the use of bone biomarkers and to confirm that marker levels provide additional information beyond traditional methods of response evaluation for patients with metastatic prostate cancer.

  8. Clinical application of biomarkers in colon cancer: studies on apoptosis, proliferation and the immune system

    OpenAIRE

    Zeestraten, Eliane Cornelia Maria

    2014-01-01

    Colon cancer is a major contributor to can- cer-related mortality worldwide. Death from colon cancer occurs in the majority of cases from widespread metastatic disease. Only 15% of stage II colon cancer patients that develop metastasis will benefit from adjuvant chemotherapy, all of them will suffer from treatment-related toxicity. This makes it essential for the clinician to precisely identify the patient cohort at risk for metastasis. Prognostic biomarkers might improve current staging crit...

  9. MicroRNAs: Promising chemoresistance biomarkers in gastric cancer with diagnostic and therapeutic potential

    OpenAIRE

    Matuszcak, Christiane; Haier, Joerg; Hummel, Richard; Lindner, Kirsten

    2014-01-01

    Gastric cancer (GC) is the fourth most common cancer worldwide and ranks second in global cancer mortality statistics. Perioperative chemotherapy plays an important role in the management and treatment of advanced stage disease. However, response to chemotherapy varies widely, with some patients presenting no or only minor response to treatment. Hence, chemotherapy resistance is a major clinical problem that impacts on outcome. Unfortunately, to date there are no reliable biomarkers available...

  10. Prediagnostic serum levels of inflammatory biomarkers are correlated with future development of lung and esophageal cancer

    OpenAIRE

    Keeley, Brieze R; Islami, Farhad; Pourshams, Akram; Poustchi, Hossein; Pak, Jamie S; Brennan, Paul; Khademi, Hooman; Genden, Eric M.; Abnet, Christian C.; Dawsey, Sanford M.; Boffetta, Paolo; Malekzadeh, Reza; Sikora, Andrew G.

    2014-01-01

    This study tests the hypothesis that prediagnostic serum levels of 20 cancer-associated inflammatory biomarkers correlate directly with future development of head and neck, esophageal, and lung cancers in a high-risk prospective cohort. This is a nested case–control pilot study of subjects enrolled in the Golestan Cohort Study, an ongoing epidemiologic project assessing cancer trends in Golestan, Iran. We measured a panel of 20 21cytokines, chemokines, and inflammatory molecules using Luminex...

  11. RNA-Seq Accurately Identifies Cancer Biomarker Signatures to Distinguish Tissue of Origin1

    OpenAIRE

    Wei, Iris H.; Shi, Yang; Jiang, Hui; Kumar-Sinha, Chandan; Arul M Chinnaiyan

    2014-01-01

    Metastatic cancer of unknown primary (CUP) accounts for up to 5% of all new cancer cases, with a 5-year survival rate of only 10%. Accurate identification of tissue of origin would allow for directed, personalized therapies to improve clinical outcomes. Our objective was to use transcriptome sequencing (RNA-Seq) to identify lineage-specific biomarker signatures for the cancer types that most commonly metastasize as CUP (colorectum, kidney, liver, lung, ovary, pancreas, prostate, and stomach)....

  12. Vascular endothelial growth factor in the circulation in cancer patients may not be a relevant biomarker

    OpenAIRE

    Tatjana M H Niers; Richel, Dick J.; Meijers, Joost C.M.; Schlingemann, Reinier O.

    2011-01-01

    BACKGROUND: Levels of circulating vascular endothelial growth factor (VEGF) have widely been used as biomarker for angiogenic activity in cancer. For this purpose, non-standardized measurements in plasma and serum were used, without correction for artificial VEGF release by platelets activated ex vivo. We hypothesize that "true" circulating (c)VEGF levels in most cancer patients are low and unrelated to cancer load or tumour angiogenesis. METHODOLOGY: We determined VEGF levels in PECT, a medi...

  13. Stress-induced Phosphoprotein 1 as a Secreted Biomarker for Human Ovarian Cancer Promotes Cancer Cell Proliferation*

    OpenAIRE

    Wang, Tzu-Hao; Chao, Angel; Tsai, Chia-Lung; Chang, Chih-Long; Chen, Shun-Hua; Lee, Yun-Shien; Chen, Jen-Kun; Lin, Yi-Jun; Chang, Pi-Yueh; Wang, Chin-Jung; Chao, An-Shine; Chang, Shuenn-Dyh; Chang, Ting-Chang; Lai, Chyong-Huey; Wang, Hsin-Shih

    2010-01-01

    Ovarian cancers are frequently not diagnosed until advanced stages, resulting in a high case fatality rate. Because of this, more tumor markers, in addition to CA125, for detecting and monitoring ovarian cancer are needed. During a systematic search for potential biomarkers of ovarian cancer, we compared the protein profiles between tumor interstitial fluid and normal interstitial fluid of ovaries, rationalizing that abnormal levels of proteins in tumor interstitial fluid may be detected in p...

  14. Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

    Directory of Open Access Journals (Sweden)

    Parida Shreemanta K

    2010-01-01

    Full Text Available Abstract Background For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in

  15. Ultrasensitive Detection of Dual Cancer Biomarkers with Integrated CMOS-Compatible Nanowire Arrays.

    Science.gov (United States)

    Lu, Na; Gao, Anran; Dai, Pengfei; Mao, Hongju; Zuo, Xiaolei; Fan, Chunhai; Wang, Yuelin; Li, Tie

    2015-11-17

    A direct, rapid, highly sensitive and specific biosensor for detection of cancer biomarkers is desirable in early diagnosis and prognosis of cancer. However, the existing methods of detecting cancer biomarkers suffer from poor sensitivity as well as the requirement of enzymatic labeling or nanoparticle conjugations. Here, we proposed a two-channel PDMS microfluidic integrated CMOS-compatible silicon nanowire (SiNW) field-effect transistor arrays with potentially single use for label-free and ultrasensitive electrical detection of cancer biomarkers. The integrated nanowire arrays showed not only ultrahigh sensitivity of cytokeratin 19 fragment (CYFRA21-1) and prostate specific antigen (PSA) with detection to at least 1 fg/mL in buffer solution but also highly selectivity of discrimination from other similar cancer biomarkers. In addition, this method was used to detect both CYFRA21-1 and PSA real samples as low as 10 fg/mL in undiluted human serums. With its excellent properties and miniaturization, the integrated SiNW-FET device opens up great opportunities for a point-of-care test (POCT) for quick screening and early diagnosis of cancer and other complex diseases. PMID:26473941

  16. In vitro biomarker discovery in the parasitic flatworm Fasciola hepatica for monitoring chemotherapeutic treatment

    Directory of Open Access Journals (Sweden)

    Russell M. Morphew

    2014-06-01

    Full Text Available The parasitic flatworm Fasciola hepatica is a global food security risk. With no vaccines, the sustainability of triclabendazole (TCBZ is threatened by emerging resistance. F. hepatica excretory/secretory (ES products can be detected in host faeces and used to estimate TCBZ success and failure. However, there are no faecal based molecular diagnostics dedicated to assessing drug failure or resistance to TCBZ in the field. Utilising in vitro maintenance and sub-proteomic approaches two TCBZ stress ES protein response fingerprints were identified: markers of non-killing and lethal doses. This study provides candidate protein/peptide biomarkers to validate for detection of TCBZ failure and resistance.

  17. Integration of metabolomics and proteomics in multiple sclerosis: From biomarkers discovery to personalized medicine.

    Science.gov (United States)

    Del Boccio, Piero; Rossi, Claudia; di Ioia, Maria; Cicalini, Ilaria; Sacchetta, Paolo; Pieragostino, Damiana

    2016-04-01

    Personalized medicine is the science of individualized prevention and therapy. In the last decade, advances in high-throughput approaches allowed the development of proteomic and metabolomic studies in evaluating the association of genetic and phenotypic variability with disease sensitivity and analgesic response. These considerations have more value in case of multiple sclerosis (MuS), a multifactorial disease with high heterogeneity in clinical course and treatment response. In this review, we reported and updated about proteomic and metabolomic studies for the research of new candidate biomarkers in MuS, and difficulties in their clinical applications. We focused especially on the description of both "omics" approaches that, once integrated, may synergically describe pathophysiology conditions. To prove this assumption, we rebuilt interaction between proteins and metabolites described in the literature as potential biomarkers for MuS, and a pathway analysis of these molecules was performed. The result of such speculation demonstrated a strong convergence of proteomic and metabolomic results in this field, showing also a poorness of available tools for incorporating "omics" approaches. In conclusion, the integration of Metabolomics and Proteomics may allow a more complete characterization of such a heterogeneous disease, providing further insights into personalized healthcare. PMID:27061322

  18. The proteome of Hypobaric Induced Hypoxic Lung: Insights from Temporal Proteomic Profiling for Biomarker Discovery

    Science.gov (United States)

    Ahmad, Yasmin; Sharma, Narendra K.; Ahmad, Mohammad Faiz; Sharma, Manish; Garg, Iti; Srivastava, Mousami; Bhargava, Kalpana

    2015-01-01

    Exposure to high altitude induces physiological responses due to hypoxia. Lungs being at the first level to face the alterations in oxygen levels are critical to counter and balance these changes. Studies have been done analysing pulmonary proteome alterations in response to exposure to hypobaric hypoxia. However, such studies have reported the alterations at specific time points and do not reflect the gradual proteomic changes. These studies also identify the various biochemical pathways and responses induced after immediate exposure and the resolution of these effects in challenge to hypobaric hypoxia. In the present study, using 2-DE/MS approach, we attempt to resolve these shortcomings by analysing the proteome alterations in lungs in response to different durations of exposure to hypobaric hypoxia. Our study thus highlights the gradual and dynamic changes in pulmonary proteome following hypobaric hypoxia. For the first time, we also report the possible consideration of SULT1A1, as a biomarker for the diagnosis of high altitude pulmonary edema (HAPE). Higher SULT1A1 levels were observed in rats as well as in humans exposed to high altitude, when compared to sea-level controls. This study can thus form the basis for identifying biomarkers for diagnostic and prognostic purposes in responses to hypobaric hypoxia. PMID:26022216

  19. New Concepts in Cancer Biomarkers: Circulating miRNAs in Liquid Biopsies.

    Science.gov (United States)

    Larrea, Erika; Sole, Carla; Manterola, Lorea; Goicoechea, Ibai; Armesto, María; Arestin, María; Caffarel, María M; Araujo, Angela M; Araiz, María; Fernandez-Mercado, Marta; Lawrie, Charles H

    2016-01-01

    The effective and efficient management of cancer patients relies upon early diagnosis and/or the monitoring of treatment, something that is often difficult to achieve using standard tissue biopsy techniques. Biological fluids such as blood hold great possibilities as a source of non-invasive cancer biomarkers that can act as surrogate markers to biopsy-based sampling. The non-invasive nature of these "liquid biopsies" ultimately means that cancer detection may be earlier and that the ability to monitor disease progression and/or treatment response represents a paradigm shift in the treatment of cancer patients. Below, we review one of the most promising classes of circulating cancer biomarkers: microRNAs (miRNAs). In particular, we will consider their history, the controversy surrounding their origin and biology, and, most importantly, the hurdles that remain to be overcome if they are really to become part of future clinical practice. PMID:27128908

  20. Cell stiffness is a biomarker of the metastatic potential of ovarian cancer cells

    Science.gov (United States)

    Xu, Wenwei; Mezencev, Roman; Kim, Byungkyu; Wang, Lijuan; McDonald, John; Sulchek, Todd; Sulchek Team; McDonald Team

    2013-03-01

    The metastatic potential of cells is an important parameter in the design of optimal strategies for the personalized treatment of cancer. Using atomic force microscopy (AFM), we show that ovarian cancer cells are generally softer and display lower intrinsic variability in cell stiffness than non-malignant ovarian epithelial cells. A detailed study of highly invasive ovarian cancer cells (HEY A8) and their less invasive parental cells (HEY), demonstrates that deformability can serve as an accurate biomarker of metastatic potential. Comparative gene expression profiling indicate that the reduced stiffness of highly metastatic HEY A8 cells is associated with actin cytoskeleton remodeling, microscopic examination of actin fiber structure in these cell lines is consistent with this prediction. Our results indicate that cell stiffness not only distinguishes ovarian cancer cells from non-malignant cells, but may also be a useful biomarker to evaluate the relative metastatic potential of ovarian and perhaps other types of cancer cells.

  1. Exosomal microRNA Biomarkers: Emerging Frontiers in Colorectal and Other Human Cancers.

    Science.gov (United States)

    Tovar-Camargo, Oscar A; Toden, Shusuke; Goel, Ajay

    2016-05-01

    Diagnostic strategies, particularly non-invasive blood-based screening approaches, are gaining increased attention for the early detection and attenuation of mortality associated with colorectal cancer (CRC). However, the majority of current screening approaches are inadequate at replacing the conventional CRC diagnostic procedures. Yet, due to technological advances and better understanding of molecular events underlying human cancer, a new category of biomarkers are on the horizon. Recent evidence indicates that cells release a distinct class of small vesicles called 'exosomes', which contain nucleic acids and proteins that reflect and typify host-cell molecular architecture. Intriguingly, exosomes released from cancer cells have a distinct genetic and epigenetic makeup, which allows them to undertake their tumorigenic function. From a clinical standpoint, these unique cancer-specific fingerprints present in exosomes appear to be detectable in a small amount of blood, making them very attractive substrates for developing cancer biomarkers, particularly noninvasive diagnostic approaches. PMID:26892862

  2. Epigenetics and cancer: implications for drug discovery and safety assessment

    International Nuclear Information System (INIS)

    It is necessary to determine whether chemicals or drugs have the potential to pose a threat to human health. Research conducted over the last two decades has led to the paradigm that chemicals can cause cancer either by damaging DNA or by altering cellular growth, probably via receptor-mediated changes in gene expression. However, recent evidence suggests that gene expression can be altered markedly via several diverse epigenetic mechanisms that can lead to permanent or reversible changes in cellular behavior. Key molecular events underlying these mechanisms include the alteration of DNA methylation and chromatin, and changes in the function of cell surface molecules. Thus, for example, DNA methyltransferase enzymes together with chromatin-associated proteins such as histone modifying enzymes and remodelling factors can modify the genetic code and contribute to the establishment and maintenance of altered epigenetic states. This is relevant to many types of toxicity including but not limited to cancer. In this paper, we describe the potential for interplay between genetic alteration and epigenetic changes in cell growth regulation and discuss the implications for drug discovery and safety assessment

  3. Identification of an epigenetic biomarker panel with high sensitivity and specificity for colorectal cancer and adenomas

    Directory of Open Access Journals (Sweden)

    Lind Guro E

    2011-07-01

    Full Text Available Abstract Background The presence of cancer-specific DNA methylation patterns in epithelial colorectal cells in human feces provides the prospect of a simple, non-invasive screening test for colorectal cancer and its precursor, the adenoma. This study investigates a panel of epigenetic markers for the detection of colorectal cancer and adenomas. Methods Candidate biomarkers were subjected to quantitative methylation analysis in test sets of tissue samples from colorectal cancers, adenomas, and normal colonic mucosa. All findings were verified in independent clinical validation series. A total of 523 human samples were included in the study. Receiver operating characteristic (ROC curve analysis was used to evaluate the performance of the biomarker panel. Results Promoter hypermethylation of the genes CNRIP1, FBN1, INA, MAL, SNCA, and SPG20 was frequent in both colorectal cancers (65-94% and adenomas (35-91%, whereas normal mucosa samples were rarely (0-5% methylated. The combined sensitivity of at least two positives among the six markers was 94% for colorectal cancers and 93% for adenoma samples, with a specificity of 98%. The resulting areas under the ROC curve were 0.984 for cancers and 0.968 for adenomas versus normal mucosa. Conclusions The novel epigenetic marker panel shows very high sensitivity and specificity for both colorectal cancers and adenomas. Our findings suggest this biomarker panel to be highly suitable for early tumor detection.

  4. Identification of cystatin SN as a novel biomarker for pancreatic cancer.

    Science.gov (United States)

    Jiang, Jie; Liu, Hui-Ling; Liu, Zhi-Hao; Tan, Si-Wei; Wu, Bin

    2015-05-01

    Cystatin SN (cystatin 1, CST1) is a member of the cystatin superfamily that inhibits the proteolytic activity of cysteine proteases. CST1 is a tumor biomarker that provides useful information for the diagnosis of esophageal, gastric, and colorectal carcinomas. However, the significance of CST1 in pancreatic cancer is unknown. The aim of this study was to assess whether CST1 is a potential biomarker for early diagnosis of malignant pancreatic neoplasms. Microarray analysis of mRNA extracted from pancreatic cancer and pancreatic normal tissues was performed. Bioinformatics revealed that CST1 was one of the highest expressed genes on the array in pancreatic cancer, compared with normal tissue. In addition, the upregulation of CST1 in pancreatic cancer and several pancreatic cancer cell lines was confirmed using real-time PCR (RT-PCR), immunohistochemistry, and Western blotting. Next, CST1 knockdown using siRNA reduced the expression of the proliferation-related proteins p-AKT and PCNA significantly, as well as colony formation and xenograft development in vitro. Consistent with this, CST1 mRNA overexpression was correlated closely with malignancy-associated proteins such as PCNA, cyclin D1, cyclin A2, and cyclin E in pancreatic cancer cell lines. In conclusion, our data suggest that CST1 might contribute to the proliferation of pancreatic cancer cells and could be a potential biomarker for the early detection of pancreatic cancer. PMID:25577248

  5. Diversity-Oriented Synthetic Strategies Applied to Cancer Chemical Biology and Drug Discovery

    OpenAIRE

    Ian Collins; Jones, Alan M.

    2014-01-01

    How can diversity-oriented strategies for chemical synthesis provide chemical tools to help shape our understanding of complex cancer pathways and progress anti-cancer drug discovery efforts? This review (surveying the literature from 2003 to the present) considers the applications of diversity-oriented synthesis (DOS), biology-oriented synthesis (BIOS) and associated strategies to cancer biology and drug discovery, summarising the syntheses of novel and often highly complex scaffolds from p...

  6. Biomarkers to Distinguish Aggressive Cancers from Non-aggressive or Non-progressing Cancer — EDRN Public Portal

    Science.gov (United States)

    Distinguishing aggressive cancers from non-aggressive or non-progressing cancers is an issue of both clinical and public health importance particularly for those cancers with an available screening test. With respect to breast cancer, mammographic screening has been shown in randomized trials to reduce breast cancer mortality, but given the limitations of its sensitivity and specificity some breast cancers are missed by screening. These so called interval detected breast cancers diagnosed between regular screenings are known to have a more aggressive clinical profile. In addition, of those cancers detected by mammography some are indolent while others are more likely to recur despite treatment. The pilot study proposed herein is highly responsive to the EDRN supplement titled “Biomarkers to Distinguish Aggressive Cancers from Nonaggressive or Non-progressing Cancers” in that it addresses both of the research objectives related to these issues outlined in the notice for this supplement: Aim 1: To identify biomarkers in tumor tissue related to risk of interval detected vs. mammography screen detected breast cancer focusing on early stage invasive disease. We will compare gene expression profiles using the whole genome-cDNA-mediated Annealing, Selection, extension and Ligation (DASL) assay of 50 screen detected cancers to those of 50 interval detected cancers. Through this approach we will advance our understanding of the molecular characteristics of interval vs. screen detected breast cancers and discover novel biomarkers that distinguish between them. Aim 2: To identify biomarkers in tumor tissue related to risk of cancer recurrence among patients with screen detected early stage invasive breast cancer. Using the DASL assay we will compare gene expression profiles from screen detected early stage breast cancer that either recurred within five years or never recurred within five years. These two groups of patients will be matched on multiple factors including

  7. Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening

    Science.gov (United States)

    Phillips, Michael; Bauer, Thomas L.; Cataneo, Renee N.; Lebauer, Cassie; Mundada, Mayur; Pass, Harvey I.; Ramakrishna, Naren; Rom, William N.; Vallières, Eric

    2015-01-01

    Background Breath volatile organic compounds (VOCs) have been reported as biomarkers of lung cancer, but it is not known if biomarkers identified in one group can identify disease in a separate independent cohort. Also, it is not known if combining breath biomarkers with chest CT has the potential to improve the sensitivity and specificity of lung cancer screening. Methods Model-building phase (unblinded): Breath VOCs were analyzed with gas chromatography mass spectrometry in 82 asymptomatic smokers having screening chest CT, 84 symptomatic high-risk subjects with a tissue diagnosis, 100 without a tissue diagnosis, and 35 healthy subjects. Multiple Monte Carlo simulations identified breath VOC mass ions with greater than random diagnostic accuracy for lung cancer, and these were combined in a multivariate predictive algorithm. Model-testing phase (blinded validation): We analyzed breath VOCs in an independent cohort of similar subjects (n = 70, 51, 75 and 19 respectively). The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening. Results Unblinded model-building phase. The algorithm identified lung cancer with sensitivity 74.0%, specificity 70.7% and C-statistic 0.78. Blinded model-testing phase: The algorithm identified lung cancer at Laboratory A with sensitivity 68.0%, specificity 68.4%, C-statistic 0.71; and at Laboratory B with sensitivity 70.1%, specificity 68.0%, C-statistic 0.70, with linear correlation between replicates (r = 0.88). In a projected outcome model, breath biomarkers increased the sensitivity, specificity, and positive and negative predictive values of chest CT for lung cancer when the tests were combined in series or parallel. Conclusions Breath VOC mass ion biomarkers identified lung cancer in a

  8. Bovine Tuberculosis in Cattle: Vaccines, DIVA Tests, and Host Biomarker Discovery.

    Science.gov (United States)

    Vordermeier, H Martin; Jones, Gareth J; Buddle, Bryce M; Hewinson, R Glyn; Villarreal-Ramos, Bernardo

    2016-02-15

    Bovine tuberculosis remains a major economic and animal welfare concern worldwide. Cattle vaccination is being considered as part of control strategies. This approach, used alongside conventional control policies, also requires the development of vaccine-compatible diagnostic assays to distinguish vaccinated from infected animals (DIVA). We discuss progress made on optimizing the only potentially available vaccine, bacille Calmette Guérin (BCG), and on strategies to improve BCG efficacy. We also describe recent advances in DIVA development based on the detection of host cellular immune responses by blood-testing or skin-testing approaches. Finally, to accelerate vaccine development, definition of host biomarkers that provide meaningful stage-gating criteria to select vaccine candidates for further testing is highly desirable. Some progress has also been made in this area of research, and we summarize studies that defined either markers predicting vaccine success or markers that correlate with disease stage or severity. PMID:26884103

  9. Discovery and identification of Serum Amyloid A protein elevated in lung cancer serum

    Institute of Scientific and Technical Information of China (English)

    DAI SongWei; WANG XiaoMin; LIU LiYun; LIU JiFu; WU ShanShan; HUANG LingYun; XIAO XueYuan; HE DaCheng

    2007-01-01

    Two hundred and eighteen serum samples from 175 lung cancer patients and 43 healthy individuals were analyzed by using Surface Enhaced Laser Desorption/lonization Time of Flight Mass Spectrometry (SELDI-TOF-MS). The data analyzed by both Biomarker WizardTM and Biomarker PatternsTM software showed that a protein peak with the molecular weight of 11.6 kDa significantly increased in lung cancer.Meanwhile, the level of this biomarker was progressively increased with the clinical stages of lung cancer. The candidate biomarker was then obtained from tricine one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis by matching the molecular weight with peaks on WCX2 chips and was identified as Serum Amyloid A protein (SAA) by MALDI/MS-MS and database searching. It was further validated in the same serum samples by immunoprecipitation with commercial SAA antibody.To confirm the SAA differential expression in lung cancer patients, the same set of serum samples was measured by ELISA assay. The result showed that at the cutoff point 0.446 (OD value) on the Receiver Operating Characteristic (ROC) curve, SAA could better discriminate lung cancer from healthy individuals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.

