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Sample records for cancer biomarker discovery

  1. Using Aptamers for Cancer Biomarker Discovery

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    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.

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

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    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.

  3. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

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    Lu, Ming; Faull, Kym F.; Whitelegge, Julian P.; He, Jianbo; Shen, Dejun; Saxton, Romaine E.; Chang, Helena R.

    2007-01-01

    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. PMID:19662217

  4. Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

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    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.

  5. A Facile Nanoparticle Immunoassay for Cancer Biomarker Discovery

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    Baker Cheryl H

    2011-05-01

    Full Text Available Abstract Background Gold nanoparticles (AuNPs scatter light intensely at or near their surface plasmon wavelength region. Using AuNPs coupled with dynamic light scattering (DLS detection, we developed a facile nanoparticle immunoassay for serum protein biomarker detection and analysis. A serum sample was first mixed with a citrate-protected AuNP solution. Proteins from the serum were adsorbed to the AuNPs to form a protein corona on the nanoparticle surface. An antibody solution was then added to the assay solution to analyze the target proteins of interest that are present in the protein corona. The protein corona formation and the subsequent binding of antibody to the target proteins in the protein corona were detected by DLS. Results Using this simple assay, we discovered multiple molecular aberrations associated with prostate cancer from both mice and human blood serum samples. From the mice serum study, we observed difference in the size of the protein corona and mouse IgG level between different mice groups (i.e., mice with aggressive or less aggressive prostate cancer, and normal healthy controls. Furthermore, it was found from both the mice model and the human serum sample study that the level of vascular endothelial growth factor (VEGF, a protein that is associated with tumor angiogenesis adsorbed to the AuNPs is decreased in cancer samples compared to non-cancerous or less malignant cancer samples. Conclusion The molecular aberrations observed from this study may become new biomarkers for prostate cancer detection. The nanoparticle immunoassay reported here can be used as a convenient and general tool to screen and analyze serum proteins and to discover new biomarkers associated with cancer and other human diseases.

  6. Discovery and development of DNA methylation-based biomarkers for lung cancer.

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    Walter, Kimberly; Holcomb, Thomas; Januario, Tom; Yauch, Robert L; Du, Pan; Bourgon, Richard; Seshagiri, Somasekar; Amler, Lukas C; Hampton, Garret M; S Shames, David

    2014-02-01

    Lung cancer remains the primary cause of cancer-related deaths worldwide. Improved tools for early detection and therapeutic stratification would be expected to increase the survival rate for this disease. Alterations in the molecular pathways that drive lung cancer, which include epigenetic modifications, may provide biomarkers to help address this major unmet clinical need. Epigenetic changes, which are defined as heritable changes in gene expression that do not alter the primary DNA sequence, are one of the hallmarks of cancer, and prevalent in all types of cancer. These modifications represent a rich source of biomarkers that have the potential to be implemented in clinical practice. This perspective describes recent advances in the discovery of epigenetic biomarkers in lung cancer, specifically those that result in the methylation of DNA at CpG sites. We discuss one approach for methylation-based biomarker assay development that describes the discovery at a genome-scale level, which addresses some of the practical considerations for design of assays that can be implemented in the clinic. We emphasize that an integrated technological approach will enable the development of clinically useful DNA methylation-based biomarker assays. While this article focuses on current literature and primary research findings in lung cancer, the principles we describe here apply to the discovery and development of epigenetic biomarkers for other types of cancer.

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

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    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.

  8. Proteomics in Cancer Biomarkers Discovery: Challenges and Applications

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    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.

  9. Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application.

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    Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

    2017-01-01

    There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed.

  10. Mass spectrometry-assisted gel-based proteomics in cancer biomarker discovery: approaches and application

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    Huang, Rongrong; Chen, Zhongsi; He, Lei; He, Nongyue; Xi, Zhijiang; Li, Zhiyang; Deng, Yan; Zeng, Xin

    2017-01-01

    There is a critical need for the discovery of novel biomarkers for early detection and targeted therapy of cancer, a major cause of deaths worldwide. In this respect, proteomic technologies, such as mass spectrometry (MS), enable the identification of pathologically significant proteins in various types of samples. MS is capable of high-throughput profiling of complex biological samples including blood, tissues, urine, milk, and cells. MS-assisted proteomics has contributed to the development of cancer biomarkers that may form the foundation for new clinical tests. It can also aid in elucidating the molecular mechanisms underlying cancer. In this review, we discuss MS principles and instrumentation as well as approaches in MS-based proteomics, which have been employed in the development of potential biomarkers. Furthermore, the challenges in validation of MS biomarkers for their use in clinical practice are also reviewed. PMID:28912895

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

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    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.

  12. Metabolomics Toward Biomarker Discovery.

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    Yin, Peiyuan; Xu, Guowang

    2017-01-01

    Metabolomics has been used as practical tool in the discovery of novel biomarkers in a broad area in the clinic. The analytical platforms including nuclear magnetic resonance (NMR) and mass spectrometry (MS) can cover thousands of metabolites. With the help of multivariate data analysis, many potential biomarkers can be defined in the studies. Since metabolites stand at the end point of metabolism, it remains difficult to find novel biomarkers with good diagnostic or prognostic performance. In this chapter, we will introduce a general protocol for biomarker discovery within the scope of metabolomics using MS.

  13. Use of a Single-Chain Antibody Library for Ovarian Cancer Biomarker Discovery*

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    Ramirez, Arturo B.; Loch, Christian M.; Zhang, Yuzheng; Liu, Yan; Wang, Xiaohong; Wayner, Elizabeth A.; Sargent, Jonathon E.; Sibani, Sahar; Hainsworth, Eugenie; Mendoza, Eliseo A.; Eugene, Ralph; LaBaer, Joshua; Urban, Nicole D.; McIntosh, Martin W.; Lampe, Paul D.

    2010-01-01

    The discovery of novel early detection biomarkers of disease could offer one of the best approaches to decrease the morbidity and mortality of ovarian and other cancers. We report on the use of a single-chain variable fragment antibody library for screening ovarian serum to find novel biomarkers for the detection of cancer. We alternately panned the library with ovarian cancer and disease-free control sera to make a sublibrary of antibodies that bind proteins differentially expressed in cancer. This sublibrary was printed on antibody microarrays that were incubated with labeled serum from multiple sets of cancer patients and controls. The antibodies that performed best at discriminating disease status were selected, and their cognate antigens were identified using a functional protein microarray. Overexpression of some of these antigens was observed in cancer serum, tumor proximal fluid, and cancer tissue via dot blot and immunohistochemical staining. Thus, our use of recombinant antibody microarrays for unbiased discovery found targets for ovarian cancer detection in multiple sample sets, supporting their further study for disease diagnosis. PMID:20467042

  14. Computational and Experimental Approaches to Cancer Biomarker Discovery

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    Krzystanek, Marcin

    at least two fundamental mechanisms responsible for DNA aberrations present in a given tumor: 1) active mutational processes caused either by endogenous or exogenous factors, for example chemical agents such as tobacco smoke or cancer cytotoxics, or by active enzymatic processes such as APOBEC related...... mutagenesis; and 2) the integrity of endogenous DNA repair processes as exemplified by BRCA1/2 dysfunction or MMR deficiency. Since lack of a given DNA repair process may make tumors particularly sensitive to certain types of therapy, identification of such defects will allow for potential enhancements...... of the therapy efficacy. State of the art mutational signatures are derived mathematically using nonnegative matrix factorization to solve a blind source separation problem arising from a multitude of mutational processes that form the observable mutational catalogs. In my ongoing projects I address this issue...

  15. Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification.

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    Fu, Shuyue; Liu, Xiang; Luo, Maochao; Xie, Ke; Nice, Edouard C; Zhang, Haiyuan; Huang, Canhua

    2017-04-01

    Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.

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

    DEFF Research Database (Denmark)

    Vieira Campos, Diana Alexandra; Freitas, Daniela; Gomes, Joana

    2015-01-01

    biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SC lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses...... at least partially truncated O-glycans. Overall we identified 499 O-glycoproteins and 1,236 O-glycosites in gastric cancer SCs, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer...... with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to demonstrate that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set...

  17. [Search for breast cancer-related biomarker proteins for drug discovery].

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    Nagano, Kazuya

    2010-12-01

    The identification of biomarkers is a promising approach for the diagnosis and effective therapy of cancer. In particular, disease proteomics is a potentially useful method for identifying such biomarkers. However, very few biomarker proteins for drug development have been discovered using this approach. The main difficulty is to efficiently select potential biomarkers from the many candidate proteins identified by the proteomics approach. To circumvent this problem, we have developed "antibody proteomics technology" that can screen for biomarker proteins by isolating antibodies against each candidate in a rapid and comprehensive manner. Here, we applied "antibody proteomics technology" to breast cancer-related biomarker discovery and evaluated the utility of this novel technology. Cell extracts derived from breast tumor cells (SKBR3) and normal cells (184A1) were analyzed by two-dimensional differential gel electrophoresis (2D-DIGE) to identify proteins over-expressed in the tumor cells. Candidate proteins were extracted from the gel pieces, immobilized onto a nitrocellulose membrane using a dot blot apparatus and then used as target antigens in scFv-phage enrichment and selection. Following this in vitro phage selection procedure, scFvs binding to 21 different over-expressed proteins in tumor cells were successfully isolated within several weeks. The expression profiles of the identified proteins were then determined by tissue microarray analysis using the scFv-phages. Consequently, we identified three breast tumor-specific proteins. Our data demonstrates the utility of an antibody proteomics system for discovering and validating tumor-related proteins in pharmaceutical proteomics. Currently, we are analyzing the functions of these proteins to use them as diagnostic markers or therapeutic targets.

  18. SITC/iSBTc Cancer Immunotherapy Biomarkers Resource Document: Online resources and useful tools - a compass in the land of biomarker discovery

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    Disis Mary L

    2011-09-01

    Full Text Available Abstract Recent positive clinical results in cancer immunotherapy point to the potential of immune-based strategies to provide effective treatment of a variety of cancers. In some patients, the responses to cancer immunotherapy are durable, dramatically extending survival. Extensive research efforts are being made to identify and validate biomarkers that can help identify subsets of cancer patients that will benefit most from these novel immunotherapies. In addition to the clear advantage of such predictive biomarkers, immune biomarkers are playing an important role in the development, clinical evaluation and monitoring of cancer immunotherapies. This Cancer Immunotherapy Resource Document, prepared by the Society for Immunotherapy of Cancer (SITC, formerly the International Society for Biological Therapy of Cancer, iSBTc, provides key references and online resources relevant to the discovery, evaluation and clinical application of immune biomarkers. These key resources were identified by experts in the field who are actively pursuing research in biomarker identification and validation. This organized collection of the most useful references, online resources and tools serves as a compass to guide discovery of biomarkers essential to advancing novel cancer immunotherapies.

  19. Translating Discovery in Zebrafish Pancreatic Development to Human Pancreatic Cancer: Biomarkers, Targets, Pathogenesis, and Therapeutics

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    Kazi, Abid A.; Yee, Rosemary K.

    2013-01-01

    Abstract Experimental studies in the zebrafish have greatly facilitated understanding of genetic regulation of the early developmental events in the pancreas. Various approaches using forward and reverse genetics, chemical genetics, and transgenesis in zebrafish have demonstrated generally conserved regulatory roles of mammalian genes and discovered novel genetic pathways in exocrine pancreatic development. Accumulating evidence has supported the use of zebrafish as a model of human malignant diseases, including pancreatic cancer. Studies have shown that the genetic regulators of exocrine pancreatic development in zebrafish can be translated into potential clinical biomarkers and therapeutic targets in human pancreatic adenocarcinoma. Transgenic zebrafish expressing oncogenic K-ras and zebrafish tumor xenograft model have emerged as valuable tools for dissecting the pathogenetic mechanisms of pancreatic cancer and for drug discovery and toxicology. Future analysis of the pancreas in zebrafish will continue to advance understanding of the genetic regulation and biological mechanisms during organogenesis. Results of those studies are expected to provide new insights into how aberrant developmental pathways contribute to formation and growth of pancreatic neoplasia, and hopefully generate valid biomarkers and targets as well as effective and safe therapeutics in pancreatic cancer. PMID:23682805

  20. Biomarkers Discovery for Colorectal Cancer: A Review on Tumor Endothelial Markers as Perspective Candidates

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    2016-01-01

    Colorectal cancer (CRC) is the third most common cancer in the world. The early detection of CRC, during the promotion/progression stages, is an enormous challenge for a successful outcome and remains a fundamental problem in clinical approach. Despite the continuous advancement in diagnostic and therapeutic methods, there is a need for discovery of sensitive and specific, noninvasive biomarkers. Tumor endothelial markers (TEMs) are associated with tumor-specific angiogenesis and are potentially useful to discriminate between tumor and normal endothelium. The most promising TEMs for oncogenic signaling in CRC appeared to be the TEM1, TEM5, TEM7, and TEM8. Overexpression of TEMs especially TEM1, TEM7, and TEM8 in colorectal tumor tissue compared to healthy tissue suggests their role in tumor blood vessels formation. Thus TEMs appear to be perspective candidates for early detection, monitoring, and treatment of CRC patients. This review provides an update on recent data on tumor endothelial markers and their possible use as biomarkers for screening, diagnosis, and therapy of colorectal cancer patients. PMID:27965519

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

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    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.

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

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    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

  3. Proteomics approaches in cervical cancer: focus on the discovery of biomarkers for diagnosis and drug treatment monitoring.

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    Kontostathi, Georgia; Zoidakis, Jerome; Anagnou, Nicholas P; Pappa, Kalliopi I; Vlahou, Antonia; Makridakis, Manousos

    2016-08-01

    The HPV virus accounts for the majority of cervical cancer cases. Although a diagnostic tool (Pap Test) is widely available, cervical cancer incidence still remains high worldwide, and especially in developing countries, attributed to a large extent to suboptimal sensitivities of the Pap test and unavailability of the test in developing countries. Proteomics approaches have been used in order to understand the HPV virus correlation to cervical cancer pathology, as well as to discover putative biomarkers for early cervical cancer diagnosis and drug mode of action. Expert commentary: The present review summarizes the latest in vitro and in vivo proteomic studies for the discovery of putative cervical cancer biomarkers and the evaluation of available drugs and treatments.

  4. Systems biology and biomarker discovery

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    Rodland, Karin D.

    2010-12-01

    Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of large complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.

  5. Discovery and validation of molecular biomarkers for colorectal adenomas and cancer with application to blood testing.

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    Lawrence C LaPointe

    Full Text Available BACKGROUND & AIMS: Colorectal cancer incidence and deaths are reduced by the detection and removal of early-stage, treatable neoplasia but we lack proven biomarkers sensitive for both cancer and pre-invasive adenomas. The aims of this study were to determine if adenomas and cancers exhibit characteristic patterns of biomarker expression and to explore whether a tissue-discovered (and validated biomarker is differentially expressed in the plasma of patients with colorectal adenomas or cancer. METHODS: Candidate RNA biomarkers were identified by oligonucleotide microarray analysis of colorectal specimens (222 normal, 29 adenoma, 161 adenocarcinoma and 50 colitis and validated in a previously untested cohort of 68 colorectal specimens using a custom-designed oligonucleotide microarray. One validated biomarker, KIAA1199, was assayed using qRT-PCR on plasma extracted RNA from 20 colonoscopy-confirmed healthy controls, 20 patients with adenoma, and 20 with cancer. RESULTS: Genome-wide analysis uncovered reproducible gene expression signatures for both adenomas and cancers compared to controls. 386/489 (79% of the adenoma and 439/529 (83% of the adenocarcinoma biomarkers were validated in independent tissues. We also identified genes differentially expressed in adenomas compared to cancer. KIAA1199 was selected for further analysis based on consistent up-regulation in neoplasia, previous studies and its interest as an uncharacterized gene. Plasma KIAA1199 RNA levels were significantly higher in patients with either cancer or adenoma (31/40 compared to neoplasia-free controls (6/20. CONCLUSIONS: Colorectal neoplasia exhibits characteristic patterns of gene expression. KIAA1199 is differentially expressed in neoplastic tissues and KIAA1199 transcripts are more abundant in the plasma of patients with either cancer or adenoma compared to controls.

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

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    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 Standardized and Reproducible Urine Preparation Protocol for Cancer Biomarkers Discovery

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    Julia Beretov

    2014-01-01

    Full Text Available A suitable and standardized protein purification technique is essential to maintain consistency and to allow data comparison between proteomic studies for urine biomarker discovery. Ultimately, efforts should be made to standardize urine preparation protocols. The aim of this study was to develop an optimal analytical protocol to achieve maximal protein yield and to ensure that this method was applicable to examine urine protein patterns that distinguish disease and disease-free states. In this pilot study, we compared seven different urine sample preparation methods to remove salts, and to precipitate and isolate urinary proteins. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE profiles showed that the sequential preparation of urinary proteins by combining acetone and trichloroacetic acid (TCA alongside high speed centrifugation (HSC provided the best separation, and retained the most urinary proteins. Therefore, this approach is the preferred method for all further urine protein analysis.

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

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    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.

  9. Glycan microarrays: powerful tools for biomarker discovery.

    Science.gov (United States)

    Muthana, Saddam M; Gildersleeve, Jeffrey C

    2014-01-01

    Over the last 10 years, glycan microarray technology has emerged as a powerful high-throughput tool for studying the interactions of carbohydrates with a variety of biomolecules. The array format allows one to screen thousands of binding interactions in a single experiment using minimal amounts of scarce materials. More recently, this technology has been applied to the discovery of biomarkers for diagnosis, prognosis, risk prediction, and monitoring immune responses. Biomarker discovery using glycan arrays has primarily focused on monitoring changes to the anti-glycan antibody repertoires in serum, since the populations of antibodies can change significantly with the onset of disease, exposure to pathogens, or vaccination. Herein, we review efforts to use glycan arrays to identify new biomarkers for cancer, infections, autoimmune diseases, and immune responses.

  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. Binary state pattern clustering: a digital paradigm for class and biomarker discovery in gene microarray studies of cancer.

    Science.gov (United States)

    Beattie, Bradley J; Robinson, Peter N

    2006-06-01

    Class and biomarker discovery continue to be among the preeminent goals in gene microarray studies of cancer. We have developed a new data mining technique, which we call Binary State Pattern Clustering (BSPC) that is specifically adapted for these purposes, with cancer and other categorical datasets. BSPC is capable of uncovering statistically significant sample subclasses and associated marker genes in a completely unsupervised manner. This is accomplished through the application of a digital paradigm, where the expression level of each potential marker gene is treated as being representative of its discrete functional state. Multiple genes that divide samples into states along the same boundaries form a kind of gene-cluster that has an associated sample-cluster. BSPC is an extremely fast deterministic algorithm that scales well to large datasets. Here we describe results of its application to three publicly available oligonucleotide microarray datasets. Using an alpha-level of 0.05, clusters reproducing many of the known sample classifications were identified along with associated biomarkers. In addition, a number of simulations were conducted using shuffled versions of each of the original datasets, noise-added datasets, as well as completely artificial datasets. The robustness of BSPC was compared to that of three other publicly available clustering methods: ISIS, CTWC and SAMBA. The simulations demonstrate BSPC's substantially greater noise tolerance and confirm the accuracy of our calculations of statistical significance.

  12. Elucidation of N-glycosites within human plasma glycoproteins for cancer biomarker discovery.

    Science.gov (United States)

    Drake, Penelope; Schilling, Birgit; Gibson, Brad; Fisher, Susan

    2013-01-01

    Glycans are an important class of post-translational modifications that decorate a wide array of protein substrates. These cell-type specific molecules, which are modulated during developmental and disease processes, are attractive biomarker candidates as biology regarding altered glycosylation can be used to guide the experimental design. The mass spectrometry (MS)-based workflow described here incorporates chromatography on affinity matrices formed from lectins, proteins that bind specific glycan motifs. The goal was to design a relatively simple method for the rapid analysis of small plasma volumes (e.g., clinical specimens). As increases in sialylation and fucosylation are prominent among cancer-associated modifications, we focused on Sambucus nigra agglutinin and AAL, which bind sialic acid- and fucose-containing structures, respectively. Positive controls (fucosylated and sialylated human lactoferrin glycopeptides), and negative controls (high-mannose glycopeptides from Saccharomyces cerevisiae invertase) were used to monitor the specificity of lectin capture and optimize the workflow. Multiple Affinity Removal System 14-depleted, trypsin-digested human plasma from healthy donors served as the target analyte. Samples were loaded onto the lectin columns and separated by high performance liquid chromatography (HPLC) into flow through and bound fractions, which were treated with PNGase F, an amidase that removes N-linked glycans and marks the underlying asparagine glycosite by a +1 Da mass shift. The deglycosylated peptide fractions were interrogated by HPLC ESI-MS/MS on a quadrupole time-of-flight mass spectrometer. The method allowed identification of 122 human plasma glycoproteins containing 247 unique glycosites. Notably, glycoproteins that circulate at ng/mL levels (e.g., cadherin-5 at 0.3-4.9 ng/mL, and neutrophil gelatinase-associated lipocalin which is present at ∼2.5 ng/mL) were routinely observed, suggesting that this method enables the detection of

  13. Profiling of circulating microRNAs for prostate cancer biomarker discovery

    DEFF Research Database (Denmark)

    Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro

    2014-01-01

    biopsy, and better and less invasive tools for PC detection are needed. Furthermore, whereas aggressive PC should be treated immediately to prevent dissemination, indolent PC often does not progress and overtreatment should be avoided. Currently, the best predictors of aggressiveness are Gleason score...... 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...

  14. 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.

  15. Discovery of gastric cancer specific biomarkers by the application of serum proteomics.

    Science.gov (United States)

    Yoo, Moon-Won; Park, Jisook; Han, Hye-Seung; Yun, Yeo-Min; Kang, Jeong Won; Choi, Do-Young; Lee, Joon Won; Jung, Jae Hun; Lee, Kyung-Yung; Kim, Kwang Pyo

    2017-03-01

    Current diagnostic markers for gastric cancer are not sufficiently specific or sensitive for use in clinical practice. The aims of this study are to compare the proteomes of serum samples from patients with gastric cancers and normal controls, and to develop useful tumor markers of gastric cancer by quantitative proteomic analysis. We identified a total of 388 proteins with a ≤1% FDR and with at least two unique peptides from the sera of each group. Among them, 215, 251, and 260 proteins were identified in serum samples of patients in an advanced cancer group, early cancer group, and normal control group, respectively. We selected differentially expressed proteins in cancer patients compared with those of normal controls via semiquantitative analyses comparing the spectral counts of identified proteins. These differentially expressed proteins were successfully verified using an MS-based quantitative assay, multiple reactions monitoring analysis. Four proteins (vitronectin, clusterin isoform 1, thrombospondin 1, and tyrosine-protein kinase SRMS) were shown to have significant changes between the cancer groups and the normal control group. These four serum proteins were able to discriminate gastric cancer patients from normal controls with sufficient specificity and selectivity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Biomarkers: in medicine, drug discovery, and environmental health

    National Research Council Canada - National Science Library

    Vaidya, Vishal S; Bonventre, Joseph V

    2010-01-01

    ... Identification Using Mass Spectrometry Sample Preparation Protein Quantitation Examples of Biomarker Discovery and Evaluation Challenges in Proteomic Biomarker Discovery The Road Forward: Targeted ...

  17. Robust statistical methods for significance evaluation and applications in cancer driver detection and biomarker discovery

    DEFF Research Database (Denmark)

    Madsen, Tobias

    2017-01-01

    In the present thesis I develop, implement and apply statistical methods for detecting genomic elements implicated in cancer development and progression. This is done in two separate bodies of work. The first uses the somatic mutation burden to distinguish cancer driver mutations from passenger...... are used to scale the aforementioned driver detection methods to a dataset consisting of more than 2,000 cancer genomes. The sizes and dimensionalities of genomic data sets, be it a large number of genes or multiple heterogeneous data sources, pose both great statistical opportunities and challenges....... These challenges include model selection and multiple testing problems. On the other hand, in large datasets we can often exploit hierarchical structures to improve inference: E.g. in differential expression studies with multiple genes, it is natural to define a distribution of the variability of each gene...

  18. Plasma membrane proteomics and its application in clinical cancer biomarker discovery

    DEFF Research Database (Denmark)

    Leth-Larsen, Rikke; Lund, Rikke; Ditzel, Henrik J

    2010-01-01

    Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions...... cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal...

  19. Shotgun Proteomics and Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    W. Hayes McDonald

    2002-01-01

    Full Text Available Coupling large-scale sequencing projects with the amino acid sequence information that can be gleaned from tandem mass spectrometry (MS/MS has made it much easier to analyze complex mixtures of proteins. The limits of this “shotgun” approach, in which the protein mixture is proteolytically digested before separation, can be further expanded by separating the resulting mixture of peptides prior to MS/MS analysis. Both single dimensional high pressure liquid chromatography (LC and multidimensional LC (LC/LC can be directly interfaced with the mass spectrometer to allow for automated collection of tremendous quantities of data. While there is no single technique that addresses all proteomic challenges, the shotgun approaches, especially LC/LC-MS/MS-based techniques such as MudPIT (multidimensional protein identification technology, show advantages over gel-based techniques in speed, sensitivity, scope of analysis, and dynamic range. Advances in the ability to quantitate differences between samples and to detect for an array of post-translational modifications allow for the discovery of classes of protein biomarkers that were previously unassailable.

  20. Immunoproteomics: From biomarker discovery to diagnostic applications.

    Science.gov (United States)

    Tjalsma, Harold; Schaeps, Renée M J; Swinkels, Dorine W

    2008-02-01

    Circulating antibodies reflect a molecular imprint of antigens that are related to autoimmune diseases, cancer or infection. Importantly, serum antibodies are useful clinical markers as they carry diagnostic information from all around the human body. Moreover, the amplification cascade governed by the humoral immune system causes a surplus of circulating antibodies after appearance of the corresponding (low abundance) antigen. In combination with the fact that antibodies are highly stable compared to many other serum proteins, they seem ideal to be implemented in clinical diagnostic assays for the detection of antigen-associated diseases. This review summarises advances in immunoproteomics with respect to technologies for biomarker discovery, with special emphasis on recently developed gel-free MS-based approaches, and looks forward to potential immunoproteomic applications in diagnostic medicine. Copyright © 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Advances in mass spectrometry-based clinical biomarker discovery.

    Science.gov (United States)

    Crutchfield, Christopher A; Thomas, Stefani N; Sokoll, Lori J; Chan, Daniel W

    2016-01-01

    The greatest unmet needs in biomarker discovery are those discoveries that lead to the development of clinical diagnostic tests. These clinical diagnostic tests can provide early intervention when a patient would present otherwise healthy (e.g., cancer or cardiovascular disease) and aid clinical decision making with improved clinical outcomes. The past two decades have seen significant technological improvements in the analytical capabilities of mass spectrometers. Mass spectrometers are unique in that they can directly analyze any biological molecule susceptible to ionization. The biological studies of human metabolites and proteins using contemporary mass spectrometry technology (metabolomics and proteomics, respectively) has been ongoing for over a decade. Some of these studies have resulted in exciting insights into human biology. However, relatively few biomarkers have been translated into clinical tests. This review will discuss some key technological developments that have occurred over this time with an emphasis on technologies that will create new avenues for biomarker discovery.

  2. Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification.

    Science.gov (United States)

    Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Pirhadi, Shiva; Garshasbi, Masoud

    2015-01-01

    The improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. Detailed examination of changes in expression levels of genes can help physicians to have efficient diagnosing, classification of tumors and cancer's types as well as effective treatments. Finding genes that can classify the group of cancers correctly based on hybrid optimization algorithms is the main purpose of this paper. In this paper, a hybrid particle swarm optimization and genetic algorithm method are used for gene selection and also artificial neural network (ANN) is adopted as the classifier. In this work, we have improved the ability of the algorithm for the classification problem by finding small group of biomarkers and also best parameters of the classifier. The proposed approach is tested on three benchmark gene expression data sets: Blood (acute myeloid leukemia, acute lymphoblastic leukemia), colon and breast datasets. We used 10-fold cross-validation to achieve accuracy and also decision tree algorithm to find the relation between the biomarkers for biological point of view. To test the ability of the trained ANN models to categorize the cancers, we analyzed additional blinded samples that were not previously used for the training procedure. Experimental results show that the proposed method can reduce the dimension of the data set and confirm the most informative gene subset and improve classification accuracy with best parameters based on datasets.

  3. [Discovery and verification of matrix gla protein, a TNM staging and prognosis-related biomarker for gastric cancer].

    Science.gov (United States)

    Guo, Lei; Guo, Xiao-bo; Jiang, Jin-ling; Zhang, Jia-nian; Ji, Jun; Liu, Bing-ya; Zhu, Zheng-gang; Yu, Ying-yan

    2010-07-01

    To analyze microarray datasets deposited in the public database and to identify TNM associated genes in gastric cancers. Microarray datasets of gastric cancer were selected from GEO database. Differentially expressed genes related to TNM staging were evaluated by significant analysis of the microarray using MultiExperiment Viewer (MEV) platform. Candidate gene expressions in gastric cancer tissues and cell lines were verified by reverse transcriptase polymerase chain reaction (RT-PCR), quantitative RT-PCR, Western blot and immunohistochemistry. GES4007 dataset was re-analyzed leading to the identification of 14 genes associated with TNM staging. Over-expression of matrix gla protein (MGP) was confirmed in gastric cancer cell lines and tumor tissues by quantitative RT-PCR, Western blot and immunohistochemistry. Increased MGP expression was found in 22 of 54 cases of (40.7%) gastric cancer specimens compared to the normal gastric tissues. The up-regulation of MGP mRNA expression closely correlated with TNM stage (P = 0.001) and prognosis (P = 0.006). Public databases of microarray studies are the valuable resources for data mining. MGP has been identified and confirmed as a novel biomarker for the TNM stage and prognosis of gastric cancer.

  4. The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set.

    Directory of Open Access Journals (Sweden)

    Heloisa Helena Milioli

    Full Text Available The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

  5. The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set.

    Science.gov (United States)

    Milioli, Heloisa Helena; Vimieiro, Renato; Riveros, Carlos; Tishchenko, Inna; Berretta, Regina; Moscato, Pablo

    2015-01-01

    The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction. The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method. The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.

  6. Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery.

    Science.gov (United States)

    Zhang, Tong; Watson, David G; Wang, Lijie; Abbas, Muhammad; Murdoch, Laura; Bashford, Lisa; Ahmad, Imran; Lam, Nga-Yee; Ng, Anthony C F; Leung, Hing Y

    2013-01-01

    Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) in combination with orthogonal Hydrophilic Interaction (HILIC) and Reversed Phase (RP) liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition). The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC) test, the area under curve (AUC) for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (Pprotocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

  7. Application of Holistic Liquid Chromatography-High Resolution Mass Spectrometry Based Urinary Metabolomics for Prostate Cancer Detection and Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Tong Zhang

    Full Text Available Human exhibit wide variations in their metabolic profiles because of differences in genetic factors, diet and lifestyle. Therefore in order to detect metabolic differences between individuals robust analytical methods are required. A protocol was produced based on the use of Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS in combination with orthogonal Hydrophilic Interaction (HILIC and Reversed Phase (RP liquid chromatography methods for the analysis of the urinary metabolome, which was then evaluated as a diagnostic tool for prostate cancer (a common but highly heterogeneous condition. The LC-HRMS method was found to be robust and exhibited excellent repeatability for retention times (0.9. In addition, using the receiver operator characteristics (ROC test, the area under curve (AUC for the combination of the four best characterised biomarker compounds was 0.896. The four biomarker compounds were also found to differ significantly (P<0.05 between an independent patient cohort and controls. This is the first time such a rigorous test has been applied to this type of model. If validated, the established protocol provides a robust approach with a potentially wide application to metabolite profiling of human biofluids in health and disease.

  8. Inflammatory biomarkers and cancer

    DEFF Research Database (Denmark)

    Rasmussen, Line Jee Hartmann; Schultz, Martin; Gaardsting, Anne

    2017-01-01

    soluble urokinase plasminogen activator receptor (suPAR) and the pattern recognition receptors (PRRs) pentraxin-3, mannose-binding lectin, ficolin-1, ficolin-2 and ficolin-3. We aimed to evaluate these biomarkers and compare their diagnostic ability to classical biomarkers for diagnosing cancer......In Denmark, patients with serious nonspecific symptoms and signs of cancer (NSSC) are referred to the diagnostic outpatient clinics (DOCs) where an accelerated cancer diagnostic program is initiated. Various immunological and inflammatory biomarkers have been associated with cancer, including...... in patients with NSSC. Patients were included from the DOC, Department of Infectious Diseases, Copenhagen University Hospital Hvidovre. Patients were given a final diagnosis based on the combined results from scans, blood work and physical examination. Weight loss, Charlson score and previous cancer were...

  9. 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.

  10. 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.

  11. Discovery of methylated circulating DNA biomarkers for comprehensive non-invasive monitoring of treatment response in metastatic colorectal cancer.

    Science.gov (United States)

    Barault, Ludovic; Amatu, Alessio; Siravegna, Giulia; Ponzetti, Agostino; Moran, Sebastian; Cassingena, Andrea; Mussolin, Benedetta; Falcomatà, Chiara; Binder, Alexandra M; Cristiano, Carmen; Oddo, Daniele; Guarrera, Simonetta; Cancelliere, Carlotta; Bustreo, Sara; Bencardino, Katia; Maden, Sean; Vanzati, Alice; Zavattari, Patrizia; Matullo, Giuseppe; Truini, Mauro; Grady, William M; Racca, Patrizia; Michels, Karin B; Siena, Salvatore; Esteller, Manel; Bardelli, Alberto; Sartore-Bianchi, Andrea; Di Nicolantonio, Federica

    2017-10-05

    Mutations in cell-free circulating DNA (cfDNA) have been studied for tracking disease relapse in colorectal cancer (CRC). This approach requires personalised assay design due to the lack of universally mutated genes. In contrast, early methylation alterations are restricted to defined genomic loci allowing comprehensive assay design for population studies. Our objective was to identify cancer-specific methylated biomarkers which could be measured longitudinally in cfDNA (liquid biopsy) to monitor therapeutic outcome in patients with metastatic CRC (mCRC). Genome-wide methylation microarrays of CRC cell lines (n=149) identified five cancer-specific methylated loci (EYA4, GRIA4, ITGA4, MAP3K14-AS1, MSC). Digital PCR assays were employed to measure methylation of these genes in tumour tissue DNA (n=82) and cfDNA from patients with mCRC (n=182). Plasma longitudinal assessment was performed in a patient subset treated with chemotherapy or targeted therapy. Methylation in at least one marker was detected in all tumour tissue samples and in 156 mCRC patient cfDNA samples (85.7%). Plasma marker prevalence was 71.4% for EYA4, 68.5% for GRIA4, 69.7% for ITGA4, 69.1% for MAP3K14-AS1% and 65.1% for MSC. Dynamics of methylation markers was not affected by treatment type and correlated with objective tumour response and progression-free survival. This five-gene methylation panel can be used to circumvent the absence of patient-specific mutations for monitoring tumour burden dynamics in liquid biopsy under different therapeutic regimens. This method might be proposed for assessing pharmacodynamics in clinical trials or when conventional imaging has limitations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  12. Biomarkers of cancer cachexia.

    Science.gov (United States)

    Loumaye, Audrey; Thissen, Jean-Paul

    2017-12-01

    Cachexia is a complex multifactorial syndrome, characterized by loss of skeletal muscle and fat mass, which affects the majority of advanced cancer patients and is associated with poor prognosis. Interestingly, reversing muscle loss in animal models of cancer cachexia leads to prolong survival. Therefore, detecting cachexia and maintaining muscle mass represent a major goal in the care of cancer patients. However, early diagnosis of cancer cachexia is currently limited for several reasons. Indeed, cachexia development is variable according to tumor and host characteristics. In addition, safe, accessible and non-invasive tools to detect skeletal muscle atrophy are desperately lacking in clinical practice. Finally, the precise molecular mechanisms and the key players involved in cancer cachexia remain poorly characterized. The need for an early diagnosis of cancer cachexia supports therefore the quest for a biomarker that might reflect skeletal muscle atrophy process. Current research offers different promising ways to identify such a biomarker. Initially, the quest for a biomarker of cancer cachexia has mostly focused on mediators of muscle atrophy, produced by both tumor and host, in an attempt to define new therapeutic approaches. In another hand, molecules released by the muscle into the circulation during the atrophy process have been also considered as potential biomarkers. More recently, several "omics" studies are emerging to identify new muscular or circulating markers of cancer cachexia. Some genetic markers could also contribute to identify patients more susceptible to develop cachexia. This article reviews our current knowledge regarding potential biomarkers of cancer cachexia. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  13. The Process Chain for Peptidomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Michael Schrader

    2006-01-01

    Full Text Available Over the last few years the interest in diagnostic markers for specific diseases has increased continuously. It is expected that they not only improve a patient's medical treatment but also contribute to accelerating the process of drug development. This demand for new biomarkers is caused by a lack of specific and sensitive diagnosis in many diseases. Moreover, diseases usually occur in different types or stages which may need different diagnostic and therapeutic measures. Their differentiation has to be considered in clinical studies as well. Therefore, it is important to translate a macroscopic pathological or physiological finding into a microscopic view of molecular processes and vice versa, though it is a difficult and tedious task. Peptides play a central role in many physiological processes and are of importance in several areas of drug research. Exploration of endogenous peptides in biologically relevant sources may directly lead to new drug substances, serve as key information on a new target and can as well result in relevant biomarker candidates. A comprehensive analysis of peptides and small proteins of a biological system corresponding to the respective genomic information (peptidomics®methods was a missing link in proteomics. A new peptidomic technology platform addressing peptides was recently presented, developed by adaptation of the striving proteomic technologies. Here, concepts of using peptidomics technologies for biomarker discovery are presented and illustrated with examples. It is discussed how the biological hypothesis and sample quality determine the result of the study. A detailed study design, appropriate choice and application of technology as well as thorough data interpretation can lead to significant results which have to be interpreted in the context of the underlying disease. The identified biomarker candidates will be characterised in validation studies before use. This approach for discovery of peptide

  14. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

    Duffy, Michael J; Sturgeon, Catherine M; Söletormos, Georg

    2015-01-01

    BACKGROUND: Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use. CONTENT: In this review, we discuss the key steps in ad...