  10. Tissue Microarrays in Non-Small Cell Lung Cancer: Reliability of Immunohistochemically-Determined Biomarkers

    DEFF Research Database (Denmark)

    Pøhl, Mette; Olsen, Karen Ege; Holst, René;

    2014-01-01

    BACKGROUND: The reliability of immunohistochemically-determined biomarkers using tissue microarrays (TMAs) of clinical specimens has long been open to question. Heterogeneity related to tumor biology might compromise determination of accurate biomarker expression in tumors, especially in small core...... biopsies. We evaluated the reliability of immunohistochemical staining scoring in small core biopsies using 11 biomarkers in non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: Four 1-mm tumor cores from 178 NSCLCs, 2 representing peripheral areas close to the border of normal lung tissue and 2...... representing central areas, were examined. The biomarkers analyzed included p63, p40, cytokeratin 1/5/10/14, cytokeratin 7, thyroid transcription factor-1, napsin A, cyclin-D1, p53, Ki-67, integrin beta-1, and thymidylate synthase. RESULTS: Using a random intercept logistic regression model...

  11. Can Biomarker Assessment on Circulating Tumor Cells Help Direct Therapy in Metastatic Breast Cancer?

    International Nuclear Information System (INIS)

    Circulating tumor cell (CTC) count has prognostic significance in metastatic breast cancer, but the predictive utility of CTCs is uncertain. Molecular studies on CTCs have often been limited by a low number of CTCs isolated from a high background of leukocytes. Improved enrichment techniques are now allowing molecular characterisation of single CTCs, whereby molecular markers on single CTCs may provide a real-time assessment of tumor biomarker status from a blood test or “liquid biopsy”, potentially negating the need for a more invasive tissue biopsy. The predictive ability of CTC biomarker analysis has predominantly been assessed in relation to HER2, with variable and inconclusive results. Limited data exist for other biomarkers, such as the estrogen receptor. In addition to the need to define and validate the most accurate and reproducible method for CTC molecular analysis, the clinical relevance of biomarkers, including gain of HER2 on CTC after HER2 negative primary breast cancer, remains uncertain. This review summarises the currently available data relating to biomarker evaluation on CTCs and its role in directing management in metastatic breast cancer, discusses limitations, and outlines measures that may enable future development of this approach

  12. Can Biomarker Assessment on Circulating Tumor Cells Help Direct Therapy in Metastatic Breast Cancer?

    Directory of Open Access Journals (Sweden)

    Natalie Turner

    2014-03-01

    Full Text Available Circulating tumor cell (CTC count has prognostic significance in metastatic breast cancer, but the predictive utility of CTCs is uncertain. Molecular studies on CTCs have often been limited by a low number of CTCs isolated from a high background of leukocytes. Improved enrichment techniques are now allowing molecular characterisation of single CTCs, whereby molecular markers on single CTCs may provide a real-time assessment of tumor biomarker status from a blood test or “liquid biopsy”, potentially negating the need for a more invasive tissue biopsy. The predictive ability of CTC biomarker analysis has predominantly been assessed in relation to HER2, with variable and inconclusive results. Limited data exist for other biomarkers, such as the estrogen receptor. In addition to the need to define and validate the most accurate and reproducible method for CTC molecular analysis, the clinical relevance of biomarkers, including gain of HER2 on CTC after HER2 negative primary breast cancer, remains uncertain. This review summarises the currently available data relating to biomarker evaluation on CTCs and its role in directing management in metastatic breast cancer, discusses limitations, and outlines measures that may enable future development of this approach.

  13. Can Biomarker Assessment on Circulating Tumor Cells Help Direct Therapy in Metastatic Breast Cancer?

    Energy Technology Data Exchange (ETDEWEB)

    Turner, Natalie [Sandro Pitigliani Medical Oncology Department, Prato Hospital, Istituto Toscano Tumori, Via Ugo Foscolo, Prato, PO 59100 (Italy); Pestrin, Marta [Sandro Pitigliani Medical Oncology Department, Prato Hospital, Istituto Toscano Tumori, Via Ugo Foscolo, Prato, PO 59100 (Italy); Translational Research Laboratory, Prato Hospital, Via Ugo Foscolo, Prato, PO 59100 (Italy); Galardi, Francesca; De Luca, Francesca [Translational Research Laboratory, Prato Hospital, Via Ugo Foscolo, Prato, PO 59100 (Italy); Malorni, Luca [Sandro Pitigliani Medical Oncology Department, Prato Hospital, Istituto Toscano Tumori, Via Ugo Foscolo, Prato, PO 59100 (Italy); Translational Research Laboratory, Prato Hospital, Via Ugo Foscolo, Prato, PO 59100 (Italy); Di Leo, Angelo, E-mail: adileo@usl4.toscana.it [Sandro Pitigliani Medical Oncology Department, Prato Hospital, Istituto Toscano Tumori, Via Ugo Foscolo, Prato, PO 59100 (Italy)

    2014-03-25

    Circulating tumor cell (CTC) count has prognostic significance in metastatic breast cancer, but the predictive utility of CTCs is uncertain. Molecular studies on CTCs have often been limited by a low number of CTCs isolated from a high background of leukocytes. Improved enrichment techniques are now allowing molecular characterisation of single CTCs, whereby molecular markers on single CTCs may provide a real-time assessment of tumor biomarker status from a blood test or “liquid biopsy”, potentially negating the need for a more invasive tissue biopsy. The predictive ability of CTC biomarker analysis has predominantly been assessed in relation to HER2, with variable and inconclusive results. Limited data exist for other biomarkers, such as the estrogen receptor. In addition to the need to define and validate the most accurate and reproducible method for CTC molecular analysis, the clinical relevance of biomarkers, including gain of HER2 on CTC after HER2 negative primary breast cancer, remains uncertain. This review summarises the currently available data relating to biomarker evaluation on CTCs and its role in directing management in metastatic breast cancer, discusses limitations, and outlines measures that may enable future development of this approach.

  14. Chromosomal aberrations and SCEs as biomarkers of cancer risk

    Czech Academy of Sciences Publication Activity Database

    Norppa, H.; Bonassi, S.; Hansteen, I. L.; Hagmar, L.; Strömberg, U.; Rössner st., Pavel; Boffetta, P.; Lindholm, C.; Gundy, S.; Lazutka, J.; Cebulska-Wasilewska, A.; Fabiánová, E.; Šrám, Radim; Knudsen, L. E.; Barale, R.; Fucic, A.

    2006-01-01

    Roč. 600, - (2006), s. 37-45. ISSN 0027-5107 Institutional research plan: CEZ:AV0Z50390512 Keywords : biomarkers * chromosomal aberration * sister chromatid exchange Subject RIV: DN - Health Impact of the Environment Quality Impact factor: 4.111, year: 2006

  15. Current Challenges in Development of Differentially Expressed and Prognostic Prostate Cancer Biomarkers

    Directory of Open Access Journals (Sweden)

    Steven M. Lucas

    2012-01-01

    Full Text Available Introduction. Predicting the aggressiveness of prostate cancer at biopsy is invaluable in making treatment decisions. In this paper we review the differential expression of genes and microRNAs identified through microarray analysis as potentially useful markers for prostate cancer prognosis and discuss some of the challenges associated with their development. Methods. A review of the literature was conducted through Medline. Articles were identified through searches of the following terms: “prostate cancer AND differential expression”, “prostate cancer prognosis”, and “prostate cancer AND microRNAs”. Results. Though numerous differentially expressed genes and microRNAs were identified as possible prognostic markers, the significance of several of these genes is either debated due to conflicting results or is not validated in other study populations. A few of the articles constructed predictive nomograms using a panel of biomarkers which require further validation. Challenges to the development of useful markers include different methodology, cancer heterogeneity, and sampling error. These can be overcome by categorizing prognostic factors into particular gene pathways or by supplementing biopsy information with blood or urine-based biomarkers. Conclusion. Though biomarkers based on differential expression offer the potential to improve decision making concerning prostate cancer, further validation of their utility and accuracy at the biopsy level is needed.

  16. Exercise, weight loss and biomarkers for breast cancer risk

    OpenAIRE

    Gemert, W.A.M. van

    2015-01-01

    Background: Postmenopausal breast cancer is the most prevalent cancer in Western women. There are several known risk factors for postmenopausal breast cancer of which few are lifestyle-related and, thereby, modifiable. These risk factors provide an opportunity for primary prevention. In this thesis, we estimated that one out of four (25.7%) breast cancer cases in the Dutch female population of >40 years is attributable to lifestyle, i.e., overweight/obesity, physical inactivity, alcohol consu...

  17. Altered Endosome Biogenesis in Prostate Cancer has Biomarker Potential

    OpenAIRE

    Johnson, Ian R D; Parkinson-Lawrence, Emma J.; Shandala, Tetyana; Weigert, Roberto; Lisa M Butler; Brooks, Doug A.

    2014-01-01

    Prostate cancer is the second most common form of cancer in males, affecting one in eight men by the time they reach the age of 70. Current diagnostic tests for prostate cancer have significant problems with both false negatives and false positives, necessitating the search for new molecular markers. A recent investigation of endosomal and lysosomal proteins revealed that the critical process of endosomal biogenesis might be altered in prostate cancer. Here, a panel of endosomal markers was e...

  18. Molecular biomarker set for early detection of ovarian cancer

    KAUST Repository

    Bajic, Vladimir B.

    2015-06-16

    Embodiments of the present invention concern methods and compositions related to detection of ovarian cancer, including detection of the stage of ovarian cancer, in some cases. In particular, the invention encompasses use of expression of TFAP2A and in some embodiments CA125 and/or E2F5 to identify ovarian cancer, including detecting mRNA and/or protein levels of the respective gene products. Kits for detection of ovarian cancer are also described.

  19. Phosphoprotein Secretome of Tumor Cells as a Source of Candidates for Breast Cancer Biomarkers in Plasma*

    OpenAIRE

    Zawadzka, Anna M.; Schilling, Birgit; Cusack, Michael P.; Sahu, Alexandria K.; Drake, Penelope; Fisher, Susan J.; Benz, Christopher C.; Gibson, Bradford W.

    2014-01-01

    Breast cancer is a heterogeneous disease whose molecular diversity is not well reflected in clinical and pathological markers used for prognosis and treatment selection. As tumor cells secrete proteins into the extracellular environment, some of these proteins reach circulation and could become suitable biomarkers for improving diagnosis or monitoring response to treatment. As many signaling pathways and interaction networks are altered in cancerous tissues by protein phosphorylation, changes...

  20. A Novel Electrochemical Microfluidic Chip Combined with Multiple Biomarkers for Early Diagnosis of Gastric Cancer

    Science.gov (United States)

    Xie, Yao; Zhi, Xiao; Su, Haichuan; Wang, Kan; Yan, Zhen; He, Nongyue; Zhang, Jingpu; Chen, Di; Cui, Daxiang

    2015-12-01

    Early diagnosis is very important to improve the survival rate of patients with gastric cancer and to understand the biology of cancer. In order to meet the clinical demands for early diagnosis of gastric cancer, we developed a disposable easy-to-use electrochemical microfluidic chip combined with multiple antibodies against six kinds of biomarkers (carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), Helicobacter pylori CagA protein (H.P.), P53oncoprotein (P53), pepsinogen I (PG I), and PG-II). The six kinds of biomarkers related to gastric cancer can be detected sensitively and synchronously in a short time. The specially designed three electrodes system enables cross-contamination to be avoided effectively. The linear ranges of detection of the electrochemical microfluidic chip were as follows: 0.37-90 ng mL-1 for CEA, 10.75-172 U mL-1 for CA19-9, 10-160 U L-1 for H.P., 35-560 ng mL-1 for P53, 37.5-600 ng mL-1 for PG I, and 2.5-80 ng mL-1for PG II. This method owns better sensitivity compared with enzyme-linked immunosorbent assay (ELISA) results of 394 specimens of gastric cancer sera. Furthermore, we established a multi-index prediction model based on the six kinds of biomarkers for predicting risk of gastric cancer. In conclusion, the electrochemical microfluidic chip for detecting multiple biomarkers has great potential in applications such as early screening of gastric cancer patients, and therapeutic evaluation, and real-time dynamic monitoring the progress of gastric cancer in near future.

  1. Evolving Role of Bone Biomarkers in Castration-Resistant Prostate Cancer1

    OpenAIRE

    Brown, Janet E.; Sim, Sheryl

    2010-01-01

    The preferential metastasis of prostate cancer cells to bone disrupts the process of bone remodeling and results in lesions that cause significant pain and patient morbidity. Although prostate-specific antigen (PSA) is an established biomarker in prostate cancer, it provides only limited information relating to bone metastases and the treatment of metastatic bone disease with bisphosphonates or novel noncytotoxic targeted or biological agents that may provide clinical benefits without affecti...

  2. Evolving Role of Bone Biomarkers in Castration-Resistant Prostate Cancer

    OpenAIRE

    Brown, Janet E.; Sheryl Sim

    2010-01-01

    The preferential metastasis of prostate cancer cells to bone disrupts the process of bone remodeling and results in lesions that cause significant pain and patient morbidity. Although prostate-specific antigen (PSA) is an established biomarker in prostate cancer, it provides only limited information relating to bone metastases and the treatment of metastatic bone disease with bisphosphonates or novel noncytotoxic targeted or biological agents that may provide clinical benefits without affecti...

  3. Body fluid MMP-2 as a putative biomarker in metastatic breast cancer

    OpenAIRE

    NOH, SEWON; Jung, Jae-Joon; Jung, Minkyu; KIM, KI-HYANG; Lee, Ha-young; WANG, BRANDON; CHO, JOANNA; Kim, Tae Soo; Jeung, Hei-Cheul; Rha, Sun Young

    2012-01-01

    In the present study, we investigated the role of matrix metalloproteinase (MMP)-2 and -9 as novel biomarkers in the body fluid of patients with metastatic breast cancer. We measured the expression of MMPs in 37 samples of body fluid (10 peritoneal and 27 pleural fluids) from metastatic breast cancer patients between 2000 and 2009. Zymography and ELISA assays were used to determine the cut-off level and to quantify MMP expression from a positive control, HT-1080 conditioned media. MMP express...

  4. Proteomic Serum Biomarkers and Their Potential Application in Cancer Screening Programs

    OpenAIRE

    Deelder, André M; Tollenaar, Rob A. E. M.; Mertens, Bart J.; Yuri E. M. van der Burgt; Anouck Huijbers; Tim J. A. Dekker; Wilma E. Mesker; Berit Velstra

    2010-01-01

    Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly use...

  5. Urinary high molecular weight matrix metalloproteinases as non-invasive biomarker for detection of bladder cancer

    OpenAIRE

    Mohammed, Mohammed A; Seleim, Manar F; Abdalla, Mohga S.; Sharada, Hayat M; Abdel Wahab, Abdel Hady A.

    2013-01-01

    Background Matrix Metalloproteinases (MMPs) are key molecules for tumor growth, invasion and metastasis. Over-expression of different MMPs in tumor tissues can disturb the homeostasis and increase the level of various body fluids. Many MMPs including high molecular weights (HMWs) were detected in the urine of prostate and bladder cancer patients. Our aim here is to assess the usefulness of HMW MMPs as non invasive biomarkers in bilharzial bladder cancer in Egyptian patients. Methods The activ...

  6. DNA Methylation in Peripheral Blood: A Potential Biomarker for Cancer Molecular Epidemiology

    OpenAIRE

    Li, Lian; Choi, Ji-Yeob; Lee, Kyoung-Mu; Sung, Hyuna; Park, Sue K; Oze, Isao; Pan, Kai-Feng; You, Wei-cheng; Chen, Ying-Xuan; Fang, Jing-Yuan; Matsuo, Keitaro; Kim, Woo Ho; Yuasa, Yasuhito; Kang, Daehee

    2012-01-01

    Aberrant DNA methylation is associated with cancer development and progression. There are several types of specimens from which DNA methylation pattern can be measured and evaluated as an indicator of disease status (from normal biological process to pathologic condition) and even of pharmacologic response to therapy. Blood-based specimens such as cell-free circulating nucleic acid and DNA extracted from leukocytes in peripheral blood may be a potential source of noninvasive cancer biomarkers...

  7. Non-invasive biomarkers in pancreatic cancer diagnosis: what we need versus what we have

    OpenAIRE

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-01-01

    Pancreatic cancer (PC) is probably the most lethal tumor being forecast as the second most fatal cancer by 2020 in developed countries. Only the earliest forms of the disease are a curable disease but it has to be diagnosed before symptoms starts. Detection at curable phase demands screening intervention for early detection and differential diagnosis. Unfortunately, no successful strategy or image technique has been concluded as effective approach and currently non-invasive biomarkers are the...

  8. Glypican-1 in exosomes as biomarker for early detection of pancreatic cancer

    OpenAIRE

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-01-01

    On June 24, 2015 Nature published an article entitle “Glypican-1 identifies cancer exosomes and detects early pancreatic cancer’’, which demonstrates that exosomes positives for the proteoglycan glypican-1 (GPC1) are expressed in serum of patients with pancreatic cancer since very early stages but not in benign pancreatic disease. Additionally, these GPC1+ circulating exosomes correlate with tumor burden and could be used as prognostic biomarker in pre and post-surgical patients. The study is...

  9. Can Prostate Specific Antigen Be Used as New Biomarker for Early Diagnosis of Breast Cancer?

    Directory of Open Access Journals (Sweden)

    Seyed Mostafa Shiryazdi

    2015-09-01

    Conclusion: Plasma PSA level is not a reliable biomarker to diagnose breast cancer, though regarding existing scientific evidence, more comprehensive studies are required to consider other features of malignant samples so as to evaluate the role of PSA in differentiating breast neoplastic lesions in a more meticulous way based on the degree of tumor differentiation.

  10. Global DNA hypomethylation in peripheral blood mononuclear cells as a biomarker of cancer risk

    Science.gov (United States)

    Global DNA hypomethylation is an early molecular event in carcinogenesis. Whether methylation measured in peripheral blood mononuclear cells (PBMCs) DNA is a clinically reliable biomarker for early detection or cancer risk assessment is to be established. From an original sample-set of 753 male and...

  11. Circulating microRNAs as specific biomarkers for breast cancer detection.

    Directory of Open Access Journals (Sweden)

    Enders K O Ng

    Full Text Available BACKGROUND: We previously showed microRNAs (miRNAs in plasma are potential biomarkers for colorectal cancer detection. Here, we aimed to develop specific blood-based miRNA assay for breast cancer detection. METHODOLOGY/PRINCIPAL FINDINGS: TaqMan-based miRNA profiling was performed in tumor, adjacent non-tumor, corresponding plasma from breast cancer patients, and plasma from matched healthy controls. All putative markers identified were verified in a training set of breast cancer patients. Selected markers were validated in a case-control cohort of 170 breast cancer patients, 100 controls, and 95 other types of cancers and then blindly validated in an independent set of 70 breast cancer patients and 50 healthy controls. Profiling results showed 8 miRNAs were concordantly up-regulated and 1 miRNA was concordantly down-regulated in both plasma and tumor tissue of breast cancer patients. Of the 8 up-regulated miRNAs, only 3 were significantly elevated (p<0.0001 before surgery and reduced after surgery in the training set. Results from the validation cohort showed that a combination of miR-145 and miR-451 was the best biomarker (p<0.0001 in discriminating breast cancer from healthy controls and all other types of cancers. In the blind validation, these plasma markers yielded Receiver Operating Characteristic (ROC curve area of 0.931. The positive predictive value was 88% and the negative predictive value was 92%. Altered levels of these miRNAs in plasma have been detected not only in advanced stages but also early stages of tumors. The positive predictive value for ductal carcinoma in situ (DCIS cases was 96%. CONCLUSIONS: These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening.

  12. Serum biomarkers reflecting specific tumor tissue remodeling processes are valuable diagnostic tools for lung cancer

    International Nuclear Information System (INIS)

    Extracellular matrix (ECM) proteins, such as collagen type I and elastin, and intermediate filament (IMF) proteins, such as vimentin are modified and dysregulated as part of the malignant changes leading to disruption of tissue homeostasis. Noninvasive biomarkers that reflect such changes may have a great potential for cancer. Levels of matrix metalloproteinase (MMP) generated fragments of type I collagen (C1M), of elastin (ELM), and of citrullinated vimentin (VICM) were measured in serum from patients with lung cancer (n = 40), gastrointestinal cancer (n = 25), prostate cancer (n = 14), malignant melanoma (n = 7), chronic obstructive pulmonary disease (COPD) (n = 13), and idiopathic pulmonary fibrosis (IPF) (n = 10), as well as in age-matched controls (n = 33). The area under the receiver operating characteristics (AUROC) was calculated and a diagnostic decision tree generated from specific cutoff values. C1M and VICM were significantly elevated in lung cancer patients as compared with healthy controls (AUROC = 0.98, P < 0.0001) and other cancers (AUROC = 0.83 P < 0.0001). A trend was detected when comparing lung cancer with COPD+IPF. No difference could be seen for ELM. Interestingly, C1M and VICM were able to identify patients with lung cancer with a positive predictive value of 0.9 and an odds ratio of 40 (95% CI = 8.7–186, P < 0.0001). Biomarkers specifically reflecting degradation of collagen type I and citrullinated vimentin are applicable for lung cancer patients. Our data indicate that biomarkers reflecting ECM and IMF protein dysregulation are highly applicable in the lung cancer setting. We speculate that these markers may aid in diagnosing and characterizing patients with lung cancer

  13. Fibroblasts from skin biopsies as a tool for biomarker discovery in Parkinson׳s disease.

    Science.gov (United States)

    Mastroberardino, Pier Giorgio; Ambrosi, Giulia; Blandini, Fabio; Milanese, Chiara; Sepe, Sara

    2014-10-01

    Parkinson׳s disease (PD) is a complex disease and the current interest and focus of scientific research is both investigating the variety of causes that underlie PD pathogenesis, and identifying reliable biomarkers to diagnose and monitor the progression of pathology. Investigation on pathogenic mechanisms in peripheral cells, such as fibroblasts derived from patients with sporadic PD and age/gender matched controls, might generate deeper understanding of the deficits affecting dopaminergic neurons and, possibly, new tools applicable to clinical practice. The chronic and slow progressing nature of PD may result from subtle yet persistent alterations in biological mechanisms, which might be undetectable in basal, unchallenged conditions. Unlike body fluids, dermal fibroblasts can be exposed to different challenges while in culture and can therefore generate information about the dynamic cellular responses to exogenous stressors. These studies may ultimately generate indicators highlighting the biological defects intrinsic to PD. In fact, fibroblasts from idiopathic PD patients' exhibit deficits typically sustaining the neurodegenerative process of PD, such as increased susceptibility to rotenone as well as deficits in protein homeostasis and mitochondrial bioenergetics Fibroblasts therefore represent a powerful and minimally invasive tool to investigate PD pathogenic mechanisms, which might translate into considerable advances in clinical management of the disease. PMID:26461279

  14. Current Challenges in Volatile Organic Compounds Analysis as Potential Biomarkers of Cancer

    Directory of Open Access Journals (Sweden)

    Kamila Schmidt

    2015-01-01

    Full Text Available An early diagnosis and appropriate treatment are crucial in reducing mortality among people suffering from cancer. There is a lack of characteristic early clinical symptoms in most forms of cancer, which highlights the importance of investigating new methods for its early detection. One of the most promising methods is the analysis of volatile organic compounds (VOCs. VOCs are a diverse group of carbon-based chemicals that are present in exhaled breath and biofluids and may be collected from the headspace of these matrices. Different patterns of VOCs have been correlated with various diseases, cancer among them. Studies have also shown that cancer cells in vitro produce or consume specific VOCs that can serve as potential biomarkers that differentiate them from noncancerous cells. This review identifies the current challenges in the investigation of VOCs as potential cancer biomarkers, by the critical evaluation of available matrices for the in vivo and in vitro approaches in this field and by comparison of the main extraction and detection techniques that have been applied to date in this area of study. It also summarises complementary in vivo, ex vivo, and in vitro studies conducted to date in order to try to identify volatile biomarkers of cancer.

  15. PET imaging biomarkers in head and neck cancer

    Energy Technology Data Exchange (ETDEWEB)

    Differding, Sarah; Gregoire, Vincent [Universite Catholique de Louvain, St-Luc University Hospital, Department of Radiation Oncology, and Center for Molecular Imaging, Radiotherapy and Oncology (MIRO), Institut de Recherche Experimentale et Clinique (IREC), Brussels (Belgium); Hanin, Francois-Xavier [Universite Catholique de Louvain, St-Luc University Hospital, Department of Nuclear Medicine, and Center for Molecular Imaging, Radiotherapy and Oncology (MIRO), Institut de Recherche Experimentale et Clinique (IREC), Brussels (Belgium)

    2015-04-01

    In locally advanced head and neck squamous cell carcinoma (HNSCC), the role of imaging becomes more and more critical in the management process. In this framework, molecular imaging techniques such as PET allow noninvasive assessment of a range of tumour biomarkers such as metabolism, hypoxia and proliferation, which can serve different purposes. First, in a pretreatment setting they can influence therapy selection strategies and target delineation for radiation therapy. Second, their predictive and/or prognostic value could help enhance the therapeutic ratio in the management of HNSCC. Third, treatment modification can be performed through the generation of a molecular-based heterogeneous dose distribution with dose escalation to the most resistant parts of the tumour, a concept known as dose painting. Fourth, they are increasingly becoming a tool for monitoring response to therapy. In this review, PET imaging biomarkers used in the routine management of HNSCC or under investigation are discussed. (orig.)

  16. AGR3 in Breast Cancer: Prognostic Impact and Suitable Serum-Based Biomarker for Early Cancer Detection

    Science.gov (United States)

    Garczyk, Stefan; von Stillfried, Saskia; Antonopoulos, Wiebke; Hartmann, Arndt; Schrauder, Michael G.; Fasching, Peter A.; Anzeneder, Tobias; Tannapfel, Andrea; Ergönenc, Yavuz; Knüchel, Ruth

    2015-01-01

    Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor α (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer. PMID:25875093

  17. Combined RASSF1A and RASSF2A Promoter Methylation Analysis as Diagnostic Biomarker for Bladder Cancer

    OpenAIRE

    Wei Meng; Alexander Huebner; Ahmad Shabsigh; Arnab Chakravarti; Tim Lautenschlaeger

    2012-01-01

    Promoter hypermethylation, a widely studied epigenetic event known to influence gene expression levels, has been proposed as a potential biomarker in multiple types of cancer. Clinical diagnostic biomarkers are needed for reliable prediction of bladder cancer recurrence. In this paper, DNA promoter methylation of five C-terminal Ras-association family members (RASSF1A, RASSF2A, RASSF4, RASSF5, and RASSF6) was studied in 64 formalin-fixed paraffin-embedded (FFPE) bladder cancer and normal adja...

  18. Non-invasive biomarkers in pancreatic cancer diagnosis: what we need versus what we have.

    Science.gov (United States)

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-04-01

    Pancreatic cancer (PC) is probably the most lethal tumor being forecast as the second most fatal cancer by 2020 in developed countries. Only the earliest forms of the disease are a curable disease but it has to be diagnosed before symptoms starts. Detection at curable phase demands screening intervention for early detection and differential diagnosis. Unfortunately, no successful strategy or image technique has been concluded as effective approach and currently non-invasive biomarkers are the hope. Multiple translational research studies have explored minimally or non-invasive biomarkers in biofluids-blood, urine, stool, saliva or pancreatic juice, but diagnostic performance has not been validated yet. Nowadays no biomarker, alone or in combination, has been superior to carbohydrate antigen 19-9 (CA19-9) in sensitivity and specificity. Although the number of novel biomarkers for early diagnosis of PC has been increasing during the last couple of years, no molecular signature is ready to be implemented in clinical routine. Under the uncertain future, miRNAs profiling and methylation status seem to be the most promising biomarkers. However, good results in larger validations are urgently needed before application. Industry efforts through biotech and pharmaceutical companies are urgently required to demonstrate accuracy and validate promising results from basic and translational results. PMID:27162784

  19. Amino acid profiling as a method of discovering biomarkers for early diagnosis of cancer.

    Science.gov (United States)

    Simińska, Edyta; Koba, Marcin

    2016-06-01

    Cancer is one of the main causes of mortality in the world and its early detection significantly increases chances of patients' survival. High cancer mortality rate is caused mainly by late-stage diagnosis and lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of cancers in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. Several recent researchers indicate amino acids as a potential marker for cancer detection. An ideal cancer biomarker should be characterized by high specificity and sensitivity, reliability, ease of measurement and, what is important, ability to detect disease in its early stage. This study is focused on indicating metabolic amino acid profiling as a method of identifying biomarkers for cancer early detection and screening. Presented results are derived from the most recent studies where patients in early, often asymptomatic stages of disease constituted a large percentage of all the patients and, what is important, where researchers have observed alterations in these patients' amino acid profiles. This review is concentrated on analyzing studies on the most common cancers with high mortality rate. Inventing effective methods of early diagnosis is particularly important in case of such diseases. Research presented in this publication is focused on patients with lung, breast and colon cancer. In all analyzed cases, significant changes in the amino acid profile in cancer patients comparing to healthy controls were observed. This study indicates potential of amino acid profiling as method for early cancer detection. PMID:27033065

  20. Top-down proteomics with mass spectrometry imaging: a pilot study towards discovery of biomarkers for neurodevelopmental disorders.

    Directory of Open Access Journals (Sweden)

    Hui Ye

    Full Text Available In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI. Our goal was to study changes in protein expression in postnatal day 10 (P10 rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801. Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19, cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers.

  1. Fucose: A biomarker in grading of oral cancer

    OpenAIRE

    Kumar, Satish; Saxena, Mona; Srinivas, Kandakurtis; Singh, Vinod Kumar

    2015-01-01

    Introduction: Early diagnosis of cancer helps a great deal in the management of oral cancer patients. Number of proteinous markers have been employed for this purpose. Majority of them are not specific. Recently conjugated oligosaccharide with proteins and lipids have gained considerable importance in the present postgenomics and postproteomic period in the diagnostic and prognostics of cancer cases. Materials and Methods: In this study, serum fucose levels were estimated in 50 control cases ...

  2. Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies

    International Nuclear Information System (INIS)

    Head and neck squamous cell carcinoma (HNSCC) remains a challenging cancer to treat with overall 5-year survival on the order of 50–60%. Therefore, predictive biomarkers for this disease would be valuable to provide more effective and individualized therapeutic approaches for these patients. While prognostic biomarkers such as p16 expression correlate with outcome; to date, no predictive biomarkers have been clinically validated for HNSCC. We generated xenografts in immunocompromised mice from six established HNSCC cell lines and evaluated response to cisplatin, cetuximab, and radiation. Tissue microarrays were constructed from pre- and posttreatment tumor samples derived from each xenograft experiment. Quantitative immunohistochemistry was performed using a semiautomated imaging and analysis platform to determine the relative expression of five potential predictive biomarkers: epidermal growth factor receptor (EGFR), phospho-EGFR, phospho-Akt, phospho-ERK, and excision repair cross-complementation group 1 (ERCC1). Biomarker levels were compared between xenografts that were sensitive versus resistant to a specific therapy utilizing a two-sample t-test with equal standard deviations. Indeed the xenografts displayed heterogeneous responses to each treatment, and we linked a number of baseline biomarker levels to response. This included low ERCC1 being associated with cisplatin sensitivity, low phospho-Akt correlated with cetuximab sensitivity, and high total EGFR was related to radiation resistance. Overall, we developed a systematic approach to identifying predictive biomarkers and demonstrated several connections between biomarker levels and treatment response. Despite these promising initial results, this work requires additional preclinical validation, likely involving the use of patient-derived xenografts, prior to moving into the clinical realm for confirmation among patients with HNSCC

  3. A meta analysis of pancreatic microarray datasets yields new targets as cancer genes and biomarkers.

    Directory of Open Access Journals (Sweden)

    Nalin C W Goonesekere

    Full Text Available The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC, which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.

  4. Collections of simultaneously altered genes as biomarkers of cancer cell drug response.

    Science.gov (United States)

    Masica, David L; Karchin, Rachel

    2013-03-15

    Computational analysis of cancer pharmacogenomics data has resulted in biomarkers predictive of drug response, but the majority of response is not captured by current methods. Methods typically select single biomarkers or groups of related biomarkers but do not account for response that is strictly dependent on many simultaneous genetic alterations. This shortcoming reflects the combinatorics and multiple-testing problem associated with many-body biologic interactions. We developed a novel approach, Multivariate Organization of Combinatorial Alterations (MOCA), to partially address these challenges. Extending on previous work that accounts for pairwise interactions, the approach rapidly combines many genomic alterations into biomarkers of drug response, using Boolean set operations coupled with optimization; in this framework, the union, intersection, and difference Boolean set operations are proxies of molecular redundancy, synergy, and resistance, respectively. The algorithm is fast, broadly applicable to cancer genomics data, is of immediate use for prioritizing cancer pharmacogenomics experiments, and recovers known clinical findings without bias. Furthermore, the results presented here connect many important, previously isolated observations. PMID:23338612

  5. Serial Patterns of Ovarian Cancer Biomarkers in a Prediagnosis Longitudinal Dataset

    Directory of Open Access Journals (Sweden)

    Oleg Blyuss

    2015-01-01

    Full Text Available Early detection of ovarian cancer through screening may have impact on mortality from the disease. Approaches based on CA125 cut-off have not been effective. Longitudinal algorithms such as the Risk of Ovarian Cancer Algorithm (ROCA to interpret CA125 have been shown to have higher sensitivity and specificity than a single cut-off. The aim of this study was to investigate whether other ovarian cancer-related biomarkers, Human Epididymis 4 (HE4, glycodelin, mesothelin, matrix metalloproteinase 7 (MMP7, and cytokeratin 19 fragment (CYFRA 21-1, could improve the performance of CA125 in detecting ovarian cancer earlier. Serum samples (single and serial predating diagnosis from 47 women taking part in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS who went on to develop primary invasive ovarian, fallopian tube, or peritoneal cancer (index cancer (170 samples and 179 matched controls (893 samples were included in the study. A multiplex immunobased assay platform (Becton Dickinson allowing simultaneous measurement of the six serum markers was used. The area under the ROC curve for the panel of three biomarkers (CA125, HE4, and glycodelin was higher than for CA125 alone for all analysed time groups, indicating that these markers can improve on sensitivity of CA125 alone for ovarian cancer detection.

  6. The Progress and Prospects of Putative Biomarkers for Liver Cancer Stem Cells in Hepatocellular Carcinoma.

    Science.gov (United States)

    Xiang, Yan; Yang, Ting; Pang, Bing-Yao; Zhu, Ying; Liu, Yong-Ning

    2016-01-01

    Accumulating evidence suggests that hepatocellular carcinoma (HCC) is organized by liver cancer stem cells (LCSCs), which are a subset of cells with "stem-like" characteristics. Identification of the LCSCs is a fundamental and important problem in HCC research. LCSCs have been investigated by various stem cell biomarkers. There is still lack of consensus regarding the existence of a "global" marker for LCSCs in HCC. In this review article, we summarize the progress and prospects of putative biomarkers for LCSCs in the past decades, which is essential to develop future therapies targeting CSCs and to predict prognosis and curative effect of these therapies. PMID:27610139

  7. Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2011-02-01

    Full Text Available Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms. Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

  8. Investigation of prostate cancer cells using NADH and Tryptophan as biomarker: multiphoton FLIM-FRET microscopy

    Science.gov (United States)

    Rehman, Shagufta; O'Melia, Meghan J.; Wallrabe, Horst; Svindrych, Zdenek; Chandra, Dhyan; Periasamy, Ammasi

    2016-03-01

    Fluorescence Lifetime Imaging (FLIM) can be used to understand the metabolic activity in cancer. Prostate cancer is one of the leading cancers in men in the USA. This research focuses on FLIM measurements of NAD(P)H and Tryptophan, used as biomarkers to understand the metabolic activity in prostate cancer cells. Two prostate cancers and one normal cell line were used for live-cell FLIM measurements on Zeiss780 2P confocal microscope with SPCM FLIM board. Glucose uptake and glycolysis proceeds about ten times faster in cancer than in non-cancerous tissues. Therefore, we assessed the glycolytic activity in the prostate cancer in comparison to the normal cells upon glucose stimulation by analyzing the NAD(P)H and Trp lifetime distribution and efficiency of energy transfer (E%). Furthermore, we treated the prostate cancer cells with 1μM Doxorubicin, a commonly used anti-cancer chemotherapeutic. Increase in NADH a2%, an indicator of increased glycolysis and increased E% between Trp and NAD(P)H were seen upon glucose stimulation for 30min. The magnitude of shift to the right for NAD(P)H a2% and E% distribution was higher in prostate cancer versus the normal cells. Upon treatment with Doxorubicin decrease in cellular metabolism was seen at 15 and 30 minutes. The histogram for NAD(P)H a2% post-treatment for prostate cancer cells showed a left shift compared to the untreated control suggesting decrease in glycolysis and metabolic activity opposite to what was observed after glucose stimulation. Hence, NAD(P)H and Trp lifetimes can be used biomarkers to understand metabolic activity in prostate cancer and upon chemotherapeutic interventions.

  9. DNA methylome and the complexity of discovering prostate cancer biomarkers

    Institute of Scientific and Technical Information of China (English)

    Shahriar Koochekpour

    2011-01-01

    @@ Prostate cancer (PCa) remains the most common malignancy and a leading cause of cancer-related deaths in men.Molecular discrimination at an early stage between indolent and aggressive primary tumors in pathologically confirmed PCa is required to develop personalized therapeutic interventions.

  10. Multi-transcript profiling in archival diagnostic prostate cancer needle biopsies to evaluate biomarkers in non-surgically treated men

    OpenAIRE

    Kachroo, Naveen; Warren, Anne Y; Gnanapragasam, Vincent J.

    2014-01-01

    Background Most biomarkers in prostate cancer have only been evaluated in surgical cohorts. The value of these biomarkers in a different therapy context remains unclear. Our objective was to test a panel of surgical biomarkers for prognostic value in men treated by external beam radiotherapy (EBRT) and primary androgen deprivation therapy (PADT). Methods The Fluidigm® PCR array was used for multi-transcript profiling of laser microdissected tumours from archival formalin-fixed diagnostic biop...

  11. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.

    Directory of Open Access Journals (Sweden)

    Elena Pereira

    Full Text Available High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential

  12. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

    Science.gov (United States)

    Anand, Sanya; Sebra, Robert; Catalina Camacho, Sandra; Garnar-Wortzel, Leopold; Nair, Navya; Moshier, Erin; Wooten, Melissa; Uzilov, Andrew; Chen, Rong; Prasad-Hayes, Monica; Zakashansky, Konstantin; Beddoe, Ann Marie; Schadt, Eric; Dottino, Peter; Martignetti, John A.

    2015-01-01

    Background High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. Methods and Findings Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. Conclusions Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic

  13. MicroRNA-18a as a promising biomarker for cancer detection: a meta-analysis

    OpenAIRE

    Jin, Shan; Tan, Shi-Sheng; Li, Hang

    2015-01-01

    Patients with cancer discovered at an early stage have relatively high survival rates. Increasing researches have shown the potential of detecting dysregulated microRNA-18a (miR-18a) to diagnose cancer. However, non-uniform results in previous studies were found. Thus, this meta-analysis was conducted to further explore the clinical applicability of miR-18a as an ideal biomarker for cancer detection. Suitable articles were obtained from online databases like PubMed, Embase, Cochrane, CBM and ...

  14. Potentials of plasma NGAL and MIC-1 as biomarker(s in the diagnosis of lethal pancreatic cancer.

    Directory of Open Access Journals (Sweden)

    Sukhwinder Kaur

    Full Text Available Pancreatic cancer (PC is lethal malignancy with very high mortality rate. Absence of sensitive and specific marker(s is one of the major factors for poor prognosis of PC patients. In pilot studies using small set of patients, secreted acute phase proteins neutrophil gelatinase associated lipocalin (NGAL and TGF-β family member macrophage inhibitory cytokine-1 (MIC-1 are proposed as most potential biomarkers specifically elevated in the blood of PC patients. However, their performance as diagnostic markers for PC, particularly in pre-treatment patients, remains unknown. In order to evaluate the diagnostic efficacy of NGAL and MIC-1, their levels were measured in plasma samples from patients with pre-treatment PC patients (n = 91 and compared it with those in healthy control (HC individuals (n = 24 and patients with chronic pancreatitis (CP, n = 23. The diagnostic performance of these two proteins was further compared with that of CA19-9, a tumor marker commonly used to follow PC progression. The levels of all three biomarkers were significantly higher in PC compared to HCs. The mean (± standard deviation, SD plasma NGAL, CA19-9 and MIC-1 levels in PC patients was 111.1 ng/mL (2.2, 219.2 U/mL (7.8 and 4.5 ng/mL (4.1, respectively. In comparing resectable PC to healthy patients, all three biomarkers were found to have comparable sensitivities (between 64%-81% but CA19-9 and NGAL had a higher specificity (92% and 88%, respectively. For distinguishing resectable PC from CP patients, CA19-9 and MIC-1 were most specific (74% and 78% respectively. CA19-9 at an optimal cut-off of 54.1 U/ml is highly specific in differentiating resectable (stage 1/2 pancreatic cancer patients from controls in comparison to its clinical cut-off (37.1 U/ml. Notably, the addition of MIC-1 to CA19-9 significantly improved the ability to distinguish resectable PC cases from CP (p = 0.029. Overall, MIC-1 in combination with CA19-9 improved the diagnostic

  15. AGE metabolites: a biomarker linked to cancer disparity?

    Science.gov (United States)

    Foster, Dion; Spruill, Laura; Walter, Katherine R; Nogueira, Lourdes M; Fedarovich, Hleb; Turner, Ryan Y; Ahmed, Mahtabuddin; Salley, Judith D; Ford, Marvella E; Findlay, Victoria J; Turner, David P

    2014-10-01

    Socioeconomic and environmental influences are established factors promoting cancer disparity, but the contribution of biologic factors is not clear. We report a mechanistic link between carbohydrate-derived metabolites and cancer that may provide a biologic consequence of established factors of cancer disparity. Glycation is the nonenzymatic glycosylation of carbohydrates to macromolecules, which produces reactive metabolites called advanced glycation end products (AGE). A sedentary lifestyle and poor diet all promote disease and the AGE accumulation pool in our bodies and also increase cancer risk. We examined AGE metabolites in clinical specimens of African American and European American patients with prostate cancer and found a higher AGE concentration in these specimens among African American patients when compared with European American patients. Elevated AGE levels corresponded with expression of the receptor for AGE (RAGE or AGER). We show that AGE-mediated increases in cancer-associated processes are dependent upon RAGE. Aberrant AGE accumulation may represent a metabolic susceptibility difference that contributes to cancer disparity. PMID:25053712

  16. Improved protein sequence coverage by on resin deglycosylation and cysteine modification for biomarker discovery.

    Science.gov (United States)

    Kamada, Haruhiko; Fugmann, Tim; Neri, Dario; Roesli, Christoph

    2009-02-01

    Membrane proteins and secreted factors (soluble proteins or extracellular matrix components) are the targets of most monoclonal antibodies, which are currently in clinical development. These proteins are frequently post-translationally modified, e.g. by the formation of disulfide bonds or by glycosylation, which complicates their identification using proteomics technologies. Here, we describe a novel methodology for the on resin deglycosylation and cysteine modification of proteins after in vitro, in vivo or ex vivo biotinylation. Biotinylated proteins are captured on streptavidin resin and all subsequent modifications, as well as the proteolytic digestion, which yields peptides for MS analysis, are performed on resin. Using biotinylated bovine fetuin-A as a test protein, an improvement in sequence coverage from 7.9 to 58.7% could be shown, including the identification of all three glycosylation sites. Furthermore, a complex mixture derived from the ex vivo biotinylation of vascular structures in human kidney with cancer obtained by perfusion after surgical resection revealed almost a doubling of sequence coverage for all checked proteins when analyzed by LC-MALDI TOF/TOF. PMID:19137555

  17. Molecular profiling of childhood cancer: Biomarkers and novel therapies

    Directory of Open Access Journals (Sweden)

    Federica Saletta

    2014-06-01

    General significance: The increasing recognition of the heterogeneity of molecular causes of cancer favors the continued development of molecularly targeted agents, and their transfer to pediatric and adolescent populations.