  15. Biomarker Motif Discovery by Integrating Mass Spectrometry and PPI Network

    Science.gov (United States)

    Zhou, Xiaobo; Wang, Yuan; Wang, Honghui; Pham, Tuan D.; Li, King

    2011-06-01

    Traditional mass spectrometry biomarker discovery studies which focus on single biomarkers or a panel of biomarkers have shown their limitations with low reproducibility. In this paper, we propose a novel biomarker motif discovery approach by integrating both mass spectrometry data and protein interaction network information together to identify biomarkers. A novel Bayesian score method is developed to score the protein subnetwork both from the expression of protein and from the protein interaction network structure. Compared with the previous biomarker discovery method, our biomarker motif identification method not only models the expression of each protein, but also the relationship of proteins affected by the protein-protein interaction network. The experiment results show that our proposed biomarker discovery method has a higher sensitivity and lower false discovery rates than previously used methods. When applying our biomarker motifs discovery approach to the real stroke mass spectrometry data, we can identify several biomarker motifs for ischemic stroke which can achieve a higher classification performance with high biological significance.

  16. Cancer Biomarkers | Division of Cancer Prevention

    Science.gov (United States)

    [[{"fid":"175","view_mode":"default","fields":{"format":"default","field_file_image_alt_text[und][0][value]":"Cancer Biomarkers Research Group Homepage Logo","field_file_image_title_text[und][0][value]":"Cancer Biomarkers Research Group Homepage Logo","field_folder[und]":"15"},"type":"media","attributes":{"alt":"Cancer Biomarkers Research Group Homepage Logo","title":"Cancer Biomarkers Research Group Homepage Logo","height":"266","width":"400","style":"width: 400px; height: 266px;","class":"i | Research to identify, develop and validate biomarkers for early cancer detection and risk assessment.

  17. Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

    Directory of Open Access Journals (Sweden)

    Manuel Fuentes

    2012-02-01

    Full Text Available During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors.

  18. DNA Methylation Biomarkers: Cancer and Beyond

    Science.gov (United States)

    Mikeska, Thomas; Craig, Jeffrey M.

    2014-01-01

    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. PMID:25229548

  19. 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.

  20. Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment.

    Science.gov (United States)

    Phan, John H; Moffitt, Richard A; Stokes, Todd H; Liu, Jian; Young, Andrew N; Nie, Shuming; Wang, May D

    2009-06-01

    Recent advances in biomarker discovery, biocomputing and nanotechnology have raised new opportunities in the emerging fields of personalized medicine (in which disease detection, diagnosis and therapy are tailored to each individual's molecular profile) and predictive medicine (in which genetic and molecular information is used to predict disease development, progression and clinical outcome). Here, we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, in addition to the prospects for and challenges involved in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases.

  1. Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

    Science.gov (United States)

    Phan, John H.; Moffitt, Richard A.; Stokes, Todd H.; Liu, Jian; Young, Andrew N.; Nie, Shuming; Wang, May D.

    2013-01-01

    Recent advances in biomarker discovery, biocomputing, and nanotechnology have raised new opportunities for the emerging field of personalized medicine in which disease detection, diagnosis, and therapy are tailored to each individual’s molecular profile, and also for predictive medicine that uses genetic/molecular information to predict disease development, progression, and clinical outcome. Here we discuss advanced biocomputing tools for cancer biomarker discovery and multiplexed nanoparticle probes for cancer biomarker profiling, together with prospects and challenges in correlating biomolecular signatures with clinical outcome. This bio-nano-info convergence holds great promise for molecular diagnosis and individualized therapy of cancer and other human diseases. PMID:19409634

  2. Soluble biomarkers development in osteoarthritis: from discovery to personalized medicine.

    Science.gov (United States)

    Henrotin, Yves; Sanchez, Christelle; Cornet, Anne; Van de Put, Joachim; Douette, Pierre; Gharbi, Myriam

    2015-01-01

    Specific soluble biomarkers could be a precious tool for diagnosis, prognosis and personalized management of osteoarthritic (OA) patients. To describe the path of soluble biomarker development from discovery to clinical qualification and regulatory adoption toward OA-related biomarker qualification. This review summarizes current guidance on the use of biomarkers in OA in clinical trials and their utility at five stages, including preclinical development and phase 1 to phase 4 trials. It also presents all the available regulatory requirements. The path through the adoption of a specific soluble biomarker for OA is steep but is worth the challenge due to the benefit that it can provide.

  3. Biomarker discovery for cervical cancer

    NARCIS (Netherlands)

    Govorukhina, Natalia I.

    2007-01-01

    Proteomics of human boy fluids is still in its early stage of development with major methodological challenges ahead. This implies that much attention is given to improving the methods and strategies. One major challenge is that many samples that have been acquired in the past may not fulfill the

  4. Current and Prospective Protein Biomarkers of Lung Cancer

    Science.gov (United States)

    Zamay, Tatiana N.; Zamay, Galina S.; Kolovskaya, Olga S.; Zukov, Ruslan A.; Petrova, Marina M.; Gargaun, Ana; Berezovski, Maxim V.

    2017-01-01

    Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate. PMID:29137182

  5. 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

  6. Robust Selection Algorithm (RSA for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

    Directory of Open Access Journals (Sweden)

    Vasudha Sehgal

    Full Text Available MicroRNAs (miRNAs play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

  7. Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

    Science.gov (United States)

    Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

    2015-01-01

    MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

  8. What does systems biology mean for biomarker discovery?

    Science.gov (United States)

    Azuaje, Francisco

    2010-01-01

    The global, integrated analysis of large-scale data sets encoding different levels of biological information opens up new possibilities to discover new biomarkers and elucidate complex mechanisms driving health and disease. This article reviews fundamental systems approaches and applications for biomarker discovery in different biomedical domains. It introduces key challenges and requirements for the development of advanced computational techniques, resources and applications. It discusses how these approaches can fill in some of the current gaps in traditional biomarker discovery and disease classification. The reader will be introduced to recent advances, techniques and applications of systems approaches to biomarker discovery and disease classification. The reader will learn fundamental research principles and tasks required in the implementation of these approaches and applications. The reader will gain a better understanding of the role of systems biology, as well as of potential opportunities and advances. Systems approaches to biomarker discovery may contribute to the discovery of more accurate and robust predictors of disease and clinical responses. Moreover, they can provide new and deeper clues of potential causal mechanisms underpinning physiological and pathological conditions.

  9. 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.

  10. Statistical design for biospecimen cohort size in proteomics-based biomarker discovery and verification studies.

    Science.gov (United States)

    Skates, Steven J; Gillette, Michael A; LaBaer, Joshua; Carr, Steven A; Anderson, Leigh; Liebler, Daniel C; Ransohoff, David; Rifai, Nader; Kondratovich, Marina; Težak, Živana; Mansfield, Elizabeth; Oberg, Ann L; Wright, Ian; Barnes, Grady; Gail, Mitchell; Mesri, Mehdi; Kinsinger, Christopher R; Rodriguez, Henry; Boja, Emily S

    2013-12-06

    Protein biomarkers are needed to deepen our understanding of cancer biology and to improve our ability to diagnose, monitor, and treat cancers. Important analytical and clinical hurdles must be overcome to allow the most promising protein biomarker candidates to advance into clinical validation studies. Although contemporary proteomics technologies support the measurement of large numbers of proteins in individual clinical specimens, sample throughput remains comparatively low. This problem is amplified in typical clinical proteomics research studies, which routinely suffer from a lack of proper experimental design, resulting in analysis of too few biospecimens to achieve adequate statistical power at each stage of a biomarker pipeline. To address this critical shortcoming, a joint workshop was held by the National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), and American Association for Clinical Chemistry (AACC) with participation from the U.S. Food and Drug Administration (FDA). An important output from the workshop was a statistical framework for the design of biomarker discovery and verification studies. Herein, we describe the use of quantitative clinical judgments to set statistical criteria for clinical relevance and the development of an approach to calculate biospecimen sample size for proteomic studies in discovery and verification stages prior to clinical validation stage. This represents a first step toward building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research.

  11. 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

  12. Detecting blood-based biomarkers in metastatic breast cancer : A systematic review of their current status and clinical utility

    NARCIS (Netherlands)

    Berghuis, A.M. Sofie; Koffijberg, Hendrik; Prakash, Jai; Terstappen, Leon W.M.M.; Ijzerman, Maarten J.

    2017-01-01

    Reviews on circulating biomarkers in breast cancer usually focus on one single biomarker or a selective group of biomarkers. An overview summarizing the discovery and evaluation of all blood-based biomarkers in metastatic breast cancer is lacking. This systematic review aims to identify the

  13. Searching for new biomarkers in ovarian cancer patients

    DEFF Research Database (Denmark)

    Hentze, Julie L.; Høgdall, Claus; Kjær, Susanne K.

    2017-01-01

    Ovarian cancer is a silent killer and, due to late diagnosis, the primary cause of death amongst gynecological cancers, killing approximately 376 women annually in Denmark. The discovery of a specific and sensitive biomarker for ovarian cancer could improve early diagnosis, but also treatment...... regarding biomarkers and/or prognostic markers, with a focus on rationale and design. The study described has 3 major branches: microRNAs, epigenetics and Next Generation Sequencing. Tissue and blood from ovarian cancer patients, already enrolled in the prospective ongoing pelvic mass cohort...

  14. Application of chemical proteomics to biomarker discovery in cardiac research

    NARCIS (Netherlands)

    Aye, T.T.

    2010-01-01

    This thesis is primarily focused on (i.) exploring chemical probes to increase sensitivity and specificity for the investigation of low abundant cardiac proteins applicable to both biology and biomarker discovery, and (ii.) exploiting different aspects of mass spectrometry-based proteomics for

  15. Utilizing human blood plasma for proteomic biomarker discovery

    Energy Technology Data Exchange (ETDEWEB)

    Jacobs, Jon M.; Adkins, Joshua N.; Qian, Weijun; Liu, Tao; Shen, Yufeng; Camp, David G.; Smith, Richard D.

    2005-08-01

    Application of proteomic biomarker discovery efforts towards human plasma entails both incredible clinical potential as well as significant challenges to overcome the intrinsic characteristics of plasma. The dynamic range of proteins within plasma, coupled with the likely presence of potential biomarkers in the more difficult to detect lower abundance range has driven the development of various methodologies and strategies to maximize the possible detective dynamic range within this biofluid. Discussed is the array of the available approaches currently used by our laboratory and others to utilized human plasma as a viable medium for biomarker discovery efforts. Various separation, depletion, enrichment, and quantitative efforts have resulted in a measurable improvement in the detectability of the low abundance fraction of proteins but more advances are needed to bridge the gap between the current range of detection and what remains unobservable to fully maximize the potential of this sample.

  16. Gastric Cancer (Biomarkers Knowledgebase (GCBKB: A Curated and Fully Integrated Knowledgebase of Putative Biomarkers Related to Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Bernett T.K. Lee

    2006-01-01

    Full Text Available The Gastric Cancer (Biomarkers Knowledgebase (GCBKB (http://biomarkers.bii.a-star.edu.sg/background/gastricCancerBiomarkersKb.php is a curated and fully integrated knowledgebase that provides data relating to putative biomarkers that may be used in the diagnosis and prognosis of gastric cancer. It is freely available to all users. The data contained in the knowledgebase was derived from a large literature source and the putative biomarkers therein have been annotated with data from the public domain. The knowledgebase is maintained by a curation team who update the data from a defined source. As well as mining data from the literature, the knowledgebase will also be populated with unpublished experimental data from investigators working in the gastric cancer biomarker discovery field. Users can perform searches to identify potential markers defined by experiment type, tissue type and disease state. Search results may be saved, manipulated and retrieved at a later date. As far as the authors are aware this is the first open access database dedicated to the discovery and investigation of gastric cancer biomarkers.

  17. Biomarkers in Cervical Cancer

    OpenAIRE

    Eun-Kyoung Yim; Jong-Sup Park

    2006-01-01

    Cervical cancer, a potentially preventable disease, remains the second most common malignancy in women worldwide. Human papillomavirus (HPV) is the single most important etiological agent in cervical cancer, contributing to neoplastic progression through the action of viral oncoproteins, mainly E6 and E7. Cervical screening programs using Pap smear testing have dramatically improved cervical cancer incidence and reduced deaths, but cervical cancer still remains a global health burden. The bio...

  18. Banking on the future: biobanking for "omics" approaches to biomarker discovery for Opisthorchis-induced cholangiocarcinoma in Thailand.

    Science.gov (United States)

    Mulvenna, Jason; Yonglitthipagon, Ponlapat; Sripa, Banchob; Brindley, Paul J; Loukas, Alex; Bethony, Jeffrey M

    2012-03-01

    Cholangiocarcinoma (CCA)--bile duct cancer--is associated with late presentation, poses challenges for diagnosis, and has high mortality. These features t highlight the desperate need for biomarkers than can be measured early and in accessible body fluids such as plasma of people at risk for developing this lethal cancer. In this manuscript, we address previous limitations in the discovery stage of biomarker(s) for CCA and indicate how new generation of "omics" technologies could be used for biomarker discovery in Thailand. A key factor in the success of this biomarker program for CCA is the combination of cutting edge technology with strategic sample acquisition by a biorepositories. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  19. Application of “omics” to Prion Biomarker Discovery

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    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.

  20. 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

  1. 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.

  2. Discovery of novel biomarkers and phenotypes by semantic technologies.

    Science.gov (United States)

    Trugenberger, Carlo A; Wälti, Christoph; Peregrim, David; Sharp, Mark E; Bureeva, Svetlana

    2013-02-13

    Biomarkers and target-specific phenotypes are important to targeted drug design and individualized medicine, thus constituting an important aspect of modern pharmaceutical research and development. More and more, the discovery of relevant biomarkers is aided by in silico techniques based on applying data mining and computational chemistry on large molecular databases. However, there is an even larger source of valuable information available that can potentially be tapped for such discoveries: repositories constituted by research documents. This paper reports on a pilot experiment to discover potential novel biomarkers and phenotypes for diabetes and obesity by self-organized text mining of about 120,000 PubMed abstracts, public clinical trial summaries, and internal Merck research documents. These documents were directly analyzed by the InfoCodex semantic engine, without prior human manipulations such as parsing. Recall and precision against established, but different benchmarks lie in ranges up to 30% and 50% respectively. Retrieval of known entities missed by other traditional approaches could be demonstrated. Finally, the InfoCodex semantic engine was shown to discover new diabetes and obesity biomarkers and phenotypes. Amongst these were many interesting candidates with a high potential, although noticeable noise (uninteresting or obvious terms) was generated. The reported approach of employing autonomous self-organising semantic engines to aid biomarker discovery, supplemented by appropriate manual curation processes, shows promise and has potential to impact, conservatively, a faster alternative to vocabulary processes dependent on humans having to read and analyze all the texts. More optimistically, it could impact pharmaceutical research, for example to shorten time-to-market of novel drugs, or speed up early recognition of dead ends and adverse reactions.

  3. Aptamer-based multiplexed proteomic technology for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Larry Gold

    Full Text Available BACKGROUND: The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. METHODOLOGY/PRINCIPAL FINDINGS: We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 µL of serum or plasma. Our current assay measures 813 proteins with low limits of detection (1 pM median, 7 logs of overall dynamic range (~100 fM-1 µM, and 5% median coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding signature of DNA aptamer concentrations, which is quantified on a DNA microarray. Our assay takes advantage of the dual nature of aptamers as both folded protein-binding entities with defined shapes and unique nucleotide sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD. We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to rapidly discover unique protein signatures characteristic of various disease states. CONCLUSIONS/SIGNIFICANCE: We describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next

  4. Metabolomics for Biomarker Discovery: Moving to the Clinic

    Science.gov (United States)

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

    2015-01-01

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

  5. Lectin microarrays: a powerful tool for glycan-based biomarker discovery.

    Science.gov (United States)

    Zhou, Shu-Min; Cheng, Li; Guo, Shu-Juan; Zhu, Heng; Tao, Sheng-Ce

    2011-09-01

    Cell surfaces, especially mammalian cell surfaces, are heavily coated with complex poly- and oligosaccharides, and these glycans have been implicated in many functions, such as cell-to-cell communication, host-pathogen interactions and cell matrix interactions. Not surprisingly then, the aberrations of glycosylation are usually indicative of the onset of specific diseases, such as cancer. Therefore, glycans are expected to serve as important biomarkers for disease diagnosis and/or prognosis. Recent development of the lectin microarray technology has allowed researchers to profile the glycans in complex biological samples in a high throughput fashion. This relatively new tool is highly suitable for both live cell and cell lysate analyses and has the potential for rapid discovery of glycan-based biomarkers. In this review, we will focus on the basic concepts and the latest advances of lectin microarray technology. We will also emphasize the application of lectin microarrays for biomarker discovery, and then discuss the challenges faced by this technology and potential future directions. Based on the tremendous progress already achieved, it seems apparent that lectin microarrays will soon become an indispensible tool for glycosylation biomarker discovery.

  6. PET Metabolic Biomarkers for Cancer

    Directory of Open Access Journals (Sweden)

    Etienne Croteau

    2016-01-01

    Full Text Available The body's main fuel sources are fats, carbohydrates (glucose, proteins, and ketone bodies. It is well known that an important hallmark of cancer cells is the overconsumption of glucose. Positron emission tomography (PET imaging using the glucose analog 18 F-fluorodeoxyglucose ( 18 F-FDG has been a powerful cancer diagnostic tool for many decades. Apart from surgery, chemotherapy and radiotherapy represent the two main domains for cancer therapy, targeting tumor proliferation, cell division, and DNA replication–-all processes that require a large amount of energy. Currently, in vivo clinical imaging of metabolism is performed almost exclusively using PET radiotracers that assess oxygen consumption and mechanisms of energy substrate consumption. This paper reviews the utility of PET imaging biomarkers for the detection of cancer proliferation, vascularization, metabolism, treatment response, and follow-up after radiation therapy, chemotherapy, and chemotherapy-related side effects.

  7. Biomarkers in Advanced Larynx Cancer

    Science.gov (United States)

    Bradford, Carol R.; Kumar, Bhavna; Bellile, Emily; Lee, Julia; Taylor, Jeremy; D’Silva, Nisha; Cordell, Kitrina; Kleer, Celina; Kupfer, Robbi; Kumar, Pawan; Urba, Susan; Worden, Francis; Eisbruch, Avraham; Wolf, Gregory T.; Teknos, Theodoros N.; Prince, Mark E.P.; Chepeha, Douglas B.; Hogikyan, Norman D.; Moyer, Jeffrey S.; Carey, Thomas E.

    2014-01-01

    Objectives/Hypothesis To determine if tumor biomarkers were predictive of outcome in a prospective cohort of patients with advanced larynx cancer treated in a phase II clinical trial. Study Design Prospectively collected biopsy specimens from 58 patients entered into a Phase II trial of organ preservation in advanced laryngeal cancer were evaluated for expression of a large panel of biomarkers and correlations with outcome were determined. Methods Tissue microarrays were constructed from pretreatment biopsies and stained for cyclin D1, CD24, EGFR, MDM2, PCNA, p53, survivin, Bcl-xL, Bcl-2, BAK, rhoC, and NFκB. Pattern of invasion and p53 mutations were assessed. Correlations with overall survival (OS), disease-specific survival (DSS), time free from indication of surgery, induction chemotherapy response, and chemoradiation response were determined. Cox models were used to assess combinations of these biomarkers. Results Low expression of BAK was associated with response to induction chemotherapy. Low expression of BAK and cytoplasmic NFκB was associated with chemoradiation response. Aggressive histologic growth pattern was associated with response induction chemotherapy. Expression of cyclin D1 was predictive of overall and disease-specific survival. Overexpression of EGFR was also associated with an increased risk of death from disease. Bcl-xL expression increased significantly in persistent/recurrent tumors specimens when compared to pretreatment specimens derived from the same patient (p = 0.0003). Conclusions Evaluation of biomarker expression in pretreatment biopsy specimens can lend important predictive and prognostic information for patients with advanced larynx cancer. PMID:23775802

  8. PSA and beyond: alternative prostate cancer biomarkers

    Science.gov (United States)

    2016-01-01

    Background The use of biomarkers for prostate cancer screening, diagnosis and prognosis has the potential to improve the clinical management of the patients. Owing to inherent limitations of the biomarker prostate-specific antigen (PSA), intensive efforts are currently directed towards a search for alternative prostate cancer biomarkers, particularly those that can predict disease aggressiveness and drive better treatment decisions. Methods A literature search of Medline articles focused on recent and emerging advances in prostate cancer biomarkers was performed. The most promising biomarkers that have the potential to meet the unmet clinical needs in prostate cancer patient management and/or that are clinically implemented were selected. Conclusions With the advent of advanced genomic and proteomic technologies, we have in recent years seen an enormous spurt in prostate cancer biomarker research with several promising alternative biomarkers being discovered that show an improved sensitivity and specificity over PSA. The new generation of biomarkers can be tested via serum, urine, or tissue-based assays that have either received regulatory approval by the US Food and Drug Administration or are available as Clinical Laboratory Improvement Amendments-based laboratory developed tests. Additional emerging novel biomarkers for prostate cancer, including circulating tumor cells, microRNAs and exosomes, are still in their infancy. Together, these biomarkers provide actionable guidance for prostate cancer risk assessment, and are expected to lead to an era of personalized medicine. PMID:26790878

  9. Emerging blood-based biomarkers for detection of gastric cancer

    Science.gov (United States)

    Kalniņa, Zane; Meistere, Irēna; Kikuste, Ilze; Tolmanis, Ivars; Zayakin, Pawel; Linē, Aija

    2015-01-01

    Early detection and efficient monitoring of tumor dynamics are prerequisites for reducing disease burden and mortality, and for improving the management of patients with gastric cancer (GC). Blood-based biomarker assays for the detection of early-stage GC could be of great relevance both for population-wide or risk group-based screening programs, while circulating biomarkers that reflect the genetic make-up and dynamics of the tumor would allow monitoring of treatment efficacy, predict recurrences and assess the genetic heterogeneity of the tumor. Recent research to identify blood-based biomarkers of GC has resulted in the identification of a wide variety of cancer-associated molecules, including various proteins, autoantibodies against tumor associated antigens, cell-free DNA fragments, mRNAs and various non-coding RNAs, circulating tumor cells and cancer-derived extracellular vesicles. Each type of these biomarkers provides different information on the disease status, has different advantages and disadvantages, and distinct clinical usefulness. In the current review, we summarize the recent developments in blood-based GC biomarker discovery, discuss the origin of various types of biomarkers and their clinical usefulness and the technological challenges in the development of biomarker assays for clinical use. PMID:26556992

  10. Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery.

    Science.gov (United States)

    Quanico, Jusal; Franck, Julien; Wisztorski, Maxence; Salzet, Michel; Fournier, Isabelle

    2017-01-01

    Mapping provides a direct means to assess the impact of protein biomarkers and puts into context their relevance in the type of cancer being examined. To this end, mass spectrometry imaging (MSI) was developed to provide the needed spatial information which is missing in traditional liquid-based mass spectrometric proteomics approaches. Aptly described as a "molecular histology" technique, MSI gives an additional dimension in characterizing tumor biopsies, allowing for mapping of hundreds of molecules in a single analysis. A decade of developments focused on improving and standardizing MSI so that the technique can be translated into the clinical setting. This review describes the progress made in addressing the technological development that allows to bridge local protein detection by MSI to its identification and to illustrate its potential in studying various aspects of cancer biomarker discovery.

  11. Quantitative imaging as cancer biomarker

    Science.gov (United States)

    Mankoff, David A.

    2015-03-01

    The ability to assay tumor biologic features and the impact of drugs on tumor biology is fundamental to drug development. Advances in our ability to measure genomics, gene expression, protein expression, and cellular biology have led to a host of new targets for anticancer drug therapy. In translating new drugs into clinical trials and clinical practice, these same assays serve to identify patients most likely to benefit from specific anticancer treatments. As cancer therapy becomes more individualized and targeted, there is an increasing need to characterize tumors and identify therapeutic targets to select therapy most likely to be successful in treating the individual patient's cancer. Thus far assays to identify cancer therapeutic targets or anticancer drug pharmacodynamics have been based upon in vitro assay of tissue or blood samples. Advances in molecular imaging, particularly PET, have led to the ability to perform quantitative non-invasive molecular assays. Imaging has traditionally relied on structural and anatomic features to detect cancer and determine its extent. More recently, imaging has expanded to include the ability to image regional biochemistry and molecular biology, often termed molecular imaging. Molecular imaging can be considered an in vivo assay technique, capable of measuring regional tumor biology without perturbing it. This makes molecular imaging a unique tool for cancer drug development, complementary to traditional assay methods, and a potentially powerful method for guiding targeted therapy in clinical trials and clinical practice. The ability to quantify, in absolute measures, regional in vivo biologic parameters strongly supports the use of molecular imaging as a tool to guide therapy. This review summarizes current and future applications of quantitative molecular imaging as a biomarker for cancer therapy, including the use of imaging to (1) identify patients whose tumors express a specific therapeutic target; (2) determine

  12. 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.

  13. Imaging biomarker roadmap for cancer studies

    NARCIS (Netherlands)

    O'Connor, James P. B.; Aboagye, Eric O.; Adams, Judith E.; Aerts, Hugo J. W. L.; Barrington, Sally F.; Beer, Ambros J.; Boellaard, Ronald; Bohndiek, Sarah E.; Brady, Michael; Brown, Gina; Buckley, David L.; Chenevert, Thomas L.; Clarke, Laurence P.; Collette, Sandra; Cook, Gary J.; Desouza, Nandita M.; Dickson, John C.; Dive, Caroline; Evelhoch, Jeffrey L.; Faivre-Finn, Corinne; Gallagher, Ferdia A.; Gilbert, Fiona J.; Gillies, Robert J.; Goh, Vicky; Griffiths, J. R.; Groves, Ashley M.; Halligan, Steve; Harris, Adrian L.; Hawkes, David J.; Hoekstra, Otto S.; Huang, Erich P.; Hutton, Brian F.; Jackson, Edward F.; Jayson, Gordon C.; Jones, Andrew; Koh, Dow-Mu; Lacombe, Denis; Lambin, Philippe; Lassau, Nathalie; Leach, Martin O.; Lee, Ting-Yim; Leen, Edward L.; Lewis, Jason S.; Liu, Yan; Lythgoe, Mark F.; Manoharan, Prakash; Maxwell, Ross J.; Miles, Kenneth A.; Morgan, Bruno; Morris, Steve; Ng, Tony; Padhani, Anwar R.; Parker, Geoff J. M.; Partridge, Mike; Pathak, Arvind P.; Peet, Andrew C.; Punwani, Shonit; Reynolds, Andrew R.; Robinson, Simon P.; Shankar, Lalitha K.; Sharma, Ricky A.; Soloviev, Dmitry; Stroobants, Sigrid G.; Sullivan, Daniel C.; Taylor, Stuart A.; Tofts, Paul S.; Tozer, Gillian M.; van Herk, Marcel B.; Walker-Samuel, Simon; Wason, James; Williams, Kaye J.; Workman, Paul; Yankeelov, Thomas E.; Brindle, Kevin M.; McShane, Lisa M.; Jackson, Alan; Waterton, John C.

    Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and

  14. Cervical cancer: Biomarkers for diagnosis and treatment.

    Science.gov (United States)

    Dasari, Subramanyam; Wudayagiri, Rajendra; Valluru, Lokanatha

    2015-05-20

    Cervical cancer is a major gynecological cancer which involves uncontrolled cell division and tissue invasiveness of the female uterine cervix. With the availability of new technologies researchers have increased their efforts to develop novel biomarkers for early diagnosis, and evaluation and monitoring of therapeutic treatments. This approach will help in the development of early diagnosis and in increasing treatment efficacy with decreased recurrence. The present review explains the currently available biomarkers for cervical cancer diagnosis and prognosis. Apart from the currently available biomarkers the review also explains strategies for the development of biomarkers based on cellular and molecular approaches such as DNA, protein and other metabolic markers with suitable clinical examples. The investigations of specific proteins, enzymes and metabolites will establish more useful biomarkers for accurate detection and management of gynecological cancers especially cervical cancer. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Diagnostic and prognostic epigenetic biomarkers in cancer.

    Science.gov (United States)

    Costa-Pinheiro, Pedro; Montezuma, Diana; Henrique, Rui; Jerónimo, Carmen

    2015-01-01

    Growing cancer incidence and mortality worldwide demands development of accurate biomarkers to perfect detection, diagnosis, prognostication and monitoring. Urologic (prostate, bladder, kidney), lung, breast and colorectal cancers are the most common and despite major advances in their characterization, this has seldom translated into biomarkers amenable for clinical practice. Epigenetic alterations are innovative cancer biomarkers owing to stability, frequency, reversibility and accessibility in body fluids, entailing great potential of assay development to assist in patient management. Several studies identified putative epigenetic cancer biomarkers, some of which have been commercialized. However, large multicenter validation studies are required to foster translation to the clinics. Herein we review the most promising epigenetic detection, diagnostic, prognostic and predictive biomarkers for the most common cancers.

  16. Functional metabolomics: from biomarker discovery to metabolome reprogramming.

    Science.gov (United States)

    Peng, Bo; Li, Hui; Peng, Xuan-Xian

    2015-09-01

    Metabolomics is emerging as a powerful tool for studying metabolic processes, identifying crucial biomarkers responsible for metabolic characteristics and revealing metabolic mechanisms, which construct the content of discovery metabolomics. The crucial biomarkers can be used to reprogram a metabolome, leading to an aimed metabolic strategy to cope with alteration of internal and external environments, naming reprogramming metabolomics here. The striking feature on the similarity of the basic metabolic pathways and components among vastly different species makes the reprogramming metabolomics possible when the engineered metabolites play biological roles in cellular activity as a substrate of enzymes and a regulator to other molecules including proteins. The reprogramming metabolomics approach can be used to clarify metabolic mechanisms of responding to changed internal and external environmental factors and to establish a framework to develop targeted tools for dealing with the changes such as controlling and/or preventing infection with pathogens and enhancing host immunity against pathogens. This review introduces the current state and trends of discovery metabolomics and reprogramming metabolomics and highlights the importance of reprogramming metabolomics.

  17. 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

  18. MicroRNAs as Novel Biomarkers for Breast Cancer

    Directory of Open Access Journals (Sweden)

    H. M. Heneghan

    2010-01-01

    Full Text Available Breast cancer is a complex phenotypically diverse genetic disease, involving a variety of changes in gene expression and structure. Recent advances in molecular profiling technology have made great progress in unravelling the molecular taxonomy of breast cancer, which has shed new light on the aetiology of the disease and also heralded great potential for the development of novel biomarkers and therapeutic targets. Mi(croRNAs are a contemporary class of small noncoding endogenous RNA molecules, generating great excitement in the clinical and scientific communities. The recent discovery that miRNA expression is frequently dysregulated in cancer has uncovered an entirely new repertoire of molecular factors upstream of gene expression, which warrants extensive investigation to further elucidate their precise role in malignancy. We present a comprehensive and timely review of the role of miRNAs in cancer: addressing miRNA function, their putative role as oncogenes or tumor suppressors, with a particular emphasis on breast cancer throughout. We discuss the recent discovery of quantifiable circulating cancer-associated miRNAs, which heralds immense potential for their use as novel minimally invasive biomarkers for breast and other cancers. Finally, we comment on the potential role of miRNAs in breast cancer management, particularly in improving current prognostic tools and achieving the goal of individualized cancer treatment.

  19. The Present and Future of Prostate Cancer Urine Biomarkers

    Directory of Open Access Journals (Sweden)

    Jeremy Clark

    2013-06-01

    Full Text Available In order to successfully cure patients with prostate cancer (PCa, it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field.

  20. 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,

  1. INDEED: Integrated differential expression and differential network analysis of omic data for biomarker discovery.

    Science.gov (United States)

    Zuo, Yiming; Cui, Yi; Di Poto, Cristina; Varghese, Rency S; Yu, Guoqiang; Li, Ruijiang; Ressom, Habtom W

    2016-12-01

    Differential expression (DE) analysis is commonly used to identify biomarker candidates that have significant changes in their expression levels between distinct biological groups. One drawback of DE analysis is that it only considers the changes on single biomolecule level. Recently, differential network (DN) analysis has become popular due to its capability to measure the changes on biomolecular pair level. In DN analysis, network is typically built based on correlation and biomarker candidates are selected by investigating the network topology. However, correlation tends to generate over-complicated networks and the selection of biomarker candidates purely based on network topology ignores the changes on single biomolecule level. In this paper, we propose a novel approach, INDEED, that builds sparse differential network based on partial correlation and integrates DE and DN analyses for biomarker discovery. We applied this approach on real proteomic and glycomic data generated by liquid chromatography coupled with mass spectrometry for hepatocellular carcinoma (HCC) biomarker discovery study. For each omic data, we used one dataset to select biomarker candidates, built a disease classifier and evaluated the performance of the classifier on an independent dataset. The biomarker candidates, selected by INDEED, were more reproducible across independent datasets, and led to a higher classification accuracy in predicting HCC cases and cirrhotic controls compared with those selected by separate DE and DN analyses. INDEED also identified some candidates previously reported to be relevant to HCC, such as intercellular adhesion molecule 2 (ICAM2) and c4b-binding protein alpha chain (C4BPA), which were missed by both DE and DN analyses. In addition, we applied INDEED for survival time prediction based on transcriptomic data acquired by analysis of samples from breast cancer patients. We selected biomarker candidates and built a regression model for survival time prediction

  2. Rapid biosensing tools for cancer biomarkers.

    Science.gov (United States)

    Ranjan, Rajeev; Esimbekova, Elena N; Kratasyuk, Valentina A

    2017-01-15

    The present review critically discusses the latest developments in the field of smart diagnostic systems for cancer biomarkers. A wide coverage of recent biosensing approaches involving aptamers, enzymes, DNA probes, fluorescent probes, interacting proteins and antibodies in vicinity to transducers such as electrochemical, optical and piezoelectric is presented. Recent advanced developments in biosensing approaches for cancer biomarker owes much credit to functionalized nanomaterials due to their unique opto-electronic properties and enhanced surface to volume ratio. Biosensing methods for a plenty of cancer biomarkers has been summarized emphasizing the key principles involved. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Connie E. [Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine. 462 First Avenue, NBV 7N24, New York, NY 10016 (United States); Tchou-Wong, Kam-Meng; Rom, William N., E-mail: william.rom@nyumc.org [Department of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine. 462 First Avenue, NBV 7N24, New York, NY 10016 (United States); Department of Environmental Medicine, New York University School of Medicine, 57 Old Forge Road, Tuxedo, NY 10987 (United States)

    2011-07-19

    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.

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

    Directory of Open Access Journals (Sweden)

    William N. Rom

    2011-07-01

    Full Text Available 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.

  5. Malignant Mesothelioma Biomarkers: From Discovery to Use in Clinical Practice for Diagnosis, Monitoring, Screening, and Treatment.

    Science.gov (United States)

    Creaney, Jenette; Robinson, Bruce W S

    2017-07-01

    Malignant pleural mesothelioma is a highly aggressive tumor associated with asbestos exposure. There are few effective treatment options for mesothelioma, and patients have a very poor prognosis with a median survival of mesothelioma biomarker has been ongoing for the last 30 years. Many traditional soluble (glyco)protein biomarkers have been evaluated over this time, and an ever-increasing list of new biomarkers, including messenger RNA, DNA, microRNA, and antibodies, is being reported from biomarker discovery projects. To date, soluble mesothelin is the only tumor biomarker to receive US Food and Drug Administration approval for clinical use in mesothelioma. Mesothelin is a glycoprotein normally expressed on the surface of mesothelial cells, and in the cancerous state it can be present in circulation. Mesothelin has a limited expression on normal, nonmalignant tissue and is thus an attractive therapeutic target for mesothelin-positive tumors. In this review we will focus on the discovery and clinical usages of mesothelin and provide an update on other mesothelioma biomarkers and show how such biomarker studies might impact on the management of this deadly tumor in the future. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  6. Imaging biomarker roadmap for cancer studies

    OpenAIRE

    O'Connor, JPB; Aboagye, EO; Adams, JE; Aerts, HJWL; Barrington, SF; Beer, AJ; Boellaard, R.; Bohndiek, SE; Brady, M.; Brown, G.; Buckley, DL; Chenevert, TL; Clarke, LP; Collette, S.; Cook, GJ

    2016-01-01

    Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthc...

  7. Novel biomarkers for cancer detection and prognostication

    NARCIS (Netherlands)

    Mehra, N.