  18. Argonaute proteins: potential biomarkers for human colon cancer

    International Nuclear Information System (INIS)

    Although Argonaute proteins are considered to play important roles in stem cell self-renewal, RNA interference (RNAi) and translational regulation, relatively little is known about their functions in human disease. In this study, we investigated the expression of eight members of human Argonaute family in colon cancer and identified their potential roles in tumor development and progression. Antibodies against human Argonaute proteins were prepared by immunizing rabbits with synthetic peptides derived from the sequences of Argonaute members. Then we constructed a tissue microarray containing 75 specimens from colon cancer and 75 specimens from adjacent non-cancer tissue, and assayed eight different proteins (EIF2C1, EIF2C2, EIF2C3, EIF2C4, PIWIL1, PIWIL2, PIWIL3 and PIWIL4) by immunohistochemistry on consecutive formalin-fixed tissue microarray sections. The expression of EIF2C1-4 and PIWIL1-4 was significantly higher in tumorous tissue than in adjacent tissue. Notably, a significant correlation was observed between the positive expression of EIF2C2, EIF2C3, EIF2C4, PIWIL4 and the presence of distant metastasis. Logistic regression analysis revealed that an increased expression of EIF2C1 and PIWIL2 was significantly associated with occurrence of colon cancer tissue compared with non-cancer tissue. Argonaute proteins are overexpressed in colon cancer relative to adjacent non-cancer tissue. The expression of EIF2C2-4 and PIWIL4 appears increased in advanced tumors with distant metastasis, suggesting it may promote tumor invasion. Furthermore, EIF2C1 and PIWIL2 might represent novel colon cancer markers with early diagnostic significance

  19. Hereditary Colorectal Cancer: Registration, Screening and Prognostic Biomarker Analysis

    OpenAIRE

    Barrow, Paul

    2015-01-01

    Aims: The purpose of the research was to investigate the benefits of a hereditary colorectal cancer registry in the management of patients and families with Lynch syndrome. In study one, a systematic review was performed to quantify the impact of registration and screening on colorectal cancer (CRC) incidence and mortality, with comparison between familial adenomatous polyposis (FAP) and Lynch syndrome (LS). In study two, a regional Lynch syndrome registry was utilised to evaluate the uptake ...

  20. ellipsoidFN: a tool for identifying a heterogeneous set of cancer biomarkers based on gene expressions.

    Science.gov (United States)

    Ren, Xianwen; Wang, Yong; Chen, Luonan; Zhang, Xiang-Sun; Jin, Qi

    2013-02-01

    Computationally identifying effective biomarkers for cancers from gene expression profiles is an important and challenging task. The challenge lies in the complicated pathogenesis of cancers that often involve the dysfunction of many genes and regulatory interactions. Thus, sophisticated classification model is in pressing need. In this study, we proposed an efficient approach, called ellipsoidFN (ellipsoid Feature Net), to model the disease complexity by ellipsoids and seek a set of heterogeneous biomarkers. Our approach achieves a non-linear classification scheme for the mixed samples by the ellipsoid concept, and at the same time uses a linear programming framework to efficiently select biomarkers from high-dimensional space. ellipsoidFN reduces the redundancy and improves the complementariness between the identified biomarkers, thus significantly enhancing the distinctiveness between cancers and normal samples, and even between cancer types. Numerical evaluation on real prostate cancer, breast cancer and leukemia gene expression datasets suggested that ellipsoidFN outperforms the state-of-the-art biomarker identification methods, and it can serve as a useful tool for cancer biomarker identification in the future. The Matlab code of ellipsoidFN is freely available from http://doc.aporc.org/wiki/EllipsoidFN. PMID:23262226

  1. miRNAs as potential biomarkers in early breast cancer detection following mammography.

    Science.gov (United States)

    Fu, Sidney W; Lee, Woojin; Coffey, Caitrin; Lean, Alexa; Wu, Xiaoling; Tan, Xiaohui; Man, Yan-Gao; Brem, Rachel F

    2016-01-01

    Breast cancer is the most common cancer among American women, except for skin cancers. About 12 % women in the United States will develop invasive breast cancer during their lifetime. Currently one of the most accepted model/theories is that ductal breast cancer (most common type of breast cancer) follows a linear progression: from normal breast epithelial cells to ductal hyperplasia to atypical ductal hyperplasia (ADH) to ductal carcinoma in situ (DCIS), and finally to invasive ductal carcinoma (IDC). Distinguishing pure ADH diagnosis from DCIS and/or IDC on mammography, and even combined with follow-up core needle biopsy (CNB) is still a challenge. Therefore subsequent surgical excision cannot be avoided to make a definitive diagnosis. MicroRNAs (miRNAs) are a highly abundant class of endogenous non-coding RNAs, which contribute to cancer initiation and progression, and are differentially expressed between normal and cancer tissues. They can function as either tumor suppressors or oncogenes. With accumulating evidence of the role of miRNAs in breast cancer progression, including our own studies, we sought to summarize the nature of early breast lesions and the potential use of miRNA molecules as biomarkers in early breast cancer detection. In particular, miRNA biomarkers may potentially serve as a companion tool following mammography screening and CNB. In the long-term, a better understanding of the molecular mechanisms underlying the miRNA signatures associated with breast cancer development could potentially result in the development of novel strategies for disease prevention and therapy. PMID:26819702

  2. Serum Amyloid A (SAA): a Novel Biomarker for Endometrial Cancer

    Science.gov (United States)

    Cocco, Emiliano; Bellone, Stefania; El-Sahwi, Karim; Cargnelutti, Marilisa; Buza, Natalia; Tavassoli, Fattaneh A.; Schwartz, Peter E.; Rutherford, Thomas J.; Pecorelli, Sergio; Santin, Alessandro D.

    2009-01-01

    Background We investigated the expression of Serum-Amyloid-A (SAA) in endometrial endometrioid carcinoma (EEC), and evaluated its potential as a serum biomarker. Methods SAA gene and protein expression levels were evaluated in EEC and normal endometrial tissues (NEC), by real time-PCR, immunohistochemistry (IHC) and flow cytometry. SAA concentration in 194 serum samples from 50 healthy-women, 42 women with benign diseases and 102 patients including 49 grade-1, 38 grade-2 and 15 grade-3 EEC was also studied by a sensitive bead-based-immunoassay. Results SAA gene expression levels were significantly higher in EEC when compared to NEC (mean-copy-number by RT-PCR = 182 vs 1.9; P=0.001). IHC revealed diffuse cytoplasmic SAA protein staining in poorly differentiated EEC tissues. High intracellular levels of SAA were identified in primary EEC cell lines evaluated by flow cytometry and SAA was found to be actively secreted in vitro. SAA concentrations (μg/ml) had medians of 6.0 in normal healthy females and 6.0 in patients with benign disease (P=0.92). In contrast, SAA values in the serum of EEC patients had a median of 23.7 significantly higher than those of the healthy group (P=0.001) and benign group (P=0.001). Patients harboring G3 EEC were found to have SAA concentrations significantly higher than G1/G2 patients. Conclusions SAA is not only a liver-secreted-protein but is also an EEC-cell product. SAA is expressed and actively secreted by G3-EEC and it is present in high concentration in the serum of EEC patients. SAA may represent a novel biomarker for EEC to monitor disease recurrence and response to therapy. PMID:20041483

  3. Identification of carboxyl terminal peptide of Fibrinogen as a potential serum biomarker for gastric cancer.

    Science.gov (United States)

    Wu, Cheng; Luo, Zhiwen; Tang, Dan; Liu, Lijie; Yao, Dingkang; Zhu, Liang; Wang, Zhiqiang

    2016-05-01

    Gastric cancer (GC) is a very common disease worldwide where new serum biomarkers are urgently needed to improve their early diagnosis. In this study, we aim to search for the potential serum protein/peptide biomarkers of GC by using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). We first obtained the serum protein/peptide profiles from a training dataset including 30 patients with GC, 16 cases with chronic benign gastric disease (CGD), and 30 normal controls (CON) where 15 protein peaks were identified to exhibit the obvious deviation (P CGD, and CON analyzed by Biomarker Wizard 3.1 software with three protein peaks with mass-to-charge (m/z) ratio 5910, 5342, and 6439 further confirmed in the validation dataset. Among the three protein peaks, peak 5910 displayed the most significantly different which could distinguish GC patients from CGD and CON with a sensitivity of 86.3 %, a specificity of 91.3 %, and the area under the receiver operating characteristic curve (AUC) of 0.89 by using the optimal cutoff value of 17.3. We further identified peak 5910 as the carboxyl terminal fraction of Fibrinogen α by LC-MS and validated its identity by antiserum-mediated SELDI-based immunodepletion assays. In sum, SELDI-TOF-MS method could effectively generate serum peptidome in cancer patients and provide a new approach to identify potentially diagnostic and prognostic biomarkers for cancer. The carboxyl terminal fraction of Fibrinogen α may be a potential serological biomarker for GC diagnosis. PMID:26662807

  4. Exploring the role of molecular biomarkers as a potential weapon against gastric cancer: A review of the literature

    Science.gov (United States)

    Matboli, Marwa; El-Nakeep, Sarah; Hossam, Nourhan; Habieb, Alaa; Azazy, Ahmed E M; Ebrahim, Ali E; Nagy, Ziad; Abdel-Rahman, Omar

    2016-01-01

    Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management.

  5. Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening

    Science.gov (United States)

    Williams, Alex C.; Hitt, Austin; Voisin, Sophie; Tourassi, Georgia

    2013-03-01

    The biological concept of bilateral symmetry as a marker of developmental stability and good health is well established. Although most individuals deviate slightly from perfect symmetry, humans are essentially considered bilaterally symmetrical. Consequently, increased fluctuating asymmetry of paired structures could be an indicator of disease. There are several published studies linking bilateral breast size asymmetry with increased breast cancer risk. These studies were based on radiologists' manual measurements of breast size from mammographic images. We aim to develop a computerized technique to assess fluctuating breast volume asymmetry in screening mammograms and investigate whether it correlates with the presence of breast cancer. Using a large database of screening mammograms with known ground truth we applied automated breast region segmentation and automated breast size measurements in CC and MLO views using three well established methods. All three methods confirmed that indeed patients with breast cancer have statistically significantly higher fluctuating asymmetry of their breast volumes. However, statistically significant difference between patients with cancer and benign lesions was observed only for the MLO views. The study suggests that automated assessment of global bilateral asymmetry could serve as a breast cancer risk biomarker for women undergoing mammographic screening. Such biomarker could be used to alert radiologists or computer-assisted detection (CAD) systems to exercise increased vigilance if higher than normal cancer risk is suspected.

  6. Composite Biomarkers For Non-invasive Screening, Diagnosis And Prognosis Of Colorectal Cancer

    KAUST Repository

    Mansour, Hicham

    2014-09-11

    The present invention concerns particular biomarkers for diagnosing and/or prognosticating colorectal cancer, in particular in a non-invasive manner. The methods and compositions concern analysis of methylation patterns of one or more genes from a set of 29 genes identified as described herein. In certain embodiments, the gene set includes at least P15.INK4b, SST, GAS7, CNRIP1, and PIK3CG.

  7. Osteopontin is a prognostic biomarker in non-small cell lung cancer

    OpenAIRE

    Rud, Ane Kristine Kongsgaard; Pedersen, Kjetil Boye; Øijordsbakken, Miriam; Lund-Iversen, Marius; Halvorsen, Ann Rita; Solberg, Steinar; Berge, Gisle; Helland, Åslaug; Brustugun, Odd Terje; Mælandsmo, Gunhild

    2013-01-01

    Background: In a previously published report we characterized the expression of the metastasis-associated proteins S100A4, osteopontin (OPN) and ephrin-A1 in a prospectively collected panel of non-small cell lung cancer (NSCLC) tumors. The aim of the present follow-up study was to investigate the prognostic impact of these potential biomarkers in the same patient cohort. In addition, circulating serum levels of OPN were measured and single nucleotide polymorphisms (SNP) in the −44...

  8. Tissue Biomarkers in Prognostication of Serous Ovarian Cancer following Neoadjuvant Chemotherapy

    OpenAIRE

    Binny Khandakar; Sandeep R Mathur; Lalit Kumar; Sunesh Kumar; Siddhartha Datta Gupta; Venkateswaran K Iyer; Kalaivani, M.

    2014-01-01

    Serous ovarian cancer (SOC) is a significant cause of morbidity and mortality in females with poor prognosis because of advanced stage at presentation. Recently, neoadjuvant chemotherapy (NACT) is being used for management of advanced SOC, but role of tissue biomarkers in prognostication following NACT is not well established. The study was conducted on advanced stage SOC patients (n = 100) that were treated either conventionally (n = 50) or with NACT (n = 50), followed by surgery. In order t...

  9. Radiotherapy diagnostic biomarkers in radioresistant human H460 lung cancer stem-like cells

    OpenAIRE

    Yun, Hong Shik; Baek, Jeong-Hwa; Yim, Ji-Hye; Um, Hong-Duck; Park, Jong Kuk; Song, Jie-Young; Park, In-Chul; KIM, JAE-SUNG; Lee, Su-Jae; Lee, Chang-Woo; Hwang, Sang-Gu

    2016-01-01

    ABSTRACT Tumor cell radioresistance is a major contributor to radiotherapy failure, highlighting the importance of identifying predictive biomarkers for radioresistance. In this work, we established a radioresistant H460 (RR-H460) cell line from parental radiosensitive H460 lung cancer cells by exposure to fractionated radiation. The radiation-resistant, anti-apoptotic phenotype of RR-H460 cell lines was confirmed by their enhanced clonogenic survival and increased expression of the radioresi...

  10. Biomarkers of endometrial cancer and related gynaecological malignancies

    NARCIS (Netherlands)

    Seeber, L.M.S.

    2010-01-01

    In the Western World, endometrial cancer is the most common malignancy of the female genital tract. Endometrioid endometrial carcinoma (EEC or Type I tumour), accounts for approximately 75% of cases. Type II tumours, of which uterine papillary serous carcinoma (UPSC) is the most common subtype, are

  11. Systematic review and meta-analysis of tumor biomarkers in predicting prognosis in esophageal cancer

    International Nuclear Information System (INIS)

    Esophageal cancer (EC) is a frequently occurring cancer with poor prognosis despite combined therapeutic strategies. Many biomarkers have been proposed as predictors of adverse events. We sought to assess the prognostic value of biomarkers in predicting the overall survival of esophageal cancer and to help guide personalized cancer treatment to give patients the best chance at remission. We conducted a systematic review and meta-analysis of the published literature to summarize evidence for the discriminatory ability of prognostic biomarkers for esophageal cancer. Relevant literature was identified using the PubMed database on April 11, 2012, and conformed to the REMARK criteria. The primary endpoint was overall survival and data were synthesized with hazard ratios (HRs). We included 109 studies, exploring 13 different biomarkers, which were subjected to quantitative meta-analysis. Promising markers that emerged for the prediction of overall survival in esophageal squamous cell cancer included VEGF (18 eligible studies, n = 1476, HR = 1.85, 95% CI, 1.55-2.21), cyclin D1 (12 eligible studies, n = 1476, HR = 1.82, 95% CI, 1.50-2.20), Ki-67 (3 eligible studies, n = 308, HR = 1.11, 95% CI, 0.70-1.78) and squamous cell carcinoma antigen (5 eligible studies, n = 700, HR = 1.28, 95% CI, 0.97-1.69); prognostic markers for esophageal adenocarcinoma included COX-2 (2 eligible studies, n = 235, HR = 3.06, 95% CI, 2.01-4.65) and HER-2 (3 eligible studies, n = 291, HR = 2.15, 95% CI, 1.39-3.33); prognostic markers for uncategorized ECs included p21 (9 eligible studies, n = 858, HR = 1.27, 95% CI, 0.75-2.16), p53 (31 eligible studies, n = 2851, HR = 1.34, 95% CI, 1.21-1.48), CRP (8 eligible studies, n = 1382, HR = 2.65, 95% CI, 1.64-4.27) and hemoglobin (5 eligible studies, n = 544, HR = 0.91, 95% CI, 0.83-1.00). Although some modest bias cannot be excluded, this review supports the involvement of biomarkers to be associated with EC overall survival

  12. Telling the story of childhood cancer: an evaluation of the Discovery Interview methodology conducted within the Queensland Children's Cancer Centre

    OpenAIRE

    Slater PJ; Philpot SP

    2016-01-01

    Penelope J Slater,1 Shoni P Philpot2 1Queensland Children's Cancer Centre, Lady Cilento Children's Hospital, Children's Health Queensland, 2Queensland Cancer Control Analysis Team, Princess Alexandra Hospital, Brisbane, QLD, Australia Abstract: This paper evaluates the process and impact of the Discovery Interview methodology developed in the National Health Service and applied in the Queensland Children's Cancer Centre. It shows how this methodology supports the family-cente...

  13. Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer | Office of Cancer Genomics

    Science.gov (United States)

    Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding.

  14. Cancer Research from Molecular Discovery to Global Health

    Science.gov (United States)

    A science writers' seminar to discuss the latest research in cancer genetics and global health efforts, including talks from leaders of NCI’s new centers of cancer genomics and global health will be held Dec. 13, 2011, at NCI.

  15. Plasma levels of the MMP-9:TIMP-1 complex as prognostic biomarker in breast cancer

    DEFF Research Database (Denmark)

    Thorsen, Stine Buch; Christensen, Sarah Louise T; Würtz, Sidse Ørnbjerg;

    2013-01-01

    Worldwide more than one million women are annually diagnosed with breast cancer. A considerable fraction of these women receive systemic adjuvant therapy; however, some are cured by primary surgery and radiotherapy alone. Prognostic biomarkers guide stratification of patients into different risk...... groups and hence improve management of breast cancer patients. Plasma levels of Matrix Metalloproteinase-9 (MMP-9) and its natural inhibitor Tissue inhibitor of metalloproteinase-1 (TIMP-1) have previously been associated with poor patient outcome and resistance to certain forms of chemotherapy. To...

  16. Proteomic Serum Biomarkers and Their Potential Application in Cancer Screening Programs

    Directory of Open Access Journals (Sweden)

    André M. Deelder

    2010-10-01

    Full Text Available Early diagnosis of cancer is of pivotal importance to reduce disease-related mortality. There is great need for non-invasive screening methods, yet current screening protocols have limited sensitivity and specificity. The use of serum biomarkers to discriminate cancer patients from healthy persons might be a tool to improve screening programs. Mass spectrometry based proteomics is widely applied as a technology for mapping and identifying peptides and proteins in body fluids. One commonly used approach in proteomics is peptide and protein profiling. Here, we present an overview of profiling methods that have the potential for implementation in a clinical setting and in national screening programs.

  17. The novel prostate cancer antigen 3 (PCA3 biomarker

    Directory of Open Access Journals (Sweden)

    Andreas Bourdoumis

    2010-12-01

    Full Text Available PCA3 is a prostate specific, nonprotein coding RNA that is significantly over expressed in prostate cancer, without any correlation to prostatic volume and/or other prostatic diseases (e.g. prostatitis. It can now easily be measured in urine with a novel transcription-mediated amplification based test. Quantification of PCA3 mRNA levels can predict the outcome of prostatic biopsies with a higher specificity rate in comparison to PSA. Several studies have demonstrated that PCA3 can be used as a prognostic marker of prostate cancer, especially in conjunction with other predictive markers. Novel PCA3-based nomograms have already been introduced into clinical practice. PCA3 test may be of valuable help in several PSA quandary situations such as negative prostatic biopsies, concomitant prostatic diseases, and active surveillance. Results from relevant clinical studies, comparative with PSA, are warranted in order to confirm the perspective of PCA3 to substitute PSA.