    2007-01-01

    In this thesis we used a variety of approaches for biomarker discovery; in Part I we assessed whether we could identify a non-invasive surrogate markers of angiogenesis, as new vessel formation plays critical roles in the growth and metastatic spread of tumors. Moreover, many agents targeting the

  8. Biomarkers of HIV-associated Cancer

    Directory of Open Access Journals (Sweden)

    Brian Thabile Flepisi

    2014-01-01

    Full Text Available 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 cancer, and predict response to chemotherapy. They offer the hope of early detection as well as tracking disease progression and recurrence. Current progress in the characterization of molecular genetics of HIV-associated cancers may form the basis for improved patient stratification and future targeted or individualized therapies. Biomarker use for cancer staging and personalization of therapy at the time of diagnosis could improve patient care. This review focuses on the relevance of biomarkers in the most common HIV-associated malignancies, namely, Kaposi sarcoma, non-Hodgkin's lymphoma, and invasive cervical cancer.

  9. 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...

  10. Methylated genes as new cancer biomarkers

    DEFF Research Database (Denmark)

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

    2009-01-01

    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...

  11. Towards reproducible MRM based biomarker discovery using dried blood spots.

    Science.gov (United States)

    Ozcan, Sureyya; Cooper, Jason D; Lago, Santiago G; Kenny, Diarmuid; Rustogi, Nitin; Stocki, Pawel; Bahn, Sabine

    2017-03-27

    There is an increasing interest in the use of dried blood spot (DBS) sampling and multiple reaction monitoring in proteomics. Although several groups have explored the utility of DBS by focusing on protein detection, the reproducibility of the approach and whether it can be used for biomarker discovery in high throughput studies is yet to be determined. We assessed the reproducibility of multiplexed targeted protein measurements in DBS compared to serum. Eighty-two medium to high abundance proteins were monitored in a number of technical and biological replicates. Importantly, as part of the data analysis, several statistical quality control approaches were evaluated to detect inaccurate transitions. After implementing statistical quality control measures, the median CV on the original scale for all detected peptides in DBS was 13.2% and in Serum 8.8%. We also found a strong correlation (r = 0.72) between relative peptide abundance measured in DBS and serum. The combination of minimally invasive sample collection with a highly specific and sensitive mass spectrometry (MS) technique allows for targeted quantification of multiple proteins in a single MS run. This approach has the potential to fundamentally change clinical proteomics and personalized medicine by facilitating large-scale studies.

  12. Advances in Biomarker Research for Pancreatic Cancer

    Science.gov (United States)

    Bhat, Kruttika; Wang, Fengfei; Ma, Qingyong; Li, Qinyu; Mallik, Sanku; Hsieh, Tze-chen; Wu, Erxi

    2012-01-01

    Pancreatic cancer (PC) is a leading cause of cancer related deaths in United States. The lack of early symptoms results in late-stage detection and a high mortality rate. Currently, the only potentially curative approach for PC is surgical resection, which is often unsuccessful because the invasive and metastatic nature of the tumor masses makes their complete removal difficult. Consequently, patients suffer relapses from remaining cancer stem cells or drug resistance that eventually lead to death. To improve the survival rate, the early detection of PC is critical. Current biomarker research in PC indicates that a serum carbohydrate antigen, CA 19-9, is the only available biomarker with approximately 90% specificity to PC. However, the efficacy of CA 19-9 for assessing prognosis and monitoring patients with PC remains contentious. Thus, advances in technology and the detection of new biomarkers with high specificity to PC are needed to reduce the mortality rate of pancreatic cancer. PMID:22372502

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

    Directory of Open Access Journals (Sweden)

    Joy eGuingab-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.

  14. 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.

  15. A Combined ULBP2 and SEMA5A Expression Signature as a Prognostic and Predictive Biomarker for Colon Cancer

    OpenAIRE

    Demirkol, Secil; Gomceli, Ismail; Isbilen, Murat; Dayanc, Baris Emre; Tez, Mesut; BOSTANCI, Erdal Birol; Turhan, Nesrin; Akoglu, Musa; Ozyerli, Ezgi; Durdu, Sevi; Konu, Ozlen; Nissan, Aviram; Gonen, Mithat; Gure, Ali Osmay

    2017-01-01

    Background: Prognostic biomarkers for cancer have the power to change the course of disease if they add value beyond known prognostic factors, if they can help shape treatment protocols, and if they are reliable. The aim of this study was to identify such biomarkers for colon cancer and to understand the molecular mechanisms leading to prognostic stratifications based on these biomarkers. Methods and Findings: We used an in house R based script (SSAT) for the in silico discovery of stage-inde...

  16. Cancer and molecular biomarkers of phase 2

    DEFF Research Database (Denmark)

    Dalhoff, Kim; Enghusen Poulsen, Henrik

    2005-01-01

    Associations between genotypes of phase 2 enzymes and cancer risk are extracted from epidemiological studies, namely case-control studies. Variant alleles in glutathione S-transferase (GST), UDP-glucuronosyltransferase (UGT), sulfotransferase (SULT), and N-acetyltransferase (NAT) have been used...... as molecular genetic biomarkers of risk. GSTM(my)1 has been associated with an increased risk of colorectal cancer, lung cancer, and bladder cancer and GSTP(pi)1 with prostate cancer. UGT1A1*28 and *37 are both associated with an increased risk of breast cancer as is SULT1A1*2. The presence of UGT1A1......*28 results in an increased risk of ovarian cancer and NAT2 of colorectal and lung cancer. A high frequency of SULT1A1*1 has been identified in patients with breast cancer; the role in colorectal cancer is more controversial. This chapter discusses the balance between carcinogen activation and detoxification...

  17. Discovery and validation of prostate cancer biomarkers

    NARCIS (Netherlands)

    F.H. Jansen (Flip)

    2013-01-01

    textabstractThe prostate, derived from the Greek word προστάτης – prostates, meaning “the one who stands before”, is a walnut-sized exocrine gland, part of the male genitourinary tract. It produces and stores an alkaline fluid, which liquefies the semen and prolongs the life-span of the spermatozoa.

  18. 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.

  19. 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.

  20. Challenges for the application of DNA methylation biomarkers in molecular diagnostic testing for cancer.

    Science.gov (United States)

    Jain, Surbhi; Wojdacz, Tomasz K; Su, Ying-Hsiu

    2013-04-01

    Aberrant DNA methylation is ubiquitous in human cancer and has been shown to occur early during carcinogenesis, thus providing attractive potential biomarkers for the early detection of cancer. The introduction of genome-wide DNA methylation analysis comparing tumor and nonmalignant tissues resulted in the discovery of many regions that undergo aberrant methylation during carcinogenesis. Those regions can potentially be used as biomarkers for cancer detection. However, a biomarker will be useful for screening or early detection of cancer only if it can be detected in a noninvasive or minimally invasive fashion without tissue biopsy. The authors discuss the challenges in translating DNA methylation biomarkers to cancer diagnosis - including obstacles in assay development, tissue-specific methylation load on tumor suppressor genes, detecting markers with sufficient sensitivity and specificity in the periphery, and ways in which these obstacles can be overcome.

  1. Biomarker discovery in subclinical mycobacterial infections of cattle.

    Directory of Open Access Journals (Sweden)

    Meetu Seth

    Full Text Available BACKGROUND: Bovine tuberculosis is a highly prevalent infectious disease of cattle worldwide; however, infection in the United States is limited to 0.01% of dairy herds. Thus detection of bovine TB is confounded by high background infection with M. avium subsp. paratuberculosis. The present study addresses variations in the circulating peptidome based on the pathogenesis of two biologically similar mycobacterial diseases of cattle. METHODOLOGY/PRINCIPAL FINDINGS: We hypothesized that serum proteomes of animals in response to either M. bovis or M. paratuberculosis infection will display several commonalities and differences. Sera prospectively collected from animals experimentally infected with either M. bovis or M. paratuberculosis were analyzed using high-resolution proteomics approaches. iTRAQ, a liquid chromatography and tandem mass spectrometry approach, was used to simultaneously identify and quantify peptides from multiple infections and contemporaneous uninfected control groups. Four comparisons were performed: 1 M. bovis infection versus uninfected controls, 2 M. bovis versus M. paratuberculosis infection, 3 early, and 4 advanced M. paratuberculosis infection versus uninfected controls. One hundred and ten differentially elevated proteins (P < or = 0.05 were identified. Vitamin D binding protein precursor (DBP, alpha-1 acid glycoprotein, alpha-1B glycoprotein, fetuin, and serine proteinase inhibitor were identified in both infections. Transthyretin, retinol binding proteins, and cathelicidin were identified exclusively in M. paratuberculosis infection, while the serum levels of alpha-1-microglobulin/bikunin precursor (AMBP protein, alpha-1 acid glycoprotein, fetuin, and alpha-1B glycoprotein were elevated exclusively in M. bovis infected animals. CONCLUSIONS/SIGNIFICANCE: The discovery of these biomarkers has significant impact on the elucidation of pathogenesis of two mycobacterial diseases at the cellular and the molecular level and

  2. 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.

  3. VOC breath biomarkers in lung cancer.

    Science.gov (United States)

    Saalberg, Yannick; Wolff, Marcus

    2016-08-01

    This review provides an overview of volatile organic compounds (VOCs) which are considered lung cancer biomarkers for diagnostic breath analysis. It includes results of scientific publications from 1985 to 2015. The identified VOCs are listed and ranked according to their occurrence of nomination. The applied detection and sampling methods are specified but not evaluated. Possible reasons for the different results of the studies are stated. Among the most frequently emerging biomarkers are 2-butanone and 1-propanol as well as isoprene, ethylbenzene, styrene and hexanal. The outcome of this review may be helpful for the development of a lung cancer screening device. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Current early diagnostic biomarkers of prostate cancer

    Directory of Open Access Journals (Sweden)

    Min Qu

    2014-08-01

    Full Text Available Prostate cancer (PCa has become to have the highest incidence and the second mortality rate in western countries, affecting men's health to a large extent. Although prostate-specific antigen (PSA was discovered to help diagnose the cancer in an early stage for decades, its specificity is relative low, resulting in unnecessary biopsy for healthy people and over-treatment for patients. Thus, it is imperative to identify more and more effective biomarkers for early diagnosis of PCa in order to distinguish patients from healthy populations, which helps guide an early treatment to lower disease-related mortality by noninvasive or minimal invasive approaches. This review generally describes the current early diagnostic biomarkers of PCa in addition to PSA and summarizes the advantages and disadvantages of these biomarkers.

  5. Validation of Biomarkers for Prostate Cancer Prognosis

    Science.gov (United States)

    2016-11-01

    prostate cancer is the development of biomarkers that predict occult or incipient aggressive disease in the low-risk population. To address this...8-10 vs. <=6 5.13 1.92 13.75 0.001 6. P27 is not significantly associated with RFS after adjusting for clinical predictors (Manuscript in

  6. Mps1/TTK: a novel target and biomarker for cancer.

    Science.gov (United States)

    Xie, Yuan; Wang, Anqiang; Lin, Jianzhen; Wu, Liangcai; Zhang, Haohai; Yang, Xiaobo; Wan, Xueshuai; Miao, Ruoyu; Sang, Xinting; Zhao, Haitao

    2017-02-01

    Monopolar spindle1 (Mps1, also known as TTK) is the core component of the spindle assembly checkpoint, which functions to ensure proper distribution of chromosomes to daughter cells. Mps1 is hardly detectable in normal organs except the testis and placenta. However, high levels of Mps1 are found in many types of human malignancies, including glioblastoma, thyroid carcinoma, breast cancer, and other cancers. Several Mps1 inhibitors can inhibit the proliferation of cancer cells and exhibit demonstrable survival benefits. Mps1 can be utilized as a new immunogenic epitope, which is able to induce potent cytotoxic T lymphocyte activity against cancer cells while sparing normal cells. Some clinical trials have validated its safety, immunogenicity and clinical response. Thus, Mps1 may be a novel target for cancer therapy. Mps1 is differentially expressed between normal and malignant tissues, indicating its potential as a molecular biomarker for diagnosis. Meanwhile, the discovery that it clearly correlates with recurrence and survival time suggests it may serve as an independent prognostic biomarker as well.

  7. Searching for new biomarkers in ovarian cancer patients: Rationale and design of a retrospective study under the Mermaid III project

    Directory of Open Access Journals (Sweden)

    Julie L. Hentze

    2017-12-01

    A thorough investigation of biomarkers in ovarian cancer, including large numbers of different markers, has never been done before. Besides from improving diagnosis and treatment, other outcomes could be markers for screening, knowledge of the molecular aspects of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives.

  8. Proteomic biomarkers in lung cancer.

    Science.gov (United States)

    Pastor, M D; Nogal, A; Molina-Pinelo, S; Carnero, A; Paz-Ares, L

    2013-09-01

    The correct understanding of tumour development relies on the comprehensive study of proteins. They are the main orchestrators of vital processes, such as signalling pathways, which drive the carcinogenic process. Proteomic technologies can be applied to cancer research to detect differential protein expression and to assess different responses to treatment. Lung cancer is the number one cause of cancer-related death in the world. Mostly diagnosed at late stages of the disease, lung cancer has one of the lowest 5-year survival rates at 15 %. The use of different proteomic techniques such as two-dimensional gel electrophoresis (2D-PAGE), isotope labelling (ICAT, SILAC, iTRAQ) and mass spectrometry may yield new knowledge on the underlying biology of lung cancer and also allow the development of new early detection tests and the identification of changes in the cancer protein network that are associated with prognosis and drug resistance.

  9. Molecular alterations and biomarkers in colorectal cancer

    Science.gov (United States)

    Grady, William M.; Pritchard, Colin C.

    2013-01-01

    The promise of precision medicine is now a clinical reality. Advances in our understanding of the molecular genetics of colorectal cancer genetics is leading to the development of a variety of biomarkers that are being used as early detection markers, prognostic markers, and markers for predicting treatment responses. This is no more evident than in the recent advances in testing colorectal cancers for specific molecular alterations in order to guide treatment with the monoclonal antibody therapies cetuximab and panitumumab, which target the epidermal growth factor receptor (EGFR). In this review, we update a prior review published in 2010 and describe our current understanding of the molecular pathogenesis of colorectal cancer and how these alterations relate to emerging biomarkers for early detection and risk stratification (diagnostic markers), prognosis (prognostic markers), and the prediction of treatment responses (predictive markers). PMID:24178577

  10. Proteomic Approaches to Biomarker Discovery in Cutaneous T-Cell Lymphoma

    Directory of Open Access Journals (Sweden)

    Alexandra Ion

    2016-01-01

    Full Text Available Cutaneous T-cell lymphoma (CTCL is the most frequently encountered type of skin lymphoma in humans. CTCL encompasses multiple variants, but the most common types are mycosis fungoides (MF and Sezary syndrome (SS. While most cases of MF run a mild course over a period of many years, other subtypes of CTCL are very aggressive. The rapidly expanding fields of proteomics and genomics have not only helped increase knowledge concerning the carcinogenesis and tumor biology of CTCL but also led to the discovery of novel markers for targeted therapy. Although multiple biomarkers linked to CTCL have been known for a relatively long time (e.g., CD25, CD45, CD45RA, and CD45R0, compared to other cancers (lymphoma, melanoma, colon carcinoma, head and neck cancer, renal cancer, and cutaneous B-cell lymphoma, information about the antigenicity of CTCL remains relatively limited and no dependable protein marker for CTCL has been discovered. Considering the aggressive nature of some types of CTCL, it is necessary to identify circulating molecules that can help in the early diagnosis, differentiation from inflammatory skin diseases (psoriasis, nummular eczema, and aid in predicting the prognosis and evolution of this pathology. This review aims to bring together some of the information concerning protein markers linked to CTCL, in an effort to further the understanding of the convolute processes involved in this complex pathology.

  11. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

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

    2014-01-01

    AIM: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients. PATIENTS AND METHODS: The study consisted of three parts: Part I: Biomarker data obtained from mass spectrometry, baseline data and, surgical outcome were.......64. CONCLUSION: Our validated model based on biomarkers was unable to predict surgical outcome for patients with ovarian cancer....

  12. Identification of biomarkers for lung cancer in never smokers — EDRN Public Portal

    Science.gov (United States)

    The overall goal of this project is to identify, verify and apply biomarkers for the early diagnosis or risk assessment of lung cancer in never smokers. The first year will be regarded as a year of discovery. After successful demonstration of the feasibility of the approach for novel marker discovery, funding will be applied for to perform confirmation and preclinical studies on the biomarkers and validation studies (specific aims 2 and 3, to be performed in years two and three). Year two can be regarded as the year of confirmation and year three as the year of validation.

  13. Drug discovery in prostate cancer mouse models.

    Science.gov (United States)

    Valkenburg, Kenneth C; Pienta, Kenneth J

    2015-01-01

    The mouse is an important, though imperfect, organism with which to model human disease and to discover and test novel drugs in a preclinical setting. Many experimental strategies have been used to discover new biological and molecular targets in the mouse, with the hopes of translating these discoveries into novel drugs to treat prostate cancer in humans. Modeling prostate cancer in the mouse, however, has been challenging, and often drugs that work in mice have failed in human trials. The authors discuss the similarities and differences between mice and men; the types of mouse models that exist to model prostate cancer; practical questions one must ask when using a mouse as a model; and potential reasons that drugs do not often translate to humans. They also discuss the current value in using mouse models for drug discovery to treat prostate cancer and what needs are still unmet in field. With proper planning and following practical guidelines by the researcher, the mouse is a powerful experimental tool. The field lacks genetically engineered metastatic models, and xenograft models do not allow for the study of the immune system during the metastatic process. There remain several important limitations to discovering and testing novel drugs in mice for eventual human use, but these can often be overcome. Overall, mouse modeling is an essential part of prostate cancer research and drug discovery. Emerging technologies and better and ever-increasing forms of communication are moving the field in a hopeful direction.

  14. A New Serum Biomarker for Lung Cancer - Transthyretin

    OpenAIRE

    Liu, Liyun; Sun, Suozhu; Liu, JiFu; WU, SHANSHAN; Songwei DAI; Wang, Xiaomin; Huang, Lingyun; Xueyuan XIAO; He, Dacheng

    2009-01-01

    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 we...

  15. Biomarker discovery for kidney diseases by mass spectrometry.

    Science.gov (United States)

    Niwa, Toshimitsu

    2008-07-15

    By the development of soft ionization such as matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI), mass spectrometry (MS) has become an indispensable technique to analyze proteins. The combination of protein separation and identification such as two-dimensional gel electrophoresis and MS, surface-enhanced laser desorption/ionization-MS, liquid chromatography/MS, and capillary electrophoresis/MS has been successfully applied for proteome analysis of urine and plasma to discover biomarkers of kidney diseases. Some urinary proteins and their proteolytic fragments have been identified as biomarker candidates for kidney diseases. This article reviews recent advances in the application of proteomics using MS to discover biomarkers for kidney diseases.

  16. Gaucher disease: a model disorder for biomarker discovery

    DEFF Research Database (Denmark)

    Boot, Rolf G; van Breemen, Mariëlle J; Wegdam, Wouter

    2009-01-01

    Gaucher disease is an inherited lysosomal storage disorder, characterized by massive accumulation of glucosylceramide-laden macrophages in the spleen, liver and bone marrow as a consequence of deficient activity of glucocerebrosidase. Gaucher disease has been the playground to develop new...... role of storage cells in the pathology, various attempts have been made to identify proteins in plasma or serum reflecting the body burden of these pathological cells. In this review, the existing data regarding biomarkers for Gaucher disease, as well as the current application of biomarkers...

  17. Metabolomic approaches in the discovery of potential urinary biomarkers of drug-induced liver injury (DILI).

    Science.gov (United States)

    Araújo, Ana Margarida; Carvalho, Márcia; Carvalho, Félix; Bastos, Maria de Lourdes; Guedes de Pinho, Paula

    2017-09-01

    Drug-induced liver injury (DILI) is a major safety issue during drug development, as well as the most common cause for the withdrawal of drugs from the pharmaceutical market. The identification of DILI biomarkers is a labor-intensive area. Conventional biomarkers are not specific and often only appear at significant levels when liver damage is substantial. Therefore, new biomarkers for early identification of hepatotoxicity during the drug discovery process are needed, thus resulting in lower development costs and safer drugs. In this sense, metabolomics has been increasingly playing an important role in the discovery of biomarkers of liver damage, although the characterization of the mechanisms of toxicity induced by xenobiotics remains a huge challenge. These new-generation biomarkers will offer obvious benefits for the pharmaceutical industry, regulatory agencies, as well as a personalized clinical follow-up of patients, upon validation and translation into clinical practice or approval for routine use. This review describes the current status of the metabolomics applied to the early diagnosis and prognosis of DILI and in the discovery of new potential urinary biomarkers of liver injury.

  18. Endo-β-N-acetylglucosaminidase H de-N-glycosylation in a domestic microwave oven: application to biomarker discovery.

    Science.gov (United States)

    Frisch, Elena; Schwedler, Christian; Kaup, Matthias; Iona Braicu, Elena; Gröne, Jörn; Lauscher, Johannes C; Sehouli, Jalid; Zimmermann, Matthias; Tauber, Rudolf; Berger, Markus; Blanchard, Véronique

    2013-02-01

    Sample preparation is the rate-limiting step in glycan analysis workflows. Among all of the steps, enzymatic digestions, which are usually performed overnight, are the most time-consuming. In the current study, we report an economical and fast preparation of N-glycans from serum, including microwave-assisted enzymatic digestion in the absence of denaturing chemicals and solvents during the release. To this end, we used a household microwave oven to accelerate both pronase and endo-β-N-acetylglucosaminidase H (Endo H) digestions. Purification was then performed using self-made SP20SS and carbon tips. We were able to prepare samples in 55 min instead of 21 h. Finally, the method was applied in the context of oncological biomarker discovery exemplarily to ovarian and colon cancer. We observed a significant downregulation of sialylated hybrid structures in ovarian cancer samples using capillary electrophoresis-laser-induced fluorescence (CE-LIF). Furthermore, sepsis, a systemic inflammatory response syndrome, was also included in the study to understand whether the changes observed in ovarian cancer patients were due to the cancer itself or to the inflammation that usually accompanies its development. Because sialylated hybrid structures were upregulated in sepsis samples, the downregulation of these structures in ovarian cancer is specific to the cancer itself and, therefore, could be used as a biomarker. Copyright © 2012 Elsevier Inc. All rights reserved.

  19. Mass spectrometry for the discovery of biomarkers of sepsis.

    Science.gov (United States)

    Ludwig, Katelyn R; Hummon, Amanda B

    2017-03-28

    Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

  20. Revisiting biomarker discovery by plasma proteomics

    DEFF Research Database (Denmark)

    Geyer, Philipp E; Holdt, Lesca M; Teupser, Daniel

    2017-01-01

    slow rate. As described in this review, mass spectrometry (MS)-based proteomics has become a powerful technology in biological research and it is now poised to allow the characterization of the plasma proteome in great depth. Previous "triangular strategies" aimed at discovering single biomarker...

  1. 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...

  2. 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...

  3. An antibody-based biomarker discovery method by mass spectrometry sequencing of complementarity determining regions

    NARCIS (Netherlands)

    L.J.M. Dekker (Lennard); L. Zeneyedpour (Lona); E. Brouwer (Eric); M.M. Duijn (Martijn); P.A.E. Sillevis Smitt (Peter); T.M. Luider (Theo)

    2011-01-01

    textabstractAutoantibodies are increasingly used as biomarkers in the detection of autoimmune disorders and cancer. Disease specific antibodies are generally detected by their binding to specific antigens. As an alternative approach, we propose to identify specific complementarity determining

  4. Neoadjuvant Trials in ER+ Breast Cancer: A Tool for Acceleration of Drug Development and Discovery.

    Science.gov (United States)

    Guerrero-Zotano, Angel L; Arteaga, Carlos L

    2017-06-01

    Neoadjuvant therapy trials offer an excellent strategy for drug development and discovery in breast cancer, particularly in triple-negative and HER2-overexpressing subtypes, where pathologic complete response is a good surrogate of long-term patient benefit. For estrogen receptor-positive (ER+) breast cancers, however, use of this strategy has been challenging because of the lack of validated surrogates of long-term efficacy and the overall good prognosis of the majority of patients with this cancer subtype. We review below the clinical benefits of neoadjuvant endocrine therapy for ER+/HER2-negative breast cancer, its use and limitations for drug development, prioritization of adjuvant and metastatic trials, and biomarker discovery.Significance: Neoadjuvant endocrine therapy is an excellent platform for the development of investigational drugs, triaging of novel combinations, biomarker validation, and discovery of mechanisms of drug resistance. This review summarizes the clinical and investigational benefits of this approach, with a focus on how to best integrate predictive biomarkers into novel clinical trial designs. Cancer Discov; 7(6); 561-74. ©2017 AACR. ©2017 American Association for Cancer Research.

  5. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

    Balog, Crina I.; Hensbergen, Paul J.; Derks, Rico

    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 ...... was negative. CONCLUSIONS: We present a practical, step-by-step method for screening and identification of urinary peptides. Alongside the analytical method evaluation on standard samples, we demonstrate its feasibility with actual clinical material....

  6. Prostate cancer biomarkers: Are we hitting the mark?

    Directory of Open Access Journals (Sweden)

    Shannon McGrath

    2016-12-01

    Conclusion: The accurate diagnosis and risk stratification of prostate cancer is critical to ensure appropriate intervention. The development of non-invasive biomarkers can add to the information provided by current screening practices and allows for individualised risk stratification of patients. The use of these biomarkers appears to increase the sensitivity and specificity of diagnosis of prostate cancer. Further studies are necessary to define the appropriate use and time points of each biomarker and their effect on the management algorithm of prostate cancer.

  7. Biomarkers of depression in cancer patients.

    Science.gov (United States)

    Jehn, Christian Friedrich; Kuehnhardt, Dagmar; Bartholomae, Andrea; Pfeiffer, Sebastian; Krebs, Michael; Regierer, Anne Constanze; Schmid, Peter; Possinger, Kurt; Flath, Bernd Christian

    2006-12-01

    Inflammation and perturbation of the hypothalamic-pituitary-adrenal (HPA) axis function appears to play a putative role in the etiology of depression. Patients with metastatic cancer demonstrate elevated prevalence rates for depression. The objective of the current study was to illustrate the efficacy of interleukin-6 (IL-6) and HPA axis function as adjuncts to support the diagnosis of depression in cancer patients. Plasma concentrations of IL-6 and cortisol were measured in 114 cancer patients with and without depression. The relative diurnal variation of cortisol (cortisol VAR), expressed as a percentage, was calculated. Receiver operating characteristics analysis was performed. Depression was associated with increased plasma concentrations of IL-6 (18.7 pg/mL vs. 2.7 pg/mL; P < .001) and higher cortisol concentrations at 8 AM and 8 PM. The relative cortisol VAR (11.7% vs. 60.6%, respectively; P < .001) was found to be decreased in cancer patients with depression, indicating a disturbed circadian function of the HPA axis. As a biomarker of depression, IL-6 yielded at a cutoff value of 10.6 pg/mL, a sensitivity of 79%, and a specificity of 87% (area under the curve [AUC] = 0.86; 95% confidence interval [95% CI], 0.78-0.94), whereas cortisol VAR demonstrated a sensitivity of 81% and a specificity of 88% (AUC = 0.85; 95% CI, 0.74-0.97) at a cutoff value of 33.5%. Depression is associated with increased plasma IL-6 concentrations in patients with cancer. These patients demonstrate a dysfunction of the HPA-axis, characterized by a decreased diurnal variation of cortisol. The high sensitivity and specificity of these parameters biomarkers of depression make IL-6 and cortisol VAR helpful tools in the diagnosis of depression in patients with cancer. (c) 2006 American Cancer Society.

  8. Cancer therapy trials employing level-of-evidence-1 disease forecast cancer biomarkers uPA and its inhibitor PAI-1

    DEFF Research Database (Denmark)

    Schmitt, Manfred; Harbeck, Nadia; Brünner, Nils

    2011-01-01

    conducted in early breast cancer to demonstrate the prognostic and predictive value for this malignancy. As a result of these investigations, uPA and PAI-1 have reached the highest level of clinical evidence, level of evidence 1. This article sheds light on the current status of major clinical Phase II......-size synthetic peptide (Å6) is tested in advanced ovarian cancer patients.......Clinical research on cancer biomarkers is essential in understanding recent discoveries in cancer biology and heterogeneity of the cancer disease. However, there are only a few examples of clinically useful studies that have identified cancer biomarkers with clinical benefit. Urokinase...

  9. Identification of Filamin-A and -B as potential biomarkers for prostate cancer

    Science.gov (United States)

    Narain, Niven R; Diers, Anne R; Lee, Arleide; Lao, Socheata; Chan, Joyce Y; Schofield, Sally; Andreazi, Joe; Ouro-Djobo, Rakibou; Jimenez, Joaquin J; Friss, Tracey; Tanna, Nikunj; Dalvi, Aditee; Wang, Sihe; Bunch, Dustin; Sun, Yezhou; Wu, Wenfang; Thapa, Khampaseuth; Gesta, Stephane; Rodrigues, Leonardo O; Akmaev, Viatcheslav R; Vishnudas, Vivek K; Sarangarajan, Rangaprasad

    2017-01-01

    Aim: A novel strategy for prostate cancer (PrCa) biomarker discovery is described. Materials & methods: In vitro perturbation biology, proteomics and Bayesian causal analysis identified biomarkers that were validated in in vitro models and clinical specimens. Results: Filamin-B (FLNB) and Keratin-19 were identified as biomarkers. Filamin-A (FLNA) was found to be causally linked to FLNB. Characterization of the biomarkers in a panel of cells revealed differential mRNA expression and regulation. Moreover, FLNA and FLNB were detected in the conditioned media of cells. Last, in patients without PrCa, FLNA and FLNB blood levels were positively correlated, while in patients with adenocarcinoma the relationship is dysregulated. Conclusion: These data support the strategy and the potential use of the biomarkers for PrCa. PMID:28344825

  10. Detecting Blood-Based Biomarkers in Metastatic Breast Cancer: A Systematic Review of Their Current Status and Clinical Utility

    Directory of Open Access Journals (Sweden)

    A. M. Sofie Berghuis

    2017-02-01

    Full Text Available Reviews on circulating biomarkers in breast cancer usually focus on one single biomarker or a selective group of biomarkers. An overview summarizing the discovery and evaluation of all blood-based biomarkers in metastatic breast cancer is lacking. This systematic review aims to identify the available evidence of known blood-based biomarkers in metastatic breast cancer, regarding their clinical utility and state-of-the-art position in the validation process. The initial search yielded 1078 original studies, of which 420 were assessed for eligibility. A total of 320 studies were included in the final synthesis. A Development, Evaluation and Application Chart (DEAC of all biomarkers was developed. Most studies focus on identifying new biomarkers and search for relations between these biomarkers and traditional molecular characteristics. Biomarkers are usually investigated in only one study (68.8%. Only 9.8% of all biomarkers was investigated in more than five studies. Circulating tumor cells, gene expression within tumor cells and the concentration of secreted proteins are the most frequently investigated biomarkers in liquid biopsies. However, there is a lack of studies focusing on identifying the clinical utility of these biomarkers, by which the additional value still seems to be limited according to the investigated evidence.

  11. Biomarker discovery by proteomics : challenges not only for the analytical chemist

    NARCIS (Netherlands)

    Horvatovich, Peter; Govorukhina, Natalia; Bischoff, Rainer

    2006-01-01

    This forum article outlines some of the major challenges in present day biomarker discovery research. Notably the dilemma of reaching sufficient concentration sensitivity versus the required analysis time per sample is highlighted using a model calculation. A number of possible developments and

  12. 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

  13. 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

  14. 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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Comprehensive Phenotyping in Multiple Sclerosis: Discovery Based Proteomics and the Current Understanding of Putative Biomarkers

    Directory of Open Access Journals (Sweden)

    Kevin C. O’Connor

    2006-01-01

    Full Text Available Currently, there is no single test for multiple sclerosis (MS. Diagnosis is confirmed through clinical evaluation, abnormalities revealed by magnetic resonance imaging (MRI, and analysis of cerebrospinal fluid (CSF chemistry. The early and accurate diagnosis of the disease, monitoring of progression, and gauging of therapeutic intervention are important but elusive elements of patient care. Moreover, a deeper understanding of the disease pathology is needed, including discovery of accurate biomarkers for MS. Herein we review putative biomarkers of MS relating to neurodegeneration and contributions to neuropathology, with particular focus on autoimmunity. In addition, novel assessments of biomarkers not driven by hypotheses are discussed, featuring our application of advanced proteomics and metabolomics for comprehensive phenotyping of CSF and blood. This strategy allows comparison of component expression levels in CSF and serum between MS and control groups. Examination of these preliminary data suggests that several CSF proteins in MS are differentially expressed, and thus, represent putative biomarkers deserving of further evaluation.

  16. Renal Cancer Biomarkers | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Laboratory of Proteomics and Analytical Technologies is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize diagnostic, therapeutic and prognostic cancer biomarkers from clinical specimens.

  17. Consortium for Imaging and Biomarkers (CIB) | Division of Cancer Prevention

    Science.gov (United States)

    Overdiagnosis and false positives present | 8 lead investigators combining imaging methods for the visualization of lesions with biomarkers to improve the accuracy of screening, early cancer detection, and the diagnosis of early stage cancers.

  18. Epigenetic Alterations in Colorectal Cancer: Emerging Biomarkers

    Science.gov (United States)

    Okugawa, Yoshinaga; Grady, William M.; Goel, Ajay

    2015-01-01

    Colorectal cancer (CRC) is a leading cause of cancer deaths worldwide. One of the fundamental processes driving the initiation and progression of CRC is the accumulation of a variety of genetic and epigenetic changes in colon epithelial cells. Over the past decade, major advances have been made in our understanding of cancer epigenetics, particularly regarding aberrant DNA methylation, microRNA (miRNA) and noncoding RNA deregulation, and alterations in histone modification states. Assessment of the colon cancer “epigenome” has revealed that virtually all CRCs have aberrantly methylated genes and altered miRNA expression. The average CRC methylome has hundreds to thousands of abnormally methylated genes and dozens of altered miRNAs. As with gene mutations in the cancer genome, a subset of these epigenetic alterations, called driver events, is presumed to have a functional role in CRC. In addition, the advances in our understanding of epigenetic alterations in CRC have led to these alterations being developed as clinical biomarkers for diagnostic, prognostic and therapeutic applications. Progress in this field suggests that these epigenetic alterations will be commonly used in the near future to direct the prevention and treatment of CRC. PMID:26216839

  19. Biomarkers as prognostic factors in endometrial cancer.

    Directory of Open Access Journals (Sweden)

    Sławomir J Terlikowski

    2010-11-01

    Full Text Available Endometrial cancer is the most common gynecologic malignancy in more developed countries. Approximately 75% of cases are diagnosed at an early stage with a tumor confined to the uterine corpus. Although most patients are cured by surgery alone, about 15-20% with no signs of locally advanced or metastatic disease at primary treatment recurs, with limited responsiveness to systemic therapy. The most common basis for determining the risk of recurrent disease has been classification of endometrial cancers into two subtypes. Type I, associated with a good prognosis and endometrioid histology and type II, associated with a poor prognosis and non-endometrioid histology. This review will focus primarily on the molecular biomarkers that have supported the dualistic model of endometrial carcinoma and help determine which patients would benefit from either adjuvant therapy or more aggressive primary treatment.

  20. Proteomic biomarkers for lung cancer progression.

    Science.gov (United States)

    Ren, Yanjiao; Zhao, Shishun; Jiang, Dandan; Feng, Xin; Zhang, Yexian; Wei, Zhipeng; Wang, Zhongyu; Zhang, Wenniu; Zhou, Qing F; Li, Yong; Hou, Hanxu; Xu, Ying; Zhou, Fengfeng

    2018-02-09

    Lung adenocarcinoma (LUAD) and lung squamous-cell carcinoma (LUSC) are two major subtypes of lung cancer and constitute about 70% of all the lung cancer cases. The patient's lifespan and living quality will be significantly improved if they are diagnosed at an early stage and adequately treated. Methodology & results: This study comprehensively screened the proteomic dataset of both LUAD and LUSC, and proposed classification models for the progression stages of LUAD and LUSC with accuracies 86.51 and 89.47%, respectively. A comparative analysis was also carried out on related transcriptomic datasets, which indicates that the proposed biomarkers provide discerning power for accurate stage prediction, and will be improved when larger-scale proteomic quantitative technologies become available.

  1. Proteomic characterization of the interstitial fluid perfusing the breast tumor microenvironment: a novel resource for biomarker and therapeutic target discovery.