  18. Circulating Biomarkers in Advanced Colorectal Cancer Patients Randomly Assigned to Three Bevacizumab-Based Regimens

    Directory of Open Access Journals (Sweden)

    Antonia Martinetti

    2014-08-01

    Full Text Available The need to identify biomarkers for bevacizumab-based treatment in advanced colorectal cancer is imperative. The aim of this study was to investigate the prognostic role of circulating VEGF, PDGF, SDF-1, osteopontin and CEA in patients randomly assigned to three bevacizumab-based regimens. Plasma samples from 50 patients treated at a single Institution were analysed using the multiplex assay BioPlex™ 2200 (Bio-Rad Laboratories, Inc, Berkeley, CA, USA at baseline, before first three cycles and subsequently every three cycles until disease progression. Prognostic analyses of baseline values were performed using multivariable Cox models, including disease extension >10 cm or ≤10 cm (measured as the sum of the diameters for all target lesions as adjustment factor. The association between progression-free and overall survival and biomarkers modulation during treatment was studied using multivariable Cox models, which included summary statistics synthesizing during-treatment modulation together with disease extension. The biomarkers significantly associated with disease extension were baseline CEA (p = 0.012 and SDF-1 (p = 0.030. High values of VEGF and SDF-1 tended to be associated with worse prognosis, especially in terms of overall survival. The negative prognostic trend was more marked for baseline CEA as compared to other biomarkers; increasing values during treatment was significantly related to worse prognosis independently of disease extension (p = 0.007 and 0.016 for progression-free and overall survival, respectively. VEGF is related to bevacizumab pharmacodynamics and is associated to other angiogenic cytokines; some of the proposed biomarkers such as SDF-1 and CEA should be further validated for prognosis assessment and monitoring of bevacizumab-based treatment of advanced colorectal cancer.

  19. Biomarkers of endometrial cancer and related gynaecological malignancies

    OpenAIRE

    Seeber, L.M.S.

    2010-01-01

    In the Western World, endometrial cancer is the most common malignancy of the female genital tract. Endometrioid endometrial carcinoma (EEC or Type I tumour), accounts for approximately 75% of cases. Type II tumours, of which uterine papillary serous carcinoma (UPSC) is the most common subtype, are less common. Since classification as EEC or UPSC has therapeutic and prognostic implications, it is important to make the proper diagnosis. UPSC share their aggressive clinical behaviour and their ...

  20. Impact of biospecimens handling on biomarker research in breast cancer

    Directory of Open Access Journals (Sweden)

    Callari Maurizio

    2009-11-01

    Full Text Available Abstract Background Gene expression profiling is moving from the research setting to the practical clinical use. Gene signatures able to correctly identify high risk breast cancer patients as well as to predict response to treatment are currently under intense investigation. While technical issues dealing with RNA preparation, choice of array platforms, statistical analytical tools are taken into account, the tissue collection process is seldom considered. The time elapsed between surgical tissue removal and freezing of samples for biological characterizations is rarely well defined and/or recorded even for recently stored samples, despite the publications of standard operating procedures for biological sample collection for tissue banks. Methods Breast cancer samples from 11 patients were collected immediately after surgical removal and subdivided into aliquots. One was immediately frozen and the others were maintained at room temperature for respectively 2, 6 and 24 hrs. RNA was extracted and gene expression profile was determined using cDNA arrays. Phosphoprotein profiles were studied in parallel. Results Delayed freezing affected the RNA quality only in 3 samples, which were not subjected to gene profiling. In the 8 breast cancer cases with apparently intact RNA also in sample aliquots frozen at delayed times, 461 genes were modulated simply as a function of freezing timing. Some of these genes were included in gene signatures biologically and clinically relevant for breast cancer. Delayed freezing also affected detection of phosphoproteins, whose pattern may be crucial for clinical decision on target-directed drugs. Conclusion Time elapsed between surgery and freezing of samples appears to have a strong impact and should be considered as a mandatory variable to control for clinical implications of inadequate tissue handling.

  1. Role of MGMT as biomarker in colorectal cancer

    OpenAIRE

    Inno, Alessandro; Fanetti, Giuseppe; Di Bartolomeo, Maria; Gori, Stefania; Maggi, Claudia; Cirillo, Massimo; Iacovelli, Roberto; Nichetti, Federico; Martinetti, Antonia; de Braud, Filippo; Bossi, Ilaria; Pietrantonio, Filippo

    2014-01-01

    O6-methylguanine DNA methyltransferase (MGMT) gene promoter methylation plays an important role in colorectal carcinogenesis, occurring in about 30%-40% of metastatic colorectal cancer. Its prognostic role has not been defined yet, but loss of expression of MGMT, which is secondary to gene promoter methylation, results in an interesting high response to alkylating agents such as dacarbazine and temozolomide. In a phase 2 study on heavily pre-treated patients with MGMT methylated metastatic co...

  2. Biomarker-specific conjugated nanopolyplexes for the active coloring of stem-like cancer cells

    Science.gov (United States)

    Hong, Yoochan; Lee, Eugene; Choi, Jihye; Haam, Seungjoo; Suh, Jin-Suck; Yang, Jaemoon

    2016-06-01

    Stem-like cancer cells possess intrinsic features and their CD44 regulate redox balance in cancer cells to survive under stress conditions. Thus, we have fabricated biomarker-specific conjugated polyplexes using CD44-targetable hyaluronic acid and redox-sensible polyaniline based on a nanoemulsion method. For the most sensitive recognition of the cellular redox at a single nanoparticle scale, a nano-scattering spectrum imaging analyzer system was introduced. The conjugated polyplexes showed a specific targeting ability toward CD44-expressing cancer cells as well as a dramatic change in its color, which depended on the redox potential in the light-scattered images. Therefore, these polyaniline-based conjugated polyplexes as well as analytical processes that include light-scattering imaging and measurements of scattering spectra, clearly establish a systematic method for the detection and monitoring of cancer microenvironments.

  3. Biomarker-specific conjugated nanopolyplexes for the active coloring of stem-like cancer cells.

    Science.gov (United States)

    Hong, Yoochan; Lee, Eugene; Choi, Jihye; Haam, Seungjoo; Suh, Jin-Suck; Yang, Jaemoon

    2016-06-01

    Stem-like cancer cells possess intrinsic features and their CD44 regulate redox balance in cancer cells to survive under stress conditions. Thus, we have fabricated biomarker-specific conjugated polyplexes using CD44-targetable hyaluronic acid and redox-sensible polyaniline based on a nanoemulsion method. For the most sensitive recognition of the cellular redox at a single nanoparticle scale, a nano-scattering spectrum imaging analyzer system was introduced. The conjugated polyplexes showed a specific targeting ability toward CD44-expressing cancer cells as well as a dramatic change in its color, which depended on the redox potential in the light-scattered images. Therefore, these polyaniline-based conjugated polyplexes as well as analytical processes that include light-scattering imaging and measurements of scattering spectra, clearly establish a systematic method for the detection and monitoring of cancer microenvironments. PMID:27098318

  4. Cell cycle arrest biomarkers in human lung cancer cells after treatment with selenium in culture.

    Science.gov (United States)

    Swede, Helen; Dong, Yan; Reid, Mary; Marshall, James; Ip, Clement

    2003-11-01

    In the planning of future intervention trials using chemopreventive agents against lung cancer, it is critical to evaluate the effect on biomarkers implicated specifically in lung carcinogenesis. With the use of the H520 and H522 human lung cancer cell lines, the present study showed that treatment with selenium (in the form of methylseleninic acid) inhibited cell growth, arrested cell cycle progression at G(1), and induced apoptosis as a late event. Because H520 cells were more sensitive to selenium than H522 cells (IC(50) of MSA was 2.5 or 10 micro M for H520 or H522 cells, respectively, at 24 h), a panel of nine cell cycle regulatory proteins known to be involved in G(1)-->S transition was assessed by Western analysis using whole cell lysate from H520 cells. These nine proteins (DP1, cdc25A, cyclin A, cyclin B(1), cyclin D(1), cdk1, cdk5, p21(WAF1), and GADD153) have been reported previously by our laboratory to be modulated by MSA in human breast and prostate cancer cells. Our data showed that only four (DP1, cdc25A, p21(WAF1), and GADD153) of nine biomarkers produced the expected changes after treatment of lung cancer cells with MSA. This finding raises the possibility that the molecular targets sensitive to selenium modulation may be tissue specific. Thus, the selection of selenium biomarkers for evaluation in an intervention trial must be based on empirical data derived from the cancer cell type of interest. PMID:14652289

  5. Correlations between diffusion-weighted imaging and breast cancer biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Martincich, Laura; Deantoni, Veronica; Bertotto, Ilaria; Liotti, Michele; Regge, Daniele [Unit of Radiology, Institute for Cancer Research and Treatment (IRCC), Candiolo, Turin (Italy); Redana, Stefania; Rossi, Valentina; Aglietta, Massimo; Montemurro, Filippo [Institute for Cancer Research and Treatment (IRCC), Division of Medical Oncology, Candiolo, Turin (Italy); Kubatzki, Franziska; Ponzone, Riccardo [Institute for Cancer Research and Treatment (IRCC), Division of Gynecological Oncology, Candiolo, Turin (Italy); Sarotto, Ivana [Unit of Pathology, Institute for Cancer Research and Treatment (IRCC), Candiolo, Turin (Italy)

    2012-07-15

    We evaluated whether the apparent diffusion coefficient (ADC) provided by diffusion-weighted imaging (DWI) varies according to biological features in breast cancer. DWI was performed in 190 patients undergoing dynamic contrast-enhanced magnetic resonance imaging (MRI) for local staging. For each of the 192 index cancers we studied the correlation between ADC and classical histopathological and immunohistochemical breast tumour features (size, histological type, grade, oestrogen receptor [ER] and Ki-67 expression, HER2 status). ADC was compared with immunohistochemical surrogates of the intrinsic subtypes (Luminal A; Luminal B; HER2-enriched; triple-negative). Correlations were analysed using the Mann-Whitney U and Kruskal-Wallis H tests. A weak, statistically significant correlation was observed between ADC values and the percentage of ER-positive cells (-0.168, P = 0.020). Median ADC values were significantly higher in ER-negative than in ER-positive tumours (1.110 vs 1.050 x 10{sup -3} mm{sup 2}/s, P = 0.015). HER2-enriched tumours had the highest median ADC value (1.190 x 10{sup -3} mm{sup 2}/s, range 0.950-2.090). Multiple comparisons showed that this value was significantly higher than that of Luminal A (1.025 x 10{sup -3} mm{sup 2}/s [0.700-1.340], P = 0.004) and Luminal B/HER2-negative (1.060 x 10{sup -3} mm{sup 2}/s [0.470-2.420], P = 0.008) tumours. A trend towards statistical significance (P = 0.018) was seen with Luminal B/HER2-positive tumours. ADC values vary significantly according to biological tumour features, suggesting that cancer heterogeneity influences imaging parameters. (orig.)

  6. Discovery of protein profiles for differentiated thyroid cancer using SELDI TOF MS

    International Nuclear Information System (INIS)

    Low sensitivity of diagnostic whole body iodine scintigraphy and intermediate range of serum thyroglobulin (Tg) with or without anti-Tg antibody make it difficult to select the patients with differentiated thyroid cancer who need further treatment. Surfaced Enhanced Laser Desorption /Ionization - Time of Flight - Mass Spectrometry (SELDI TOF MS) is a useful method to evaluate cancer proteome, biomarkers and patterns of biomarkers. In this preliminary study, we evaluated and developed protein profiles for the discrimination between patients with differentiated thyroid cancer and non-cancer controls using SELDI technology. Serum samples from 10 healthy controls and from 14 patients with papillary thyroid cancer before thyroidectomy were analyzed by SELDI MS. Multiple protein peaks detected were analyzed by the computer software to develop a classifier for separating cancer patients form controls. The classifier was then challenged to 24 serum samples to determine the validity and accuracy of the classification system. All patients with papillary thyroid cancer had no other concomitant cancer or thyroiditis. Their serum Tg concentration was 55.8 (1.5 - 249.7) and 2 patients had extra-thyroidal extension. According to the SELDI analysis, protein peaks at 3696 Da, 4178 Da, and 8149 Da were more prominent in cancer patients than controls in various degrees. Among those, protein peak at 4178 Da was determined as classifier by computer software, and the sensitivity, specificity and accuracy for discrimination of cancer patients from controls was 92.9% (13/14), 90% (9/10) and 91.7% respectively. This preliminary study suggests that serum protein profiles of differentiated thyroid cancer can be used for differentiation between cancer patients and non-cancer controls. And further clinical studies in various test sets will offer useful information in selecting patients who require treatment

  7. Evaluation of serum procathepsin B, cystatin B and cystatin C as possible biomarkers of ovarian cancer

    Directory of Open Access Journals (Sweden)

    Elena A. Gashenko

    2013-08-01

    Full Text Available Objectives. To evaluate procathepsin B, as well as endogenous inhibitors of cysteine proteases (cystatin B and cystatin C in biological fluids as possible biomarkers of ovarian cancer. To observe levels of serum procathepsin B in different age groups. Study design. The sample (N=27 of women with gynaecological tumours included 18 patients with ovarian cancer (n=18 and 9 patients with benign ovarian tumours (n=9; 72 healthy women were in the control group. All patients were treated in Novosibirsk Regional Oncological Center, Russia. Serum samples of healthy women (n=40 aged 18–70 years were used as controls for common biomarker of ovarian cancer CA-125. In the Procathepsin B study, serum samples of healthy women (n=32 aged 18–40 years (n=14, 41–55 years (n=10 and 56–80 (n=8 years were used as controls. Methods. Common biomarker of ovarian cancer, CA-125, was assayed by using a commercial kit (Vector, Koltsovo, Novosibirsk Region, Russia. Procathepsin B was measured by means of a commercial kit for human procathepsin B (R&D, USA; cystatin C was measured by commercial ELISA kits for human (BioVendor, Czechia; cystatin B was measured by ELISA kits for human (USCN Life Science Inc., Wuhan, China. Statistical analysis was performed by one-way ANOVA (Statistica 10 Program. Results. In the control group, serum procathepsin B concentration did not reveal age dependency. In the ovarian cancer group, both levels of serum procathepsin B and standard biomarker CA-125 increased significantly (both p<0.001 compared with the control group. In the benign ovarian tumour group, serum procathepsin B (p<0.001 and CA-125 (p=0.004 increased about 2.5- and 8-fold compared to the control group. Serum cystatin B level increased up to 1.7-fold in the ovarian cancer group compared to the control group. The increase of serum CA-125 was about 3.5-fold higher (p=0.017 and procathepsin B was 1.8-fold higher (p<0.05 in the ovarian cancer group compared to the benign

  8. Screening for colorectal cancer risk biomarkers related to diet

    OpenAIRE

    Da Pieve, Chiara; Moore, Sharon; Velasco, Maria

    2010-01-01

    Background: Red and processed meat are associated with high risks of colorectal cancer due to the endogenous formation of O6-carboxymethyl guanine (O6CMG), a potent carcinogen. The aim of our research is to develop liquid chromatography tandem mass spectrometry (LC-MS/MS) analytical methods for the measurement of the DNA adducts, such as O6CMG and its nucleoside O6-carboxymethyl deoxyguanosine (O6CMdG), in urine samples and correlate it to different diets. Methods: Urine samples were coll...

  9. Aberrant p16 promoter hypermethylation in bronchial mucosae as a biomarker for the early detection of lung cancer

    Institute of Scientific and Technical Information of China (English)

    XIE Guang-shun; HOU Ai-rong; LI Long-yun; GAO Yan-ning; CHENG Shu-jun

    2006-01-01

    @@ Lung cancer is the leading cause of cancer related death in the world and its mortality could be greatly reduced by diagnosis and treatment in its early stages. Effective tools for the early detection of lung cancer and its high risk factors remain a major challenge. Biomarkers that detect lung cancer in its early stages or identify its pretumour lesions,enabling early therapeutic intervention, would be invaluable to improve its dismal prognosis.

  10. Detection of Melanoma Cancer Biomarker Dimethyl Disulfide Using Cavity Ringdown Spectroscopy at 266 nm.

    Science.gov (United States)

    Wang, Zhennan; Sun, Meixiu; Wang, Chuji

    2016-06-01

    Skin cells emit volatile organic compounds (VOCs), and some of them can be used as biomarkers for screening specific diseases. Dimethyl disulfide (DMDS) has been recently reported as a biomarker of melanoma skin cancer (Kwak et al. "Volatile Biomarkers from Human Melanoma Cells". J. Chromatogr. B. 2013. 931: 90-96.). With the motivation of diagnosing melanoma using DMDS as its biomarker, we explore the potential of measuring DMDS using an advanced laser spectroscopic technique as an alternative method. We report on the first DMDS measurements using an experimental system based on cavity ringdown spectroscopy (CRDS). The test samples were mixtures of DMDS vapor and nitrogen in different concentrations. Two sampling methods were investigated to dilute the DMDS sample to low concentrations for ringdown measurements. The results showed that the ringdown system responded to various DMDS concentrations linearly and a theoretical detection limit of sub-ppb (parts per billion) could be achieved at the absorption wavelength of 266 nm. This ringdown system exhibited a high dynamic range for DMDS measurements, from ppm (parts per million) to ppt (parts per trillion) levels, given different laser wavelengths used. The feasibility of developing a portable melanoma screening sensor using the CRDS technique was also demonstrated in this study. PMID:27076515

  11. The ADAMs family of proteases: new biomarkers and therapeutic targets for cancer?

    LENUS (Irish Health Repository)

    Duffy, Michael J

    2011-06-09

    Abstract The ADAMs are transmembrane proteins implicated in proteolysis and cell adhesion. Forty gene members of the family have been identified, of which 21 are believed to be functional in humans. As proteases, their main substrates are the ectodomains of other transmembrane proteins. These substrates include precursor forms of growth factors, cytokines, growth factor receptors, cytokine receptors and several different types of adhesion molecules. Although altered expression of specific ADAMs has been implicated in different diseases, their best-documented role is in cancer formation and progression. ADAMs shown to play a role in cancer include ADAM9, ADAM10, ADAM12, ADAM15 and ADAM17. Two of the ADAMs, i.e., ADAM10 and 17 appear to promote cancer progression by releasing HER\\/EGFR ligands. The released ligands activate HER\\/EGFR signalling that culminates in increased cell proliferation, migration and survival. Consistent with a causative role in cancer, several ADAMs are emerging as potential cancer biomarkers for aiding cancer diagnosis and predicting patient outcome. Furthermore, a number of selective ADAM inhibitors, especially against ADAM10 and ADAM17, have been shown to have anti-cancer effects. At least one of these inhibitors is now undergoing clinical trials in patients with breast cancer.

  12. Biomarker and animal models for assessment of retinoid efficacy in cancer chemoprevention

    Institute of Scientific and Technical Information of China (English)

    Richard M NILES

    2007-01-01

    Vitamin A is essential for normal growth and development. Epidemiology and laboratory studies suggest that decreased vitamin A levels and defective metabo-lisrn/action may contribute to the genesis of certain cancers. Based on this information, natural and synthetic derivatives of vitamin A (retinoids) have been used for chemoprevention of cancer. Retinoids have had some success in the chemoprevention of leukoplakia and in the decreased incidence of second prima-ties in head and neck cancer. There is little information on biomarkers that can be used to assess the efficacy of the chemopreventive activity of retinoids. The ability of retinoids to induce RARb has been consistently shown to correlate with the response of cells and tissues to retinoic acid, but few other biomarkers have been certified as indicators of retinoid activity. In light of the failure of the ATBC and CARET clinical intervention trials for chemoprevention of lung cancer, greater use of animal models for chemoprevention studies is necessary. The potential combination of phytochemicals that inhibit DNA methyltransferase activity with retinoids holds promise for more effective chemoprevention of retinoid-unrespon-sive premalignant lesions.

  13. Cytochrome P450 1A1 genetic polymorphisms as cancer biomarkers

    Directory of Open Access Journals (Sweden)

    A Bag

    2015-01-01

    Full Text Available Phase I metabolic enzyme CYP1A1 plays an important role in xenobiotics metabolism and has been extensively studied as a cancer risk biomarker. CYP1A1 is polymorphic and its four variants, e.g., CYP1A1* 2 A, CYP1A1* 2C, CYP1A1* 3 and CYP1A1* 4 with trivial names m1, m2, m3, and m4 respectively, are most commonly studied for cancer link. Gene- gene interaction studies combining polymorphisms of this enzyme with those of phase II detoxifying enzymes, especially glutathione S- transferases (GSTs revealed greater risk for cancer susceptibility. Variants of CYP1A1 have also been found to be associated with chemotherapeutic adverse- effects. Results of these studies, however, remained largely contradictory mainly because of lack of statistical power due to involvement of small sample size. Strongly powered experimental designs involving gene- gene, gene- environment interactions are required in order to validate CYP1A1 as reliable cancer- biomarker.