    Science.gov (United States)

    Celis, Julio E; Gromov, Pavel; Cabezón, Teresa; Moreira, José M A; Ambartsumian, Noona; Sandelin, Kerstin; Rank, Fritz; Gromova, Irina

    2004-04-01

    Clinical cancer proteomics aims at the identification of markers for early detection and predictive purposes, as well as to provide novel targets for drug discovery and therapeutic intervention. Proteomics-based analysis of traditional sources of biomarkers, such as serum, plasma, or tissue lyzates, has resulted in a wealth of information and the finding of several potential tumor biomarkers. However, many of these markers have shown limited usefulness in a clinical setting, underscoring the need for new clinically relevant sources. Here we present a novel and highly promising source of biomarkers, the tumor interstitial fluid (TIF) that perfuses the breast tumor microenvironment. We collected TIFs from small pieces of freshly dissected invasive breast carcinomas and analyzed them by two-dimensional polyacrylamide gel electrophoresis in combination with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry, Western immunoblotting, as well as by cytokine-specific antibody arrays. This approach provided for the first time a snapshot of the protein components of the TIF, which we show consists of more than one thousand proteins--either secreted, shed by membrane vesicles, or externalized due to cell death--produced by the complex network of cell types that make up the tumor microenvironment. So far, we have identified 267 primary translation products including, but not limited to, proteins involved in cell proliferation, invasion, angiogenesis, metastasis, inflammation, protein synthesis, energy metabolism, oxidative stress, the actin cytoskeleton assembly, protein folding, and transport. As expected, the TIF contained several classical serum proteins. Considering that the protein composition of the TIF reflects the physiological and pathological state of the tissue, it should provide a new and potentially rich resource for diagnostic biomarker discovery and for identifying more selective targets for therapeutic intervention.

  2. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

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

    2014-01-01

    Aim: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients.......Aim: We aimed to construct and validate a model based on biomarkers to predict complete primary debulking surgery for ovarian cancer patients....

  3. Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

    Directory of Open Access Journals (Sweden)

    Oguzhan Begik

    2017-07-01

    Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

  4. Tissue compartment analysis for biomarker discovery by gene expression profiling.

    Directory of Open Access Journals (Sweden)

    Antoine Disset

    Full Text Available BACKGROUND: Although high throughput technologies for gene profiling are reliable tools, sample/tissue heterogeneity limits their outcomes when applied to identify molecular markers. Indeed, inter-sample differences in cell composition contribute to scatter the data, preventing detection of small but relevant changes in gene expression level. To date, attempts to circumvent this difficulty were based on isolation of the different cell structures constituting biological samples. As an alternate approach, we developed a tissue compartment analysis (TCA method to assess the cell composition of tissue samples, and applied it to standardize data and to identify biomarkers. METHODOLOGY/PRINCIPAL FINDINGS: TCA is based on the comparison of mRNA expression levels of specific markers of the different constitutive structures in pure isolated structures, on the one hand, and in the whole sample on the other. TCA method was here developed with human kidney samples, as an example of highly heterogeneous organ. It was validated by comparison of the data with those obtained by histo-morphometry. TCA demonstrated the extreme variety of composition of kidney samples, with abundance of specific structures varying from 5 to 95% of the whole sample. TCA permitted to accurately standardize gene expression level amongst >100 kidney biopsies, and to identify otherwise imperceptible molecular disease markers. CONCLUSIONS/SIGNIFICANCE: Because TCA does not require specific preparation of sample, it can be applied to all existing tissue or cDNA libraries or to published data sets, inasmuch specific operational compartments markers are available. In human, where the small size of tissue samples collected in clinical practice accounts for high structural diversity, TCA is well suited for the identification of molecular markers of diseases, and the follow up of identified markers in single patients for diagnosis/prognosis and evaluation of therapy efficiency. In laboratory

  5. Do serum biomarkers really measure breast cancer?

    Directory of Open Access Journals (Sweden)

    Yurkovetsky Zoya

    2009-05-01

    Full Text Available Abstract Background Because screening mammography for breast cancer is less effective for premenopausal women, we investigated the feasibility of a diagnostic blood test using serum proteins. Methods This study used a set of 98 serum proteins and chose diagnostically relevant subsets via various feature-selection techniques. Because of significant noise in the data set, we applied iterated Bayesian model averaging to account for model selection uncertainty and to improve generalization performance. We assessed generalization performance using leave-one-out cross-validation (LOOCV and receiver operating characteristic (ROC curve analysis. Results The classifiers were able to distinguish normal tissue from breast cancer with a classification performance of AUC = 0.82 ± 0.04 with the proteins MIF, MMP-9, and MPO. The classifiers distinguished normal tissue from benign lesions similarly at AUC = 0.80 ± 0.05. However, the serum proteins of benign and malignant lesions were indistinguishable (AUC = 0.55 ± 0.06. The classification tasks of normal vs. cancer and normal vs. benign selected the same top feature: MIF, which suggests that the biomarkers indicated inflammatory response rather than cancer. Conclusion Overall, the selected serum proteins showed moderate ability for detecting lesions. However, they are probably more indicative of secondary effects such as inflammation rather than specific for malignancy.

  6. Discovery and validation of plasma-protein biomarker panels for the detection of colorectal cancer and advanced adenoma in a Danish collection of samples from patients referred for diagnostic colonoscopy

    DEFF Research Database (Denmark)

    Blume, John E.; Wilhelmsen, Michael; Benz, Ryan W.

    2016-01-01

    Background: Well-collected and well-documented sample repositories are necessary for disease biomarker development. The availability of significant numbers of samples with the associated patient information enables biomarker validation to proceed with maximum efficacy and minimum bias. The creati...

  7. 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.

  8. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-10-18

    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.

  9. Identification of cancer protein biomarkers using proteomic techniques

    Science.gov (United States)

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

    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.

  10. Discovery of sexual dimorphisms in metabolic and genetic biomarkers.

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass

    2011-08-01

    Full Text Available Metabolomic profiling and the integration of whole-genome genetic association data has proven to be a powerful tool to comprehensively explore gene regulatory networks and to investigate the effects of genetic variation at the molecular level. Serum metabolite concentrations allow a direct readout of biological processes, and association of specific metabolomic signatures with complex diseases such as Alzheimer's disease and cardiovascular and metabolic disorders has been shown. There are well-known correlations between sex and the incidence, prevalence, age of onset, symptoms, and severity of a disease, as well as the reaction to drugs. However, most of the studies published so far did not consider the role of sexual dimorphism and did not analyse their data stratified by gender. This study investigated sex-specific differences of serum metabolite concentrations and their underlying genetic determination. For discovery and replication we used more than 3,300 independent individuals from KORA F3 and F4 with metabolite measurements of 131 metabolites, including amino acids, phosphatidylcholines, sphingomyelins, acylcarnitines, and C6-sugars. A linear regression approach revealed significant concentration differences between males and females for 102 out of 131 metabolites (p-values<3.8×10(-4; Bonferroni-corrected threshold. Sex-specific genome-wide association studies (GWAS showed genome-wide significant differences in beta-estimates for SNPs in the CPS1 locus (carbamoyl-phosphate synthase 1, significance level: p<3.8×10(-10; Bonferroni-corrected threshold for glycine. We showed that the metabolite profiles of males and females are significantly different and, furthermore, that specific genetic variants in metabolism-related genes depict sexual dimorphism. Our study provides new important insights into sex-specific differences of cell regulatory processes and underscores that studies should consider sex-specific effects in design and

  11. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

    Kracun, Stjepan Kresimir; Cló, Emiliano; Clausen, Henrik

    2010-01-01

    glycopeptides were resynthesized at the preparative scale by automated parallel peptide synthesis and printed on microarrays for validation and broader analysis with larger sets of sera. We further showed that chemical synthesis of the monosaccharide O-glycopeptide library (Tn-glycoform) could be diversified...... have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA......) for release of glycopeptides and sequence determination by ESI-Orbitrap-MS(n). As proof-of-principle, tumor -specific glycopeptide reporter epitopes were built-in into the libraries and were detected by tumor-specific monoclonal antibodies and autoantibodies from cancer patients. Sequenced and identified...

  12. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

    OpenAIRE

    Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N.; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well p...

  13. Innovative Programmable Bio-Nano-Chip Digitizes Biology Using Sensors That Learn Bridging Biomarker Discovery and Clinical Implementation

    Directory of Open Access Journals (Sweden)

    Nicolaos J. Christodoulides

    2017-05-01

    Full Text Available The lack of standard tools and methodologies and the absence of a streamlined multimarker approval process have hindered the translation rate of new biomarkers into clinical practice for a variety of diseases afflicting humankind. Advanced novel technologies with superior analytical performance and reduced reagent costs, like the programmable bio-nano-chip system featured in this article, have potential to change the delivery of healthcare. This universal platform system has the capacity to digitize biology, resulting in a sensor modality with a capacity to learn. With well-planned device design, development, and distribution plans, there is an opportunity to translate benchtop discoveries in the genomics, proteomics, metabolomics, and glycomics fields by transforming the information content of key biomarkers into actionable signatures that can empower physicians and patients for a better management of healthcare. While the process is complicated and will take some time, showcased here are three application areas for this flexible platform that combines biomarker content with minimally invasive or non-invasive sampling, such as brush biopsy for oral cancer risk assessment; serum, plasma, and small volumes of blood for the assessment of cardiac risk and wellness; and oral fluid sampling for drugs of abuse testing at the point of need.

  14. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Science.gov (United States)

    Villanova, Federica; Di Meglio, Paola; Inokuma, Margaret; Aghaeepour, Nima; Perucha, Esperanza; Mollon, Jennifer; Nomura, Laurel; Hernandez-Fuentes, Maria; Cope, Andrew; Prevost, A Toby; Heck, Susanne; Maino, Vernon; Lord, Graham; Brinkman, Ryan R; Nestle, Frank O

    2013-01-01

    Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid) flow cytometry platform (CFP) and a unique lyoplate-based flow cytometry platform (LFP) in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10) and activation markers (Foxp3 and CD25). Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  15. Integration of lyoplate based flow cytometry and computational analysis for standardized immunological biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Federica Villanova

    Full Text Available Discovery of novel immune biomarkers for monitoring of disease prognosis and response to therapy in immune-mediated inflammatory diseases is an important unmet clinical need. Here, we establish a novel framework for immunological biomarker discovery, comparing a conventional (liquid flow cytometry platform (CFP and a unique lyoplate-based flow cytometry platform (LFP in combination with advanced computational data analysis. We demonstrate that LFP had higher sensitivity compared to CFP, with increased detection of cytokines (IFN-γ and IL-10 and activation markers (Foxp3 and CD25. Fluorescent intensity of cells stained with lyophilized antibodies was increased compared to cells stained with liquid antibodies. LFP, using a plate loader, allowed medium-throughput processing of samples with comparable intra- and inter-assay variability between platforms. Automated computational analysis identified novel immunophenotypes that were not detected with manual analysis. Our results establish a new flow cytometry platform for standardized and rapid immunological biomarker discovery with wide application to immune-mediated diseases.

  16. A systematic analysis of eluted fraction of plasma post immunoaffinity depletion: implications in biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Amit Kumar Yadav

    Full Text Available Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20 cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house, we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

  17. Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS

    Science.gov (United States)

    Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco

    2017-09-01

    In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.

  18. Plasma YKL-40: a potential new cancer biomarker?

    DEFF Research Database (Denmark)

    Johansen, Julia S; Schultz, Nicolai A; Jensen, Benny V

    2009-01-01

    tissue remodeling. Plasma levels of YKL-40 are elevated in a subgroup of patients with primary or advanced cancer compared with age-matched healthy subjects, but also in patients with many different diseases characterized by inflammation. Elevated plasma YKL-40 levels are an independent prognostic...... by inflammation. Large prospective, longitudinal clinical cancer studies are needed to determine if plasma YKL-40 is a new cancer biomarker, or is mainly a biomarker of inflammation....

  19. 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

    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....... 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...... cancer progression and ultimately of improving patient survival and quality of life. The unifying concept behind our approach is the use of various experimental paradigms for the prospective analysis of clinically relevant samples obtained from the same patient, along with the systematic integration...

  20. Clinical Use of Cancer Biomarkers in Epithelial Ovarian Cancer

    DEFF Research Database (Denmark)

    Söletormos, Georg; Duffy, Michael J; Othman Abu Hassan, Suher

    2016-01-01

    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 License 4......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...

  1. 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.

  2. The Proteomics Big Challenge for Biomarkers and New Drug-Targets Discovery

    Science.gov (United States)

    Savino, Rocco; Paduano, Sergio; Preianò, Mariaimmacolata; Terracciano, Rosa

    2012-01-01

    In the modern process of drug discovery, clinical, functional and chemical proteomics can converge and integrate synergies. Functional proteomics explores and elucidates the components of pathways and their interactions which, when deregulated, lead to a disease condition. This knowledge allows the design of strategies to target multiple pathways with combinations of pathway-specific drugs, which might increase chances of success and reduce the occurrence of drug resistance. Chemical proteomics, by analyzing the drug interactome, strongly contributes to accelerate the process of new druggable targets discovery. In the research area of clinical proteomics, proteome and peptidome mass spectrometry-profiling of human bodily fluid (plasma, serum, urine and so on), as well as of tissue and of cells, represents a promising tool for novel biomarker and eventually new druggable targets discovery. In the present review we provide a survey of current strategies of functional, chemical and clinical proteomics. Major issues will be presented for proteomic technologies used for the discovery of biomarkers for early disease diagnosis and identification of new drug targets. PMID:23203042

  3. A Multiplatform Approach for the Discovery of Novel Drug-Induced Kidney Injury Biomarkers.

    Science.gov (United States)

    Chen, Liuxi; Smith, James; Mikl, Jaromir; Fryer, Ryan; Pack, Frank; Williams, Brad J; Phillips, Jonathan A; Papov, Vladimir V

    2017-10-16

    Drug-induced kidney injury (DIKI) is a common toxicity observed in pharmaceutical development. We demonstrated the use of label-free liquid chromatography-mass spectrometry (LC-MS) and multiplex liquid chromatography-single reaction monitoring (LC-SRM) as practical extensions of standard immunoassay based safety biomarker assessments for identification of new toxicity marker candidates and for improved mechanistic understanding. Two different anticancer drugs, doxorubicin (DOX) and cisplatin (cis-diamminedichloridoplatinum, CDDP), were chosen as the toxicants due to their different modes of nephrotoxicity. Analyses of urine samples from toxicant treated and untreated rats were compared to identify biochemical analytes that changed in response to toxicant exposure. A discovery (label-free LC-MS) and targeted proteomics (multiplex LC-SRM) approach was used in combination with well established immunoassay experiments for the identification of a panel of urinary protein markers related to drug induced nephrotoxicity in rats. The initial generation of an expanded set of markers was accomplished using the label-free LC-MS discovery screen and ELISA based analysis of six nephrotoxicity biomarker proteins. Diagnostic performance of the expanded analyte set was statistically compared to conventional nephrotoxicity biomarkers. False discovery rate (FDR) analysis revealed 18 and 28 proteins from the CDDP and DOX groups, respectively, exhibiting significant differences between the vehicle and treated groups. Multiplex SRM assays were constructed to more precisely quantify candidate markers selected from the discovery screen and immunoassay experiments. To evaluate the sensitivity and specificity for each of the candidate biomarkers, histopathology severity scores were used as a benchmark for renal injury followed by receiver-operating characteristic (ROC) curve analysis on selected biomarkers. Further examination of the best performing analytes revealed relevant biological

  4. Candidate biomarker discovery and selection for ‘Granny Smith' superficial scald risk management and diagnosis, poster board

    Science.gov (United States)

    Discovery of candidate biomarkers for superficial scald, a peel disorder that develops during storage of susceptible apple cultivars, is part of a larger project aimed at developing biomarker-based risk-management and diagnostic tools for multiple apple postharvest disorders (http://www.tfrec.wsu.ed...

  5. 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

    The EU multi-disciplinary personalised RNA interference to enhance the delivery of individualised chemotherapeutics and targeted therapies (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer a...

  6. [A new serum biomarker for lung cancer - transthyretin.].

    Science.gov (United States)

    Liu, Liyun; Sun, Suozhu; Liu, Jifu; Wu, Shanshan; Dai, Songwei; Wang, Xiaomin; Huang, Lingyun; Xiao, Xueyuan; He, Dacheng

    2009-04-20

    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. Serum sample 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. Three protein peaks with the molecular weight 13.78 kDa, 13.90 kDa and 14.07 kDa were found significantly decreased 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. TTRs acted as the potentially useful biomarkers for lung cancer by SELDI technique.

  7. 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.

  8. Mapping ethical and social aspects of cancer biomarkers.

    Science.gov (United States)

    Blanchard, Anne

    2016-12-25

    Cancer biomarkers represent a revolutionary advance toward personalised cancer treatment, promising therapies that are tailored to subgroups of patients sharing similar generic traits. Notwithstanding the optimism driving this development, biomarkers also present an array of social and ethical questions, as witnessed in sporadic debates across different literatures. This review article seeks to consolidate these debates in a mapping of the complex terrain of ethical and social aspects of cancer biomarker research. This mapping was undertaken from the vantage point offered by a working cancer biomarker research centre called the Centre for Cancer Biomarkers (CCBIO) in Norway, according to a dialectic move between the literature and discussions with researchers and practitioners in the laboratory. Starting in the lab, we found that, with the exception of some classical bioethical dilemmas, researchers regarded many issues relative to the ethos of the biomarker community; how the complexity and uncertainty characterising biomarker research influence their scientific norms of quality. Such challenges to the ethos of cancer research remain largely implicit, outside the scope of formal bioethical enquiry, yet form the basis for other social and ethical issues. Indeed, looking out from the lab we see how questions of complexity, uncertainty and quality contribute to debates around social and global justice; undermining policies for the prioritisation of care, framing the stratification of those patients worthy of treatment, and limiting global access to this highly sophisticated research. We go on to discuss biomarker research within the culturally-constructed 'war on cancer' and highlight an important tension between the expectations of 'magic bullets' and the complexity and uncertainty faced in the lab. We conclude by arguing, with researchers in the CCBIO, for greater reflexivity and humility in cancer biomarker research and policy. Copyright © 2016 The Author

  9. Plasma biomarker discovery in preeclampsia using a novel differential isolation technology for circulating extracellular vesicles.

    Science.gov (United States)

    Tan, Kok Hian; Tan, Soon Sim; Sze, Siu Kwan; Lee, Wai Kheong Ryan; Ng, Mor Jack; Lim, Sai Kiang

    2014-10-01

    To circumvent the complex protein milieu of plasma and discover robust predictive biomarkers for preeclampsia (PE), we investigate if phospholipid-binding ligands can reduce the milieu complexity by extracting plasma extracellular vesicles for biomarker discovery. Cholera toxin B chain (CTB) and annexin V (AV) which respectively binds GM1 ganglioside and phosphatidylserine were used to isolate extracellular vesicles from plasma of PE patients and healthy pregnant women. The proteins in the vesicles were identified using enzyme-linked immunosorbent assay, antibody array, and mass spectrometry. CTB and AV were found to bind 2 distinct groups of extracellular vesicles. Antibody array and enzyme-linked immunosorbent assay revealed that PE patients had elevated levels of CD105, interleukin-6, placental growth factor, tissue inhibitor of metallopeptidase 1, and atrial natriuretic peptide in cholera toxin B- but not AV-vesicles, and elevated levels of plasminogen activator inhibitor-1, pro-calcitonin, S100b, tumor growth factor β, vascular endothelial growth factor receptor 1, brain natriuretic peptide, and placental growth factor in both cholera toxin B- and AV-vesicles. CD9 level was elevated in cholera toxin B-vesicles but reduced in AV vesicles of PE patients. Proteome analysis revealed that in cholera toxin B-vesicles, 87 and 222 proteins were present only in PE patients and healthy pregnant women respectively while in AV-vesicles, 104 and 157 proteins were present only in PE and healthy pregnant women, respectively. This study demonstrated for the first time that CTB and AV bind unique extracellular vesicles, and their protein cargo reflects the disease state of the patient. The successful use of these 2 ligands to isolate circulating plasma extracellular vesicles for biomarker discovery in PE represents a novel technology for biomarker discovery that can be applied to other specialties. Copyright © 2014 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2017-02-01

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

  11. More Accurate Oral Cancer Screening with Fewer Salivary Biomarkers

    Directory of Open Access Journals (Sweden)

    James Michael Menke

    2017-10-01

    Full Text Available Signal detection and Bayesian inferential tools were applied to salivary biomarkers to improve screening accuracy and efficiency in detecting oral squamous cell carcinoma (OSCC. Potential cancer biomarkers are identified by significant differences in assay concentrations, receiver operating characteristic areas under the curve (AUCs, sensitivity, and specificity. However, the end goal is to report to individual patients their risk of having disease given positive or negative test results. Likelihood ratios (LRs and Bayes factors (BFs estimate evidential support and compile biomarker information to optimize screening accuracy. In total, 26 of 77 biomarkers were mentioned as having been tested at least twice in 137 studies and published in 16 summary papers through 2014. Studies represented 10 212 OSCC and 25 645 healthy patients. The measure of biomarker and panel information value was number of biomarkers needed to approximate 100% positive predictive value (PPV. As few as 5 biomarkers could achieve nearly 100% PPV for a disease prevalence of 0.2% when biomarkers were ordered from highest to lowest LR. When sequentially interpreting biomarker tests, high specificity was more important than test sensitivity in achieving rapid convergence toward a high PPV. Biomarkers ranked from highest to lowest LR were more informative and easier to interpret than AUC or Youden index. The proposed method should be applied to more recently published biomarker data to test its screening value.

  12. Development of Nanomechanical Sensors for Breast Cancer Biomarkers

    National Research Council Canada - National Science Library

    Erramilli, Shyamsunder

    2006-01-01

    ... to similar breakthroughs in array sensors for biomolecules of interest to the breast cancer community. Nanotechnology can meet the need for high throughput, sensitive methods for rapidly recording biomarker profiles of tumors in individual patients...

  13. Breast Cancer Biomarkers Based on Nipple and Fine Needle Aspirates

    National Research Council Canada - National Science Library

    Russo, Irma H

    2005-01-01

    ... of the cytological normal breast epithelium of women at high risk for breast cancer. This signature will serve as an intermediate biomarker for evaluating the response of the breast to novel chemopreventive agents...

  14. The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

    Science.gov (United States)

    Serkova, Natalie J.; Standiford, Theodore J.

    2011-01-01

    Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

  15. NMR and pattern recognition methods in metabolomics: from data acquisition to biomarker discovery: a review.

    Science.gov (United States)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M C; Wijmenga, Sybren S

    2012-10-31

    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). Copyright © 2012 Elsevier B.V. All rights reserved.

  16. tRNAs as Biomarkers and Regulators for Breast Cancer

    Science.gov (United States)

    2010-08-01

    metastasized to bones). Cell Line ER PgR HER2 Tumor Type Tissue Source Tumorigenic Tumor Classification MCF10A - - Fibrocystic Disease Mammary...TITLE: tRNAs as Biomarkers and Regulators for Breast Cancer PRINCIPAL INVESTIGATOR: Tao Pan, Ph.D...tRNAs as Biomarkers and Regulators for Breast Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-07-1-0595 5c. PROGRAM ELEMENT NUMBER

  17. Strategies for Utilizing Neuroimaging Biomarkers in CNS Drug Discovery and Development: CINP/JSNP Working Group Report.

    Science.gov (United States)

    Suhara, Tetsuya; Chaki, Shigeyuki; Kimura, Haruhide; Furusawa, Makoto; Matsumoto, Mitsuyuki; Ogura, Hiroo; Negishi, Takaaki; Saijo, Takeaki; Higuchi, Makoto; Omura, Tomohiro; Watanabe, Rira; Miyoshi, Sosuke; Nakatani, Noriaki; Yamamoto, Noboru; Liou, Shyh-Yuh; Takado, Yuhei; Maeda, Jun; Okamoto, Yasumasa; Okubo, Yoshiaki; Yamada, Makiko; Ito, Hiroshi; Walton, Noah M; Yamawaki, Shigeto

    2017-04-01

    Despite large unmet medical needs in the field for several decades, CNS drug discovery and development has been largely unsuccessful. Biomarkers, particularly those utilizing neuroimaging, have played important roles in aiding CNS drug development, including dosing determination of investigational new drugs (INDs). A recent working group was organized jointly by CINP and Japanese Society of Neuropsychopharmacology (JSNP) to discuss the utility of biomarkers as tools to overcome issues of CNS drug development.The consensus statement from the working group aimed at creating more nuanced criteria for employing biomarkers as tools to overcome issues surrounding CNS drug development. To accomplish this, a reverse engineering approach was adopted, in which criteria for the utilization of biomarkers were created in response to current challenges in the processes of drug discovery and development for CNS disorders. Based on this analysis, we propose a new paradigm containing 5 distinct tiers to further clarify the use of biomarkers and establish new strategies for decision-making in the context of CNS drug development. Specifically, we discuss more rational ways to incorporate biomarker data to determine optimal dosing for INDs with novel mechanisms and targets, and propose additional categorization criteria to further the use of biomarkers in patient stratification and clinical efficacy prediction. Finally, we propose validation and development of new neuroimaging biomarkers through public-private partnerships to further facilitate drug discovery and development for CNS disorders. © The Author 2016. Published by Oxford University Press on behalf of CINP.

  18. Correlation between preoperative serum levels of five biomarkers and relationships between these biomarkers and cancer stage in epithelial overian cancer

    National Research Council Canada - National Science Library

    Hwang, Jongyun; Na, Sunghun; Lee, Hyangah; Lee, Dongheon

    2009-01-01

    To examine the correlation among the preoperative serum levels of five biomarkers presumed to be useful for early detection of epithelial ovarian cancer and evaluate the relationships between serum...

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

    DEFF Research Database (Denmark)

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn

    2016-01-01

    Background 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. Methods...... to determine a vast array of HFrEF-related urinary peptide biomarkers which might help improving our understanding and diagnosis of heart failure.......EF103 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...

  20. Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances.

    Science.gov (United States)

    Lech, Gustaw; Słotwiński, Robert; Słodkowski, Maciej; Krasnodębski, Ireneusz Wojciech

    2016-02-07

    Colorectal cancer (CRC) is the second most commonly diagnosed cancer among females and third among males worldwide. It also contributes significantly to cancer-related deaths, despite the continuous progress in diagnostic and therapeutic methods. Biomarkers currently play an important role in the detection and treatment of patients with colorectal cancer. Risk stratification for screening might be augmented by finding new biomarkers which alone or as a complement of existing tests might recognize either the predisposition or early stage of the disease. Biomarkers have also the potential to change diagnostic and treatment algorithms by selecting the proper chemotherapeutic drugs across a broad spectrum of patients. There are attempts to personalise chemotherapy based on presence or absence of specific biomarkers. In this review, we update review published last year and describe our understanding of tumour markers and biomarkers role in CRC screening, diagnosis, treatment and follow-up. Goal of future research is to identify those biomarkers that could allow a non-invasive and cost-effective diagnosis, as well as to recognise the best prognostic panel and define the predictive biomarkers for available treatments.

  1. Lung cancer screening beyond low-dose computed tomography: the role of novel biomarkers.

    Science.gov (United States)

    Hasan, Naveed; Kumar, Rohit; Kavuru, Mani S

    2014-10-01

    Lung cancer is the most common and lethal malignancy in the world. The landmark National lung screening trial (NLST) showed a 20% relative reduction in mortality in high-risk individuals with screening low-dose computed tomography. However, the poor specificity and low prevalence of lung cancer in the NLST provide major limitations to its widespread use. Furthermore, a lung nodule on CT scan requires a nuanced and individualized approach towards management. In this regard, advances in high through-put technology (molecular diagnostics, multi-gene chips, proteomics, and bronchoscopic techniques) have led to discovery of lung cancer biomarkers that have shown potential to complement the current screening standards. Early detection of lung cancer can be achieved by analysis of biomarkers from tissue samples within the respiratory tract such as sputum, saliva, nasal/bronchial airway epithelial cells and exhaled breath condensate or through peripheral biofluids such as blood, serum and urine. Autofluorescence bronchoscopy has been employed in research setting to identify pre-invasive lesions not identified on CT scan. Although these modalities are not yet commercially available in clinic setting, they will be available in the near future and clinicians who care for patients with lung cancer should be aware. In this review, we present up-to-date state of biomarker development, discuss their clinical relevance and predict their future role in lung cancer management.

  2. 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.

  3. Clinical and pharmaceutical success from discovery to regulatory approval: biomarkers, modeling and analytical technologies.

    Science.gov (United States)

    Zhang, Tianyi Tee; Weng, Naidong; Lee, Mike

    2017-10-01

    The 8th Annual Shanghai Symposium on Clinical and Pharmaceutical Solutions through Analysis (CPSA): Clinical and Pharmaceutical Success from Discovery to Regulatory Approval: Biomarkers, Modeling and Analytical Technologies (CPSA Shanghai 2017); Renaissance Shanghai Pudong Hotel, Shanghai, China, 12-14 April 2017 was held on 12-14 April 2017 in Shanghai, China. The meeting was featured with highly interactive events including diversified symposia, workshops, roundtable discussions, conference awards and poster sessions. There were over 220 participants with 61 oral presentations and 20 posters presented. In addition, the meeting included a preconference workshop with an inaugural session on the evaluation of quality and efficacy for generic drugs in China.

  4. Update on biomarkers for the detection of lung cancer

    Directory of Open Access Journals (Sweden)

    Jantus-Lewintre E

    2012-06-01

    Full Text Available Eloisa Jantus-Lewintre,1 Marta Usó,1 Elena Sanmartín,1 Carlos Camps,1–31Molecular Oncology Laboratory, Fundación para la Investigación del Hospital General Universitario, Valencia, Spain; 2Deparment of Medical Oncology, Consorcio Hospital General Universitario, Valencia, Spain; 3Department of Medicine, Universitat de València, Valencia, SpainAbstract: Patients at risk for lung cancer may have subclinical disease for years before presentation. The diagnosis of this disease is primarily based on symptoms, and detection often occurs after curative intervention is no longer possible. At present, no lung cancer early-detection biomarker is clinically available. This study reviews the most recent advances in early detection and molecular diagnostic biomarkers for the detection of lung cancer. This review includes an overview of the various biological specimens and matrices in which these biomarkers could be analyzed, as well as the diverse strategies and approaches for identifying new biomarkers that are currently being explored. Several novel and attractive biomarker candidates for the early detection of lung cancer exist. A remarkable shift is taking place from research based on single markers to analyzing signatures that are more complex in order to take advantage of new high-throughput technologies. However, it is still necessary to validate the most promising markers and the standardization of procedures that will lead to specific clinical applications.Keywords: biomarker, detection, lung cancer, diagnosis

  5. Mathematical modeling for novel cancer drug discovery and development.

    Science.gov (United States)

    Zhang, Ping; Brusic, Vladimir

    2014-10-01

    Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

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

    Directory of Open Access Journals (Sweden)

    Heewon Park

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

  7. DWI as an Imaging Biomarker for Bladder Cancer

    NARCIS (Netherlands)

    Yoshida, Soichiro; Takahara, Taro; Kwee, Thomas C.; Waseda, Yuma; Kobayashi, Shuichiro; Fujii, Yasuhisa

    OBJECTIVE. DWI has been increasingly applied in the management of bladder cancer. In this article, we discuss the role of DWI as an imaging biomarker for bladder cancer. CONCLUSION. The DWI signal is derived from the motion of water molecules, which represents the physiologic characteristics of the

  8. 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...... as biomarkers in the identification of women at increased risk of developing breast cancer......., 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...

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

    Science.gov (United States)

    Mustafa, Gul M; Larry, Denner; Petersen, John R; 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 require novel methodological approaches. Proteomic profiling of body fluids presents a sensitive diagnostic tool for early cancer detection. Here we describe such a strategy of comparative proteomics to identify potential serum-based biomarkers to distinguish high-risk chronic hepatitis C virus infected patients from HCC patients. In order to compensate for the extraordinary dynamic range in serum proteins, enrichment methods that compress the dynamic range without surrendering proteome complexity can help minimize the problems associated with many depletion methods. The enriched serum can be resolved using 2D-difference in-gel electrophoresis and the spots showing statistically significant changes selected for identification by liquid chromatography-tandem mass spectrometry. Subsequent quantitative verification and validation of these candidate biomarkers represent an obligatory and rate-limiting process that is greatly enabled by selected reaction monitoring (SRM). SRM is a tandem mass spectrometry method suitable for identification and quantitation of target peptides within complex mixtures independent on peptide-specific antibodies. Ultimately, multiplexed SRM and dynamic multiple reaction monitoring can be utilized for the simultaneous analysis of a biomarker panel derived from support vector machine learning approaches, which allows monitoring a specific disease state such as early HCC. Overall, this approach yields high probability biomarkers for clinical validation in

  10. Defining the purity of exosomes required for diagnostic profiling of small RNA suitable for biomarker discovery.

    Science.gov (United States)

    Quek, Camelia; Bellingham, Shayne A; Jung, Chol-Hee; Scicluna, Benjamin J; Shambrook, Mitch C; Sharples, Robyn A; Cheng, Lesley; Hill, Andrew F

    2017-02-01

    Small non-coding RNAs (ncRNA), including microRNAs (miRNA), enclosed in exosomes are being utilised for biomarker discovery in disease. Two common exosome isolation methods involve differential ultracentrifugation or differential ultracentrifugation coupled with Optiprep gradient fractionation. Generally, the incorporation of an Optiprep gradient provides better separation and increased purity of exosomes. The question of whether increased purity of exosomes is required for small ncRNA profiling, particularly in diagnostic and biomarker purposes, has not been addressed and highly debated. Utilizing an established neuronal cell system, we used next-generation sequencing to comprehensively profile ncRNA in cells and exosomes isolated by these 2 isolation methods. By comparing ncRNA content in exosomes from these two methods, we found that exosomes from both isolation methods were enriched with miRNAs and contained a diverse range of rRNA, small nuclear RNA, small nucleolar RNA and piwi-interacting RNA as compared with their cellular counterparts. Additionally, tRNA fragments (30-55 nucleotides in length) were identified in exosomes and may act as potential modulators for repressing protein translation. Overall, the outcome of this study confirms that ultracentrifugation-based method as a feasible approach to identify ncRNA biomarkers in exosomes.

  11. 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.

  12. 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).

  13. Biomarker discovery and applications for foods and beverages: proteomics to nanoproteomics.

    Science.gov (United States)

    Agrawal, Ganesh Kumar; Timperio, Anna Maria; Zolla, Lello; Bansal, Vipul; Shukla, Ravi; Rakwal, Randeep

    2013-11-20

    Foods and beverages have been at the heart of our society for centuries, sustaining humankind - health, life, and the pleasures that go with it. The more we grow and develop as a civilization, the more we feel the need to know about the food we eat and beverages we drink. Moreover, with an ever increasing demand for food due to the growing human population food security remains a major concern. Food safety is another growing concern as the consumers prefer varied foods and beverages that are not only traded nationally but also globally. The 21st century science and technology is at a new high, especially in the field of biological sciences. The availability of genome sequences and associated high-throughput sensitive technologies means that foods are being analyzed at various levels. For example and in particular, high-throughput omics approaches are being applied to develop suitable biomarkers for foods and beverages and their applications in addressing quality, technology, authenticity, and safety issues. Proteomics are one of those technologies that are increasingly being utilized to profile expressed proteins in different foods and beverages. Acquired knowledge and protein information have now been translated to address safety of foods and beverages. Very recently, the power of proteomic technology has been integrated with another highly sensitive and miniaturized technology called nanotechnology, yielding a new term nanoproteomics. Nanoproteomics offer a real-time multiplexed analysis performed in a miniaturized assay, with low-sample consumption and high sensitivity. To name a few, nanomaterials - quantum dots, gold nanoparticles, carbon nanotubes, and nanowires - have demonstrated potential to overcome the challenges of sensitivity faced by proteomics for biomarker detection, discovery, and application. In this review, we will discuss the importance of biomarker discovery and applications for foods and beverages, the contribution of proteomic technology in

  14. Biomarkers in the lung cancer diagnosis: a clinical perspective.

    Science.gov (United States)

    Li, X; Asmitananda, T; Gao, L; Gai, D; Song, Z; Zhang, Y; Ren, H; Yang, T; Chen, T; Chen, M

    2012-01-01

    The propensity for tumor biomarkers to be detected in serum at an early disease stage has become an area of interest for clinicians. This study aimed to evaluate the efficiency of 7 tumor biomarkers, namely, carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin 19 (CYFRA-21-1), alpha-fetoprotein, carbohydrate antigen-125 (CA-125), carbohydrate antigen-19.9 (CA-19.9), and ferritin, independently or in combination for the diagnosis of lung cancer. Electrochemiluminescence immunization was used to determine biomarker levels expressed in 530 patients with pulmonary disease and 229 healthy subjects. The observed levels of CEA, NSE, CYFRA-21-1, CA-125, and CA-19.9 in patients with pathologically confirmed lung cancer were significantly higher than those in patients with benign pulmonary disease or control subjects. Adenocarcinoma, squamous cell carcinoma, and small cell carcinoma of the lung were associated with the highest observed levels of CA-125, CYFRA-21-1, and NSE, respectively. Combining biomarkers successfully led to the diagnosis of lung cancer. CEA + NSE + CA-125 showed the highest sensitivity for small cell carcinoma, at 83.33%, whereas CEA + NSE + CYFRA-21-1 + CA-125 showed 94.11% sensitivity for squamous cell carcinoma. The combination of 6 biomarkers, namely, CEA + NSE + CYFRA-21-1 + CA-125 + ferritin + CA-19.9, showed 80.49% sensitivity for adenocarcinoma. Combining biomarkers significantly aided in the diagnosis of lung cancer. However, this increased sensitivity on combination was accompanied by a decreased specificity for lung cancer subtypes. Combining biomarkers appropriately increases their sensitivity and helps with the diagnosis of lung cancer.

  15. 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.