  14. Exosomes are fingerprints of originating cells: potential biomarkers for ovarian cancer

    Directory of Open Access Journals (Sweden)

    Kobayashi M

    2015-03-01

    Full Text Available Miharu Kobayashi, Gregory E Rice, Jorge Tapia, Murray D Mitchell, Carlos Salomon Exosome Biology Laboratory, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia. Abstract: The past decade has seen an extraordinary explosion of research in the field of extracellular vesicles, especially in a specific type of extracellular vesicles originating from endosomal compartments, called exosomes. Exosomes are a specific subtype of secreted vesicles that are defined as small (~30–120 nm but very stable membrane vesicles that are released from a wide range of cells, including normal and cancer cells. As the content of exosomes is cell type specific, it is believed that they are a "fingerprint" of the releasing cell and its metabolic status. We hypothesized that the exosomes and their specific exosomal content (eg, microribonucleic acid represent a precious biomedical tool and may be used as biomarkers for the diagnosis and prognosis of malignant tumors. In addition, exosomes may modify the phenotype of the parent and/or target cell by transferring pro-oncogenic molecules to induce cancerous phenotype of recipient cells and contribute to the formation of the premetastatic niche. The mechanism involved in these phenomena remains unclear; however, inclusion of signaling mediators into exosomes or exosome release may reduce their intracellular bioavailability in the parent cell, thereby altering cell phenotype and their metastatic potential. The aim of this review therefore is to analyze the biogenesis and role of exosomes from tumor cells, focusing primarily on ovarian cancer. Ovarian cancer is the most lethal gynecologic cancer, and an effective early diagnosis has the potential to improve patient survival. Ovarian cancer currently lacks a reliable method for early detection, however, exosomes have received great attention as potential biomarkers and mediators

  15. Mitochondrial DNA mutations—candidate biomarkers for breast cancer diagnosis in Bangladesh

    Institute of Scientific and Technical Information of China (English)

    Gazi Nurun Nahar Sultana; Atiqur Rahman; Abu Din Ahmed Shahinuzzaman; Rowshan Ara Begum; Chowdhury Faiz Hossain

    2012-01-01

    Breast cancer is a major health problem that affects more than 24% of women in Bangladesh.Furthermore,among low-income countries including Bangladesh,individuals have a high risk for developing breast cancer.This study aimed to identify candidate mitochondrial DNA (mtDNA) biomarkers for breast cancer diagnosis in Bangladeshi women to be used as a preventive approach.We screened the blood samples from 24 breast cancer patients and 20 healthy controls to detect polymorphisms in the D-loop and the ND3- and ND4-coding regions of mtDNA by direct sequencing.Among 14 distinct mutations,10 polymorphisms were found in the D-loop,3 were found in the ND3-coding region,and 1 was found in the ND4-coding region.The frequency of two novel polymorphisms in the D-loop,one at position 16290 (T-ins) and the other at position 16293 (A-del),was higher in breast cancer patients than in control subjects (position 16290:odds ratio =6.011,95% confidence interval =1.2482 to 28.8411,P =0.002; position 16293:odds ratio =5.6028,95% confidence interval =1.4357 to 21.8925,P =0.010).We also observed one novel mutation in the ND3-coding region at position 10316 (A > G) in 69% of breast cancer patients but not in control subjects.The study suggests that two novel polymorphisms in the D-loop may be candidate biomarkers for breast cancer diagnosis in Bangladeshi women.

  16. Mitochondrial DNA mutations--candidate biomarkers for breast cancer diagnosis in Bangladesh

    Directory of Open Access Journals (Sweden)

    Rowshan Ara Begum

    2012-09-01

    Full Text Available Breast cancer is a major health problem that affects more than 24% of women in Bangladesh. Further- more, among low-income countries including Bangladesh, individuals have a high risk for developing breast cancer. This study aimed to identify candidate mitochondrial DNA (mtDNA biomarkers for breast cancer diagnosis in Bangladeshi women to be used as a preventive approach. We screened the blood samples from 24 breast cancer patients and 20 healthy controls to detect polymorphisms in the D-loop and the ND3- and ND4-coding regions of mtDNA by direct sequencing. Among 14 distinct mutations, 10 polymorphisms were found in the D-loop, 3 were found in the ND3-coding region, and 1 was found in the ND4-coding region. The frequency of two novel polymorphisms in the D-loop, one at position 16290 (T-ins and the other at position 16293 (A-del, was higher in breast cancer patients than in control subjects (position 16290: odds ratio = 6.011, 95% confidence interval = 1.2482 to 28.8411, P = 0.002; position 16293: odds ratio = 5.6028, 95% confidence interval = 1.4357 to 21.8925, P = 0.010. We also observed one novel mutation in the ND3-coding region at position 10316 (A > G in 69% of breast cancer patients but not in control subjects. The study suggests that two novel polymorphisms in the D-loop may be candidate biomarkers for breast cancer diagnosis in Bangladeshi women.

  17. Identification of biomarkers for cervical cancer in peripheral blood lymphocytes using oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    SHENG Jie; ZHANG Wei-yuan

    2010-01-01

    Background Oligonucleotide microarrays are increasingly being used to identify gene expression profiles that associated with complex genetic diseases. Peripheral lymphocytes communicate with cells and extracellular matrixes in almost all tissues and organs in human body, suggesting that the gene expression profiles in peripheral lymphocytes may reflect the presence of disease in the body. This study aimed to identify molecular biomarkers for cervical cancer in peripheral blood lymphocytes by using oligonucleotide microarrays.Methods Total RNA was extracted from peripheral blood lymphocytes of 24 early stage cervical cancer patients and 18 healthy controls. We used 22K Human Genome microarrays to profile peripheral blood lymphocytes from 4 early stage cervical cancer patients and compared their gene expression profiles with those from 3 healthy controls. Differentially expressed genes would be identified if they had adjusted P values of less than 0.05 and a groupwise average fold change greater than 1.5 or less than 0.67. Then the selected 5 genes were validated in the remaining 20 early stage cervical cancer patients and the 15 healthy controls by using real-time reverse-transcription polymerase chain reaction (RT-PCR).Results Genes identified by the gene selection program expressed differently between the blood samples of the early stage cervical cancer patients and those of the healthy controls. To validate the gene expression data, 5 genes were analyzed by real-time RT-PCR. In three of the 5 identified genes, tenasin-c (TNC), nuceolin (NCL), and enolase 2 (ENO2) showed a significant up-regulation in the blood samples of the early stage cervical cancer patients versus that of the healthy controls.Conclusions The up-regulation of TNC, NCL, and ENO2 in peripheral blood may be used to identify novel blood biomarkers for detecting cervical cancer in a clinically accessible surrogate tissue, and thus to provide a possibility to develop a noninvasive and predictive

  18. Diagnostic accuracy of serum biomarkers for head and neck cancer: A systematic review and meta-analysis.

    Science.gov (United States)

    Guerra, Eliete Neves Silva; Rêgo, Daniela Fortunato; Elias, Silvia Taveira; Coletta, Ricardo D; Mezzomo, Luis André Mendonça; Gozal, David; De Luca Canto, Graziela

    2016-05-01

    Serum biomarkers could be helpful to characterize head and neck squamous cell carcinoma (HNSCC). Thus, the purpose of this systematic review and meta-analysis was to determine the diagnostic capability of serum biomarkers in the assessment of HNSCC patients. Studies were gathered by searching LILACS, PubMed, Science Direct, Scopus and Web of Science up to April 10th, 2015. Studies that focused on serum biomarkers in the diagnosis of HNSCC compared with controls were considered. Sixty-five studies were identified, and the sample size included 9098 subjects. Combined biomarkers demonstrated improved accuracy than those tested individually. Therefore, 12.8% of single and 34.3% of combined indicated that serum biomarkers discriminate patients with HNSCC from controls. The combined biomarkers with better diagnostic capability included Epidermal growth factor receptor (EGFR)+Cyclin D1 and squamous cell cancer-associated antigen (SCCA)+EGFR+Cyclin D1. Beta2-microglobin may also be a promising single biomarker for future studies. Serum biomarkers can be potentially useful in the diagnosis of HNSCC. However, further research is required to validate these biomarkers. PMID:26971993

  19. Transposons for cancer gene discovery: Sleeping Beauty and beyond

    OpenAIRE

    Collier, Lara S.; Largaespada, David A

    2007-01-01

    The use of Sleeping Beauty transposons as somatic mutagens to discover cancer genes in hematopoietic tumors and sarcomas has been documented. Here, we discuss the future of Sleeping Beauty for cancer genetic studies and the potential use of additional transposable elements for somatic mutagenesis.

  20. Gene set-based module discovery in the breast cancer transcriptome

    Directory of Open Access Journals (Sweden)

    Zhang Michael Q

    2009-02-01

    Full Text Available Abstract Background Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data have recently succeeded in identifying expression modules, which is defined as co-expressed gene sets under common regulatory mechanisms. However, such module discovery methods are not applied cancer transcriptome data. Results In order to decode oncogenic regulatory programs in cancer cells, we developed a novel module discovery method termed EEM by extending a previously reported module discovery method, and applied it to breast cancer expression data. Starting from seed gene sets prepared based on cis-regulatory elements, ChIP-chip data, and gene locus information, EEM identified 10 principal expression modules in breast cancer based on their expression coherence. Moreover, EEM depicted their activity profiles, which predict regulatory programs in each subtypes of breast tumors. For example, our analysis revealed that the expression module regulated by the Polycomb repressive complex 2 (PRC2 is downregulated in triple negative breast cancers, suggesting similarity of transcriptional programs between stem cells and aggressive breast cancer cells. We also found that the activity of the PRC2 expression module is negatively correlated to the expression of EZH2, a component of PRC2 which belongs to the E2F expression module. E2F-driven EZH2 overexpression may be responsible for the repression of the PRC2 expression modules in triple negative tumors. Furthermore, our network analysis predicts regulatory circuits in breast cancer cells. Conclusion These results demonstrate that the gene set-based module discovery approach is a powerful tool to decode regulatory programs in cancer cells.

  1. Synthesis and characterization of a HAp-based biomarker with controlled drug release for breast cancer.

    Science.gov (United States)

    González, Maykel; Merino, Ulises; Vargas, Susana; Quintanilla, Francisco; Rodríguez, Rogelio

    2016-04-01

    A biocompatible hybrid porous polymer-ceramic material was synthesized to be used as a biomarker in the treatment of breast cancer. This device was equipped with the capacity to release medicaments locally in a controlled manner. The biomaterial was Hydroxyapatite(HAp)-based and had a controlled pore size and pore volume fraction. It was implemented externally using a sharp end and a pair of barbed rings placed opposite each other to prevent relative movement once implanted. The biomarker was impregnated with cis-diamine dichloride platinum (II) [Cl2-Pt-(NH3)2]; the rate of release was obtained using inductively coupled plasma atomic emission spectroscopy (ICP-AES), and release occurred over the course of three months. Different release profiles were obtained as a function of the pore volume fraction. The biomaterial was characterized using scanning electron microscopy (SEM) and Raman spectroscopy. PMID:26838911

  2. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune

    2010-01-01

    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease pr...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....

  3. Diversity-Oriented Synthetic Strategies Applied to Cancer Chemical Biology and Drug Discovery

    Directory of Open Access Journals (Sweden)

    Ian Collins

    2014-10-01

    Full Text Available How can diversity-oriented strategies for chemical synthesis provide chemical tools to help shape our understanding of complex cancer pathways and progress anti-cancer drug discovery efforts? This review (surveying the literature from 2003 to the present considers the applications of diversity-oriented synthesis (DOS, biology-oriented synthesis (BIOS and associated strategies to cancer biology and drug discovery, summarising the syntheses of novel and often highly complex scaffolds from pluripotent or synthetically versatile building blocks. We highlight the role of diversity-oriented synthetic strategies in producing new chemical tools to interrogate cancer biology pathways through the assembly of relevant libraries and their application to phenotypic and biochemical screens. The use of diversity-oriented strategies to explore structure-activity relationships in more advanced drug discovery projects is discussed. We show how considering appropriate and variable focus in library design has provided a spectrum of DOS approaches relevant at all stages in anti-cancer drug discovery.

  4. SHOX2 DNA Methylation is a Biomarker for the diagnosis of lung cancer based on bronchial aspirates

    Directory of Open Access Journals (Sweden)

    Liloglou Triantafillos

    2010-11-01

    Full Text Available Abstract Background This study aimed to show that SHOX2 DNA methylation is a tumor marker in patients with suspected lung cancer by using bronchial fluid aspirated during bronchoscopy. Such a biomarker would be clinically valuable, especially when, following the first bronchoscopy, a final diagnosis cannot be established by histology or cytology. A test with a low false positive rate can reduce the need for further invasive and costly procedures and ensure early treatment. Methods Marker discovery was carried out by differential methylation hybridization (DMH and real-time PCR. The real-time PCR based HeavyMethyl technology was used for quantitative analysis of DNA methylation of SHOX2 using bronchial aspirates from two clinical centres in a case-control study. Fresh-frozen and Saccomanno-fixed samples were used to show the tumor marker performance in different sample types of clinical relevance. Results Valid measurements were obtained from a total of 523 patient samples (242 controls, 281 cases. DNA methylation of SHOX2 allowed to distinguish between malignant and benign lung disease, i.e. abscesses, infections, obstructive lung diseases, sarcoidosis, scleroderma, stenoses, at high specificity (68% sensitivity [95% CI 62-73%], 95% specificity [95% CI 91-97%]. Conclusions Hypermethylation of SHOX2 in bronchial aspirates appears to be a clinically useful tumor marker for identifying subjects with lung carcinoma, especially if histological and cytological findings after bronchoscopy are ambiguous.

  5. SHOX2 DNA Methylation is a Biomarker for the diagnosis of lung cancer based on bronchial aspirates

    International Nuclear Information System (INIS)

    This study aimed to show that SHOX2 DNA methylation is a tumor marker in patients with suspected lung cancer by using bronchial fluid aspirated during bronchoscopy. Such a biomarker would be clinically valuable, especially when, following the first bronchoscopy, a final diagnosis cannot be established by histology or cytology. A test with a low false positive rate can reduce the need for further invasive and costly procedures and ensure early treatment. Marker discovery was carried out by differential methylation hybridization (DMH) and real-time PCR. The real-time PCR based HeavyMethyl technology was used for quantitative analysis of DNA methylation of SHOX2 using bronchial aspirates from two clinical centres in a case-control study. Fresh-frozen and Saccomanno-fixed samples were used to show the tumor marker performance in different sample types of clinical relevance. Valid measurements were obtained from a total of 523 patient samples (242 controls, 281 cases). DNA methylation of SHOX2 allowed to distinguish between malignant and benign lung disease, i.e. abscesses, infections, obstructive lung diseases, sarcoidosis, scleroderma, stenoses, at high specificity (68% sensitivity [95% CI 62-73%], 95% specificity [95% CI 91-97%]). Hypermethylation of SHOX2 in bronchial aspirates appears to be a clinically useful tumor marker for identifying subjects with lung carcinoma, especially if histological and cytological findings after bronchoscopy are ambiguous

  6. Ultrasensitive, multiplexed detection of cancer biomarkers directly in serum by using a quantum dot-based microfluidic protein chip.

    Science.gov (United States)

    Hu, Mei; Yan, Juan; He, Yao; Lu, Haoting; Weng, Lixing; Song, Shiping; Fan, Chunhai; Wang, Lianhui

    2010-01-26

    Sensitive and selective detection for cancer biomarkers are critical in cancer clinical diagnostics. Here we developed a microfluidic protein chip for an ultrasensitive and multiplexed assay of cancer biomarkers. Aqueous-phase-synthesized CdTe/CdS quantum dots (aqQDs) were employed as fluorescent signal amplifiers to improve the detection sensitivity. Secondary antibodies (goat anti-mouse IgG) were conjugated to luminescent CdTe/CdS QDs to realize a versatile fluorescent probe that could be used for multiplexed detection in both sandwich and reverse phase immunoassays. We found that our microfluidic protein chip not only possessed ultrahigh femtomolar sensitivity for cancer biomarkers, but was selective enough to be directly used in serum. This protein chip thus combines the high-throughput capabilities of a microfluidic network with the high sensitivity and multicolor imaging ability offered by highly fluorescent QDs, which can become a promising diagnostic tool in clinical applications. PMID:20041634

  7. Molecular portraits: the evolution of the concept of transcriptome-based cancer signatures

    OpenAIRE

    Modelska, Angelika; Quattrone, Alessandro; Re, Angela

    2015-01-01

    Cancer results from dysregulation of multiple steps of gene expression programs. We review how transcriptome profiling has been widely explored for cancer classification and biomarker discovery but resulted in limited clinical impact. Therefore, we discuss alternative and complementary omics approaches.

  8. 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

    (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......Impaired DNA damage response pathways may create vulnerabilities of cancer cells that can be exploited therapeutically. One such selective vulnerability is the sensitivity of BRCA1- or BRCA2-defective tumors (hence defective in DNA repair by homologous recombination, HR) to inhibitors of the poly...... to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i...

  9. Development of micro immunosensors to study genomic and proteomic biomarkers related to cancer and Alzheimer's disease

    Science.gov (United States)

    Prabhulkar, Shradha

    A report from the National Institutes of Health defines a disease biomarker as a "characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer's disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with biorecognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0--100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Abeta) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Abeta1-40/42 (or Abeta ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Abeta1-40 and Abeta1-42 in

  10. Discovery – Lung Cancer Screening Saves Lives: The NLST

    Science.gov (United States)

    NCI funded the National Lung Screening Trial, an eight-year study that used new technology to detect small, aggressive tumors early enough to surgically remove them. This approach reduced lung cancer deaths among participants by 20 percent.

  11. Transforming Discovery into Health (Cancer Therapy and Obesity)

    Science.gov (United States)

    ... genetic profile of each patient's cancer." Taking on Obesity More than one-third of adults in the ... may face an even greater struggle. Since 1980, obesity has more than doubled among U.S. children ages ...

  12. Discovery – BRCA Connection to Breast and Ovarian Cancer

    Science.gov (United States)

    NCI-funded research helped identify inherited BRCA1 and BRCA2 genetic mutations and their connection to breast and ovarian cancer. From this research, a screening test was also developed to help patients make informed decisions about their health.

  13. PiggyBac Transposon Mutagenesis: A Tool for Cancer Gene Discovery in Mice

    OpenAIRE

    Rad, Roland; Rad, Lena; Wang, Wei; Cadinanos, Juan; Vassiliou, George; Rice, Stephen; Campos, Lia S.; Yusa, Kosuke; Banerjee, Ruby; Li, Meng Amy; de la Rosa, Jorge; Strong, Alexander; Lu, Dong; Ellis, Peter; Conte, Nathalie

    2010-01-01

    Transposons are mobile DNA segments that can disrupt gene function by inserting in or near genes. Here we show that insertional mutagenesis by the PiggyBac transposon can be used for cancer gene discovery in mice. PiggyBac transposition in genetically engineered transposon/transposase mice induced cancers whose type (hematopoietic versus solid) and latency were dependent on the regulatory elements introduced into transposons. Analysis of 63 hematopoietic tumors revealed the unique qualities o...

  14. Prediction of lung cancer based on serum biomarkers by gene expression programming methods.

    Science.gov (United States)

    Yu, Zhuang; Chen, Xiao-Zheng; Cui, Lian-Hua; Si, Hong-Zong; Lu, Hai-Jiao; Liu, Shi-Hai

    2014-01-01

    In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are frequently- used lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer. PMID:25422226

  15. Label-free electrical detection of ovarian cancer biomarker CA-125 with a novel nanoscale coaxial array

    Science.gov (United States)

    Archibald, Michelle; Rizal, Binod; Cai, Dong; Connolly, Timothy; Burns, Michael; Naughton, Michael; Chiles, Thomas

    2013-03-01

    Technologies to detect early stage cancer would provide significant benefit to cancer disease patients. Clinical measurement of biomarkers offers the promise of a noninvasive and cost effective screening for early stage detection. We have developed a novel 3-dimensional nanocavity array for the detection of human cancer biomarkers. This all-electronic diagnostic sensor is based on a nanoscale coaxial array architecture that enables molecular-level detection. Each individual sensor in the array is a vertically-oriented coaxial capacitor, whose capacitance is measurably changed when target molecules enter the coax annulus. The coaxial array facilitates electrical-based detection in response to antibody or molecular imprint based recognition of a specific cancer biomarker, thereby providing a label-free, non-optical measurement. Here, we describe this nanoscale 3D architecture and its application to the detection of the ovarian cancer biomarker CA-125. We report our efforts on the development of molecular detection of CA-125 based on antibody-functionalized nanocoax arrays as well as molecular imprints. The results demonstrate the feasibility of using these arrays as ultrasensitive devices to detect a wide range of molecular targets, including disease biomarkers. Supported by the NIH grants NCI CA137681 and NIAID AI100216.

  16. Molecular biomarkers in extrahepatic bile duct cancer patients undergoing chemoradiotherapy for gross residual disease after surgery

    Energy Technology Data Exchange (ETDEWEB)

    Koh, Hyeon Kang; Kim, Kyu Bo; Chie, Eui Kyu; Ha, Sung W. [Seoul National University College of Medicine, Seoul (Korea, Republic of); Park, Hae Jin [Dept. of Radiation Oncology, Soonchunhyang University Hospital, Seoul (Korea, Republic of)

    2012-12-15

    To analyze the outcomes of chemoradiotherapy for extrahepatic bile duct (EHBD) cancer patients who underwent R2 resection or bypass surgery and to identify prognostic factors affecting clinical outcomes, especially in terms of molecular biomarkers. Medical records of 21 patients with EHBD cancer who underwent R2 resection or bypass surgery followed by chemoradiotherapy from May 2001 to June 2010 were retrospectively reviewed. All surgical specimens were re-evaluated by immunohistochemical staining using phosphorylated protein kinase B (pAKT), CD24, matrix metalloproteinase 9 (MMP9), survivin, and {beta}-catenin antibodies. The relationship between clinical outcomes and immunohistochemical results was investigated. At a median follow-up of 20 months, the actuarial 2-year locoregional progression-free, distant metastasis-free and overall survival were 37%, 56%, and 54%, respectively. On univariate analysis using clinicopathologic factors, there was no significant prognostic factor. In the immunohistochemical staining, cytoplasmic staining, and nuclear staining of pAKT was positive in 10 and 6 patients, respectively. There were positive CD24 in 7 patients, MMP9 in 16 patients, survivin in 8 patients, and {beta}-catenin in 3 patients. On univariate analysis, there was no significant value of immunohistochemical results for clinical outcomes. There was no significant association between clinical outcomes of patients with EHBD cancer who received chemoradiotherapy after R2 resection or bypass surgery and pAKT, CD24, MMP9, survivin, and {beta}-catenin. Future research is needed on a larger data set or with other molecular biomarkers.