  16. Serologic autoantibodies as diagnostic cancer biomarkers--a review.

    Science.gov (United States)

    Zaenker, Pauline; Ziman, Melanie R

    2013-12-01

    Current diagnostic techniques used for the early detection of cancers are successful but subject to detection bias. A recent focus lies in the development of more accurate diagnostic tools. An increase in serologic autoantibody levels has been shown to precede the development of cancer disease symptoms. Therefore, autoantibody levels in patient blood serum have been proposed as diagnostic biomarkers for early-stage diagnosis of cancers. Their clinical application has, however, been hindered by low sensitivity, specificity, and low predictive value scores. These scores have been shown to improve when panels of multiple diagnostic autoantibody biomarkers are used. A five-marker biomarker panel has been shown to increase the sensitivity of prostate cancer diagnosis to 95% as compared with 12.2% for prostate-specific antigen alone. New potential biomarker panels were also discovered for lung, colon, and stomach cancer diagnosis with sensitivity of 76%, 65.4%, and 50.8%, respectively. Studies in breast and liver cancer, however, seem to favor single markers, namely α-2-HS-glycoprotein and des-γ-carboxyprothrombin with sensitivities of 79% and 89% for the early detection of the cancers. The aim of this review is to discuss the relevance of autoantibodies in cancer diagnosis and to outline the current methodologies used in the detection of autoantibodies. The review concludes with a discussion of the autoantibodies currently used in the diagnosis of cancers of the prostate, breast, lung, colon, stomach, and liver. A discussion of the potential future use of autoantibodies as diagnostic cancer biomarkers is also included in this review. ©2013 AACR.

  17. Proteomics in the search for biomarkers of animal cancer.

    Science.gov (United States)

    Kycko, Anna; Reichert, Michal

    2014-02-01

    The prevalence of cancer in companion animals has increased in the recent decade, making this disease one of the major causes of deaths. As in human medicine, veterinary medicine faces the problem of cancer prevention as well as early diagnosis and effective therapy. Early diagnosis of cancer is crucial for the successful treatment of the disease and there is a need for biomarkers that could be used as a diagnostic tool, and to guide a targeted therapy or monitor a therapeutic response. Proteomic technologies that were introduced to human cancer research over a decade ago provide the opportunity to identify distinct protein patterns for cancer diagnosis and therapy monitoring. These also have potential to be utilised in veterinary medicine. The present paper summarises the current knowledge about proteomic studies on animal cancer biomarker research published to date.

  18. Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

    Directory of Open Access Journals (Sweden)

    Craig A Gedye

    Full Text Available Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell

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

    Science.gov (United States)

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

    2015-08-01

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

  20. Bioinformatics for cancer immunotherapy target discovery

    DEFF Research Database (Denmark)

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

    2014-01-01

    therapy target discovery in a bioinformatics analysis pipeline. We describe specialized bioinformatics tools and databases for three main bottlenecks in immunotherapy target discovery: the cataloging of potentially antigenic proteins, the identification of potential HLA binders, and the selection epitopes...... 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....

  1. Biomarkers, the molecular gaze and the transformation of cancer survivorship.

    Science.gov (United States)

    Bell, Kirsten

    2013-06-01

    Over the past two decades, molecular technologies have transformed the landscape of cancer diagnosis, treatment and disease surveillance. However, although the effects of these technologies in the areas of primary and secondary cancer prevention have been the focus of growing study, their role in tertiary prevention remains largely unexamined. Treating this topic as a problematic to be conceptually explored rather than empirically demonstrated, this article focuses on the molecularisation of tertiary prevention, especially the growing use of molecular biomarkers to monitor disease recurrence. Taking a semiotic approach, I speculate on the potential meanings of molecular biomarkers for people living with and beyond cancer and suggest the meanings of these technologies may differ in important ways for those on both sides of the risk divide: that is, those 'at risk' for cancer and those living with realised risk. Although molecular biomarkers may intensify a sense of 'measured vulnerability', by indexing cancer's presence they may also prove reassuring. Moreover, as an invisible but ostensibly 'transparent' sign, in some contexts they appear to enable cancer survivors to challenge biomedical decision making. In the light of recent oncological debates about the value of these biomarkers in tertiary prevention, I conclude by suggesting that signs can never be reduced to their 'objective' biomedical denotation in spite of professional attempts to expunge meaning and value from care.

  2. Towards Precision Medicine in the Clinic: From Biomarker Discovery to Novel Therapeutics.

    Science.gov (United States)

    Collins, Dearbhaile C; Sundar, Raghav; Lim, Joline S J; Yap, Timothy A

    2017-01-01

    Precision medicine continues to be the benchmark to which we strive in cancer research. Seeking out actionable aberrations that can be selectively targeted by drug compounds promises to optimize treatment efficacy and minimize toxicity. Utilizing these different targeted agents in combination or in sequence may further delay resistance to treatments and prolong antitumor responses. Remarkable progress in the field of immunotherapy adds another layer of complexity to the management of cancer patients. Corresponding advances in companion biomarker development, novel methods of serial tumor assessments, and innovative trial designs act synergistically to further precision medicine. Ongoing hurdles such as clonal evolution, intra- and intertumor heterogeneity, and varied mechanisms of drug resistance continue to be challenges to overcome. Large-scale data-sharing and collaborative networks using next-generation sequencing (NGS) platforms promise to take us further into the cancer 'ome' than ever before, with the goal of achieving successful precision medicine. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. 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

  4. A systematic approach to biomarker discovery; Preamble to "the iSBTc-FDA taskforce on immunotherapy biomarkers"

    Directory of Open Access Journals (Sweden)

    Schendel Dolores

    2008-12-01

    Full Text Available Abstract The International Society for the Biological Therapy of Cancer (iSBTc has initiated in collaboration with the United States Food and Drug Administration (FDA a programmatic look at innovative avenues for the identification of relevant parameters to assist clinical and basic scientists who study the natural course of host/tumor interactions or their response to immune manipulation. The task force has two primary goals: 1 identify best practices of standardized and validated immune monitoring procedures and assays to promote inter-trial comparisons and 2 develop strategies for the identification of novel biomarkers that may enhance our understating of principles governing human cancer immune biology and, consequently, implement their clinical application. Two working groups were created that will report the developed best practices at an NCI/FDA/iSBTc sponsored workshop tied to the annual meeting of the iSBTc to be held in Washington DC in the Fall of 2009. This foreword provides an overview of the task force and invites feedback from readers that might be incorporated in the discussions and in the final document.

  5. 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. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  6. Body fatness, related biomarkers and cancer risk: an epidemiological perspective.

    Science.gov (United States)

    Nimptsch, Katharina; Pischon, Tobias

    2015-05-01

    Higher body fatness is not only associated with a higher risk of hypertension, type 2 diabetes, and coronary heart disease but also with certain types of cancer. The scope of this review is to summarize the epidemiological evidence for an association between body fatness and specific types of cancer and to outline the mediating role of obesity-related biomarkers in this context. Epidemiological studies have gathered convincing evidence that greater body fatness is associated with a higher risk of colorectal cancer, postmenopausal breast cancer, endometrial cancer, esophageal adenocarcinoma, renal cell carcinoma, and pancreatic cancer. Further, evidence for an association between higher body fatness and higher risk of ovarian cancer, advanced prostate cancer, and hepatocellular carcinoma is growing. Abdominal obesity is an independent risk factor for colorectal cancer beyond general obesity, whereas an independent role is less clear for other obesity-related cancer types. Epidemiological biomarker studies have shown that the positive association between body fatness and risk of cancer may be partly explained by hyperinsulinemia and altered concentrations in adipokines and sex-steroid hormones. In addition, obesity-associated low-grade inflammation plays a role in colorectal carcinogenesis. While epidemiology has contributed substantially to the understanding of the role of higher body fatness and related metabolic alterations in the development of cancer, further epidemiological biomarker studies are necessary to elucidate the complex interrelations between mediating pathways as well as to study novel pathways. Knowledge resulting from this research may help identify an obesity phenotype that is particularly strongly associated with cancer risk and thus pave the way for targeted prevention of cancer morbidity and mortality.

  7. Systems biology meets -omic technologies: novel approaches to biomarker discovery and companion diagnostic development.

    Science.gov (United States)

    Caberlotto, Laura; Lauria, Mario

    2015-02-01

    The next generation of biomarkers and companion diagnostics will require the development of technologies capable of conjugating the advances in high-throughput techniques in biology with computational methods. Systems biology is poised to contribute through an integrated view, capturing the complexity of the system, both in terms of a collection of interacting molecular components and also in terms of multiple intersecting views. Following this system-centered view, novel approaches have been developed for the identification of signatures of both disease processes and drug modes of action with the promising perspectives of better diagnosis of disease and of the discovery of more efficacious and safe drugs. The application of systems biology to the development of companion diagnostics is very recent and to date a few pioneering steps have been made in this direction. In this review, we describe the ongoing studies and the potential developments in this area of research.

  8. Prostate Cancer Gene Discovery Using ROMA

    National Research Council Canada - National Science Library

    Isaacs, William B

    2007-01-01

    We hypothesized that a subset of men who develop prostate cancer (PCa) do so as a result of an inherited chromosomal deletion or amplification affecting the function of one or more critical prostate cancer susceptibility genes...

  9. Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

    Science.gov (United States)

    Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

    2017-10-01

    While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

  10. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

    Directory of Open Access Journals (Sweden)

    Daisuke Saigusa

    Full Text Available Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met using mass spectrometry (MS, largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

  11. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

    Science.gov (United States)

    Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

  12. [Discovery and clinical application of mutations in the cancer genome].

    Science.gov (United States)

    Mano, Hiroyuki

    2015-08-01

    Cancer genome/epigenome analyses have identified a wide array of somatic mutations that can confer cancer cell characteristics. These genomic/epigenomic alterations can be targeted for cancer treatment, and, indeed, inhibitors against oncogenic protein-tyrosine kinases have been proved clinically effective. Other types of molecularly targeted therapies, such as epigenetic modifiers, are currently under clinical testing. In addition to the discovery of such driver mutations, profiling of genome/epigenome in cancer becomes especially important in the selection of most appropriate drug in for given cancer patient.

  13. Novel Biomarker Signature That May Predict Aggressive Disease in African American Men With Prostate Cancer

    Science.gov (United States)

    Yamoah, Kosj; Johnson, Michael H.; Choeurng, Voleak; Faisal, Farzana A.; Yousefi, Kasra; Haddad, Zaid; Ross, Ashley E.; Alshalafa, Mohammed; Den, Robert; Lal, Priti; Feldman, Michael; Dicker, Adam P.; Klein, Eric A.; Davicioni, Elai; Rebbeck, Timothy R.; Schaeffer, Edward M.

    2015-01-01

    Purpose We studied the ethnicity-specific expression of prostate cancer (PC) –associated biomarkers to evaluate whether genetic/biologic factors affect ethnic disparities in PC pathogenesis and disease progression. Patients and Methods A total of 154 African American (AA) and 243 European American (EA) patients from four medical centers were matched according to the Cancer of the Prostate Risk Assessment postsurgical score within each institution. The distribution of mRNA expression levels of 20 validated biomarkers reported to be associated with PC initiation and progression was compared with ethnicity using false discovery rate, adjusted Wilcoxon-Mann-Whitney, and logistic regression models. A conditional logistic regression model was used to evaluate the interaction between ethnicity and biomarkers for predicting clinicopathologic outcomes. Results Of the 20 biomarkers examined, six showed statistically significant differential expression in AA compared with EA men in one or more statistical models. These include ERG (P < .001), AMACR (P < .001), SPINK1 (P = .001), NKX3-1 (P = .03), GOLM1 (P = .03), and androgen receptor (P = .04). Dysregulation of AMACR (P = .036), ERG (P = .036), FOXP1 (P = .041), and GSTP1 (P = .049) as well as loss-of-function mutations for tumor suppressors NKX3-1 (P = .025) and RB1 (P = .037) predicted risk of pathologic T3 disease in an ethnicity-dependent manner. Dysregulation of GOLM1 (P = .037), SRD5A2 (P = .023), and MKi67 (P = .023) predicted clinical outcomes, including 3-year biochemical recurrence and metastasis at 5 years. A greater proportion of AA men than EA men had triple-negative (ERG-negative/ETS-negative/SPINK1-negative) disease (51% v 35%; P = .002). Conclusion We have identified a subset of PC biomarkers that predict the risk of clinicopathologic outcomes in an ethnicity-dependent manner. These biomarkers may explain in part the biologic contribution to ethnic disparity in PC outcomes between EA and AA men. PMID

  14. Utility of the Blood for Gene Expression Profiling and Biomarker Discovery in Chronic Fatigue Syndrome

    Directory of Open Access Journals (Sweden)

    Suzanne D. Vernon

    2002-01-01

    Full Text Available Chronic fatigue syndrome (CFS is a debilitating illness lacking consistent anatomic lesions and eluding conventional laboratory diagnosis. Demonstration of the utility of the blood for gene expression profiling and biomarker discovery would have implications into the pathophysiology of CFS. The objective of this study was to determine if gene expression profiles of peripheral blood mononuclear cells (PMBCs could distinguish between subjects with CFS and healthy controls. Total RNA from PBMCs of five CFS cases and seventeen controls was labeled and hybridized to 1764 genes on filter arrays. Gene intensity values were analyzed by various classification algorithms and nonparametric statistical methods. The classification algorithms grouped the majority of the CFS cases together, and distinguished them from the healthy controls. Eight genes were differentially expressed in both an age-matched case-control analysis and when comparing all CFS cases to all controls. Several of the diffrentially expressed genes are associated with immunologic functions (e.g., CMRF35 antigen, IL-8, HD protein and implicate immune dysfunction in the pathophysiology of CFS. These results successfully demonstrate the utility of the blood for gene expression profiling to distinguish subjects with CFS from healthy controls and for identifying genes that could serve as CFS biomarkers.

  15. NMR-based metabolomics coupled with pattern recognition methods in biomarker discovery and disease diagnosis.

    Science.gov (United States)

    Zhang, Ai-hua; Sun, Hui; Qiu, Shi; Wang, Xi-jun

    2013-09-01

    Molecular biomarkers could detect biochemical changes associated with disease processes. The key metabolites have become an important part for improving the diagnosis, prognosis, and therapy of diseases. Because of the chemical diversity and dynamic concentration range, the analysis of metabolites remains a challenge. Assessment of fluctuations on the levels of endogenous metabolites by advanced NMR spectroscopy technique combined with multivariate statistics, the so-called metabolomics approach, has proved to be exquisitely valuable in human disease diagnosis. Because of its ability to detect a large number of metabolites in intact biological samples with isotope labeling of metabolites using nuclei such as H, C, N, and P, NMR has emerged as one of the most powerful analytical techniques in metabolomics and has dramatically improved the ability to identify low concentration metabolites and trace important metabolic pathways. Multivariate statistical methods or pattern recognition programs have been developed to handle the acquired data and to search for the discriminating features from biosample sets. Furthermore, the combination of NMR with pattern recognition methods has proven highly effective at identifying unknown metabolites that correlate with changes in genotype or phenotype. The research and clinical results achieved through NMR investigations during the first 13 years of the 21st century illustrate areas where this technology can be best translated into clinical practice. In this review, we will present several special examples of a successful application of NMR for biomarker discovery, implications for disease diagnosis, prognosis, and therapy evaluation, and discuss possible future improvements. Copyright © 2013 John Wiley & Sons, Ltd.

  16. Metabolic profiling of an Echinostoma caproni infection in the mouse for biomarker discovery.

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

    Full Text Available BACKGROUND: Metabolic profiling holds promise with regard to deepening our understanding of infection biology and disease states. The objectives of our study were to assess the global metabolic responses to an Echinostoma caproni infection in the mouse, and to compare the biomarkers extracted from different biofluids (plasma, stool, and urine in terms of characterizing acute and chronic stages of this intestinal fluke infection. METHODOLOGY/PRINCIPAL FINDINGS: Twelve female NMRI mice were infected with 30 E. caproni metacercariae each. Plasma, stool, and urine samples were collected at 7 time points up to day 33 post-infection. Samples were also obtained from non-infected control mice at the same time points and measured using (1H nuclear magnetic resonance (NMR spectroscopy. Spectral data were subjected to multivariate statistical analyses. In plasma and urine, an altered metabolic profile was already evident 1 day post-infection, characterized by reduced levels of plasma choline, acetate, formate, and lactate, coupled with increased levels of plasma glucose, and relatively lower concentrations of urinary creatine. The main changes in the urine metabolic profile started at day 8 post-infection, characterized by increased relative concentrations of trimethylamine and phenylacetylglycine and lower levels of 2-ketoisocaproate and showed differentiation over the course of the infection. CONCLUSION/SIGNIFICANCE: The current investigation is part of a broader NMR-based metabonomics profiling strategy and confirms the utility of this approach for biomarker discovery. In the case of E. caproni, a diagnosis based on all three biofluids would deliver the most comprehensive fingerprint of an infection. For practical purposes, however, future diagnosis might aim at a single biofluid, in which case urine would be chosen for further investigation, based on quantity of biomarkers, ease of sampling, and the degree of differentiation from the non

  17. 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...

  18. Cancer drug discovery: recent innovative approaches to tumor modeling.

    Science.gov (United States)

    Lovitt, Carrie J; Shelper, Todd B; Avery, Vicky M

    2016-09-01

    Cell culture models have been at the heart of anti-cancer drug discovery programs for over half a century. Advancements in cell culture techniques have seen the rapid evolution of more complex in vitro cell culture models investigated for use in drug discovery. Three-dimensional (3D) cell culture research has become a strong focal point, as this technique permits the recapitulation of the tumor microenvironment. Biologically relevant 3D cellular models have demonstrated significant promise in advancing cancer drug discovery, and will continue to play an increasing role in the future. In this review, recent advances in 3D cell culture techniques and their application in tumor modeling and anti-cancer drug discovery programs are discussed. The topics include selection of cancer cells, 3D cell culture assays (associated endpoint measurements and analysis), 3D microfluidic systems and 3D bio-printing. Although advanced cancer cell culture models and techniques are becoming commonplace in many research groups, the use of these approaches has yet to be fully embraced in anti-cancer drug applications. Furthermore, limitations associated with analyzing information-rich biological data remain unaddressed.

  19. Serendipity in Cancer Drug Discovery: Rational or Coincidence?

    Science.gov (United States)

    Prasad, Sahdeo; Gupta, Subash C; Aggarwal, Bharat B

    2016-06-01

    Novel drug development leading to final approval by the US FDA can cost as much as two billion dollars. Why the cost of novel drug discovery is so expensive is unclear, but high failure rates at the preclinical and clinical stages are major reasons. Although therapies targeting a given cell signaling pathway or a protein have become prominent in drug discovery, such treatments have done little in preventing or treating any disease alone because most chronic diseases have been found to be multigenic. A review of the discovery of numerous drugs currently being used for various diseases including cancer, diabetes, cardiovascular, pulmonary, and autoimmune diseases indicates that serendipity has played a major role in the discovery. In this review we provide evidence that rational drug discovery and targeted therapies have minimal roles in drug discovery, and that serendipity and coincidence have played and continue to play major roles. The primary focus in this review is on cancer-related drug discovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. 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

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

    LENUS (Irish Health Repository)

    Tonry, Claire L

    2016-07-18

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

  2. Exosomal non-coding RNAs: a promising cancer biomarker.

    Science.gov (United States)

    Yang, Huan; Fu, Hailong; Xu, Wenrong; Zhang, Xu

    2016-12-01

    Novel and non-invasive biomarkers are urgently needed for early detection of cancer. Exosomes are nano-sized particles released by cells and contain various bioactive molecules including proteins, DNA, mRNAs, and non-coding RNAs. Increasing evidence suggests that exosomes play critical roles in tumorigenesis, tumor growth, metastasis, and therapy resistance. Exosomes could be readily accessible in nearly all the body fluids. The altered production of exosomes and aberrant expression of exosomal contents could reflect the pathological state of the body, indicating that exosomes and exosomal contents can be utilized as novel cancer biomarkers. Herein, we review the basic properties of exosomes, the functional roles of exosomes in cancer, and the methods of detecting exosomes and exosomal contents. In particular, we highlight the clinical values of exosomal non-coding RNAs in cancer diagnosis and prognosis.

  3. Exploring alternative ovarian cancer biomarkers using innovative nanotechnology strategies.

    Science.gov (United States)

    Castro, Cesar M; Im, Hyungsoon; Le, Christine; Lee, Hakho; Weissleder, Ralph; Birrer, Michael J

    2015-03-01

    Our increased understanding of ovarian cancer's blueprints (mediated by DNA and RNA) and behavior (mediated by proteins) points to wide differences across patients that cannot be depicted by histology alone. Conventional diagnosis usually entails an adequate tissue biopsy, which limits serial testing. There is thus a motivation to shift towards easier to obtain clinical samples (e.g., ascites or blood). In response, investigators are increasingly leveraging alternative circulating biomarkers in blood or proximal fluids and harnessing novel profiling platforms to help explore treatment-related effects on such biomarkers in serial fashion. In this review, we discuss how new nanotechnologies we developed intersect with alternative ovarian cancer biomarkers for improved understanding of metastases and therapeutic response.

  4. Proteome Profiling of Diabetic Mellitus Patient Urine for Discovery of Biomarkers by Comprehensive MS-Based Proteomics

    Directory of Open Access Journals (Sweden)

    Yoshitoshi Hirao

    2018-02-01

    Full Text Available Diabetic mellitus (DM is a disease that affects glucose homeostasis and causes complications, such as diabetic nephropathy (DN. For early diagnosis of DN, microalbuminuria is currently one of the most frequently used biomarkers. However, more early diagnostic biomarkers are desired in addition to microalbuminuria. In this study, we performed comprehensive proteomics analysis of urine proteomes of diabetic mellitus patients without microalbuminuria and healthy volunteers to compare the protein profiles by mass spectrometry. With high confidence criteria, 942 proteins in healthy volunteer urine and 645 proteins in the DM patient urine were identified with label-free semi-quantitation, respectively. Gene ontology and pathway analysis were performed with the proteins, which were up- or down-regulated in the DM patient urine to elucidate significant changes in pathways. The discovery of a useful biomarker for early DN discovery is expected.

  5. Translational bioinformatics in mental health: open access data sources and computational biomarker discovery.

    Science.gov (United States)

    Tenenbaum, Jessica D; Bhuvaneshwar, Krithika; Gagliardi, Jane P; Fultz Hollis, Kate; Jia, Peilin; Ma, Liang; Nagarajan, Radhakrishnan; Rakesh, Gopalkumar; Subbian, Vignesh; Visweswaran, Shyam; Zhao, Zhongming; Rozenblit, Leon

    2017-11-27

    Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data. © The Author 2017. Published by Oxford University Press.

  6. Zebrafish xenograft models of cancer and metastasis for drug discovery.

    Science.gov (United States)

    Brown, Hannah K; Schiavone, Kristina; Tazzyman, Simon; Heymann, Dominique; Chico, Timothy Ja

    2017-04-01

    Patients with metastatic cancer suffer the highest rate of cancer-related death, but existing animal models of metastasis have disadvantages that limit our ability to understand this process. The zebrafish is increasingly used for cancer modelling, particularly xenografting of human cancer cell lines, and drug discovery, and may provide novel scientific and therapeutic insights. However, this model system remains underexploited. Areas covered: The authors discuss the advantages and disadvantages of the zebrafish xenograft model for the study of cancer, metastasis and drug discovery. They summarise previous work investigating the metastatic cascade, such as tumour-induced angiogenesis, intravasation, extravasation, dissemination and homing, invasion at secondary sites, assessing metastatic potential and evaluation of cancer stem cells in zebrafish. Expert opinion: The practical advantages of zebrafish for basic biological study and drug discovery are indisputable. However, their ability to sufficiently reproduce and predict the behaviour of human cancer and metastasis remains unproven. For this to be resolved, novel mechanisms must to be discovered in zebrafish that are subsequently validated in humans, and for therapeutic interventions that modulate cancer favourably in zebrafish to successfully translate to human clinical studies. In the meantime, more work is required to establish the most informative methods in zebrafish.

  7. Epigenetic prognostic biomarkers in colorectal cancer

    NARCIS (Netherlands)

    Benard, Anne

    2015-01-01

    Colorectal cancer is one of the most common diagnosed cancers worldwide, and is the second most important cause of cancer mortality in Europe. The current TNM staging system used at the time of diagnosis is insufficient, as patients with the same tumor stage show wide variations in survival and

  8. 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

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

    NARCIS (Netherlands)

    Reimers, Marlies Suzanne

    2015-01-01

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

  10. Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

    Directory of Open Access Journals (Sweden)

    David G Covell

    Full Text Available Developing reliable biomarkers of tumor cell drug sensitivity and resistance can guide hypothesis-driven basic science research and influence pre-therapy clinical decisions. A popular strategy for developing biomarkers uses characterizations of human tumor samples against a range of cancer drug responses that correlate with genomic change; developed largely from the efforts of the Cancer Cell Line Encyclopedia (CCLE and Sanger Cancer Genome Project (CGP. The purpose of this study is to provide an independent analysis of this data that aims to vet existing and add novel perspectives to biomarker discoveries and applications. Existing and alternative data mining and statistical methods will be used to a evaluate drug responses of compounds with similar mechanism of action (MOA, b examine measures of gene expression (GE, copy number (CN and mutation status (MUT biomarkers, combined with gene set enrichment analysis (GSEA, for hypothesizing biological processes important for drug response, c conduct global comparisons of GE, CN and MUT as biomarkers across all drugs screened in the CGP dataset, and d assess the positive predictive power of CGP-derived GE biomarkers as predictors of drug response in CCLE tumor cells. The perspectives derived from individual and global examinations of GEs, MUTs and CNs confirm existing and reveal unique and shared roles for these biomarkers in tumor cell drug sensitivity and resistance. Applications of CGP-derived genomic biomarkers to predict the drug response of CCLE tumor cells finds a highly significant ROC, with a positive predictive power of 0.78. The results of this study expand the available data mining and analysis methods for genomic biomarker development and provide additional support for using biomarkers to guide hypothesis-driven basic science research and pre-therapy clinical decisions.

  11. Data Mining Approaches for Genomic Biomarker Development: Applications Using Drug Screening Data from the Cancer Genome Project and the Cancer Cell Line Encyclopedia.

    Science.gov (United States)

    Covell, David G

    2015-01-01

    Developing reliable biomarkers of tumor cell drug sensitivity and resistance can guide hypothesis-driven basic science research and influence pre-therapy clinical decisions. A popular strategy for developing biomarkers uses characterizations of human tumor samples against a range of cancer drug responses that correlate with genomic change; developed largely from the efforts of the Cancer Cell Line Encyclopedia (CCLE) and Sanger Cancer Genome Project (CGP). The purpose of this study is to provide an independent analysis of this data that aims to vet existing and add novel perspectives to biomarker discoveries and applications. Existing and alternative data mining and statistical methods will be used to a) evaluate drug responses of compounds with similar mechanism of action (MOA), b) examine measures of gene expression (GE), copy number (CN) and mutation status (MUT) biomarkers, combined with gene set enrichment analysis (GSEA), for hypothesizing biological processes important for drug response, c) conduct global comparisons of GE, CN and MUT as biomarkers across all drugs screened in the CGP dataset, and d) assess the positive predictive power of CGP-derived GE biomarkers as predictors of drug response in CCLE tumor cells. The perspectives derived from individual and global examinations of GEs, MUTs and CNs confirm existing and reveal unique and shared roles for these biomarkers in tumor cell drug sensitivity and resistance. Applications of CGP-derived genomic biomarkers to predict the drug response of CCLE tumor cells finds a highly significant ROC, with a positive predictive power of 0.78. The results of this study expand the available data mining and analysis methods for genomic biomarker development and provide additional support for using biomarkers to guide hypothesis-driven basic science research and pre-therapy clinical decisions.

  12. Endometrial cancer and obesity: epidemiology, biomarkers, prevention and survivorship.

    Science.gov (United States)

    Fader, Amanda Nickles; Arriba, Lucybeth Nieves; Frasure, Heidi E; von Gruenigen, Vivian E

    2009-07-01

    Endometrial cancer is the most common gynecologic malignancy in the Western world and is strongly associated with obesity. Despite the fact that most cases are diagnosed in early, more favorable stages, endometrial cancer incidence and mortality rates are on the rise. Morbidly obese women with endometrial cancer are more likely to die of their co-morbidities and also of their cancers when compared to their leaner cohorts. Given the increasing rates of morbid obesity in the United States, it is essential to develop appropriate screening tools and guidelines to reduce cancer morbidity and death amongst this group. Through an analysis of the existing literature, we present a review of the epidemiologic trends in obesity and endometrial cancer, discuss the promising role of screening biomarker studies, review prevention efforts and modifiable risk factors, and ways in which health outcomes and quality of life for endometrial cancer survivors may be optimized.

  13. Current mathematical models for cancer drug discovery.

    Science.gov (United States)

    Carrara, Letizia; Lavezzi, Silvia Maria; Borella, Elisa; De Nicolao, Giuseppe; Magni, Paolo; Poggesi, Italo

    2017-08-01

    Pharmacometric models represent the most comprehensive approaches for extracting, summarizing and integrating information obtained in the often sparse, limited, and less-than-optimally designed experiments performed in the early phases of oncology drug discovery. Whilst empirical methodologies may be enough for screening and ranking candidate drugs, modeling approaches are needed for optimizing and making economically viable the learn-confirm cycles within an oncology research program and anticipating the dose regimens to be investigated in the subsequent clinical development. Areas covered: Papers appearing in the literature of approximately the last decade reporting modeling approaches applicable to anticancer drug discovery have been listed and commented. Papers were selected based on the interest in the proposed methodology or in its application. Expert opinion: The number of modeling approaches used in the discovery of anticancer drugs is consistently increasing and new models are developed based on the current directions of research of new candidate drugs. These approaches have contributed to a better understanding of new oncological targets and have allowed for the exploitation of the relatively sparse information generated by preclinical experiments. In addition, they are used in translational approaches for guiding and supporting the choice of dosing regimens in early clinical development.

  14. Towards discovery-driven translational research in breast cancer

    DEFF Research Database (Denmark)

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

    2005-01-01

    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......, 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...... biology approach to fight breast cancer....

  15. Functional Proteomics-Based Ovarian Cancer Biomarkers

    Science.gov (United States)

    2010-11-01

    34 Oncogene 23.34 (2004): 5853-5857. 6  Alvi, A. J., et al. " Microsatellite instability and mutational analysis of transforming growth factor β...Olexander, et al. "Expression of Smad proteins in human colorectal cancer ." International journal of cancer 82.2 (1999): 197-202. 79  Krockenberger...polymorphism of the XRCC1 gene predicts for response to platinum based treatment in advanced colorectal cancer ." Anticancer research 21.4B (2001): 3075

  16. Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

    Directory of Open Access Journals (Sweden)

    Cui Ziyou

    2009-03-01

    Full Text Available Abstract Background Acute lymphoblastic leukemia (ALL is a common form of cancer in children. Currently, bone marrow biopsy is used for diagnosis. Noninvasive biomarkers for the early diagnosis of pediatric ALL are urgently needed. The aim of this study was to discover potential protein biomarkers for pediatric ALL. Methods Ninety-four pediatric ALL patients and 84 controls were randomly divided into a "training" set (45 ALL patients, 34 healthy controls and a test set (49 ALL patients, 30 healthy controls and 30 pediatric acute myeloid leukemia (AML patients. Serum proteomic profiles were measured using surface-enhanced laser desorption/ionization-time-of-flight mass spectroscopy (SELDI-TOF-MS. A classification model was established by Biomarker Pattern Software (BPS. Candidate protein biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays. Results A total of 7 protein peaks (9290 m/z, 7769 m/z, 15110 m/z, 7564 m/z, 4469 m/z, 8937 m/z, 8137 m/z were found with differential expression levels in the sera of pediatric ALL patients and controls using SELDI-TOF-MS and then analyzed by BPS to construct a classification model in the "training" set. The sensitivity and specificity of the model were found to be 91.8%, and 90.0%, respectively, in the test set. Two candidate protein peaks (7769 and 9290 m/z were found to be down-regulated in ALL patients, where these were identified as platelet factor 4 (PF4 and pro-platelet basic protein precursor (PBP. Two other candidate protein peaks (8137 and 8937 m/z were found up-regulated in the sera of ALL patients, and these were identified as fragments of the complement component 3a (C3a. Conclusion Platelet factor (PF4, connective tissue activating peptide III (CTAP-III and two fragments of C3a may be potential protein biomarkers of pediatric ALL and used to distinguish pediatric ALL patients from healthy controls and pediatric AML patients. Further studies with

  17. Cancer biology and genomics: translating discoveries, transforming pathology.

    Science.gov (United States)

    Ladanyi, Marc; Hogendoorn, Pancras C W

    2011-01-01

    Advances in our understanding of cancer biology and discoveries emerging from cancer genomics are being translated into real clinical benefits for patients with cancer. The 2011 Journal of Pathology Annual Review Issue provides a snapshot of recent rapid progress on multiple fronts in the war on cancer or, more precisely, the wars on cancers. Indeed, perhaps the most notable recent shift is reflected by the sharp increase in understanding the biology of multiple specific cancers and using these new insights to inform rationally targeted therapies, with often striking successes. These recent developments, as reviewed in this issue, show how the long-term investments in basic cancer research are finally beginning to bear fruit. Copyright © 2010 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

  18. Biomarkers of ambient air pollution and lung cancer

    DEFF Research Database (Denmark)

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

    2012-01-01

    and progression from external exposure to tumour formation and some have also been suggested as risk predictors of future cancer, reinforcing causal reasoning. However, methodological issues such as confounding, publication bias and use of surrogate tissues instead of target tissues in studies on these markers......The association between ambient air pollution exposure and lung cancer risk has been investigated in prospective studies and the results are generally consistent, indicating that long-term exposure to air pollution may cause lung cancer. Despite the prospective nature and consistent findings...... of 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...

  19. Non-invasive actionable biomarkers for metastatic prostate cancer

    Directory of Open Access Journals (Sweden)

    Jun Luo

    2016-10-01

    Full Text Available In the current clinical setting, many disease management options are available for men diagnosed with prostate cancer. For metastatic prostate cancer, first-line therapies almost always involve agents designed to inhibit androgen receptor (AR signaling. Castration-resistant prostate cancers (CRPCs that arise following first-line androgen deprivation therapies (ADT may continue to respond to additional lines of AR-targeting therapies (abiraterone and enzalutamide, chemotherapies (docetaxel and cabazitaxel, bone-targeting Radium-223 therapy, and immunotherapy sipuleucel-T. The rapidly expanding therapies for CRPC is expected to transform this lethal disease into one that can be managed for prolonged period of time. In the past 3 years, a number of promising biomarkers that may help to guide treatment decisions have been proposed and evaluated, including androgen receptor splice variant-7 (AR-V7, a truncated AR lacking the ligand-binding domain (LBD and mediate constitutively-active AR signaling. Putative treatment selection markers such as AR-V7 may further improve survival benefit of existing therapies and help to accelerate development of new agents for metastatic prostate cancer. In the metastatic setting, it is important to consider compatibility between the putative biomarker with non-invasive sampling. In this review, biomarkers relevant to the setting of metastatic prostate cancer are discussed with respect to a number of key attributes critical for clinical development of non-invasive, actionable markers. It is envisioned that biomarkers for metastatic prostate cancer will continue to be discovered, developed, and refined to meet the unmet needs in both standard-of-care and clinical trial settings.

  20. Aberrantly methylated DNA as a biomarker in breast cancer

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...... 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...... 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...

  1. DNA methylation-based biomarkers in bladder cancer.

    Science.gov (United States)

    Kandimalla, Raju; van Tilborg, Angela A; Zwarthoff, Ellen C

    2013-06-01

    Urinary bladder cancer is the fifth most common cancer in the Western world. Increasing evidence has shown that DNA methylation in bladder cancer is expansive and is implicated in pathogenesis. Furthermore, distinct methylation patterns have been identified between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), as well as between FGFR3-mutant and wild-type tumours. Given these distinctions in expression, methylated genes have been proposed as diagnostic and prognostic biomarkers for patients with bladder cancer. Indeed, several studies have revealed that methylated genes--including CDH1, FHIT, LAMC2, RASSF1A, TIMP3, SFRP1, SOX9, PMF1 and RUNX3--are associated with poor survival in patients with MIBC. Further validation of these markers for prognostication as well as surveillance (of patients with NMIBC) is required. Validated markers for progression, diagnosis, survival and BCG response will contribute to clinical decision-making and individualized treatment.

  2. 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.

  3. Chromosomal aberrations and SCEs as biomarkers of cancer risk

    DEFF Research Database (Denmark)

    Norppa, H; Bonassi, S; Hansteen, I-L

    2006-01-01

    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...

  4. 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.

  5. In vitro derby imaging of cancer biomarkers using quantum dots.

    Science.gov (United States)

    Ko, Mee Hyang; Kim, Soonhag; Kang, Won Jun; Lee, Jung Hwan; Kang, Hyungu; Moon, Sung Hwan; Hwang, Do Won; Ko, Hae Young; Lee, Dong Soo

    2009-05-01

    Semiconductor quantum dots (QDs), which have broad absorption with narrow emission spectra, are useful for multiplex imaging. Here, fluorescence derby imaging using dual color QDs conjugated by the AS1411 aptamer (targeting nucleolin) and the arginine-glycine-aspartic acid (targeting the integrin alpha(v)beta(3)) in cancer cells is reported. Simultaneous fluorescence imaging of cellular distribution of nucleolin and integrin alpha(v)beta(3) using QDs enables easy monitoring of separate targets in the cancer cells and the normal healthy cells. These results suggest the feasibility of a concurrent visualization of QD-based multiple cancer biomarkers using small molecules such as aptamer or peptide ligands.

  6. 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

  7. Multi-parametric profiling of renal cell, colorectal, and ovarian cancer identifies tumour-type-specific stroma phenotypes and a novel vascular biomarker

    NARCIS (Netherlands)

    Corvigno, Sara; Frödin, Magnus; Wisman, G Bea A; Nijman, Hans W; Van der Zee, Ate Gj; Jirström, Karin; Nodin, Björn; Hrynchyk, Ina; Edler, David; Ragnhammar, Peter; Johansson, Martin; Dahlstrand, Hanna; Mezheyeuski, Artur; Östman, Arne

    A novel set of integrated procedures for quantification of fibroblast-rich stroma and vascular characteristics has recently been presented allowing discovery of novel perivascular and stromal biomarkers in colorectal, renal cell, and ovarian cancer. In the present study, data obtained through these

  8. 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

  9. Comprehensive Analysis of Cancer-Proteogenome to Identify Biomarkers for the Early Diagnosis and Prognosis of Cancer

    Directory of Open Access Journals (Sweden)

    Hem D. Shukla

    2017-10-01

    Full Text Available During the past century, our understanding of cancer diagnosis and treatment has been based on a monogenic approach, and as a consequence our knowledge of the clinical genetic underpinnings of cancer is incomplete. Since the completion of the human genome in 2003, it has steered us into therapeutic target discovery, enabling us to mine the genome using cutting edge proteogenomics tools. A number of novel and promising cancer targets have emerged from the genome project for diagnostics, therapeutics, and prognostic markers, which are being used to monitor response to cancer treatment. The heterogeneous nature of cancer has hindered progress in understanding the underlying mechanisms that lead to abnormal cellular growth. Since, the start of The Cancer Genome Atlas (TCGA, and the International Genome consortium projects, there has been tremendous progress in genome sequencing and immense numbers of cancer genomes have been completed, and this approach has transformed our understanding of the diagnosis and treatment of different types of cancers. By employing Genomics and proteomics technologies, an immense amount of genomic data is being generated on clinical tumors, which has transformed the cancer landscape and has the potential to transform cancer diagnosis and prognosis. A complete molecular view of the cancer landscape is necessary for understanding the underlying mechanisms of cancer initiation to improve diagnosis and prognosis, which ultimately will lead to personalized treatment. Interestingly, cancer proteome analysis has also allowed us to identify biomarkers to monitor drug and radiation resistance in patients undergoing cancer treatment. Further, TCGA-funded studies have allowed for the genomic and transcriptomic characterization of targeted cancers, this analysis aiding the development of targeted therapies for highly lethal malignancy. High-throughput technologies, such as complete proteome, epigenome, protein–protein interaction

  10. New Paradigms in Translational Science Research in Cancer Biomarkers

    Science.gov (United States)

    Wagner, Paul D.; Srivastava, Sudhir

    2012-01-01

    Despite significant investments in basic science by the US National Institutes of Health, there is a concern that the return on this investment has been limited in terms of clinical utility. In the field of biomarkers, translational research is used to bridge the gap between the results of basic research that identify biomolecules involved in or the consequence of carcinogenesis and their incorporation into medical application. The cultural separation between different scientific disciplines often makes it difficult to establish the multidisciplinary and multi-skilled teams that are necessary for successful translational research. The field of biomarker research requires extensive interactions between academic researchers and industrial developers, and clinicians are needed to help shape the research direction that can only be addressed by multi-disciplinary, multi-institutional approach. In this article, we provide our perspective on the relatively slow pace of cancer biomarker translation, especially those for early detection and screening. PMID:22424436

  11. 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.

  12. Seminal plasma as a source of prostate cancer peptide biomarker candidates for detection of indolent and advanced disease.

    Directory of Open Access Journals (Sweden)

    Jochen Neuhaus

    Full Text Available BACKGROUND: Extensive prostate specific antigen screening for prostate cancer generates a high number of unnecessary biopsies and over-treatment due to insufficient differentiation between indolent and aggressive tumours. We hypothesized that seminal plasma is a robust source of novel prostate cancer (PCa biomarkers with the potential to improve primary diagnosis of and to distinguish advanced from indolent disease. METHODOLOGY/PRINCIPAL FINDINGS: In an open-label case/control study 125 patients (70 PCa, 21 benign prostate hyperplasia, 25 chronic prostatitis, 9 healthy controls were enrolled in 3 centres. Biomarker panels a for PCa diagnosis (comparison of PCa patients versus benign controls and b for advanced disease (comparison of patients with post surgery Gleason score 7 were sought. Independent cohorts were used for proteomic biomarker discovery and testing the performance of the identified biomarker profiles. Seminal plasma was profiled using capillary electrophoresis mass spectrometry. Pre-analytical stability and analytical precision of the proteome analysis were determined. Support vector machine learning was used for classification. Stepwise application of two biomarker signatures with 21 and 5 biomarkers provided 83% sensitivity and 67% specificity for PCa detection in a test set of samples. A panel of 11 biomarkers for advanced disease discriminated between patients with Gleason score 7 and organ-confined (biomarkers were identified as fragments of N-acetyllactosaminide beta-1,3-N-acetylglucosaminyltransferase, prostatic acid phosphatase, stabilin-2, GTPase IMAP family member 6, semenogelin-1 and -2. Restricted sample size was the major limitation of the study. CONCLUSIONS/SIGNIFICANCE: Seminal plasma represents a robust source of potential peptide makers

  13. Obesity Biomarkers, Metabolism and Risk of Cancer: An Epidemiological Perspective.

    Science.gov (United States)

    Nimptsch, Katharina; Pischon, Tobias

    Obesity is associated with metabolic alterations that may pose a biological link between body fatness and risk of cancer. Elucidating the role of obesity-related biomarkers in cancer development is essential for developing targeted strategies aiming at obesity-associated cancer prevention. Molecular epidemiological studies of the past decades have provided evidence that major hormonal pathways linking obesity and cancer risk include the insulin and insulin-like growth factor-1 (IGF-1) axis, sex-steroid hormones, adipokines and chronic low-grade inflammation. These pathways are interrelated with each other, and their importance varies by obesity-related cancer type. The insulin/IGF-1 axis has been implicated to play an important mediating role in the association between obesity and risk of pancreatic, colorectal and prostate cancer. Endogenous sex-steroid hormone concentrations, in particular obesity-associated pre-diagnostic elevations of estrogens and androgens, play an important role in postmenopausal breast cancer and endometrial cancer development. The adipokines adiponectin and leptin and adipocyte-mediated chronic low-grade inflammation represented by the acute-phase C-reactive protein may explain a substantial part of the association between obesity and risk of colorectal cancer. There is less evidence on whether these hormonal pathways play a mediating role in other obesity-associated types of cancer. In this chapter, the molecular epidemiologic evidence from prospective studies relating circulating obesity-related biomarkers to cancer risk is summarized, taking into account available evidence from Mendelian Randomization investigations aiming at improving causal inference.

  14. 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

  15. Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

    Science.gov (United States)

    Tut, Thein Ga

    Colorectal cancer (CRC) is the third most common cancer in the world. Australia, New Zealand, Canada, the United States, and parts of Europe have the highest incidence rates of CRC. China, India, South America and parts of Africa have the lowest risk of CRC. CRC is the second most common cancer in both sexes in Australia. Even though the death rates from CRC involving the colon have diminished, those arising from the rectum have revealed no improvement. The greatest obstacle in attaining a complete surgical resection of large rectal cancers is the close anatomical relation to surrounding structures, as opposed to the free serosal surfaces enfolding the colon. To assist complete resection, pre-operative radiotherapy (DXT) can be applied, but the efficacy of ionising radiation (IR) is extremely variable between individual tumours. Reliable predictive marker/s that enable patient stratification in the application of this otherwise toxic therapy is still not available. Current therapeutic management of rectal cancer can be improved with the availability of better predictive and prognostic biomarkers. Proteins such as Plk1, gammaH2AX and MMR proteins (MSH2, MSH6, MLH1 and PMS2), involved in DNA damage response (DDR) pathway may be possible biomarkers for radiation response prediction and prognostication of rectal cancer. Serine/threonine protein kinase Plk1 is overexpressed in most of cancers including CRC. Plk1 functional activity is essential in the restoration of DNA damage following IR, which causes DNA double strand break (DSB). The earliest manifestation of this reparative process is histone H2AX phosphorylation at serine 139, leading to gammaH2AX. Colorectal normal mucosa showed the lowest level of gammaH2AX with gradually increasing levels in early adenoma and then in advanced malignant colorectal tissues, leading to the possibility that gammaH2AX may be a prospective biomarker in rectal cancer management. There are numerous publications regarding DNA mismatch

  16. Biomarker discovery for early detection of hepatocellular carcinoma in hepatitis C-infected patients.

    Science.gov (United States)

    Mustafa, Mehnaz G; Petersen, John R; Ju, Hyunsu; Cicalese, Luca; Snyder, Ned; Haidacher, Sigmund J; Denner, Larry; Elferink, Cornelis

    2013-12-01

    Chronic hepatic disease damages the liver, and the resulting wound-healing process leads to liver fibrosis and the subsequent development of cirrhosis. The leading cause of hepatic fibrosis and cirrhosis is infection with hepatitis C virus (HCV), and of the patients with HCV-induced cirrhosis, 2% to 5% develop hepatocellular carcinoma (HCC), with a survival rate of 7%. HCC is one of the leading causes of cancer-related death worldwide, and the poor survival rate is largely due to late-stage diagnosis, which makes successful intervention difficult, if not impossible. The lack of sensitive and specific diagnostic tools and the urgent need for early-stage diagnosis prompted us to discover new candidate biomarkers for HCV and HCC. We used aptamer-based fractionation technology to reduce serum complexity, differentially labeled samples (six HCV and six HCC) with fluorescent dyes, and resolved proteins in pairwise two-dimensional difference gel electrophoresis. DeCyder software was used to identify differentially expressed proteins and spots picked, and MALDI-MS/MS was used to determine that ApoA1 was down-regulated by 22% (p Differential expression quantified via two-dimensional difference gel electrophoresis was confirmed by means of (18)O/(16)O stable isotope differential labeling with LC-MS/MS zoom scans. Technically independent confirmation was demonstrated by triple quadrupole LC-MS/MS selected reaction monitoring (SRM) assays with three peptides specific to human ApoA1 (DLATVYVDVLK, WQEEMELYR, and VSFLSALEEYTK) using (18)O/(16)O-labeled samples and further verified with AQUA peptides as internal standards for quantification. In 50 patient samples (24 HCV and 26 HCC), all three SRM assays yielded highly similar differential expression of ApoA1 in HCC and HCV patients. These results validated the SRM assays, which were independently confirmed by Western blotting. Thus, ApoA1 is a candidate member of an SRM biomarker panel for early diagnosis, prognosis, and

  17. 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

  18. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer

    Directory of Open Access Journals (Sweden)

    Raquel Conde-Muíño

    2015-01-01

    Full Text Available There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40–60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile’s ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice.

  19. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer.

    Science.gov (United States)

    Conde-Muíño, Raquel; Cuadros, Marta; Zambudio, Natalia; Segura-Jiménez, Inmaculada; Cano, Carlos; Palma, Pablo

    2015-01-01

    There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40-60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice.

  20. A Proteomic Analysis of Eccrine Sweat: Implications for the Discovery of Schizophrenia Biomarker Proteins

    Science.gov (United States)

    Raiszadeh, Michelle M.; Ross, Mark M.; Russo, Paul S.; Schaepper, Mary Ann H.; Zhou, Weidong; Deng, Jianghong; Ng, Daniel; Dickson, April; Dickson, Cindy; Strom, Monica; Osorio, Carolina; Soeprono, Thomas; Wulfkuhle, Julia D.; Kabbani, Nadine; Petricoin, Emanuel F.; Liotta, Lance A.; Kirsch, Wolff M.

    2012-01-01

    Liquid chromatography tandem mass spectrometry (LC-MS/MS) and multiple reaction monitoring mass spectrometry (MRM-MS) proteomics analyses were performed on eccrine sweat of healthy controls, and the results were compared with those from individuals diagnosed with schizophrenia (SZ). This is the first large scale study of the sweat proteome. First, we performed LC-MS/MS on pooled SZ samples and pooled control samples for global proteomics analysis. Results revealed a high abundance of diverse proteins and peptides in eccrine sweat. Most of the proteins identified from sweat samples were found to be different than the most abundant proteins from serum, which indicates that eccrine sweat is not simply a plasma transudate, and may thereby be a source of unique disease-associated biomolecules. A second independent set of patient and control sweat samples were analyzed by LC-MS/MS and spectral counting to determine qualitative protein differential abundances between the control and disease groups. Differential abundances of selected proteins, initially determined by spectral counting, were verified by MRM-MS analyses. Seventeen proteins showed a differential abundance of approximately two-fold or greater between the SZ pooled sample and the control pooled sample. This study demonstrates the utility of LC-MS/MS and MRM-MS as a viable strategy for the discovery and verification of potential sweat protein disease biomarkers. PMID:22256890

  1. Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

    Science.gov (United States)

    Keshishian, Hasmik; Burgess, Michael W; Specht, Harrison; Wallace, Luke; Clauser, Karl R; Gillette, Michael A; Carr, Steven A

    2017-08-01

    Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of 4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

  2. Validation of Biomarkers for Prostate Cancer Prognosis

    Science.gov (United States)

    2017-06-01

    Ly M, Mann BF, Marx K, Mechref Y, Meyer B, Moginger U, Neusubeta C, Nilsson J, Novotny MV, Nyalwidhe JO, Packer NH, Pompach P, Reiz B, Resemann A...Immunohistochemistry Assay Is Associated with Worse Recurrence-free Survival in Prostate Cancer Tamara L. Lotana,b,*, Wei Weic, Carlos L. Moraisa, Sarah T...Immunohistochemistry Assay in Prostate Cancer by Comparison to PTEN FISH Tamara L. Lotan1,2, Wei Wei3, Olga Ludkovski4, Carlos L. Morais1, Liana B. Guedes1, Tamara

  3. Optimizing Molecular-Targeted Therapies in Ovarian Cancer: The Renewed Surge of Interest in Ovarian Cancer Biomarkers and Cell Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Donavon Hiss

    2012-01-01

    Full Text Available The hallmarks of ovarian cancer encompass the development of resistance, disease recurrence and poor prognosis. Ovarian cancer cells express gene signatures which pose significant challenges for cancer drug development, therapeutics, prevention and management. Despite enhancements in contemporary tumor debulking surgery, tentative combination regimens and abdominal radiation which can achieve beneficial response rates, the majority of ovarian cancer patients not only experience adverse effects, but also eventually relapse. Therefore, additional therapeutic possibilities need to be explored to minimize adverse events and prolong progression-free and overall response rates in ovarian cancer patients. Currently, a revival in cancer drug discovery is devoted to identifying diagnostic and prognostic ovarian cancer biomarkers. However, the sensitivity and reliability of such biomarkers may be complicated by mutations in the BRCA1 or BRCA2 genes, diverse genetic risk factors, unidentified initiation and progression elements, molecular tumor heterogeneity and disease staging. There is thus a dire need to expand existing ovarian cancer therapies with broad-spectrum and individualized molecular targeted approaches. The aim of this review is to profile recent developments in our understanding of the interrelationships among selected ovarian tumor biomarkers, heterogeneous expression signatures and related molecular signal transduction pathways, and their translation into more efficacious targeted treatment rationales.

  4. Chromosome 1q21.3 amplification is a trackable biomarker and actionable target for breast cancer recurrence

    DEFF Research Database (Denmark)

    Goh, Jian Yuan; Feng, Min; Wang, Wenyu

    2017-01-01

    Tumor recurrence remains the main reason for breast cancer-associated mortality, and there are unmet clinical demands for the discovery of new biomarkers and development of treatment solutions to benefit patients with breast cancer at high risk of recurrence. Here we report the identification...... of chromosomal copy-number amplification at 1q21.3 that is enriched in subpopulations of breast cancer cells bearing characteristics of tumor-initiating cells (TICs) and that strongly associates with breast cancer recurrence. Amplification is present in ∼10-30% of primary tumors but in more than 70% of recurrent...... tumors, regardless of breast cancer subtype. Detection of amplification in cell-free DNA (cfDNA) from blood is strongly associated with early relapse in patients with breast cancer and could also be used to track the emergence of tumor resistance to chemotherapy. We further show that 1q21.3-encoded S100...

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

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    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.

  6. Assessing blood platelets as RNA biomarker source for prostate cancer.

    Science.gov (United States)

    Hänze, Jörg; Jakubowski, Peter; Heers, Hendrik; Hegele, Axel; Timmesfeld, Nina; Hofmann, Rainer; Olbert, Peter J

    2016-11-01

    Blood platelets may offer as RNA biomarker source for cancer as recently described for an oncogenic transcript in glioma patients and for PCA3 in prostate cancer (PCa) patients. Here, we elaborated on this aspect for PCa. PCA3 and other PCa-associated RNA markers were measured in platelets of PCa patients (cases) and healthy subjects (controls) in comparison to PCa cell lines by relative quantitative RT-PCR. The RNA markers displayed heterogeneous expression patterns in cell lines and platelets, however, without significant differences between cases and controls. The data do not support platelets as a profitable RNA source for early detection of PCa. Nonetheless, certain PCa-derived RNA markers in platelets may merit further investigation as potential prognostic biomarkers for PCa.

  7. The Use of Biomarkers for Bladder Cancer Diagnosis and Surveillance.

    Science.gov (United States)

    Grubmüller, Bernhard; Roupret, Morgan; Briganti, Alberto; Shariat, Shahrokh F

    2016-01-01

    Bladder cancer - a propensity that is associated with high recurrence and mortality rates. Various molecular alterations are reflected by diverse cellular morphological manifestations and vast tumor heterogeneity. Many biomarkers have been described that have undergone clinical trials and are approved for clinical use, but most still remain investigational. The question how molecular markers can support surveillance of different patient groups is still a matter of controversy. However, it can be expected that major advancement in the understanding of molecular pathways involved in urothelial carcinogenesis will enable improved patient management. The scope of this review is to discuss the established diagnostic tests and urinary biomarkers and their application for screening and surveillance of bladder cancer.

  8. Highly sulfated chondroitin sulfates, a novel class of prognostic biomarkers in ovarian cancer tissue.

    NARCIS (Netherlands)

    Vallen, M.J.E.; Massuger, L.F.A.G.; Dam, G.B. ten; Bulten, J.; Kuppevelt, T. van

    2012-01-01

    OBJECTIVE: Clinical decision making in ovarian cancer needs new (prognostic) biomarkers. Although the search for biomarkers has traditionally focused on tumor cells, their surrounding contains important information as well. Glycosaminoglycans, heterogeneous polysaccharides which are abundantly

  9. Methylated genes as new cancer biomarkers.

    NARCIS (Netherlands)

    Duffy, M.J.; Napieralski, R.; Martens, J.W.; Span, P.N.; Spyratos, F.; Sweep, C.G.J.; Brunner, N.; Foekens, J.A.; Schmitt, M.

    2009-01-01

    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

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

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    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. 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

  12. The exon-level biomarker SLC39A14 has organ-confined cancer-specificity in colorectal cancer.

    Science.gov (United States)

    Sveen, Anita; Bakken, Anne Cathrine; Ågesen, Trude H; Lind, Guro E; Nesbakken, Arild; Nordgård, Oddmund; Brackmann, Stephan; Rognum, Torleiv O; Lothe, Ragnhild A; Skotheim, Rolf I

    2012-09-15

    An alternative transcript variant of SLC39A14, caused by pre-mRNA splicing, was recently suggested as a biomarker for colorectal cancer (CRC). In our study, we have validated the cancer-specific splicing pattern of the mutually exclusive exons 4A and 4B in altogether 244 colorectal tissue samples. Exon-specific quantitative RT-PCR analyses across 136 Stage I-IV CRC samples and 44 normal colonic mucosa samples showed complete cancer-specificity, as well as 94% sensitivity of SLC39A14-exon4B relative to SLC39A14-exon4A expression. However, across 20 samples from a range of healthy tissues, 18 expressed the CRC variant. This was true also for ten benign lymph nodes, demonstrating that the cancer-specificity is mainly confined to the colon and rectum. Hence, clinical use of SLC39A14-exon4B as a detection marker for CRC other than in samples taken from the bowel wall is diminished. Prognostic value by detection of metastasis to lymph nodes is also abated, elucidating an important pitfall to biomarker discovery. However, analyses of ten nondysplastic biopsies from patients with active inflammatory bowel disease showed negative results in seven samples and only weakly positive results in three samples, suggesting value of SLC39A14-exon4B as a marker to distinguish CRC from other pathologic conditions of the colon. In conclusion, the SLC39A14-exon4B transcript variant is a CRC biomarker with high sensitivity and organ-confined specificity. Further use of the transcript and its encoded protein isoform should be explored in an organ-confined context. Copyright © 2011 UICC.

  13. Gene expression profile of cervical tissue compared to exfoliated cells: Impact on biomarker discovery

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    Vernon Suzanne D

    2005-05-01

    Full Text Available Abstract Background Exfoliated cervical cells are used in cytology-based cancer screening and may also be a source for molecular biomarkers indicative of neoplastic changes in the underlying tissue. However, because of keratinization and terminal differentiation it is not clear that these cells have an mRNA profile representative of cervical tissue, and that the profile can distinguish the lesions targeted for early detection. Results We used whole genome microarrays (25,353 unique genes to compare the transcription profiles from seven samples of normal exfoliated cells and one cervical tissue. We detected 10,158 genes in exfoliated cells, 14,544 in the tissue and 7320 genes in both samples. For both sample types the genes grouped into the same major gene ontology (GO categories in the same order, with exfoliated cells, having on average 20% fewer genes in each category. We also compared microarray results of samples from women with cervical intraepithelial neoplasia grade 3 (CIN3, n = 15 to those from age and race matched women without significant abnormalities (CIN1, CIN0; n = 15. We used three microarray-adapted statistical packages to identify differential gene expression. The six genes identified in common were two to four fold upregulated in CIN3 samples. One of these genes, the ubiquitin-conjugating enzyme E2 variant 1, participates in the degradation of p53 through interaction with the oncogenic HPV E6 protein. Conclusion The findings encourage further exploration of gene expression using exfoliated cells to identify and validate applicable biomarkers. We conclude that the gene expression profile of exfoliated cervical cells partially represents that of tissue and is complex enough to provide potential differentiation between disease and non-disease.

  14. Recent advances in biosensor development for the detection of cancer biomarkers.

    Science.gov (United States)

    Jayanthi, V S P K Sankara Aditya; Das, Asim Bikas; Saxena, Urmila

    2017-05-15

    Cancer is the second largest disease throughout the world with an increasing mortality rate over the past few years. The patient's survival rate is uncertain due to the limitations of cancer diagnosis and therapy. Early diagnosis of cancer is decisive for its successful treatment. A biomarker-based cancer diagnosis may significantly improve the early diagnosis and subsequent treatment. Biosensors play a crucial role in the detection of biomarkers as they are easy to use, portable, and can do analysis in real time. This review describes various biosensors designed for detecting nucleic acid and protein-based cancer biomarkers for cancer diagnosis. It mainly lays emphasis on different approaches to use electrochemical, optical, and mass-based transduction systems in cancer biomarker detection. It also highlights the analytical performances of various biosensor designs concerning cancer biomarkers in detail. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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    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.

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

    Science.gov (United States)

    Wang, Yinhai; Savage, Kienan; Grills, Claire; McCavigan, Andrena; James, Jacqueline A; Fennell, Dean A; Hamilton, Peter W

    2011-01-01

    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. 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. 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.

  17. E3 Ubiquitin Ligases as Cancer Targets and Biomarkers

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    Yi Sun

    2006-08-01

    Full Text Available E3 ubiquitin ligases are a large family of proteins that are engaged in the regulation of the turnover and activity of many target proteins. Together with ubiquitinactivating enzyme El and ubiquitin-conjugating enzyme E2, E3 ubiquitin ligases catalyze the ubiquitination of a variety of biologically significant protein substrates for targeted degradation through the 26S proteasome, as well as for nonproteolytic regulation of their functions or subcellular localizations. E3 ubiquitin ligases, therefore, play an essential role in the regulation of many biologic processes. Increasing amounts of evidence strongly suggest that the abnormal regulation of some E3 ligases is involved in cancer development. Furthermore, some E3 ubiquitin ligases are frequently overexpressed in human cancers, which correlates well with increased chemoresistance and poor clinic prognosis. In this review, E3 ubiquitin ligases (such as murine double minute 2, inhibitor of apoptosis protein, and Skpi-Cullin-F-box protein will be evaluated as potential cancer drug targets and prognostic biomarkers. Extensive study in this field would lead to a better understanding of the molecular mechanism by which E3 ligases regulate cellular processes and of how their deregulations contribute to carcinogenesis. This would eventually lead to the development of a novel class of anticancer drugs targeting specific E3 ubiquitin ligases, as well as the development of sensitive biomarkers for cancer treatment, diagnosis, and prognosis.

  18. Immunohistochemistry of colorectal cancer biomarker phosphorylation requires controlled tissue fixation.

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    Abbey P Theiss

    Full Text Available Phosphorylated signaling molecules are biomarkers of cancer pathophysiology and resistance to therapy, but because phosphoprotein analytes are often labile, poorly controlled clinical laboratory practices could prevent translation of research findings in this area from the bench to the bedside. We therefore compared multiple biomarker and phosphoprotein immunohistochemistry (IHC results in 23 clinical colorectal carcinoma samples after either a novel, rapid tissue fixation protocol or a standard tissue fixation protocol employed by clinical laboratories, and we also investigated the effect of a defined post-operative "cold" ischemia period on these IHC results. We found that a one-hour cold ischemia interval, allowed by ASCO/CAP guidelines for certain cancer biomarker assays, is highly deleterious to certain phosphoprotein analytes, specifically the phosphorylated epidermal growth factor receptor (pEGFR, but shorter ischemic intervals (less than 17 minutes facilitate preservation of phosphoproteins. Second, we found that a rapid 4-hour, two temperature, formalin fixation yielded superior staining in several cases with select markers (pEGFR, pBAD, pAKT compared to a standard overnight room temperature fixation protocol, despite taking less time. These findings indicate that the future research and clinical utilities of phosphoprotein IHC for assessing colorectal carcinoma pathophysiology absolutely depend upon attention to preanalytical factors and rigorously controlled tissue fixation protocols.

  19. Conventional frequency ultrasonic biomarkers of cancer treatment response in vivo.

    Science.gov (United States)

    Sadeghi-Naini, Ali; Falou, Omar; Tadayyon, Hadi; Al-Mahrouki, Azza; Tran, William; Papanicolau, Naum; Kolios, Michael C; Czarnota, Gregory J

    2013-06-01

    Conventional frequency quantitative ultrasound in conjunction with textural analysis techniques was investigated to monitor noninvasively the effects of cancer therapies in an in vivo preclinical model. Conventional low-frequency (∼7 MHz) and high-frequency (∼20 MHz) ultrasound was used with spectral analysis, coupled with textural analysis on spectral parametric maps, obtained from xenograft tumor-bearing animals (n = 20) treated with chemotherapy to extract noninvasive biomarkers of treatment response. Results indicated statistically significant differences in quantitative ultrasound-based biomarkers in both low- and high-frequency ranges between untreated and treated tumors 12 to 24 hours after treatment. Results of regression analysis indicated a high level of correlation between quantitative ultrasound-based biomarkers and tumor cell death estimates from histologic analysis. Applying textural characterization to the spectral parametric maps resulted in an even stronger correlation (r (2) = 0.97). The results obtained in this research demonstrate that quantitative ultrasound at a clinically relevant frequency can monitor tissue changes in vivo in response to cancer treatment administration. Using higher order textural information extracted from quantitative ultrasound spectral parametric maps provides more information at a high sensitivity related to tumor cell death.

  20. Noncoding RNAs as Novel Biomarkers in Prostate Cancer

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    C. G. H. Rönnau

    2014-01-01

    Full Text Available Prostate cancer (PCa is the second most common diagnosed malignant disease in men worldwide. Although serum PSA test dramatically improved the early diagnosis of PCa, it also led to an overdiagnosis and as a consequence to an overtreatment of patients with an indolent disease. New biomarkers for diagnosis, prediction, and monitoring of the disease are needed. These biomarkers would enable the selection of patients with aggressive or progressive disease and, hence, would contribute to the implementation of individualized therapy of the cancer patient. Since the FDA approval of the long noncoding PCA3 RNA-based urine test for the diagnosis of PCa patients, many new noncoding RNAs (ncRNAs associated with PCa have been discovered. According to their size and function, ncRNAs can be divided into small and long ncRNAs. NcRNAs are expressed in (tumor tissue, but many are also found in circulating tumor cells and in all body fluids as protein-bound or incorporated in extracellular vesicles. In these protected forms they are stable and so they can be easily analyzed, even in archival specimens. In this review, the authors will focus on ncRNAs as novel biomarker candidates for PCa diagnosis, prediction, prognosis, and monitoring of therapeutic response and discuss their potential for an implementation into clinical practice.

  1. Proteomic Profiling of Paraffin-Embedded Samples Identifies Metaplasia-Specific and Early-Stage Gastric Cancer Biomarkers

    Science.gov (United States)

    Sousa, Josane F.; Ham, Amy-Joan L.; Whitwell, Corbin; Nam, Ki Taek; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Zhang, Bing; Li, Ming; LaFleur, Bonnie; Liebler, Daniel C.; Goldenring, James R.

    2013-01-01

    Early diagnosis and curative resection are the predominant factors associated with increased survival in patients with gastric cancer. However, most gastric cancer cases are still diagnosed at later stages. Since most pathologic specimens are archived as FFPE samples, the ability to use them to generate expression profiles can greatly improve cancer biomarker discovery. We sought to uncover new biomarkers for stomach preneoplastic metaplasias and neoplastic lesions by generating proteome profiles using FFPE samples. We combined peptide isoelectric focusing and liquid chromatography–tandem mass spectrometry analysis to generate proteomic profiles from FFPE samples of intestinal-type gastric cancer, metaplasia, and normal mucosa. The expression patterns of selected proteins were analyzed by immunostaining first in single tissue sections from normal stomach, metaplasia, and gastric cancer and later in larger tissue array cohorts. We detected 60 proteins up-regulated and 87 proteins down-regulated during the progression from normal mucosa to metaplasia to gastric cancer. Two of the up-regulated proteins, LTF and DMBT1, were validated as specific markers for spasmolytic polypeptide–expressing metaplasia and intestinal metaplasia, respectively. In cancers, significantly lower levels of DMBT1 or LTF correlated with more advanced disease and worse prognosis. Thus, proteomic profiling using FFPE samples has led to the identification of two novel markers for stomach metaplasias and gastric cancer prognosis. PMID:22944598

  2. Hypermethylated DNA, a circulating biomarker for colorectal cancer detection.

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    Simon Ladefoged Rasmussen

    Full Text Available Colorectal cancer (CRC is one of the most common cancers in the western world. Screening is an efficient method of reducing cancer-related mortality. Molecular biomarkers for cancer in general and CRC in particular have been proposed, and hypermethylated DNA from stool or blood samples are already implemented as biomarkers for CRC screening. We aimed to evaluate the performance of proven hypermethylated DNA promoter regions as plasma based biomarkers for CRC detection.We conducted a cross-sectional case-control study of 193 CRC patients and 102 colonoscopy-verified healthy controls. Using methylation specific polymerase chain reaction, we evaluated 30 DNA promoter regions previously found to be CRC specific. We used multivariable logistic regression with stepwise backwards selection, and subsequent leave-pair-out cross validation, to calculate the optimism corrected area under the receiver operating characteristics curve (AUC for all stage as well as early stage CRC.None of the individual DNA promoter regions provided an overall sensitivity above 30% at a reasonable specificity. However, seven hypermethylated promoter regions (ALX4, BMP3, NPTX2, RARB, SDC2, SEPT9, and VIM along with the covariates sex and age yielded an optimism corrected AUC of 0.86 for all stage CRC and 0.85 for early stage CRC. Overall sensitivity for CRC detection was 90.7% at 72.5% specificity using a cut point value of 0.5.Individual hypermethylated DNA promoter regions have limited value as CRC screening markers. However, a panel of seven hypermethylated promoter regions show great promise as a model for CRC detection.

  3. Proteomic biomarkers for ovarian cancer risk in women with polycystic ovary syndrome: a systematic review and biomarker database integration.

    Science.gov (United States)

    Galazis, Nicolas; Olaleye, Olalekan; Haoula, Zeina; Layfield, Robert; Atiomo, William

    2012-12-01

    To review and identify possible biomarkers for ovarian cancer (OC) in women with polycystic ovary syndrome (PCOS). Systematic literature searches of MEDLINE, EMBASE, and Cochrane using the search terms "proteomics," "proteomic," and "ovarian cancer" or "ovarian carcinoma." Proteomic biomarkers for OC were then integrated with an updated previously published database of all proteomic biomarkers identified to date in patients with PCOS. Academic department of obstetrics and gynecology in the United Kingdom. A total of 180 women identified in the six studies. Tissue samples from women with OC vs. tissue samples from women without OC. Proteomic biomarkers, proteomic technique used, and methodologic quality score. A panel of six biomarkers was overexpressed both in women with OC and in women with PCOS. These biomarkers include calreticulin, fibrinogen-γ, superoxide dismutase, vimentin, malate dehydrogenase, and lamin B2. These biomarkers could help improve our understanding of the links between PCOS and OC and could potentially be used to identify subgroups of women with PCOS at increased risk of OC. More studies are required to further evaluate the role these biomarkers play in women with PCOS and OC. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  4. Immune biomarkers for chronic inflammation related complications in non-cancerous and cancerous diseases.

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    Meirow, Yaron; Baniyash, Michal

    2017-08-01

    Chronic inflammation arising in a diverse range of non-cancerous and cancerous diseases, dysregulates immunity and exposes patients to a variety of complications. These include immunosuppression, tissue damage, cardiovascular diseases and more. In cancer, chronic inflammation and related immunosuppression can directly support tumor growth and dramatically reduce the efficacies of traditional treatments, as well as novel immune-based therapies, which require a functional immune system. Nowadays, none of the immune biomarkers, regularly used by clinicians can sense a developing chronic inflammation, thus complications can only be detected upon their appearance. This review focuses on the necessity for such immune status biomarkers, which could predict complications prior to their appearance. Herein we bring examples for the use of cellular and molecular biomarkers in diagnosis, prognosis and follow-up of patients suffering from various cancers, for prediction of response to immune-based anti-cancer therapy and for prediction of cardiovascular disease in type 2 diabetes patients. Monitoring such biomarkers is expected to have a major clinical impact in addition to unraveling of the entangled complexity underlying dysregulated immunity in chronic inflammation. Thus, newly discovered biomarkers and those that are under investigation are projected to open a new era towards combating the silent damage induced by chronic inflammation.

  5. Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer

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    Sudhanshu Shukla

    2016-08-01

    Full Text Available Rapid advances in the discovery of long noncoding RNAs (lncRNAs have identified lineage- and cancer-specific biomarkers that may be relevant in the clinical management of prostate cancer (PCa. Here we assembled and analyzed a large RNA-seq dataset, from 585 patient samples, including benign prostate tissue and both localized and metastatic PCa to discover and validate differentially expressed genes associated with disease aggressiveness. We performed Sample Set Enrichment Analysis (SSEA and identified genes associated with low versus high Gleason score in the RNA-seq database. Comparing Gleason 6 versus 9+ PCa samples, we identified 99 differentially expressed genes with variable association to Gleason grade as well as robust expression in prostate cancer. The top-ranked novel lncRNA PCAT14, exhibits both cancer and lineage specificity. On multivariate analysis, low PCAT14 expression independently predicts for BPFS (P = .00126, PSS (P = .0385, and MFS (P = .000609, with trends for OS as well (P = .056. An RNA in-situ hybridization (ISH assay for PCAT14 distinguished benign vs malignant cases, as well as high vs low Gleason disease. PCAT14 is transcriptionally regulated by AR, and endogenous PCAT14 overexpression suppresses cell invasion. Thus, Using RNA-sequencing data we identify PCAT14, a novel prostate cancer and lineage-specific lncRNA. PCAT14 is highly expressed in low grade disease and loss of PCAT14 predicts for disease aggressiveness and recurrence.

  6. Is myelin basic protein a potential biomarker of brain cancer?

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    Zavialova, M G; Shevchenko, V E; Nikolaev, E N; Zgoda, V G

    2017-08-01

    Myelin basic protein is a potential biomarker for the central nervous system diseases in which the myelin sheath is destroyed. Using pseudo-selected reaction monitoring and the method of standard additions, we have measured the myelin basic protein level in the cerebrospinal fluid of patients with neurotrauma (n = 6), chronic neurodegenerative diseases (n = 2) and brain cancer (n = 5). Myelin basic protein was detected only in four out of five cerebrospinal fluid samples of patients with brain cancer. The cerebrospinal fluid myelin basic protein level ranged from 3.7 to 8.8 ng ml-1. We suggest that monitoring of myelin basic protein in cerebrospinal fluid can serve as a diagnostic test for the brain cancer.

  7. Circulating DNA as Potential Biomarker for Cancer Individualized Therapy

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    Shaorong Yu

    2013-09-01

    Full Text Available 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 sufficient 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 find 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.