  17. MicroRNA dysregulation as a prognostic biomarker in colorectal cancer

    International Nuclear Information System (INIS)

    Colorectal cancer (CRC) is one of the most potentially curable cancers, yet it remains the fourth most common overall cause of cancer death worldwide. The identification of robust molecular prognostic biomarkers can refine the conventional tumor–node–metastasis staging system, avoid understaging of tumor, and help pinpoint patients with early-stage CRC who may benefit from aggressive treatments. Recently, epigenetic studies have provided new molecular evidence to better categorize the CRC subtypes and predict clinical outcomes. In this review, we summarize recent findings concerning the prognostic potential of microRNAs (miRNAs) in CRC. We first discuss the prognostic value of three tissue miRNAs (miR-21-5p, miR-29-3p, miR-148-3p) that have been examined in multiple studies. We also summarize the dysregulation of miRNA processing machinery DICER in CRC and its association with risk for mortality. We also reviewe the potential application of miRNA-associated single-nucleotide polymorphisms as prognostic biomarkers for CRC, especially the miRNA-associated polymorphism in the KRAS gene. Last but not least, we discuss the microsatellite instability-related miRNA candidates. Among all these candidates, miR-21-5p is the most promising prognostic marker, yet further prospective validation studies are required before it can go into clinical usage

  18. Merging person-specific bio-markers for predicting oral cancer recurrence through an ontology.

    Science.gov (United States)

    Salvi, Dario; Picone, Marco; Arredondo, María Teresa; Cabrera-Umpierrez, María Fernanda; Esteban, Ángel; Steger, Sebastian; Poli, Tito

    2013-01-01

    One of the major problems related to cancer treatment is its recurrence. Without knowing in advance how likely the cancer will relapse, clinical practice usually recommends adjuvant treatments that have strong side effects. A way to optimize treatments is to predict the recurrence probability by analyzing a set of bio-markers. The NeoMark European project has identified a set of preliminary bio-markers for the case of oral cancer by collecting a large series of data from genomic, imaging, and clinical evidence. This heterogeneous set of data needs a proper representation in order to be stored, computed, and communicated efficiently. Ontologies are often considered the proper mean to integrate biomedical data, for their high level of formality and for the need of interoperable, universally accepted models. This paper presents the NeoMark system and how an ontology has been designed to integrate all its heterogeneous data. The system has been validated in a pilot in which data will populate the ontology and will be made public for further research. PMID:22955869

  19. Single-walled carbon nanotube based transparent immunosensor for detection of a prostate cancer biomarker osteopontin

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, Abhinav; Hong, Seongkyeol; Singh, Renu [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); Jang, Jaesung, E-mail: jjang@unist.ac.kr [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); School of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of)

    2015-04-15

    Highlights: • A transparent CNT immunosensor is presented for detection of a prostate cancer biomarker osteopontin. • This immunosensor showed a highly linear and reproducible behavior from 1 pg mL{sup −1} to 1 μg mL{sup −1}. • The limit of detection of the immunosensor was 0.3 pg mL{sup −1}. • This immunosensor demonstrated high selectivity against bovine serum albumin and human serum. - Abstract: Osteopontin (OPN) is involved in almost all steps of cancer development, and it is being investigated as a potential biomarker for a diagnosis and prognosis of prostate cancer. Here, we report a label-free, highly sensitive and transparent immunosensor based on single-walled carbon nanotubes (SWCNTs) for detection of OPN. A high density of −COOH functionalized SWCNTs was deposited between two gold/indium tin oxide electrodes on a glass substrate by dielectrophoresis. Monoclonal antibodies specific to OPN were covalently immobilized on the SWCNTs. Relative resistance change of the immunosensors was measured as the concentration of OPN in phosphate buffer saline (PBS) and human serum was varied from 1 pg mL{sup −1} to 1 μg mL{sup −1} for different channel lengths of 2, 5, and 10 μm, showing a highly linear and reproducible behavior (R{sup 2} > 97%). These immunosensors were also specific to OPN against another test protein, bovine serum albumin, PBS and human serum, showing that a limit of detection for OPN was 0.3 pg mL{sup −1}. This highly sensitive and transparent immunosensor has a great potential as a simple point-of-care test kit for various protein biomarkers.

  20. Biomarkers for hepatocellular carcinoma.

    Science.gov (United States)

    Behne, Tara; Copur, M Sitki

    2012-01-01

    The hepatocellular carcinoma (HCC) is one of the most common malignant tumors and carries a poor survival rate. The management of patients at risk for developing HCC remains challenging. Increased understanding of cancer biology and technological advances have enabled identification of a multitude of pathological, genetic, and molecular events that drive hepatocarcinogenesis leading to discovery of numerous potential biomarkers in this disease. They are currently being aggressively evaluated to establish their value in early diagnosis, optimization of therapy, reducing the emergence of new tumors, and preventing the recurrence after surgical resection or liver transplantation. These markers not only help in prediction of prognosis or recurrence but may also assist in deciding appropriate modality of therapy and may represent novel potential targets for therapeutic interventions. In this paper, a summary of most relevant available data from published papers reporting various tissue and serum biomarkers involved in hepatocellular carcinoma was presented. PMID:22655201

  1. Clinical relevance of breast cancer-related genes as potential biomarkers for oral squamous cell carcinoma

    International Nuclear Information System (INIS)

    Squamous cell carcinoma of the oral cavity (OSCC) is a common cancer form with relatively low 5-year survival rates, due partially to late detection and lack of complementary molecular markers as targets for treatment. Molecular profiling of head and neck cancer has revealed biological similarities with basal-like breast and lung carcinoma. Recently, we showed that 16 genes were consistently altered in invasive breast tumors displaying varying degrees of aggressiveness. To extend our findings from breast cancer to another cancer type with similar characteristics, we performed an integrative analysis of transcriptomic and proteomic data to evaluate the prognostic significance of the 16 putative breast cancer-related biomarkers in OSCC using independent microarray datasets and immunohistochemistry. Predictive models for disease-specific (DSS) and/or overall survival (OS) were calculated for each marker using Cox proportional hazards models. We found that CBX2, SCUBE2, and STK32B protein expression were associated with important clinicopathological features for OSCC (peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumor size). Consequently, SCUBE2 and STK32B are involved in the hedgehog signaling pathway which plays a pivotal role in metastasis and angiogenesis in cancer. In addition, CNTNAP2 and S100A8 protein expression were correlated with DSS and OS, respectively. Taken together, these candidates and the hedgehog signaling pathway may be putative targets for drug development and clinical management of OSCC patients

  2. Candidate serum biomarkers for early intestinal cancer using 15N metabolic labeling and quantitative proteomics in the Apcmin/+ mouse

    OpenAIRE

    Ivancic, Melanie M.; Huttlin, Edward L.; Chen, Xiaodi; Pleiman, Jennifer K; Irving, Amy A; Hegeman, Adrian D.; Dove, William F.; Sussman, Michael R.

    2013-01-01

    Current screening procedures for colorectal cancer are imperfect, highly invasive and result in increased mortality rates due to low compliance. The goal of the experiments reported herein is to identify potential blood-based biomarkers indicative of early-stage intestinal cancers using the ApcMin/+ mouse model of intestinal cancer as an experimental system. Serum proteins from tumor-bearing ApcMin/+ mice were quantitatively compared to tumor-free Apc+/+ wild-type mice via in anima metabolic ...

  3. Recent discoveries concerning the involvement of transcription factors from the Grainyhead-like family in cancer.

    Science.gov (United States)

    Mlacki, Michal; Kikulska, Agnieszka; Krzywinska, Ewa; Pawlak, Magdalena; Wilanowski, Tomasz

    2015-11-01

    The Grainyhead-like (GRHL) family of transcription factors has three mammalian members, which are currently termed Grainyhead-like 1 (GRHL1), Grainyhead-like 2 (GRHL2), and Grainyhead-like 3 (GRHL3). These factors adopt a DNA-binding immunoglobulin fold homologous to the DNA-binding domain of key tumor suppressor p53. Their patterns of expression are tissue and developmentally specific. Earlier studies of the GRHL proteins focused on their functions in mammalian development. In recent years, these factors have been linked to many different types of cancer: squamous cell carcinoma of the skin, breast cancer, gastric cancer, hepatocellular carcinoma, colorectal cancer, clear cell renal cell carcinoma, neuroblastoma, prostate cancer, and cervical cancer. The roles of GRHL proteins in these various types of cancer are complex, and in some cases appear to be contradictory: they can serve to promote cancer development, or they may act as tumor suppressors, depending on the particular GRHL protein involved and on the cancer type. The reasons for obvious discrepancies in results from different studies remain unclear. At the molecular level, the GRHL transcription factors regulate the expression of genes whose products are involved in cellular proliferation, differentiation, adhesion, and polarity. We herein review the roles of GRHL proteins in cancer development, and we critically examine relevant molecular mechanisms, which were proposed by different authors. We also discuss the significance of recent discoveries implicating the involvement of GRHL transcription factors in cancer and highlight potential future applications of this knowledge in cancer treatment. PMID:26069269

  4. Extracellular vesicles – biomarkers and effectors of the cellular interactome in cancer

    Directory of Open Access Journals (Sweden)

    Janusz eRak

    2013-03-01

    Full Text Available In multicellular organisms both health and disease are defined by patterns of communications between the constituent cells. In addition to networks of soluble mediators, cells are also programmed to exchange complex messages pre-assembled as multimolecular cargo of membraneous structures known extracellular vesicles (EV. Several biogenetic pathways produce EVs with different properties and known as exosomes, ectosomes and apoptotic bodies. In cancer, EVs carry molecular signatures and effectors of the disease, such as mutant oncoproteins, oncogenic transcripts, microRNA and DNA sequences. Intercellular trafficking of such EVs (oncosomes may contribute to horizontal cellular transformation, phenotypic reprogramming and functional re-education of recipient cells, both locally and systemically. The EV-mediated, reciprocal molecular exchange also includes tumor suppressors, phosphoproteins, proteases, growth factors and bioactive lipids, all of which participate in the functional integration of multiple cells and their collective involved in tumor angiogenesis, inflammation, immunity, coagulopathy, mobilization of bone marrow derived effectors, metastasis, drug resistance or cellular stemness. In cases where the EV involvement is rate limiting their production and uptake may represent and unexplored anticancer therapy target. Moreover, oncosomes circulating in biofluids of cancer patients offer an unprecedented, remote and non-invasive access to crucial molecular information about cancer cells, including their driver mutations, classifiers, molecular subtypes, therapeutic targets and biomarkers of drug resistance. New nanotechnologies are being developed to exploit this unique biomarker platform. Indeed, embracing the notion that human cancers are defined not only by processes occurring within cancer cells, but also between them, and amidst the altered tumor and systemic microenvironment may open new diagnostic and therapeutic opportunities.

  5. Targeted biomarker profiling of matched primary and metastatic estrogen receptor positive breast cancers.

    Directory of Open Access Journals (Sweden)

    Erica B Schleifman

    Full Text Available Patients with newly diagnosed, early stage estrogen receptor positive (ER+ breast cancer often show disease free survival in excess of five years following surgery and systemic adjuvant therapy. An important question is whether diagnostic tumor tissue from the primary lesion offers an accurate molecular portrait of the cancer post recurrence and thus may be used for predictive diagnostic purposes for patients with relapsed, metastatic disease. As the class I phosphatidylinositol 3' kinase (PI3K pathway is frequently activated in ER+ breast cancer and has been linked to acquired resistance to hormonal therapy, we hypothesized pathway status could evolve over time and treatment. Biomarker analyses were conducted on matched, asynchronous primary and metastatic tumors from 77 patients with ER+ breast cancer. We examined whether PIK3CA and AKT1 alterations or PTEN and Ki67 levels showed differences between primary and metastatic samples. We also sought to look more broadly at gene expression markers reflective of proliferation, molecular subtype, and key receptors and signaling pathways using an mRNA analysis platform developed on the Fluidigm BioMark™ microfluidics system to measure the relative expression of 90 breast cancer related genes in formalin-fixed paraffin-embedded (FFPE tissue. Application of this panel of biomarker assays to matched tumor pairs showed a high concordance between primary and metastatic tissue, with generally few changes in mutation status, proliferative markers, or gene expression between matched samples. The collection of assays described here has been optimized for FFPE tissue and may have utility in exploratory analyses to identify patient subsets responsive to targeted therapies.

  6. Serum level of interleukin-17 and interleukin-35 as a biomarker for diagnosis of thyroid cancer

    Directory of Open Access Journals (Sweden)

    Yi Lu

    2015-01-01

    Full Text Available Objective: The aim of this study was to evaluate the serum level of interleukin-17 (IL-17 and IL-35 in thyroid cancer patients and its diagnostic value as a biomarker. Methods: Sixty-one thyroid carcinoma patients were recruited from January 2012 to December 2014 in our hospital. Of the 61 included cases, 42 subjects were pathology confirmed with thyroid cancer and other 19 cases were diagnosed with thyroid adenoma. The serum level of IL-17 and IL-35 were compared between the two groups. The diagnosed sensitivity, specificity, and receiver operating characteristic curve (ROC for serum IL-17 and IL-35 were evaluated according to Bayes theorem. Results: The serum level of IL-17 were 16.3 ± 4.1 pg/ml and 9.4 ± 3.6 pg/ml for the thyroid cancer and thyroid adenoma patients respectively, with statistical difference (P < 0.05. The serum level of IL-35 were 48.8 ± 7.8 pg/ml and 62.3 ± 9.6 pg/ml for the thyroid cancer and thyroid adenoma patients, respectively, which indicated that the thyroid adenoma group was much higher with statistical difference (P < 0.05. The diagnosis sensitivity and specificity for serum IL-17 were 71.4% and 80.2% at the cutoff value of 12.1 pg/ml with the area under the ROC of 0.8239. The diagnosis sensitivity and specificity for serum IL-35 were 76.8% and 82.4% at the cutoff value of 57.6 pg/ml with the area under the ROC of 0.8722. Conclusion: The serum level of IL-17 and IL-35 was significantly different between thyroid cancer and thyroid adenoma patients, which could be a potential biomarker for the diagnosis of malignant thyroid tumor.

  7. Protein Z: A putative novel biomarker for early detection of ovarian cancer.

    Science.gov (United States)

    Russell, Matthew R; Walker, Michael J; Williamson, Andrew J K; Gentry-Maharaj, Aleksandra; Ryan, Andy; Kalsi, Jatinderpal; Skates, Steven; D'Amato, Alfonsina; Dive, Caroline; Pernemalm, Maria; Humphryes, Phillip C; Fourkala, Evangelia-Ourania; Whetton, Anthony D; Menon, Usha; Jacobs, Ian; Graham, Robert L J

    2016-06-15

    Ovarian cancer (OC) has the highest mortality of all gynaecological cancers. Early diagnosis offers an approach to achieving better outcomes. We conducted a blinded-evaluation of prospectively collected preclinical serum from participants in the multimodal group of the United Kingdom Collaborative Trial of Ovarian Cancer Screening. Using isobaric tags (iTRAQ) we identified 90 proteins differentially expressed between OC cases and controls. A second targeted mass spectrometry analysis of twenty of these candidates identified Protein Z as a potential early detection biomarker for OC. This was further validated by ELISA analysis in 482 serial serum samples, from 80 individuals, 49 OC cases and 31 controls, spanning up to 7 years prior to diagnosis. Protein Z was significantly down-regulated up to 2 years pre-diagnosis (p = 0.000000411) in 8 of 19 Type I patients whilst in 5 Type II individuals, it was significantly up-regulated up to 4 years before diagnosis (p = 0.01). ROC curve analysis for CA-125 and CA-125 combined with Protein Z showed a statistically significant (p= 0.00033) increase in the AUC from 77 to 81% for Type I and a statistically significant (p= 0.00003) increase in the AUC from 76 to 82% for Type II. Protein Z is a novel independent early detection biomarker for Type I and Type II ovarian cancer; which can discriminate between both types. Protein Z also adds to CA-125 and potentially the Risk of Ovarian Cancer algorithm in the detection of both subtypes. PMID:26815306

  8. The Effect of Atorvastatin on Breast Cancer Biomarkers in High-Risk Women.

    Science.gov (United States)

    Ji, YongLi; Rounds, Tiffany; Crocker, Abigail; Sussman, Betsy; Hovey, Russell C; Kingsley, Fonda; Muss, Hyman B; Garber, Judy E; Wood, Marie E

    2016-05-01

    Statins have the potential to reduce breast cancer incidence and recurrence as shown in both epidemiologic and laboratory studies. The purpose of this study was to evaluate the effect of a lipophilic statin, atorvastatin, on breast cancer biomarkers of risk [mammographic density (MD) and insulin growth factor 1 (IGF-1)] in high-risk premenopausal women.Premenopausal women at increased risk for breast cancer received either 40 mg of atorvastatin or placebo for 1 year. Biomarker assessment was performed prior to initiation and at completion of study medication. MD was determined using both Breast Imaging Reporting and Data System and the visual analogue scale. Serum IGF-1 was determined by ELISA assay at the end of the study.Sixty-three women were enrolled between December 2005 and May 2010. Sixteen (25%) women withdrew. The mean age of participants was 43 (range, 35-50), 100% were white, and the average body mass index (BMI) was 26.4. The statin group demonstrated a significant decrease in cholesterol and low-density lipoprotein (LDL), suggesting compliance with study medication. After accounting for BMI, there was no difference in change in MD between groups. There was a significant increase in serum IGF-1 in the statin group.In this multi-institutional randomized prospective clinical trial of premenopausal women at increased risk for breast cancer, we did not see an effect of atorvastatin on MD. Further investigation of statins may be warranted; however, design of prior trials and potential mechanism of action of the agent need to be considered in the design of future trials. Cancer Prev Res; 9(5); 379-84. ©2016 AACR. PMID:26908565

  9. Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness.

    Directory of Open Access Journals (Sweden)

    Guro F Giskeødegård

    Full Text Available Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients with a high cancer content (mean: 61.8% were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS. Multivariate analysis (PLS, PLS-DA and absolute quantification (LCModel were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30 and high grade (GS≥7, n = 81 cancer with normal adjacent tissue (n = 47. High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044 and citrate (p = 7.73·10(-4, and an increase in the clinically applied (total choline+creatine+polyamines/citrate (CCP/C ratio (p = 2.17·10(-4. The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71, and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.

  10. Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

    Directory of Open Access Journals (Sweden)

    Shen Hu

    2010-09-01

    Full Text Available Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC. A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B. We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients.

  11. Circulating Fibroblast Growth Factor 21 (Fgf21) as Diagnostic and Prognostic Biomarker in Renal Cancer

    Science.gov (United States)

    Knott, ME; Minatta, JN; Roulet, L; Gueglio, G; Pasik, L; Ranuncolo, SM; Nuñez, M; Puricelli, L; De Lorenzo, MS

    2016-01-01

    Background The finding of new biomarkers is needed to have a better sub-classification of primary renal tumors (RCC) as well as more reliable predictors of outcome and therapy response. In this study, we evaluated the role of circulating FGF21, an endocrine factor, as a diagnostic and prognostic biomarker for ccRCC. Materials and Methods Serum samples from healthy controls (HC), clear cell and chromophobe RCC cancer patients were obtained from the serum biobank “Biobanco Público de Muestras Séricas Oncológicas” (BPMSO) of the “Instituto de Oncología “Ángel H. Roffo”. Serum FGF21 and leptin were measured by ELISA while other metabolic markers were measured following routinely clinical procedures. Results One of our major findings was that FGF21 levels were significantly increased in ccRCC patients compared with HC. Moreover, we showed an association between the increased serum FGF21 levels and the shorter disease free survival in a cohort of 98 ccRCC patients, after adjustment for other predictors of outcome. Conclusion Our results suggest that higher FGF21 serum level is an independent prognostic biomarker, associated with worse free-disease survival. PMID:27358750

  12. The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

    Science.gov (United States)

    de Franciscis, Stefano; Metzinger, Laurent; Serra, Raffaele

    2016-01-01

    Cardiovascular disease (CD) and peripheral vascular disease (PVD) are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD. PMID:27298828

  13. Biomarker candidate discovery in Atlantic cod (Gadus morhua) continuously exposed to North Sea produced water from egg to fry

    DEFF Research Database (Denmark)

    Bohne-Kjersem, Anneli; Bache, Nicolai; Meier, Sonnich;

    2010-01-01

    In this study Atlantic cod (Gadus morhua) were exposed to different levels of North Sea produced water (PW) and 17beta-oestradiol (E(2)), a natural oestrogen, from egg to fry stage (90 days). By comparing changes in protein expression following E(2) exposure to changes induced by PW treatment, we...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

  14. Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Nørskov, Natalja; Yde, Christian Clement;

    2015-01-01

    stability of the selected variables. The performance of the method was evaluated using a simulated data set and a multi-block data set from a dietary intervention study with pigs used as model for humans. The objective of the study was to investigate the biochemical effects in plasma after dietary...... intervention with breads varying in types of dietary fiber and to identify potential biomarkers. By introducing Sparse MBPLSR, we aimed at identifying the biomarkers where data from LC–MS and NMR instruments were analyzed simultaneously and therefore in addition we intended to explore the relationships among...

  15. Noncoding RNA Expression Aberration Is Associated with Cancer Progression and Is a Potential Biomarker in Esophageal Squamous Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Hidetaka Sugihara

    2015-11-01

    Full Text Available Esophageal cancer is one of the most common cancers worldwide. Esophageal squamous cell carcinoma (ESCC is the major histological type of esophageal cancer in Eastern Asian countries. Several types of noncoding RNAs (ncRNAs function as key epigenetic regulators of gene expression and are implicated in various physiological processes. Unambiguous evidence indicates that dysregulation of ncRNAs is deeply implicated in carcinogenesis, cancer progression and metastases of various cancers, including ESCC. The current review summarizes recent findings on the ncRNA-mediated mechanisms underlying the characteristic behaviors of ESCC that will help support the development of biomarkers and the design of novel therapeutic strategies.