  8. Utilizing biomarkers in colorectal cancer: an interview with Ajay Goel.

    Science.gov (United States)

    Goel, Ajay

    2017-12-01

    Ajay Goel speaks to Rachel Jenkins, Commissioning Editor. Ajay Goel, PhD, is a Professor and Director, Center for Gastrointestinal Research, and Director, Center for Translational Genomics and Oncology, at the Baylor Scott & White Research Institute, Baylor University Medical Center in Dallas, Texas. Dr Goel has spent more than 20 years researching cancer and has been the lead author or contributor to over 240 scientific articles published in peer-reviewed international journals and several book chapters. He is also a primary inventor on more than 15 international patents aimed at developing various biomarkers for the diagnosis, prognosis and prediction of gastrointestinal cancers. He is currently using advanced genomic and transcriptomic approaches to develop novel DNA- and miRNA-based biomarkers for the early detection of colorectal cancers. In addition, he is researching the prevention of gastrointestinal cancers using integrative and alternative approaches, including botanical products such as curcumin (from turmeric) and boswellia. Dr Goel is a member of the American Association for Cancer Research (AACR) and the American Gastroenterology Association (AGA) and is on the international editorial boards of several journals including Gastroenterology, Clinical Cancer Research, Carcinogenesis, PLoS ONE, Scientific Reports, Epigenomics, Future Medicine, Alternative Therapies in Heath and Medicine and World Journal of Gastroenterology. He is also actively involved in peer-reviewing activities for more than 100 international scientific journals and various grant review panels of various national and international funding organizations. His research has been actively funded by various private and federal organizations, including funding from the National Cancer Institute (NCI) at the NIH, American Cancer Society (ACS) and other state organizations. He has won more than dozen awards and honors, including the Union of European Gastroenterology Federation's Distinguished

  9. NanoString expression profiling identifies candidate biomarkers of RAD001 response in metastatic gastric cancer.

    Science.gov (United States)

    Das, Kakoli; Chan, Xiu Bin; Epstein, David; Teh, Bin Tean; Kim, Kyoung-Mee; Kim, Seung Tae; Park, Se Hoon; Kang, Won Ki; Rozen, Steve; Lee, Jeeyun; Tan, Patrick

    2016-01-01

    Gene expression profiling has contributed greatly to cancer research. However, expression-driven biomarker discovery in metastatic gastric cancer (mGC) remains unclear. A gene expression profile predicting RAD001 response in refractory GC was explored in this study. Total RNA isolated from 54 tumour specimens from patients with mGC, prior to RAD001 treatment, was analysed via the NanoString nCounter gene expression assay. This assay targeted 477 genes representing 10 different GC-related oncogenic signalling and molecular subtype-specific expression signatures. Gene expression profiles were correlated with patient clinicopathological variables. NanoString data confirmed similar gene expression profiles previously identified by microarray analysis. Signature I with 3 GC subtypes (mesenchymal, metabolic and proliferative) showed approximately 90% concordance where the mesenchymal and proliferative subtypes were significantly associated with signet ring cell carcinoma and the WHO classified tubular adenocarcinoma GC, respectively (p=0.042). Single-gene-level correlations with patient clinicopathological variables showed strong associations between FHL1 expression (mesenchymal subtype) and signet ring cell carcinoma, and NEK2 , OIP5 , PRC1 , TPX2 expression (proliferative subtype) with tubular adenocarcinoma (adjusted pNanoString nCounter gene expression profiling. Additionally, BRCA2 and MMP9 expression are potential predictive biomarkers for good response in RAD001-treated mGC.

  10. 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 < 0.001). PBX3 expression had a high predictive accuracy (area under the curve (AUC) = 0.82) when combined with Gleason score and age. Patients undergoing radical prostatectomy, with high levels of PBX3 mRNA, had improved prostate cancer specific survival compared to patients expressing low levels (SHR 0.21, 95% CI: 0.46-0.93, p values < 0.001, and AUC = 0.75). Our findings strongly indicate that PBX3 has potential as a biomarker, both as part of a larger gene panel and as an immunohistochemical marker, for aggressive prostate cancer. © 2016 UICC.

  11. Current clinical application of serum biomarkers to detect ovarian cancer.

    Science.gov (United States)

    Nowak, Marek; Janas, Łukasz; Stachowiak, Grzegorz; Stetkiewicz, Tomasz; Wilczyński, Jacek R

    2015-12-01

    For the last decades, hundreds of potential serum biomarkers have been assessed in diagnosing of ovarian cancer including the wide spectrum of cytokines, growth factors, adhesion molecules, proteases, hormones, coagulation factors, acute phase reactants, and apoptosis factors but except CA125 none of them have been applied to everyday clinical practice. Nowadays, the growing number of evidence suggests that the classic marker CA125 should be accompanied by HE4 and in fact, Risk of Ovarian Malignancy Algorithm (ROMA) is becoming more and more widespread in clinical practice for the evaluation of adnexal masses. Early ovarian cancer is often asymptomatic, so the challenge still exists to develop serum markers suitable for early diagnosis and screening. Current knowledge strongly points to different mechanisms of pathogenesis, genetic disturbances and clinical course of major histological subtypes of ovarian cancer. Thus, future biomarker/multimarker panels should take into consideration the implications of different molecular patterns and biological behavior of various subtypes of ovarian cancer. Very promising are studies on miRNAs - small non-protein coding gene-regulatory RNA molecules functionally involved in the pathogenesis of cancers acting as oncogenes (oncomirs) or tumor suppressors. The studies devoted to ovarian cancer tissue miRNA profiling have shown that miRNAs could be useful in diagnosing and predicting the OC outcome. They also confirmed that OC is a highly heterogeneous disease, gathering four distinct histological tumor subtypes characterized not only by distinct origin, behavior and response to chemotherapy but also by different patterns of miRNA expression.

  12. 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

    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 ...

  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

    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 ROC curve (AUC) values....

  14. RNA Editing and Drug Discovery for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Wei-Hsuan Huang

    2013-01-01

    Full Text Available RNA editing is vital to provide the RNA and protein complexity to regulate the gene expression. Correct RNA editing maintains the cell function and organism development. Imbalance of the RNA editing machinery may lead to diseases and cancers. Recently, RNA editing has been recognized as a target for drug discovery although few studies targeting RNA editing for disease and cancer therapy were reported in the field of natural products. Therefore, RNA editing may be a potential target for therapeutic natural products. In this review, we provide a literature overview of the biological functions of RNA editing on gene expression, diseases, cancers, and drugs. The bioinformatics resources of RNA editing were also summarized.

  15. 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.

  16. Application of urine proteomics for biomarker discovery in drug-induced liver injury

    NARCIS (Netherlands)

    van Swelm, Rachel P L; Kramers, Cornelis; Masereeuw, R.|info:eu-repo/dai/nl/155644033; Russel, Frans G M

    2014-01-01

    Abstract The leading cause of hepatic damage is drug-induced liver injury (DILI), for which currently no adequate predictive biomarkers are available. Moreover, for most drugs related to DILI, the mechanisms underlying the adverse reaction have not yet been elucidated. Urinary protein biomarker

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    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...... states of the validity of biomarkers in the identification of novel anti-schizophrenic drug candidates....

  18. Thoracic surface temperature rhythms as circadian biomarkers for cancer chronotherapy

    Science.gov (United States)

    Roche, Véronique Pasquale; Mohamad-Djafari, Ali; Innominato, Pasquale Fabio; Karaboué, Abdoulaye; Gorbach, Alexander; Lévi, Francis Albert

    2014-01-01

    The disruption of the temperature circadian rhythm has been associated with cancer progression, while its amplification resulted in cancer inhibition in experimental tumor models. The current study investigated the relevance of skin surface temperature rhythms as biomarkers of the Circadian Timing System (CTS) in order to optimize chronotherapy timing in individual cancer patients. Baseline skin surface temperature at four sites and wrist accelerations were measured every minute for 4 days in 16 patients with metastatic gastro-intestinal cancer before chronotherapy administration. Temperature and rest-activity were recorded, respectively, with wireless skin surface temperature patches (Respironics, Phillips) and an actigraph (Ambulatory Monitoring). Both variables were further monitored in 10 of these patients during and after a 4-day course of a fixed chronotherapy protocol. Collected at baseline, during and after therapy longitudinal data sets were processed using Fast Fourier Transform Cosinor and Linear Discriminant Analyses methods. A circadian rhythm was statistically validated with a period of 24 h (p|0.7|; p<0.05). Individual circadian acrophases at baseline were scattered from 15:18 to 6:05 for skin surface temperature, and from 12:19 to 15:18 for rest-activity, with respective median values of 01:10 (25–75% quartiles, 22:35–3:07) and 14:12 (13:14–14:31). The circadian patterns in skin surface temperature and rest-activity persisted or were amplified during and after fixed chronotherapy delivery for 5/10 patients. In contrast, transient or sustained disruption of these biomarkers was found for the five other patients, as indicated by the lack of any statistically significant dominant period in the circadian range. No consistent correlation (r<|0.7|, p ≥ 0.05) was found between paired rest-activity and temperature time series during fixed chronotherapy delivery. In conclusion, large inter-patient differences in circadian amplitudes and acrophases of

  19. Thoracic surface temperature rhythms as circadian biomarkers for cancer chronotherapy.

    Science.gov (United States)

    Roche, Véronique Pasquale; Mohamad-Djafari, Ali; Innominato, Pasquale Fabio; Karaboué, Abdoulaye; Gorbach, Alexander; Lévi, Francis Albert

    2014-04-01

    The disruption of the temperature circadian rhythm has been associated with cancer progression, while its amplification resulted in cancer inhibition in experimental tumor models. The current study investigated the relevance of skin surface temperature rhythms as biomarkers of the Circadian Timing System (CTS) in order to optimize chronotherapy timing in individual cancer patients. Baseline skin surface temperature at four sites and wrist accelerations were measured every minute for 4 days in 16 patients with metastatic gastro-intestinal cancer before chronotherapy administration. Temperature and rest-activity were recorded, respectively, with wireless skin surface temperature patches (Respironics, Phillips) and an actigraph (Ambulatory Monitoring). Both variables were further monitored in 10 of these patients during and after a 4-day course of a fixed chronotherapy protocol. Collected at baseline, during and after therapy longitudinal data sets were processed using Fast Fourier Transform Cosinor and Linear Discriminant Analyses methods. A circadian rhythm was statistically validated with a period of 24 h (p surface temperature (median, 0.72 °C), and from 16.6 to 146.1 acc/min for rest-activity (median, 88.9 acc/min). Thirty-nine pairs of baseline temperature and rest-activity time series (75%) were correlated (r > |0.7|; p surface temperature, and from 12:19 to 15:18 for rest-activity, with respective median values of 01:10 (25-75% quartiles, 22:35-3:07) and 14:12 (13:14-14:31). The circadian patterns in skin surface temperature and rest-activity persisted or were amplified during and after fixed chronotherapy delivery for 5/10 patients. In contrast, transient or sustained disruption of these biomarkers was found for the five other patients, as indicated by the lack of any statistically significant dominant period in the circadian range. No consistent correlation (r surface temperature were demonstrated for the first time in cancer patients, despite rather

  20. Blood-based biomarkers of aggressive prostate cancer.

    Directory of Open Access Journals (Sweden)

    Men Long Liong

    Full Text Available PURPOSE: Prostate cancer is a bimodal disease with aggressive and indolent forms. Current prostate-specific-antigen testing and digital rectal examination screening provide ambiguous results leading to both under-and over-treatment. Accurate, consistent diagnosis is crucial to risk-stratify patients and facilitate clinical decision making as to treatment versus active surveillance. Diagnosis is currently achieved by needle biopsy, a painful procedure. Thus, there is a clinical need for a minimally-invasive test to determine prostate cancer aggressiveness. A blood sample to predict Gleason score, which is known to reflect aggressiveness of the cancer, could serve as such a test. MATERIALS AND METHODS: Blood mRNA was isolated from North American and Malaysian prostate cancer patients/controls. Microarray analysis was conducted utilizing the Affymetrix U133 plus 2·0 platform. Expression profiles from 255 patients/controls generated 85 candidate biomarkers. Following quantitative real-time PCR (qRT-PCR analysis, ten disease-associated biomarkers remained for paired statistical analysis and normalization. RESULTS: Microarray analysis was conducted to identify 85 genes differentially expressed between aggressive prostate cancer (Gleason score ≥8 and controls. Expression of these genes was qRT-PCR verified. Statistical analysis yielded a final seven-gene panel evaluated as six gene-ratio duplexes. This molecular signature predicted as aggressive (ie, Gleason score ≥8 55% of G6 samples, 49% of G7(3+4, 79% of G7(4+3 and 83% of G8-10, while rejecting 98% of controls. CONCLUSION: In this study, we have developed a novel, blood-based biomarker panel which can be used as the basis of a simple blood test to identify men with aggressive prostate cancer and thereby reduce the overdiagnosis and overtreatment that currently results from diagnosis using PSA alone. We discuss possible clinical uses of the panel to identify men more likely to benefit from

  1. 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

  2. 1-D grating based SPR biosensor for the detection of lung cancer biomarkers using Vroman effect

    Science.gov (United States)

    Teotia, Pradeep Kumar; Kaler, R. S.

    2018-01-01

    Grating based surface plasmon resonance waveguide biosensor have been reported for the detection of lung cancer biomarkers using Vroman effect. The proposed grating based multilayered biosensor is designed with high detection accuracy for Epidermal growth factor receptor (EGFR) and also analysed to show high detection accuracy with acceptable sensitivity for both cancer biomarkers. The introduction of periodic grating with multilayer metals generates a good resonance that make it possible for early detection of cancerous cells. Using finite difference time domain method, it is observed wavelength of biosensor get red-shifted on variations of the refractive index due to the presence of both the cancerous bio-markers. The reported detection accuracy and sensitivity of proposed biosensor is quite acceptable for both lung cancer biomarkers i.e. Carcinoembryonic antigen (CEA) and Epidermal growth factor receptor (EGFR) which further offer us label free early detection of lung cancer using these biomarkers.

  3. NPPB is a novel candidate biomarker expressed by cancer-associated fibroblasts in epithelial ovarian cancer.

    Science.gov (United States)

    Lawrenson, Kate; Grun, Barbara; Lee, Nathan; Mhawech-Fauceglia, Paulette; Kan, Jenny; Swenson, Steve; Lin, Yvonne G; Pejovic, Tanja; Millstein, Joshua; Gayther, Simon A

    2015-03-15

    Most solid tumors contain cancer-associated fibroblasts (CAFs) that support tumorigenesis and malignant progression. However, the cellular origins of CAFs in epithelial ovarian cancers (EOCs) remain poorly understood, and their utility as a source of clinical biomarkers for cancer diagnosis has not been explored in great depth. Here, we report establishing in vitro and in vivo models of CAFs in ovarian cancer development. Normal ovarian fibroblasts and mesenchymal stem cells cultured in the presence of EOC cells acquired a CAF-like phenotype, and promoted EOC cell migration in vitro. CAFs also promoted ovarian cancer growth in vivo in both subcutaneous and intraperitoneal murine xenograft assays. Molecular profiling of CAFs identified gene expression signatures that were highly enriched for extracellular and secreted proteins. We identified novel candidate CAF-specific biomarkers for ovarian cancer including NPPB, which was expressed in the stroma of 60% primary ovarian cancer tissues (n = 145) but not in the stroma of normal ovaries (n = 4). NPPB is a secreted protein that was also elevated in the blood of 50% of women with ovarian cancer (n = 8). Taken together, these data suggest that the tumor stroma is a novel source of biomarkers, including NPPB, that may be of clinical utility for detection of EOC. © 2014 UICC.

  4. 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.

  5. Endometrial cancer risk prediction including serum-based biomarkers : results from the EPIC cohort

    NARCIS (Netherlands)

    Fortner, Renée T.; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H. Bas|info:eu-repo/dai/nl/06929528X; Peeters, Petra H M|info:eu-repo/dai/nl/074099655; Weiderpass, Elisabete; Gram, Inger T.; Gavrilyuk, Oxana; Quirós, J. Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay Tee; Allen, Naomi E.; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A.; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

    2017-01-01

    Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested

  6. Identification of New Serum Biomarkers for Early Breast Cancer Diagnosis and Prognosis Using Lipid Microarrays

    National Research Council Canada - National Science Library

    Du, Guangwei

    2008-01-01

    Breast cancer is the most common form of cancer among women. Compared with other serum polypeptides, autoantibodies have many appealing features as biomarkers including sensitivity, stability, and easy detection...

  7. voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data

    Directory of Open Access Journals (Sweden)

    Gokmen Zararsiz

    2017-10-01

    Full Text Available RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom extensions of the nearest shrunken centroids (NSC and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom’s precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

  8. Biomarkers of acute kidney injury: the pathway from discovery to clinical adoption.

    Science.gov (United States)

    Kashani, Kianoush; Cheungpasitporn, Wisit; Ronco, Claudio

    2017-07-26

    Acute kidney injury (AKI) is a common complication of critical illnesses and has a significant impact on outcomes, including mortality and morbidities. Unfortunately, apart from prophylactic measures, no effective treatment for this syndrome is known. Therefore, early recognition of AKI not only can provide better opportunities for preventive interventions, but also opens many gates for research and development of effective therapeutic options. Over the last few years, several new AKI biomarkers have been discovered and validated to improve early detection, differential diagnosis, and differentiation of patients into risk groups for progressive renal failure, need for renal replacement therapy (RRT), or death. These novel AKI biomarkers complement serum creatinine (SCr) and urine output, which are the standard diagnostic tools for AKI detection. In this article, we review the available literature on characteristics of promising AKI biomarkers that are currently the focus of preclinical and clinical investigations. These biomarkers include neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1), liver-type fatty acid-binding protein, interleukin 18 (lL-18), insulin-like growth factor-binding protein 7, tissue inhibitor of metalloproteinase 2 (TIMP-2), calprotectin, urine angiotensinogen (AGT), and urine microRNA. We then describe the clinical performance of these biomarkers for diagnosis and prognostication. We also appraise each AKI biomarker's advantages and limitations as a tool for early AKI recognition and prediction of clinical outcomes after AKI. Finally, we review the current and future states of implementation of biomarkers in the clinical practice.

  9. Original Article : Correlation between preoperative serum Levels of five biomarkers and relationships between these biomarkers and cancer stage in epithelial overian cancer

    National Research Council Canada - National Science Library

    Jong Yun Hwang; ; Sung Hun Na; Hyang Ah Lee; Dong Heon Lee

    2009-01-01

    Objective: To examine the correlation among the preoperative serum levels of five biomarkers presumed to be useful for early detection of epithelial ovarian cancer and evaluate the relationships between serum...

  10. MicroRNAs as novel biomarkers in colorectal cancer

    Directory of Open Access Journals (Sweden)

    Damjan eGlavac

    2012-10-01

    Full Text Available MicroRNAs (miRNAs play an important role in various physiologic and developmental processes and in the initiation and progression of cancer. This class of small, non-coding RNAs critically regulate gene expression at the post-transcriptional level and evidence suggests that they may function as both oncogenes and tumour suppressors. Colorectal cancer (CRC is a major healthcare concern worldwide and in order to reduce CRC related deaths, research is aimed into the search for some novel screening approaches. In this sense, miRNAs are rapidly emerging as a novel class of biomarkers, with good potential as diagnostic and therapeutic targets. This review summarizes the recent findings of the clinicopathological relevance that miRNAs have in CRC initiation, development and progress, highlighting their potential diagnostic, prognostic and therapeutic use in CRC, focusing on the group of microsatellite unstable and the group of hypermethylated CRCs, as well as discussing future prospects.

  11. 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

  12. 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.

  13. Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation

    Directory of Open Access Journals (Sweden)

    Greco Ines

    2012-10-01

    Full Text Available Abstract Background Alzheimer’s Disease (AD is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders.

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

    Directory of Open Access Journals (Sweden)

    Yu Myeong-Hee

    2010-03-01

    Full Text Available Abstract Background 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. Methods 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. Results 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. Conclusions Our study suggests that BTD is a potential serological biomarker for the detection of breast cancer.

  15. Discovery analysis of TCGA data reveals association between germline genotype and survival in ovarian cancer patients.

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    Rosemary Braun

    Full Text Available Ovarian cancer remains a significant public health burden, with the highest mortality rate of all the gynecological cancers. This is attributable to the late stage at which the majority of ovarian cancers are diagnosed, coupled with the low and variable response of advanced tumors to standard chemotherapies. To date, clinically useful predictors of treatment response remain lacking. Identifying the genetic determinants of ovarian cancer survival and treatment response is crucial to the development of prognostic biomarkers and personalized therapies that may improve outcomes for the late-stage patients who comprise the majority of cases.To identify constitutional genetic variations contributing to ovarian cancer mortality, we systematically investigated associations between germline polymorphisms and ovarian cancer survival using data from The Cancer Genome Atlas Project (TCGA. Using stage-stratified Cox proportional hazards regression, we examined >650,000 SNP loci for association with survival. We additionally examined whether the association of significant SNPs with survival was modified by somatic alterations.Germline polymorphisms at rs4934282 (AGAP11/C10orf116 and rs1857623 (DNAH14 were associated with stage-adjusted survival (p= 1.12e-07 and 1.80e-07, FDR q= 1.2e-04 and 2.4e-04, respectively. A third SNP, rs4869 (C10orf116, was additionally identified as significant in the exome sequencing data; it is in near-perfect LD with rs4934282. The associations with survival remained significant when somatic alterations.Discovery analysis of TCGA data reveals germline genetic variations that may play a role in ovarian cancer survival even among late-stage cases. The significant loci are located near genes previously reported as having a possible relationship to platinum and taxol response. Because the variant alleles at the significant loci are common (frequencies for rs4934282 A/C alleles = 0.54/0.46, respectively; rs1857623 A/G alleles = 0

  16. The AIDS and Cancer Specimen Resource: Role in HIV/AIDS scientific discovery

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    McGrath Michael S

    2007-03-01

    Full Text Available Abstract The AIDS Cancer and Specimen Resource (ACSR supports scientific discovery in the area of HIV/AIDS-associated malignancies. The ACSR was established as a cooperative agreement between the NCI (Office of the Director, Division of Cancer Treatment and Diagnosis and regional consortia, University of California, San Francisco (West Coast, George Washington University (East Coast and Ohio State University (Mid-Region to collect, preserve and disperse HIV-related tissues and biologic fluids and controls along with clinical data to qualified investigators. The available biological samples with clinical data and the application process are described on the ACSR web site. The ACSR tissue bank has more than 100,000 human HIV positive specimens that represent different processing (43, specimen (15, and anatomical site (50 types. The ACSR provides special biospecimen collections and prepares speciality items, e.g., tissue microarrays (TMA, DNA libraries. Requests have been greatest for Kaposi's sarcoma (32% and non-Hodgkin's lymphoma (26%. Dispersed requests include 83% tissue (frozen and paraffin embedded, 18% plasma/serum and 9% other. ACSR also provides tissue microarrays of, e.g., Kaposi's sarcoma and non-Hodgkin's lymphoma, for biomarker assays and has developed collaborations with other groups that provide access to additional AIDS-related malignancy specimens. ACSR members and associates have completed 63 podium and poster presentations. Investigators have submitted 125 letters of intent requests. Discoveries using ACSR have been reported in 61 scientific publications in notable journals with an average impact factor of 7. The ACSR promotes the scientific exploration of the relationship between HIV/AIDS and malignancy by participation at national and international scientific meetings, contact with investigators who have productive research in this area and identifying, collecting, preserving, enhancing, and dispersing HIV

  17. Immunohistochemical Biomarkers in Gastric Cancer Research and Management

    Directory of Open Access Journals (Sweden)

    Elena Lastraioli

    2012-01-01

    Full Text Available Gastric cancer still represents a major health problem, despite a decrease in its incidence in the last years. Due to the social impact of gastric cancer (GC, there is a need for novel biomarkers in order to stratify patients into appropriate screening, surveillance, or treatment programs. Although histopathology remains the most reliable and less expensive method, numerous efforts have been made searching for novel biomarkers. In recent years, several molecules have been identified and tested for their clinical relevance in GC management. In this paper, we will focus on a well-known GC marker, whose determination is mandatory in GC, HER2, a marker whose correlation with prognosis is still controversial (VEGF-A and a quite novel, unconventional marker, the ether-à-go-go-related gene 1 (hERG1. All these proteins can be easily detected with immunohistochemistry, a technique widely used both in diagnostic and research laboratories that represents a link between surgical and molecular pathology, basic science, and clinical medicine.

  18. SU-F-R-24: Identifying Prognostic Imaging Biomarkers in Early Stage Lung Cancer Using Radiomics

    Energy Technology Data Exchange (ETDEWEB)

    Zeng, X [Shanghai Jiao Tong University, Shanghai, Shanghai (China); Wu, J [Stanford University Palo Alto, CA (United States); Cui, Y; Li, R [Stanford University, Palo Alto, CA (United States); Gao, H [Shanghai Jiao Tong University, Boston, MA (United States)

    2016-06-15

    Purpose: Patients diagnosed with early stage lung cancer have favorable outcomes when treated with surgery or stereotactic radiotherapy. However, a significant proportion (∼20%) of patients will develop metastatic disease and eventually die of the disease. The purpose of this work is to identify quantitative imaging biomarkers from CT for predicting overall survival in early stage lung cancer. Methods: In this institutional review board-approved HIPPA-compliant retrospective study, we retrospectively analyzed the diagnostic CT scans of 110 patients with early stage lung cancer. Data from 70 patients were used for training/discovery purposes, while those of remaining 40 patients were used for independent validation. We extracted 191 radiomic features, including statistical, histogram, morphological, and texture features. Cox proportional hazard regression model, coupled with the least absolute shrinkage and selection operator (LASSO), was used to predict overall survival based on the radiomic features. Results: The optimal prognostic model included three image features from the Law’s feature and wavelet texture. In the discovery cohort, this model achieved a concordance index or CI=0.67, and it separated the low-risk from high-risk groups in predicting overall survival (hazard ratio=2.72, log-rank p=0.007). In the independent validation cohort, this radiomic signature achieved a CI=0.62, and significantly stratified the low-risk and high-risk groups in terms of overall survival (hazard ratio=2.20, log-rank p=0.042). Conclusion: We identified CT imaging characteristics associated with overall survival in early stage lung cancer. If prospectively validated, this could potentially help identify high-risk patients who might benefit from adjuvant systemic therapy.

  19. Androgen receptor: structure, role in prostate cancer and drug discovery

    Science.gov (United States)

    Tan, MH Eileen; Li, Jun; Xu, H Eric; Melcher, Karsten; Yong, Eu-leong

    2015-01-01

    Androgens and androgen receptors (AR) play a pivotal role in expression of the male phenotype. Several diseases, such as androgen insensitivity syndrome (AIS) and prostate cancer, are associated with alterations in AR functions. Indeed, androgen blockade by drugs that prevent the production of androgens and/or block the action of the AR inhibits prostate cancer growth. However, resistance to these drugs often occurs after 2–3 years as the patients develop castration-resistant prostate cancer (CRPC). In CRPC, a functional AR remains a key regulator. Early studies focused on the functional domains of the AR and its crucial role in the pathology. The elucidation of the structures of the AR DNA binding domain (DBD) and ligand binding domain (LBD) provides a new framework for understanding the functions of this receptor and leads to the development of rational drug design for the treatment of prostate cancer. An overview of androgen receptor structure and activity, its actions in prostate cancer, and how structural information and high-throughput screening have been or can be used for drug discovery are provided herein. PMID:24909511

  20. Discovery and identification of potential biomarkers for alcohol-induced oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Hu, Qingping; Wei, Jianteng; Liu, Yewei; Fei, Xiulan; Hao, Yuwei; Pei, Dong; Di, Duolong

    2017-07-01

    Biomarkers involved in alcohol-induced oxidative stress play an important role in alcoholic liver disease prevention and diagnosis. Alcohol-induced oxidative stress in human liver L-02 cells was used to discover the potential biomarkers. Metabolites from L-02 cells induced by alcohol were measured by high-performance liquid chromatography and mass spectrometry. Fourteen metabolites that allowed discrimination between control and model groups were discovered by multivariate statistical data analysis (i.e. principal components analysis, orthogonal partial least-squares discriminate analysis). Based on the retention time, UV spectrum and LC-MS findings of the samples and compared with the authentic standards, eight biomarkers involved in alcohol-induced oxidative stress, namely, malic acid, oxidized glutathione, γ-glutamyl-cysteinyl-glycine, adenosine triphosphate, phenylalanine, adenosine monophosphate, nitrotyrosine and tryptophan, were identified. These biomarkers offered important targets for disease diagnosis and other researches. Copyright © 2016 John Wiley & Sons, Ltd.

  1. Discovery of Novel Biomarkers for Alzheimer’s Disease from Blood

    Directory of Open Access Journals (Sweden)

    Jintao Long

    2016-01-01

    Full Text Available 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%.

  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. Reliable Biomarker discovery from Metagenomic data via RegLRSD algorithm.

    Science.gov (United States)

    Alshawaqfeh, Mustafa; Bashaireh, Ahmad; Serpedin, Erchin; Suchodolski, Jan

    2017-07-10

    Biomarker detection presents itself as a major means of translating biological data into clinical applications. Due to the recent advances in high throughput sequencing technologies, an increased number of metagenomics studies have suggested the dysbiosis in microbial communities as potential biomarker for certain diseases. The reproducibility of the results drawn from metagenomic data is crucial for clinical applications and to prevent incorrect biological conclusions. The variability in the sample size and the subjects participating in the experiments induce diversity, which may drastically change the outcome of biomarker detection algorithms. Therefore, a robust biomarker detection algorithm that ensures the consistency of the results irrespective of the natural diversity present in the samples is needed. Toward this end, this paper proposes a novel Regularized Low Rank-Sparse Decomposition (RegLRSD) algorithm. RegLRSD models the bacterial abundance data as a superposition between a sparse matrix and a low-rank matrix, which account for the differentially and non-differentially abundant microbes, respectively. Hence, the biomarker detection problem is cast as a matrix decomposition problem. In order to yield more consistent and solid biological conclusions, RegLRSD incorporates the prior knowledge that the irrelevant microbes do not exhibit significant variation between samples belonging to different phenotypes. Moreover, an efficient algorithm to extract the sparse matrix is proposed. Comprehensive comparisons of RegLRSD with the state-of-the-art algorithms on three realistic datasets are presented. The obtained results demonstrate that RegLRSD consistently outperforms the other algorithms in terms of reproducibility performance and provides a marker list with high classification accuracy. The proposed RegLRSD algorithm for biomarker detection provides high reproducibility and classification accuracy performance regardless of the dataset complexity and the

  4. 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.

  5. Molecular profiling of breast cancer cell lines defines relevant tumor models and provides a resource for cancer gene discovery.

    Directory of Open Access Journals (Sweden)

    Jessica Kao

    2009-07-01

    genes.Overall, breast cancer cell lines were genetically more complex than tumors, but retained expression patterns with relevance to the luminal-basal subtype distinction. The compendium of molecular profiles defines cell lines suitable for investigations of subtype-specific pathobiology, cancer stem cell biology, biomarkers and therapies, and provides a resource for discovery of new breast cancer genes.

  6. Comparison of GC-MS and GC×GC-MS in the analysis of human serum samples for biomarker discovery.

    Science.gov (United States)

    Winnike, Jason H; Wei, Xiaoli; Knagge, Kevin J; Colman, Steven D; Gregory, Simon G; Zhang, Xiang

    2015-04-03

    We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

  7. Quantitative label-free proteomics for discovery of biomarkers in cerebrospinal fluid: assessment of technical and inter-individual variation.

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

    Full Text Available Biomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS for CSF biomarker discovery by (1 identifying reparable sources of technical variability, (2 assessing subject variance and residual technical variability for numerous CSF proteins, and (3 testing its ability to segregate samples on the basis of desired biomarker characteristics.Fourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i incomplete MAF and keratins; ii globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5% whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and

  8. Identification of a Novel Cancer Biomarker | Center for Cancer Research

    Science.gov (United States)

    During cancer development, cells accumulate a variety of mutations which alter their normal components and activities. One potential change is in the carbohydrate or sugar polymers which decorate proteins predominately found on the cell surface. The accessibility of these residues makes them ideal targets for the development of diagnostics or therapeutics.

  9. Overlap in serum metabolic profiles between non-related diseases: Implications for LC-MS metabolomics biomarker discovery.

    Science.gov (United States)

    Lindahl, Anna; Forshed, Jenny; Nordström, Anders

    2016-09-23

    Untargeted metabolic profiling has generated large activity in the field of clinical biomarker discovery. Yet, no clinically approved metabolite biomarkers have emerged with failure in validation phases often being a reason. To investigate why, we have applied untargeted metabolic profiling in a retrospective cohort of serum samples representing non-related diseases. Age and gender matched samples from patients diagnosed with pneumonia, congestive heart failure, lymphoma and healthy controls were subject to comprehensive metabolic profiling using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). The metabolic profile of each diagnosis was compared to the healthy control group and significant metabolites were filtered out using t-test with FDR correction. Metabolites found to be significant between each disease and healthy controls were compared and analyzed for overlap. Results show that despite differences in etiology and clinical disease presentation, the fraction of metabolites with an overlap between two or more diseases was 61%. A majority of these metabolites can be associated with immune responses thus representing non-disease specific events. We show that metabolic serum profiles from patients representing non-related diseases display very similar metabolic differences when compared to healthy controls. Many of the metabolites discovered as disease specific in this study have further been associated with other diseases in the literature. Based on our findings we suggest non-related disease controls in metabolomics biomarker discovery studies to increase the chances of a successful validation and future clinical applications. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

  10. Nutrition and biomarkers in psychiatry: research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    OpenAIRE

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain polyunsaturated fatty acids (LCPUFA), B-vitamins and platelet (PLT) serotonin (5-HT) in schizophrenia and autism. The thesis proposes also that biomarker research in psychiatric disease is of great rel...

  11. Genetics and Genetic Biomarkers in Sporadic Colorectal Cancer

    Science.gov (United States)

    Carethers, John M.; Jung, Barbara H.

    2015-01-01

    Sporadic colorectal cancer (CRC) is a somatic genetic disease in which pathogenesis is influenced by the local colonic environment and the patient’s genetic background. Consolidating the knowledge of genetic and epigenetic events that occur with initiation, progression, and metastasis of sporadic CRC has identified some biomarkers that might be utilized to predict behavior and prognosis beyond staging, and inform treatment approaches. Modern next generation sequencing of sporadic CRCs has confirmed prior identified genetic alterations, and has classified new alterations. Each patient’s CRC is genetically unique, propelled by 2 to 8 driver gene alterations that have accumulated within the CRC since initiation. Commonly observed alterations across sporadic CRCs have allowed classification into a: (1) hypermutated group that includes defective DNA mismatch repair with microsatellite instability (MSI) and POLE mutations in ~15%, containing multiple frameshifted genes and BRAFV600E; (2) non-hypermutated group with multiple somatic copy number alterations and aneuploidy in ~85%, containing oncogenic activation of KRAS and PIK3CA and mutation and loss of heterozygosity of tumor suppressor genes such as APC and TP53; (3) CpG Island Methylator Phenotype CRCs in ~20% that overlap greatly with MSI CRCs and some non-hypermutated CRCs; and (4) elevated microsatellite alterations at selected tetranucleotide repeats (EMAST) in ~60% that associates with metastatic behavior in both hypermutated and non-hypermutated groups. Components from these classifications are now used as diagnostic, prognostic and treatment biomarkers. Additional common biomarkers may come from genome-wide association studies and microRNAs among other sources, as well as from the unique alteration profile of an individual CRC to apply a precision medicine approach to care. PMID:26216840

  12. Discovery – Cisplatin and The Treatment of Testicular and Other Cancers

    Science.gov (United States)

    Prior to the discovery of cisplatin in 1965, men with testicular cancer had few medical options. Now, thanks to NCI research, cisplatin and similar chemotherapy drugs are known for curing testicular and other forms of cancer.

  13. Epigenetic biomarkers of colorectal cancer: Focus on DNA methylation.

    Science.gov (United States)

    Coppedè, Fabio

    2014-01-28

    The original theory of the multi-step process of colorectal cancer (CRC), suggesting that the disease resulted from the accumulation of mutations in oncogenes and tumor suppressor genes in colonic mucosa cells, has been largely revised following the observation that epigenetic modifications of several genes occur in the average CRC genome. Therefore, the current opinion is that CRCs are the consequence of the accumulation of both mutations and epigenetic modifications of several genes. This mini-review article focuses on DNA methylation biomarkers in CRC. Recent large-scale DNA methylation studies suggest that CRCs can be divided into at least three-four subtypes according to the frequency of DNA methylation and those of mutations in key CRC genes. Despite hundreds of genes might be epigenetically modified in CRC cells, there is interest in the identification of DNA methylation biomarkers to be used for CRC diagnosis, progression, tendency to tissue invasion and metastasis, prognosis, and response to chemotherapeutic agents. Moreover, DNA methylation largely depends on one-carbon metabolism, the metabolic pathway required for the production of S-adenosylmethionine, the major intracellular methylating agent. Complex interactions are emerging among dietary one-carbon nutrients (folates, vitamin B6, vitamin B12, methionine, and others), their metabolic genes, CRC risk, and DNA methylation profiles in CRC. Moreover, active research is also focused on the possible contribution of folic acid dietary fortification during pregnancy and the possible methylation of CRC-related genes in the offspring. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  14. Lipid Biomarkers Identified for Liver Cancer | Center for Cancer Research

    Science.gov (United States)

    Hepatocellular carcinoma (HCC) is an aggressive cancer of the liver with poor prognosis and growing incidence in developed countries. Pathology and genetic profiles of HCC are heterogeneous, suggesting that it can begin growing in different cell types. Although human tumors such as HCC have been profiled in-depth by genomics-based studies, not much is known about their overall metabolite modifications and how these changes can form a network that leads to aggressive disease and poor outcome.