  16. Oncoprotein DEK as a tissue and urinary biomarker for bladder cancer

    International Nuclear Information System (INIS)

    Bladder cancer is a significant healthcare problem in the United States of America with a high recurrence rate. Early detection of bladder cancer is essential for removing the tumor with preservation of the bladder, avoiding metastasis and hence improving prognosis and long-term survival. The objective of this study was to analyze the presence of DEK protein in voided urine of bladder cancer patients as a urine-based bladder cancer diagnostic test. We examined the expression of DEK protein by western blot in 38 paired transitional cell carcinoma (TCC) bladder tumor tissues and adjacent normal tissue. The presence of DEK protein in voided urine was analyzed by western blot in 42 urine samples collected from patients with active TCC, other malignant urogenital disease and healthy individuals. The DEK protein is expressed in 33 of 38 bladder tumor tissues with no expression in adjacent normal tissue. Based on our sample size, DEK protein is expressed in 100% of tumors of low malignant potential, 92% of tumors of low grade and in 71% of tumors of high grade. Next, we analyzed 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals for DEK protein expression by western blot analysis. We are the first to show that the DEK protein is present in the urine of bladder cancer patients. Approximately 84% of TCC patient urine specimens were positive for urine DEK. Based on our pilot study of 38 bladder tumor tissue and 42 urine samples from patients with active TCC, other malignant urogenital disease, non-malignant urogenital disease and healthy individuals; DEK protein is expressed in bladder tumor tissue and voided urine of bladder cancer patients. The presence of DEK protein in voided urine is potentially a suitable biomarker for bladder cancer and that the screening for the presence of DEK protein in urine can be explored as a noninvasive diagnostic test for bladder cancer

  17. iTRAQ identification of candidate serum biomarkers associated with metastatic progression of human prostate cancer.

    Science.gov (United States)

    Rehman, Ishtiaq; Evans, Caroline A; Glen, Adam; Cross, Simon S; Eaton, Colby L; Down, Jenny; Pesce, Giancarlo; Phillips, Joshua T; Yen, Ow Saw; Thalmann, George N; Wright, Phillip C; Hamdy, Freddie C

    2012-01-01

    A major challenge in the management of patients with prostate cancer is identifying those individuals at risk of developing metastatic disease, as in most cases the disease will remain indolent. We analyzed pooled serum samples from 4 groups of patients (n = 5 samples/group), collected prospectively and actively monitored for a minimum of 5 yrs. Patients groups were (i) histological diagnosis of benign prostatic hyperplasia with no evidence of cancer 'BPH', (ii) localised cancer with no evidence of progression, 'non-progressing' (iii) localised cancer with evidence of biochemical progression, 'progressing', and (iv) bone metastasis at presentation 'metastatic'. Pooled samples were immuno-depleted of the 14 most highly abundant proteins and analysed using a 4-plex iTRAQ approach. Overall 122 proteins were identified and relatively quantified. Comparisons of progressing versus non-progressing groups identified the significant differential expression of 25 proteins (pfactor 1 alpha 1 (eEF1A1), one of the candidates identified, was significantly higher in osteoblasts in close proximity to metastatic tumour cells compared with osteoblasts in control bone (p = 0.0353, Mann Whitney U). Our proteomic approach has identified leads for potentially useful serum biomarkers associated with the metastatic progression of prostate cancer. The panels identified, including eEF1A1 warrant further investigation and validation. PMID:22355332

  18. Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

    Directory of Open Access Journals (Sweden)

    Ioannis Valavanis

    2015-11-01

    Full Text Available DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies.

  19. Scientific basis of biomarkers and benefits of functional foods for reduction of disease risk: cancer.

    Science.gov (United States)

    Rafter, Joseph J

    2002-11-01

    One of the most promising areas for the development of functional foods lies in modification of the activity of the gastrointestinal tract by use of probiotics, prebiotics and synbiotics. While a myriad of healthful effects have been attributed to the probiotic lactic acid bacteria, perhaps the most controversial remains that of anticancer activity. However, it must be emphasised that, to date, there is no direct experimental evidence for cancer suppression in man as a result of consumption of lactic cultures in fermented or unfermented dairy products, although there is a wealth of indirect evidence, based largely on laboratory studies. Presently, there are a large number of biomarkers available for assessing colon cancer risk in dietary intervention studies, which are validated to varying degrees. These include colonic mucosal markers, faecal water markers and immunological markers. Overwhelming evidence from epidemiological, in vivo, in vitro and clinical trial data indicates that a plant-based diet can reduce the risk of chronic disease, particularly cancer. It is now clear that there are components in a plant-based diet other than traditional nutrients that can reduce cancer risk. More than a dozen classes of these biologically active plant chemicals, now known as 'phytochemicals', have been identified. Although the vast number of naturally occurring health-enhancing substances appear to be of plant origin, there are a number of physiologically active components in animal products (such as the probiotics referred to above) that deserve attention for their potential role in cancer prevention. PMID:12495463

  20. LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

    Science.gov (United States)

    González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

    2012-03-01

    Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense. PMID:22234525

  1. Chromosomal aberrations in lymphocytes predict human cancer: a report from the European Study Group on Cytogenetic Biomarkers and Health (ESCH)

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U; Brøgger, A; Knudsen, Lisbeth E.; Norppa, H; Reuterwall, C

    1998-01-01

    .35-2.89) was obtained for those with a high CA frequency level, whereas the SMRs for those with medium or low did not noticeably differ from unity. Cox's proportional hazards models gave no evidence that the effect of CAs on total cancer incidence/mortality was modified by gender, age at test, or time since...... test. No association was seen between the SCEs or the MN frequencies and subsequent cancer incidence/mortality. The present study further supports our previous observation on the cancer predictivity of the CA biomarker, which seems to be independent of age at test, gender, and time since test. The risk...... patterns were similar within each national cohort. This result suggests that the frequency of CAs in peripheral blood lymphocytes is a relevant biomarker for cancer risk in humans, reflecting either early biological effects of genotoxic carcinogens or individual cancer susceptibility....

  2. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    Science.gov (United States)

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  3. Proteomic profiling of mammary carcinomas identifies C7orf24, a gamma-glutamyl cyclotransferase, as a potential cancer biomarker

    DEFF Research Database (Denmark)

    Gromov, Pavel; Gromova, Irina; Friis, Esbern;

    2010-01-01

    Breast cancer is the leading cause of cancer deaths in women today and is the most common cancer (excluding skin cancers) among women in the Western world. Although cancers detected by screening mammography are significantly smaller than nonscreening ones, noninvasive biomarkers for detection...... found in other cancer types. Four of these were investigated in greater detail, and we found that a proportion of tumors (58% in cervical, 38% in lung, 72% in colon, and 46% in breast cancer) expressed C7orf24 at levels exceeding those seen in normal samples. The observed overexpression of this protein...... in different types of cancer suggests deregulation of C7orf24 to be a general event in epithelial carcinogenesis, indicating that this protein may play an important role in cancer cell biology and thus constitute a novel therapeutic target. Furthermore, as C7orf24 is externalized to the tissue extracellular...

  4. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    International Nuclear Information System (INIS)

    YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer

  5. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, Nicolai A. [Departments of Surgical Gastroenterology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark); Johansen, Julia S., E-mail: julia.johansen@post3.tele.dk [Departments of Oncology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark); Departments of Medicine, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark)

    2010-07-12

    YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer.

  6. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    Directory of Open Access Journals (Sweden)

    Julia S. Johansen

    2010-07-01

    Full Text Available YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer.

  7. Biomarker discovery with SELDI-TOF MS in human urine associated with early renal injury : evaluation with computational analytical tools.

    NARCIS (Netherlands)

    Houtte, K.J.A. van; Laarakkers, C.; Marchiori, E.; Pickkers, P.; Wetzels, J.F.M.; Willems, J.L.; Heuvel, L.P.W.J. van den; Russel, F.G.M.; Masereeuw, R.

    2007-01-01

    BACKGROUND: Urine proteomics is one of the key emerging technologies to discover new biomarkers for renal disease, which may be used in the early diagnosis, prognosis and treatment of patients. In the present study, we validated surface-enhanced laser desorption/ionization time-of-flight mass spectr

  8. Regulatory Forum Opinion Piece*: Veterinary Pathologists in Translational Pharmacology and Biomarker Integration in Drug Discovery and Development.

    Science.gov (United States)

    Ramaiah, Shashi K; Walker, Dana B

    2016-02-01

    This article highlights emerging roles for veterinary pathologists outside of traditional functions and in line with the translational research (TR) approach. Veterinary pathologists offer unique and valuable expertise toward addressing particular TR and associated translational pharmacology questions, identifying gaps and risks in biomarker and pathology strategies, and advancing TR team decision making. Veterinary pathologists' attributes that are integral to the TR approach include (i) well-developed understanding of comparative physiology, pathology, and disease; (ii) extensive experience in interpretation and integration of complex data sets on whole-body responses and utilizing this for deciphering pathogenesis and translating events between laboratory species and man; (iii) proficiency in recognizing differences in disease end points among individuals, animal species and strains, and assessing correlations between these differences and other investigative (including biomarker) findings; and (iv) strong background in a wide spectrum of research technologies that can address pathomechanistic questions and biomarker needs. Some of the more evident roles in which veterinary pathologists can offer their greatest contributions to address questions and strategies of TR and biomarker integration will be emphasized. PMID:26839329

  9. Discovery of coding genetic variants influencing diabetes-related serum biomarkers and their impact on risk of type 2 diabetes

    DEFF Research Database (Denmark)

    Ahluwalia, Tarunveer Singh; Allin, Kristine Højgaard; Sandholt, Camilla Helene;

    2015-01-01

    biomarkers associated with T2D: adiponectin, C-reactive protein, ferritin, heat shock 70-kDa protein 1B, IGF binding protein 1 and IGF binding protein 2, IL-18, IL-2 receptor-α, and leptin. DESIGN AND PARTICIPANTS: A population-based sample of 6215 adult Danes was genotyped for 16 340 coding single...... therapeutic strategies....

  10. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    Science.gov (United States)

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  11. An evaluation of logic regression-based biomarker discovery across multiple intergenic regions for predicting host specificity in Escherichia coli.

    Science.gov (United States)

    Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Banting, Graham; Edge, Thomas A; Topp, Edward; McAllister, Tim A; Neumann, Norman F

    2016-10-01

    Several studies have demonstrated that E. coli appears to display some level of host adaptation and specificity. Recent studies in our laboratory support these findings as determined by logic regression modeling of single nucleotide polymorphisms (SNP) in intergenic regions (ITGRs). We sought to determine the degree of host-specific information encoded in various ITGRs across a library of animal E. coli isolates using both whole genome analysis and a targeted ITGR sequencing approach. Our findings demonstrated that ITGRs across the genome encode various degrees of host-specific information. Incorporating multiple ITGRs (i.e., concatenation) into logic regression model building resulted in greater host-specificity and sensitivity outcomes in biomarkers, but the overall level of polymorphism in an ITGR did not correlate with the degree of host-specificity encoded in the ITGR. This suggests that distinct SNPs in ITGRs may be more important in defining host-specificity than overall sequence variation, explaining why traditional unsupervised learning phylogenetic approaches may be less informative in terms of revealing host-specific information encoded in DNA sequence. In silico analysis of 80 candidate ITGRs from publically available E. coli genomes was performed as a tool for discovering highly host-specific ITGRs. In one ITGR (ydeR-yedS) we identified a SNP biomarker that was 98% specific for cattle and for which 92% of all E. coli isolates originating from cattle carried this unique biomarker. In the case of humans, a host-specific biomarker (98% specificity) was identified in the concatenated ITGR sequences of rcsD-ompC, ydeR-yedS, and rclR-ykgE, and for which 78% of E. coli originating from humans carried this biomarker. Interestingly, human-specific biomarkers were dominant in ITGRs regulating antibiotic resistance, whereas in cattle host-specific biomarkers were found in ITGRs involved in stress regulation. These data suggest that evolution towards host

  12. Emerging Glycolysis Targeting and Drug Discovery from Chinese Medicine in Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Zhiyu Wang

    2012-01-01

    Full Text Available Molecular-targeted therapy has been developed for cancer chemoprevention and treatment. Cancer cells have different metabolic properties from normal cells. Normal cells mostly rely upon the process of mitochondrial oxidative phosphorylation to produce energy whereas cancer cells have developed an altered metabolism that allows them to sustain higher proliferation rates. Cancer cells could predominantly produce energy by glycolysis even in the presence of oxygen. This alternative metabolic characteristic is known as the “Warburg Effect.” Although the exact mechanisms underlying the Warburg effect are unclear, recent progress indicates that glycolytic pathway of cancer cells could be a critical target for drug discovery. With a long history in cancer treatment, traditional Chinese medicine (TCM is recognized as a valuable source for seeking bioactive anticancer compounds. A great progress has been made to identify active compounds from herbal medicine targeting on glycolysis for cancer treatment. Herein, we provide an overall picture of the current understanding of the molecular targets in the cancer glycolytic pathway and reviewed active compounds from Chinese herbal medicine with the potentials to inhibit the metabolic targets for cancer treatment. Combination of TCM with conventional therapies will provide an attractive strategy for improving clinical outcome in cancer treatment.

  13. Salivary microRNAs as promising biomarkers for detection of esophageal cancer.

    Directory of Open Access Journals (Sweden)

    Zijun Xie

    Full Text Available BACKGROUND AND PURPOSE: Tissue microRNAs (miRNAs can detect cancers and predict prognosis. Several recent studies reported that tissue, plasma, and saliva miRNAs share similar expression profiles. In this study, we investigated the discriminatory power of salivary miRNAs (including whole saliva and saliva supernatant for detection of esophageal cancer. MATERIALS AND METHODS: By Agilent microarray, six deregulated miRNAs from whole saliva samples from seven patients with esophageal cancer and three healthy controls were selected. The six selected miRNAs were subjected to validation of their expression levels by RT-qPCR using both whole saliva and saliva supernatant samples from an independent set of 39 patients with esophageal cancer and 19 healthy controls. RESULTS: Six miRNAs (miR-10b*, miR-144, miR-21, miR-451, miR-486-5p, and miR-634 were identified as targets by Agilent microarray. After validation by RT-qPCR, miR-10b*, miR-144, and miR-451 in whole saliva and miR-10b*, miR-144, miR-21, and miR-451 in saliva supernatant were significantly upregulated in patients, with sensitivities of 89.7, 92.3, 84.6, 79.5, 43.6, 89.7, and 51.3% and specificities of 57.9, 47.4, 57.9%, 57.9, 89.5, 47.4, and 84.2%, respectively. CONCLUSIONS: We found distinctive miRNAs for esophageal cancer in both whole saliva and saliva supernatant. These miRNAs possess discriminatory power for detection of esophageal cancer. Because saliva collection is noninvasive and convenient, salivary miRNAs show great promise as biomarkers for detection of esophageal cancer in areas at high risk.

  14. Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2013-01-01

    Full Text Available Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

  15. Screening biomarkers of bladder cancer using combined miRNA and mRNA microarray analysis.

    Science.gov (United States)

    Jin, Ning; Jin, Xuefei; Gu, Xinquan; Na, Wanli; Zhang, Muchun; Zhao, Rui

    2015-08-01

    Biomarkers, such as microRNAs (miRNAs) may be useful for the diagnosis of bladder cancer. In order to understand the molecular mechanisms underlying bladder cancer, differentially expressed miRNAs (DE-miRNAs) and their target genes in bladder cancer were analyzed. In the present study, miRNA and mRNA expression profiles (GSE40355) were obtained from the Gene Expression Omnibus. These consisted of healthy bladder samples (n=8) and urothelial carcinoma samples (low-grade, n=8 and high-grade, n=8). DE-miRNAs and differentially expressed genes (DEGs) were identified using the limma package and the Benjamin and Hochberg method from the multtest package in R. Target genes of DE-miRNAs were screened. Associations between DEGs were investigated using STRING, and an interaction network was constructed using Cytoscape. Functional and pathway enrichment analyses were performed for DEGs from the interaction network. 87 DE-miRNAs and 2058 DEGs were screened from low-grade bladder cancer samples, and 40 DE-miRNAs and 2477 DEGs were screened from high-grade bladder cancer samples. DE-target genes were significantly associated with the regulation of cell apoptosis. Bladder cancer, non-small cell lung cancer and pancreatic cancer biological pathways were found to be enriched. The results of the present study demonstrated that E2F transcription factor 1, which is targeted by miR-106b, and cyclin-dependent kinase inhibitor 2A (CDKN2A) and V-Erb-B2 avian erythroblastic leukemia viral oncogene homolog-2, which are targeted by miR-125b, participate in the bladder cancer pathway. In conclusion, DE-miRNAs in bladder cancer tissue samples and DE-targeted genes, such as miR-106b and CDKN2A, which were identified in the present study, may provide the basis for targeted therapy for breast cancer and enhance understanding of its pathogenesis. PMID:25955758

  16. TMPRSS2-ERG -specific transcriptional modulation is associated with prostate cancer biomarkers and TGF-β signaling

    International Nuclear Information System (INIS)

    TMPRSS2-ERG gene fusions occur in about 50% of all prostate cancer cases and represent promising markers for molecular subtyping. Although TMPRSS2-ERG fusion seems to be a critical event in prostate cancer, the precise functional role in cancer development and progression is still unclear. We studied large-scale gene expression profiles in 47 prostate tumor tissue samples and in 48 normal prostate tissue samples taken from the non-suspect area of clinical low-risk tumors using Affymetrix GeneChip Exon 1.0 ST microarrays. Comparison of gene expression levels among TMPRSS2-ERG fusion-positive and negative tumors as well as benign samples demonstrated a distinct transcriptional program induced by the gene fusion event. Well-known biomarkers for prostate cancer detection like CRISP3 were found to be associated with the gene fusion status. WNT and TGF-β/BMP signaling pathways were significantly associated with genes upregulated in TMPRSS2-ERG fusion-positive tumors. The TMPRSS2-ERG gene fusion results in the modulation of transcriptional patterns and cellular pathways with potential consequences for prostate cancer progression. Well-known biomarkers for prostate cancer detection were found to be associated with the gene fusion. Our results suggest that the fusion status should be considered in retrospective and future studies to assess biomarkers for prostate cancer detection, progression and targeted therapy

  17. TMPRSS2-ERG -specific transcriptional modulation is associated with prostate cancer biomarkers and TGF-β signaling

    Directory of Open Access Journals (Sweden)

    Brase Jan C

    2011-12-01

    Full Text Available Abstract Background TMPRSS2-ERG gene fusions occur in about 50% of all prostate cancer cases and represent promising markers for molecular subtyping. Although TMPRSS2-ERG fusion seems to be a critical event in prostate cancer, the precise functional role in cancer development and progression is still unclear. Methods We studied large-scale gene expression profiles in 47 prostate tumor tissue samples and in 48 normal prostate tissue samples taken from the non-suspect area of clinical low-risk tumors using Affymetrix GeneChip Exon 1.0 ST microarrays. Results Comparison of gene expression levels among TMPRSS2-ERG fusion-positive and negative tumors as well as benign samples demonstrated a distinct transcriptional program induced by the gene fusion event. Well-known biomarkers for prostate cancer detection like CRISP3 were found to be associated with the gene fusion status. WNT and TGF-β/BMP signaling pathways were significantly associated with genes upregulated in TMPRSS2-ERG fusion-positive tumors. Conclusions The TMPRSS2-ERG gene fusion results in the modulation of transcriptional patterns and cellular pathways with potential consequences for prostate cancer progression. Well-known biomarkers for prostate cancer detection were found to be associated with the gene fusion. Our results suggest that the fusion status should be considered in retrospective and future studies to assess biomarkers for prostate cancer detection, progression and targeted therapy.

  18. Predictive and Prognostic Protein Biomarkers in Epithelial Ovarian Cancer: Recommendation for Future Studies

    International Nuclear Information System (INIS)

    Epithelial ovarian cancer is the most lethal gynecological malignancy. Due to its lack of symptoms, this disease is diagnosed at an advanced stage when the cancer has already spread to secondary sites. While initial rates of response to first treatment is >80%, the overall survival rate of patients is extremely low, mainly due to development of drug resistance. To date, there are no reliable clinical factors that can properly stratify patients for suitable chemotherapy strategies. Clinical parameters such as disease stage, tumor grade and residual disease, although helpful in the management of patients after their initial surgery to establish the first line of treatment, are not efficient enough. Accordingly, reliable markers that are independent and complementary to clinical parameters are needed for a better management of these patients. For several years, efforts to identify prognostic factors have focused on molecular markers, with a large number having been investigated. This review aims to present a summary of the recent advances in the identification of molecular biomarkers in ovarian cancer patient tissues, as well as an overview of the need and importance of molecular markers for personalized medicine in ovarian cancer

  19. Predictive and Prognostic Protein Biomarkers in Epithelial Ovarian Cancer: Recommendation for Future Studies

    Directory of Open Access Journals (Sweden)

    Cécile Le Page

    2010-05-01

    Full Text Available Epithelial ovarian cancer is the most lethal gynecological malignancy. Due to its lack of symptoms, this disease is diagnosed at an advanced stage when the cancer has already spread to secondary sites. While initial rates of response to first treatment is >80%, the overall survival rate of patients is extremely low, mainly due to development of drug resistance. To date, there are no reliable clinical factors that can properly stratify patients for suitable chemotherapy strategies. Clinical parameters such as disease stage, tumor grade and residual disease, although helpful in the management of patients after their initial surgery to establish the first line of treatment, are not efficient enough. Accordingly, reliable markers that are independent and complementary to clinical parameters are needed for a better management of these patients. For several years, efforts to identify prognostic factors have focused on molecular markers, with a large number having been investigated. This review aims to present a summary of the recent advances in the identification of molecular biomarkers in ovarian cancer patient tissues, as well as an overview of the need and importance of molecular markers for personalized medicine in ovarian cancer.

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

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, Brian M., E-mail: bmalexander@lroc.harvard.edu [Department of Radiation Oncology, Dana-Farber/Brigham and Women' s Cancer Center, Boston, Massachusetts (United States); Wang Xiaozhe [On-Q-ity, Inc., Waltham, Massachusetts (United States); Niemierko, Andrzej [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States); Weaver, David T. [On-Q-ity, Inc., Waltham, Massachusetts (United States); Mak, Raymond H. [Department of Radiation Oncology, Dana-Farber/Brigham and Women' s Cancer Center, Boston, Massachusetts (United States); Roof, Kevin S. [Southeast Radiation Oncology, Charlotte, North Carolina (United States); Fidias, Panagiotis [Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts (United States); Wain, John [Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts (United States); Choi, Noah C. [Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts (United States)

    2012-05-01

    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