  15. Molecular Characterization of H.pylori Strains and Biomarkers in Gastric Cancer

    Science.gov (United States)

    2017-07-01

    AWARD NUMBER: W81XWH-16-1-0274 TITLE: Molecular Characterization of H.pylori Strains and Biomarkers in Gastric Cancer PRINCIPAL INVESTIGATOR...SUBTITLE Molecular Characterization of H.pylori Strains and Biomarkers in Gastric Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-16-1-0274 5c...gastric cancer (GC), but it is unclear why infected individuals develop different diseases. GC annually claims 700,000 lives worldwide

  16. Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity Among Minority Populations

    Science.gov (United States)

    2014-03-01

    visibility of microcalcification (MCs) in clinical images is of critical importance for breast imaging, as MCs can be the only sign of early cancer . To...AD_________________ Award Number: W81XWH-09-1-0062 TITLE: Image Based Biomarker of Breast Cancer ...Report 3. DATES COVERED (From - To) – 14 1212 4. TITLE AND SUBTITLE Image Based Biomarker of Breast Cancer Risk: 5a. CONTRACT

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

    Directory of Open Access Journals (Sweden)

    Sauter Edward R

    2012-01-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

    Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a

  19. Enhancing knowledge discovery from cancer genomics data with Galaxy

    Science.gov (United States)

    Albuquerque, Marco A.; Grande, Bruno M.; Ritch, Elie J.; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K.; Shah, Sohrab P.; Boutros, Paul C.

    2017-01-01

    Abstract The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. PMID:28327945

  20. Enhancing knowledge discovery from cancer genomics data with Galaxy.

    Science.gov (United States)

    Albuquerque, Marco A; Grande, Bruno M; Ritch, Elie J; Pararajalingam, Prasath; Jessa, Selin; Krzywinski, Martin; Grewal, Jasleen K; Shah, Sohrab P; Boutros, Paul C; Morin, Ryan D

    2017-05-01

    The field of cancer genomics has demonstrated the power of massively parallel sequencing techniques to inform on the genes and specific alterations that drive tumor onset and progression. Although large comprehensive sequence data sets continue to be made increasingly available, data analysis remains an ongoing challenge, particularly for laboratories lacking dedicated resources and bioinformatics expertise. To address this, we have produced a collection of Galaxy tools that represent many popular algorithms for detecting somatic genetic alterations from cancer genome and exome data. We developed new methods for parallelization of these tools within Galaxy to accelerate runtime and have demonstrated their usability and summarized their runtimes on multiple cloud service providers. Some tools represent extensions or refinement of existing toolkits to yield visualizations suited to cohort-wide cancer genomic analysis. For example, we present Oncocircos and Oncoprintplus, which generate data-rich summaries of exome-derived somatic mutation. Workflows that integrate these to achieve data integration and visualizations are demonstrated on a cohort of 96 diffuse large B-cell lymphomas and enabled the discovery of multiple candidate lymphoma-related genes. Our toolkit is available from our GitHub repository as Galaxy tool and dependency definitions and has been deployed using virtualization on multiple platforms including Docker. © The Author 2017. Published by Oxford University Press.

  1. A social network analysis of treatment discoveries in cancer.

    Directory of Open Access Journals (Sweden)

    Athanasios Tsalatsanis

    Full Text Available Controlled clinical trials are widely considered to be the vehicle to treatment discovery in cancer that leads to significant improvements in health outcomes including an increase in life expectancy. We have previously shown that the pattern of therapeutic discovery in randomized controlled trials (RCTs can be described by a power law distribution. However, the mechanism generating this pattern is unknown. Here, we propose an explanation in terms of the social relations between researchers in RCTs. We use social network analysis to study the impact of interactions between RCTs on treatment success. Our dataset consists of 280 phase III RCTs conducted by the NCI from 1955 to 2006. The RCT networks are formed through trial interactions formed i at random, ii based on common characteristics, or iii based on treatment success. We analyze treatment success in terms of survival hazard ratio as a function of the network structures. Our results show that the discovery process displays power law if there are preferential interactions between trials that may stem from researchers' tendency to interact selectively with established and successful peers. Furthermore, the RCT networks are "small worlds": trials are connected through a small number of ties, yet there is much clustering among subsets of trials. We also find that treatment success (improved survival is proportional to the network centrality measures of closeness and betweenness. Negative correlation exists between survival and the extent to which trials operate within a limited scope of information. Finally, the trials testing curative treatments in solid tumors showed the highest centrality and the most influential group was the ECOG. We conclude that the chances of discovering life-saving treatments are directly related to the richness of social interactions between researchers inherent in a preferential interaction model.

  2. 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.

  3. Biomarkers in Tumorigenesis Using Cancer Cell Lines: A Systematic Review

    Science.gov (United States)

    Raju K, Lizbeth; Augustine, Dominic; Rao, Roopa S; S V, Sowmya; Haragannavar, Vanishri C; Nambiar, Shwetha; Prasad, Kavitha; Awan, Kamran Habib; Patil, Shankargouda

    2017-09-27

    Cancer is a leading cause of death worldwide. Despite many research advancements in the field, the genetic changes regulating the transformation of normal oral cells into malignant cells have not been fully elucidated. Several studies have evaluated carcinogenesis at the molecular level. Cancer cell lines are commonly used in biomedical research because they provide an unlimited source of cells and represent various stages of initiation and progression of carcinogenesis in vitro. Aims: The objective of the study was to review original research articles using cancer cell lines as a tool to understand carcinogenesis and to identify the genes involved in tumor development. Additionally, we also examined the application of the genes as predictive biomarkers. Methods and Materials: Several databases, including PubMed, Google Scholar, Ebsco, and Science Direct, were searched from 1985 to December 2016 using various combinations of the following key words: “mouth neoplasm”, “cell lines”, and “tumorigenesis”. Original experimental studies published in English were included. We excluded letters to the editor, historic reviews, and unpublished data from the analysis. Results: There were 17 studies (in vitro) included in the analysis. There were 14 genes and 4 miRNAs involved in malignant transformation of oral keratinocytes into cancer cells. The most commonly studied genes were p53, cyclin D1, and hTERT. Conclusion: Additional reviews and studies are needed to identify a panel of genes specific to various potentially malignant disorders and to aid in the early detection of oral squamous cell carcinoma (OSCC) because tumorigenesis involves the mutation of multiple genes. Furthermore, improving advanced cost-effective diagnostic methods may benefit the public health sector. Creative Commons Attribution License

  4. Modeling Biomarker Dynamics with Implications for the Treatment of Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Erin B. Hedican

    2007-01-01

    Full Text Available The authors review existing models of biomarker dynamics and develop and investigate several new models which may better accommodate the underlying biology. While the general foundations of the models studied could be applied to a number of biomarker systems, the parameter values and specific applications to treatment regimens are focused on the role of prostate-specific antigen (PSA as a biomarker for prostate cancer. Included are suggestions for possible clinical validation studies.

  5. RNA Biomarkers: Frontier of Precision Medicine for Cancer

    Directory of Open Access Journals (Sweden)

    Xiaochen Xi

    2017-02-01

    Full Text Available As an essential part of central dogma, RNA delivers genetic and regulatory information and reflects cellular states. Based on high‐throughput sequencing technologies, cumulating data show that various RNA molecules are able to serve as biomarkers for the diagnosis and prognosis of various diseases, for instance, cancer. In particular, detectable in various bio‐fluids, such as serum, saliva and urine, extracellular RNAs (exRNAs are emerging as non‐invasive biomarkers for earlier cancer diagnosis, tumor progression monitor, and prediction of therapy response. In this review, we summarize the latest studies on various types of RNA biomarkers, especially extracellular RNAs, in cancer diagnosis and prognosis, and illustrate several well‐known RNA biomarkers of clinical utility. In addition, we describe and discuss general procedures and issues in investigating exRNA biomarkers, and perspectives on utility of exRNAs in precision medicine.

  6. Cancer biomarkers defined by autoantibody signatures to aberrant O-glycopeptide epitopes

    DEFF Research Database (Denmark)

    Wandall, Hans H; Blixt, Ola; Tarp, Mads A

    2010-01-01

    aberrent O-glycopeptide epitopes derived from MUC1. These autoantibodies represent a previously unaddressed source of sensitive biomarkers for early detection of cancer. The methods we have developed for chemoenzymatic synthesis of O-glycopeptides on microarrays may allow for broader mining of the entire......Autoantibodies to cancer antigens hold promise as biomarkers for early detection of cancer. Proteins that are aberrantly processed in cancer cells are likely to present autoantibody targets. The extracellular mucin MUC1 is overexpressed and aberrantly glycosylated in many cancers; thus, we...... evaluated whether autoantibodies generated to aberrant O-glycoforms of MUC1 might serve as sensitive diagnostic biomarkers for cancer. Using an antibody-based glycoprofiling ELISA assay, we documented that aberrant truncated glycoforms were not detected in sera of cancer patients. An O...

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

    Science.gov (United States)

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

    2015-08-21

    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.

  8. Current and future trends in biomarker discovery and development of companion diagnostics for arthritis.

    Science.gov (United States)

    Gibson, David S; Bustard, Michael J; McGeough, Cathy M; Murray, Helena A; Crockard, Martin A; McDowell, Andrew; Blayney, Jayne K; Gardiner, Philip V; Bjourson, Anthony J

    2015-02-01

    Musculoskeletal diseases such as rheumatoid arthritis are complex multifactorial disorders that are chronic in nature and debilitating for patients. A number of drug families are available to clinicians to manage these disorders but few tests exist to target these to the most responsive patients. As a consequence, drug failure and switching to drugs with alternate modes of action is common. In parallel, a limited number of laboratory tests are available which measure biological indicators or 'biomarkers' of disease activity, autoimmune status, or joint damage. There is a growing awareness that assimilating the fields of drug selection and diagnostic tests into 'companion diagnostics' could greatly advance disease management and improve outcomes for patients. This review aims to highlight: the current applications of biomarkers in rheumatology with particular focus on companion diagnostics; developments in the fields of proteomics, genomics, microbiomics, imaging and bioinformatics and how integration of these technologies into clinical practice could support therapeutic decisions.

  9. Multimodal lung cancer screening using the ITALUNG biomarker panel and low dose computed tomography. Results of the ITALUNG biomarker study.

    Science.gov (United States)

    Carozzi, Francesca Maria; Bisanzi, Simonetta; Carrozzi, Laura; Falaschi, Fabio; Lopes Pegna, Andrea; Mascalchi, Mario; Picozzi, Giulia; Peluso, Marco; Sani, Cristina; Greco, Luana; Ocello, Cristina; Paci, Eugenio

    2017-07-01

    Asymptomatic high-risk subjects, randomized in the intervention arm of the ITALUNG trial (1,406 screened for lung cancer), were enrolled for the ITALUNG biomarker study (n = 1,356), in which samples of blood and sputum were analyzed for plasma DNA quantification (cut off 5 ng/ml), loss of heterozygosity and microsatellite instability. The ITALUNG biomarker panel (IBP) was considered positive if at least one of the two biomarkers included in the panel was positive. Subjects with and without lung cancer diagnosis at the end of the screening cycle with LDCT (n = 517) were evaluated. Out of 18 baseline screen detected lung cancer cases, 17 were IBP positive (94%). Repeat screen-detected lung cancer cases were 18 and 12 of them positive at baseline IBP test (66%). Interval cancer cases (2-years) and biomarker tests after a suspect Non Calcific Nodule follow-up were investigated. The single test versus multimodal screening measures of accuracy were compared in a simulation within the screened ITALUNG intervention arm, considering screen-detected and interval cancer cases. Sensitivity was 90% at baseline screening. Specificity was 71 and 61% for LDCT and IBP as baseline single test, and improved at 89% with multimodal, combined screening. The positive predictive value was 4.3% for LDCT at baseline and 10.6% for multimodal screening. Multimodal screening could improve the screening efficiency at baseline and strategies for future implementation are discussed. If IBP was used as primary screening test, the LDCT burden might decrease of about 60%. © 2017 UICC.

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

    Science.gov (United States)

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

    2017-11-15

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

  11. Advances in epigenetic biomarker research in colorectal cancer

    National Research Council Canada - National Science Library

    Xi Wang Ye-Ye Kuang Xiao-Tong Hu

    2014-01-01

    ... making.Since there exists a need to find new biomarkers to improve diagnosis of CRC,the research on epigenetic biomarkers for molecular diagnostics encourages the translation of this field from the bench to clinical...

  12. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery

    NARCIS (Netherlands)

    Merchant, M.L.; Rood, I.M.; Deegens, J.K.J.; Klein, J.B.

    2017-01-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies.

  13. Chromosome 1q21.3 amplification is a trackable biomarker and actionable target for breast cancer recurrence.

    Science.gov (United States)

    Goh, Jian Yuan; Feng, Min; Wang, Wenyu; Oguz, Gokce; Yatim, Siti Maryam J M; Lee, Puay Leng; Bao, Yi; Lim, Tse Hui; Wang, Panpan; Tam, Wai Leong; Kodahl, Annette R; Lyng, Maria B; Sarma, Suman; Lin, Selena Y; Lezhava, Alexander; Yap, Yoon Sim; Lim, Alvin S T; Hoon, Dave S B; Ditzel, Henrik J; Lee, Soo Chin; Tan, Ern Yu; Yu, Qiang

    2017-11-01

    Tumor recurrence remains the main reason for breast cancer-associated mortality, and there are unmet clinical demands for the discovery of new biomarkers and development of treatment solutions to benefit patients with breast cancer at high risk of recurrence. Here we report the identification of chromosomal copy-number amplification at 1q21.3 that is enriched in subpopulations of breast cancer cells bearing characteristics of tumor-initiating cells (TICs) and that strongly associates with breast cancer recurrence. Amplification is present in ∼10-30% of primary tumors but in more than 70% of recurrent tumors, regardless of breast cancer subtype. Detection of amplification in cell-free DNA (cfDNA) from blood is strongly associated with early relapse in patients with breast cancer and could also be used to track the emergence of tumor resistance to chemotherapy. We further show that 1q21.3-encoded S100 calcium-binding protein (S100A) family members, mainly S100A7, S100A8, and S100A9 (S100A7/8/9), and IL-1 receptor-associated kinase 1 (IRAK1) establish a reciprocal feedback loop driving tumorsphere growth. Notably, this functional circuitry can be disrupted by the small-molecule kinase inhibitor pacritinib, leading to preferential impairment of the growth of 1q21.3-amplified breast tumors. Our study uncovers the 1q21.3-directed S100A7/8/9-IRAK1 feedback loop as a crucial component of breast cancer recurrence, serving as both a trackable biomarker and an actionable therapeutic target for breast cancer.

  14. 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

    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...

  15. Exosomal proteins as prognostic biomarkers in non-small cell lung cancer

    DEFF Research Database (Denmark)

    Paulsen, Birgitte Sandfeld; Aggerholm-Pedersen, N; Bæk, R

    2016-01-01

    BACKGROUND: Use of exosomes as biomarkers in non-small cell lung cancer (NSCLC) is an intriguing approach in the liquid-biopsy era. Exosomes are nano-sized vesicles with membrane-bound proteins that reflect their originating cell. Prognostic biomarkers are needed to improve patient selection...

  16. Nutrition and biomarkers in psychiatry : research on micronutrient deficiencies in schizophrenia, the role of the intestine in the hyperserotonemia of autism, and a method for non-hypothesis driven discovery of biomarkers in urine

    NARCIS (Netherlands)

    Kemperman, Ramses Franciscus Jacobus

    2007-01-01

    This thesis describes the study of markers of nutrition and intestinal motility in mental disorders with a focus on schizophrenia and autism, and the development, evaluation and application of a biomarker discovery method for urine. The aim of the thesis is to investigate the role of long-chain

  17. Tumor subtype-specific cancer-testis antigens as potential biomarkers and immunotherapeutic targets for cancers.

    Science.gov (United States)

    Yao, Jun; Caballero, Otavia L; Yung, W K Alfred; Weinstein, John N; Riggins, Gregory J; Strausberg, Robert L; Zhao, Qi

    2014-04-01

    Cancer-testis (CT) antigens are potential targets for cancer immunotherapy because of their restricted expression in immune-privileged germ cells and various malignancies. Current application of CT-based immunotherapy has been focused on CT expression-rich tumors such as melanoma and lung cancers. In this study, we surveyed CT expression using The Cancer Genome Atlas (TCGA) datasets for ten common cancer types. We show that CT expression is specific and enriched within certain cancer molecular subtypes. For example, HORMAD1, CXorf61, ACTL8, and PRAME are highly enriched in the basal subtype of breast cancer; MAGE and CSAG are most frequently activated in the magnoid subtype of lung adenocarcinoma; and PRAME is highly upregulated in the ccB subtype of clear cell renal cell carcinoma. Analysis of CT gene expression and DNA methylation indicates that some CTs are regulated epigenetically, whereas others are controlled primarily by tissue- and subtype-specific transcription factors. Our results suggest that although for some CT expression is associated with patient outcome, not many are independent prognostic markers. Thus, CTs with shared expression pattern are heterogeneous molecules with distinct activation modes and functional properties in different cancers and cancer subtypes. These data suggest a cancer subtype-orientated application of CT antigen as biomarkers and immunotherapeutic targets.

  18. Plasma Biomarker Profiles Differ Depending on Breast Cancer Subtype but RANTES is Consistently Increased

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Rachel M.; Daly, Don S.; Tan, Ruimin; Marks, Jeffrey R.; Zangar, Richard C.

    2011-07-01

    Background: Current biomarkers for breast cancer have little potential for detection. We determined if breast cancer subtypes influence circulating protein biomarkers. Methods: A sandwich-ELISA microarray platform was used to evaluate 23 candidate biomarkers in plasma samples that were obtained from subjects with either benign breast disease or invasive breast cancer. All plasma samples were collected at the time of biopsy, after a referral due to a suspicious screen (e.g., mammography). Cancer samples were evaluated based on breast cancer subtypes, as defined by the HER2 and estrogen receptor statuses. Results: Ten proteins were statistically altered in at least one breast cancer subtype, including four epidermal growth factor receptor ligands, two matrix metalloproteases, two cytokines, and two angiogenic factors. Only one cytokine, RANTES, was significantly increased (P<0.01 for each analysis) in all four subtypes, with areas under receiver operating characteristic curves (AUC) that ranged from 0.76 to 0.82, depending on cancer subtype. The best AUC values were observed for analyses that combined data from multiple biomarkers, with values ranging from 0.70 to 0.99, depending on the cancer subtype. Although the results for RANTES are consistent with previous publications, the multi-assay results need to be validated in independent sample sets. Conclusions: Different breast cancer subtypes produce distinct biomarker profiles, and circulating protein biomarkers have potential to differentiate between true and false positive screens for breast cancer. Impact: Subtype-specific biomarker panels may be useful for detecting breast cancer or as an adjunct assay to improve the accuracy of current screening methods.

  19. 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.

  20. Molecular Biomarkers of Colorectal Cancer: A Review of Published Articles From Iran

    Directory of Open Access Journals (Sweden)

    Geramizadeh

    2015-10-01

    Full Text Available Context Colorectal cancer is one of the most common cancers worldwide (the third most common cancer in the world and is especially more common in Western countries; however, its incidence has been increased significantly during the last few years in Eastern countries such as Iran and considered as one of the five common cancers in this country. According to molecular pathways, numerous biomarkers have been identified for colorectal cancers which help patients’ management. Evidence aquisition In this study, we tried to review published articles about the molecular biomarkers of colorectal cancer from Iran. We searched medical databases such as google scholar, Scopus, PubMed, Magiran, SID and Iran Medex for keywords of “colon cancer, KRAS, BRAF, mismatch repair gene, Microsatellite instability, molecular genetics, molecular pathogenesis, biomarker and Iran” to find studies published about colorectal cancers from Iran regarding molecular biomarkers. Conclusion This study showed that molecular biomarkers in colorectal cancer of Iranian patients are not so different from Western population.

  1. High-Resolution Taxonomic Profiling of the Subgingival Microbiome for Biomarker Discovery and Periodontitis Diagnosis

    Science.gov (United States)

    Szafranski, Szymon P.; Wos-Oxley, Melissa L.; Vilchez-Vargas, Ramiro; Jáuregui, Ruy; Plumeier, Iris; Klawonn, Frank; Tomasch, Jürgen; Meisinger, Christa; Kühnisch, Jan; Sztajer, Helena; Pieper, Dietmar H.

    2014-01-01

    The oral microbiome plays a key role for caries, periodontitis, and systemic diseases. A method for rapid, high-resolution, robust taxonomic profiling of subgingival bacterial communities for early detection of periodontitis biomarkers would therefore be a useful tool for individualized medicine. Here, we used Illumina sequencing of the V1-V2 and V5-V6 hypervariable regions of the 16S rRNA gene. A sample stratification pipeline was developed in a pilot study of 19 individuals, 9 of whom had been diagnosed with chronic periodontitis. Five hundred twenty-three operational taxonomic units (OTUs) were obtained from the V1-V2 region and 432 from the V5-V6 region. Key periodontal pathogens like Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia could be identified at the species level with both primer sets. Principal coordinate analysis identified two outliers that were consistently independent of the hypervariable region and method of DNA extraction used. The linear discriminant analysis (LDA) effect size algorithm (LEfSe) identified 80 OTU-level biomarkers of periodontitis and 17 of health. Health- and periodontitis-related clusters of OTUs were identified using a connectivity analysis, and the results confirmed previous studies with several thousands of samples. A machine learning algorithm was developed which was trained on all but one sample and then predicted the diagnosis of the left-out sample (jackknife method). Using a combination of the 10 best biomarkers, 15 of 17 samples were correctly diagnosed. Training the algorithm on time-resolved community profiles might provide a highly sensitive tool to detect the onset of periodontitis. PMID:25452281

  2. 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

  3. Tropomyosin-1, A Putative Tumor-Suppressor and a Biomarker of Human Breast Cancer

    Science.gov (United States)

    2004-10-01

    cDNA. Lobular carcinoma - 2 A polyclonal pan-TM antibody that recognizes multiple TM Phyllodes tumor - 1 Not determined from the initial pathology...AD Award Number: DAMD17-98-1-8162 TITLE: Tropomyosin-1, A Putative Tumor -Suppressor and a Biomarker of Human Breast Cancer PRINCIPAL INVESTIGATOR...4. TITLE AND SUBTITLE 5. FUNDING NUMBERS Tropomyosin-l, A Putative Tumor -Suppressor and a Biomarker DAMD17-98-1-8162 of Human Breast Cancer 6. A UTHOR

  4. Incorporation of Novel MRI and Biomarkers into Prostate Cancer Active Surveillance Risk Assessment

    Science.gov (United States)

    2017-09-01

    AWARD NUMBER: W81XWH-15-1-0441 TITLE: Incorporation of Novel MRI and Biomarkers into Prostate Cancer Active Surveillance Risk Assessment...REPORT TYPE Annual 3. DATES COVERED 09/01/2016 – 08/31/2017 4. TITLE AND SUBTITLE Incorporation of Novel MRI and Biomarkers into Prostate Cancer Active...have engaged my mentors, enrolled in courses and conferences to augment my knowledge of translational science and MRI imaging, and I have developed and

  5. The Thoc1 Ribonucleoprotein as a Novel Biomarker for Prostate Cancer Treatment Assignment

    Science.gov (United States)

    2017-10-01

    AWARD NUMBER: W81XWH-14-1-0475 TITLE: The Thoc1 Ribonucleoprotein as a Novel Biomarker for Prostate Cancer Treatment Assignment PRINCIPAL...provision of law , no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a currently...15Sept 2016 - 14Sep2017 4. TITLE AND SUBTITLE The Thoc1 Ribonucleoprotein as a Novel Biomarker for Prostate 5a. CONTRACT NUMBER Cancer Treatment

  6. Integrated Genomic Biomarkers to Identify Aggressive Disease in African Americans with Prostate Cancer

    Science.gov (United States)

    2016-09-01

    AWARD NUMBER: W81XWH-15-1-0395 TITLE: Integrated Genomic Biomarkers to Identify Aggressive Disease in African Americans with Prostate Cancer...2015- 31 Aug 2016 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Integrated Genomic Biomarkers to Identify Aggressive Disease In African Americans with...the copy number assay. We have also started a manuscript exploring the effectiveness of a commonly used clinicopathologic predictor of prostate cancer

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

    DEFF Research Database (Denmark)

    Mikkelsen, Jens D; Thomsen, Morten S; Hansen, Henrik H

    2010-01-01

    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......Schizophrenia is characterized by a diverse symptomatology that often includes positive, cognitive and negative symptoms. Current anti-schizophrenic drugs act at multiple receptors, but little is known about how each of these receptors contributes to their mechanisms of action. Screening of novel...

  8. 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.

  9. Epigenetic Biomarkers of Breast Cancer Risk: Across the Breast Cancer Prevention Continuum

    Science.gov (United States)

    McDonald, Jasmine A.; Wu, Hui Chen; Eng, Sybil; Santella, Regina M.

    2017-01-01

    Epigenetic biomarkers, such as DNA methylation, can increase cancer risk through altering gene expression. The Cancer Genome Atlas (TCGA) Network has demonstrated breast cancer-specific DNA methylation signatures. DNA methylation signatures measured at the time of diagnosis may prove important for treatment options and in predicting disease-free and overall survival (tertiary prevention). DNA methylation measurement in cell free DNA may also be useful in improving early detection by measuring tumor DNA released into the blood (secondary prevention). Most evidence evaluating the use of DNA methylation markers in tertiary and secondary prevention efforts for breast cancer comes from studies that are cross-sectional or retrospective with limited corresponding epidemiologic data, raising concerns about temporality. Few prospective studies exist that are large enough to address whether DNA methylation markers add to the prediction of tertiary and secondary outcomes over and beyond standard clinical measures. Determining the role of epigenetic biomarkers in primary prevention can help in identifying modifiable pathways for targeting interventions and reducing disease incidence. The potential is great for DNA methylation markers to improve cancer outcomes across the prevention continuum. Large, prospective epidemiological studies will provide essential evidence of the overall utility of adding these markers to primary prevention efforts, screening, and clinical care. PMID:26987530

  10. Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

    Science.gov (United States)

    Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

    2017-09-01

    Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

  11. Plasma peptide biomarker discovery for amyotrophic lateral sclerosis by MALDI-TOF mass spectrometry profiling.

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    Laurence Conraux

    Full Text Available The diagnostic of Amyotrophic lateral sclerosis (ALS remains based on clinical and neurophysiological observations. The actual delay between the onset of the symptoms and diagnosis is about 1 year, preventing early inclusion of patients into clinical trials and early care of the disease. Therefore, finding biomarkers with high sensitivity and specificity remains urgent. In our study, we looked for peptide biomarkers in plasma samples using reverse phase magnetic beads (C18 and C8 and MALDI-TOF mass spectrometry analysis. From a set of ALS patients (n=30 and healthy age-matched controls (n=30, C18- or C8-SVM-based models for ALS diagnostic were constructed on the base of the minimum of the most discriminant peaks. These two SVM-based models end up in excellent separations between the 2 groups of patients (recognition capability overall classes > 97% and classify blinded samples (10 ALS and 10 healthy age-matched controls with very high sensitivities and specificities (>90%. Some of these discriminant peaks have been identified by Mass Spectrometry (MS analyses and correspond to (or are fragments of major plasma proteins, partly linked to the blood coagulation.

  12. A review on oral cancer biomarkers: Understanding the past and learning from the present.

    Science.gov (United States)

    Santosh, Arvind Babu Rajendra; Jones, Thaon; Harvey, John

    2016-01-01

    Biomarkers are broadly classified as genomic, proteomic, or metabolomic. Molecular biology and oncology research studies on oral cancer biomarkers focus on identifying key biological molecules or markers that could be linked to cancer development, risk assessment, screening, recurrence prediction, indicating prognosis, indicating invasion/metastasis and monitoring therapeutic responses of cancer. Cluster of differentiation factor 34 is a salivary biomarker that can identify recurrence potential of oral squamous cell carcinoma (OSCC). Integrin α3 and integrin β4 are genomic biomarkers that are helpful in estimating the risk of regional and hematogenous dissemination of malignant oral squamous cells. Other examples are vascular endothelial growth factor, B-cell lymphoma-2, claudin 4, yes-associated protein 1 and MET proto-oncogene, and receptor tyrosine kinase, which are genomic biomarkers that are used to predict radio-resistance in OSCC tissue. The present article reviews the clinical application, methodologies and steps in developing candidate biomarkers, protocols in reporting, evaluating candidate biomarkers, and challenges in biomarker research with a focus OSCC.

  13. Potential Biomarkers of Fat Loss as a Feature of Cancer Cachexia.

    Science.gov (United States)

    Ebadi, Maryam; Mazurak, Vera C

    2015-01-01

    Fat loss is associated with shorter survival and reduced quality of life in cancer patients. Effective intervention for fat loss in cachexia requires identification of the condition using prognostic biomarkers for early detection and prevention of further depletion. No biomarkers of fat mass alterations have been defined for application to the neoplastic state. Several inflammatory cytokines have been implicated in mediating fat loss associated with cachexia; however, plasma levels may not relate to adipose atrophy. Zinc-α2-glycoprotein may be a local catabolic mediator within adipose tissue rather than serving as a plasma biomarker of fat loss. Plasma glycerol and leptin associate with adipose tissue atrophy and mass, respectively; however, no study has evaluated their potential as a prognostic biomarker of cachexia-associated fat loss. This review confirms the need for further studies to identify valid prognostic biomarkers to identify loss of fat based on changes in plasma levels of biomarkers.

  14. Potential Biomarkers of Fat Loss as a Feature of Cancer Cachexia

    Directory of Open Access Journals (Sweden)

    Maryam Ebadi

    2015-01-01

    Full Text Available Fat loss is associated with shorter survival and reduced quality of life in cancer patients. Effective intervention for fat loss in cachexia requires identification of the condition using prognostic biomarkers for early detection and prevention of further depletion. No biomarkers of fat mass alterations have been defined for application to the neoplastic state. Several inflammatory cytokines have been implicated in mediating fat loss associated with cachexia; however, plasma levels may not relate to adipose atrophy. Zinc-α2-glycoprotein may be a local catabolic mediator within adipose tissue rather than serving as a plasma biomarker of fat loss. Plasma glycerol and leptin associate with adipose tissue atrophy and mass, respectively; however, no study has evaluated their potential as a prognostic biomarker of cachexia-associated fat loss. This review confirms the need for further studies to identify valid prognostic biomarkers to identify loss of fat based on changes in plasma levels of biomarkers.

  15. DNA methylation biomarkers as diagnostic and prognostic tools in colorectal cancer.

    Science.gov (United States)

    Gyparaki, Melina-Theoni; Basdra, Efthimia K; Papavassiliou, Athanasios G

    2013-11-01

    Colorectal cancer (CRC) is the third most common type of cancer and is responsible for 9 % of cancer deaths in both men and women in the USA for 2013. It is a heterogenous disease, and its three classification types are microsatellite instability, chromosomal instability, and CpG island methylator phenotype. Biomarkers are molecules, which can be used as indicators of cancer. They have the potential to achieve great sensitivities and specificities in diagnosis and prognosis of CRC. DNA methylation biomarkers are epigenetic markers, more specifically genes that become silenced after aberrant methylation of their promoter in CRC. Some methylation biomarkers like SEPT9 (ColoVantage®) and vimentin (ColoSure(TM)) are already commercially available. Other blood and fecal-based biomarkers are currently under investigation and clinical studies so that they can be used in the near future. Biomarker panels are also currently being studied since they show great potential in diagnosis as they can combine robust biomarkers to achieve even greater sensitivities than single markers. Finally, methylation-sensitive microRNAs (miRNAs) are very promising markers, and their investigation as biomarkers, is only at primitive stage.

  16. “Omics”-Informed Drug and Biomarker Discovery: Opportunities, Challenges and Future Perspectives

    Directory of Open Access Journals (Sweden)

    Holly Matthews

    2016-09-01

    Full Text Available The pharmaceutical industry faces unsustainable program failure despite significant increases in investment. Dwindling discovery pipelines, rapidly expanding R&D budgets and increasing regulatory control, predict significant gaps in the future drug markets. The cumulative duration of discovery from concept to commercialisation is unacceptably lengthy, and adds to the deepening crisis. Existing animal models predicting clinical translations are simplistic, highly reductionist and, therefore, not fit for purpose. The catastrophic consequences of ever-increasing attrition rates are most likely to be felt in the developing world, where resistance acquisition by killer diseases like malaria, tuberculosis and HIV have paced far ahead of new drug discovery. The coming of age of Omics-based applications makes available a formidable technological resource to further expand our knowledge of the complexities of human disease. The standardisation, analysis and comprehensive collation of the “data-heavy” outputs of these sciences are indeed challenging. A renewed focus on increasing reproducibility by understanding inherent biological, methodological, technical and analytical variables is crucial if reliable and useful inferences with potential for translation are to be achieved. The individual Omics sciences—genomics, transcriptomics, proteomics and metabolomics—have the singular advantage of being complimentary for cross validation, and together could potentially enable a much-needed systems biology perspective of the perturbations underlying disease processes. If current adverse trends are to be reversed, it is imperative that a shift in the R&D focus from speed to quality is achieved. In this review, we discuss the potential implications of recent Omics-based advances for the drug development process.

  17. Free circulating DNA as a biomarker of colorectal cancer.

    Science.gov (United States)

    Cassinotti, Elisa; Boni, Luigi; Segato, Sergio; Rausei, Stefano; Marzorati, Alessandro; Rovera, Francesca; Dionigi, Gianlorenzo; David, Giulia; Mangano, Alberto; Sambucci, Daniele; Dionigi, Renzo

    2013-01-01

    The purpose of this study is to evaluate the sensitivity and specificity of free circulating DNA (FCDNA) as a biomarker in patients suffering from colorectal cancer (CRC), investigating both its prognostic value correlated with stage of disease and its potential role in early recurrence diagnosis. The quantification of plasma DNA was achieved through the use of real time quantitative polymerase chain reaction (PCR) amplification of the RNAse P gene. The study enrolled patients undergoing surgery for primary CRC, at different stages of disease; samples were collected before surgery and during follow-up examinations every 3 months after surgery. Data were statistically analyzed using Software Packages SPSS® for Windows. FCDNA was detectable in all pre-operative samples and the mean value was 47.8 ng/mL. FCDNA values increased progressively related to UICC stage of disease, although statistical significance was demonstrated only when comparing patients by pT stage. The analysis of postoperative samples showed a significant decrease of FCDNA quantity after radical surgery and in specific cases a rise preceding disease recurrence. This study shows that absolute quantification of FCDNA in CRC patients could have a prognostic value, being related to stage of disease, and could be used as potential tool for early detection of recurrences. Copyright © 2013 Elsevier Ltd and Surgical Associates Ltd. All rights reserved.

  18. Biomarkers and their use in cervical cancer chemoprevention.

    Science.gov (United States)

    Vlastos, Anne Thérèse; Schottenfeld, David; Follen, Michele

    2003-06-01

    Cervical cancer chemoprevention agents under study include diet and micronutrients (particularly beta-carotene, folate, and vitamins A, C, and E); medications such as retinoids (retinyl acetate gel, all-trans-retinoic acid, and 4-hydroxyphenylretinamide) that are chemically related to micronutrients; and other chemopreventives meant to affect the carcinogenic process at the cellular level, including such polyamine synthesis inhibitors as alpha-difluoromethylornithine. Agents become reasonable candidates for study when they have a biologic rationale, they are of low toxicity, and they can be taken for a long period of time. Since the human papillomavirus (HPV) is the major etiologic agent, the medication should show activity against HPV-positive preinvasive and invasive cell lines. The medication needs to be of low toxicity because it may be taken for long periods of time and less toxicity is tolerated in the precancerous setting. Until 1995, none of the studies used surrogate end point biomarkers (SEBs), relying instead on histologic and colposcopic regression as end points. All studies typically included subjects with cervical intraepithelial neoplasia. Conclusions to be drawn from these studies include the following: Though micronutrients are logical candidates for chemoprevention, they haven't worked consistently, and the reasons remain unclear. Furthermore, SEBs need to be validated in phase I trials. Finally, a better understanding of the role of HPV needs elucidation, including an understanding of the relationship of the medication to HPV status and of the immunobiology of HPV throughout the trial.

  19. Identification of potential biomarkers and drugs for papillary thyroid cancer based on gene expression profile analysis.

    Science.gov (United States)

    Qu, Ting; Li, Yan-Ping; Li, Xiao-Hong; Chen, Yan

    2016-12-01

    The present study aimed to systematically examine the molecular mechanisms of papillary thyroid cancer (PTC), and identify potential biomarkers and drugs for the treatment of PTC. Two microarray data sets (GSE3467 and GSE3678), containing 16 PTC samples and 16 paired normal samples, were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Analysis package. Subsequently, the common DEGs were screened for functional and pathway enrichment analysis using the Database for Annotation Visualization and Integrated Discovery. The representative interaction subnetwork was further derived using Molecular Complex Detection software. In addition, the potential drugs for the hub DEGs in the subnetwork were screened from DrugBank and the potential drug‑like ligands, which interacted with genes, were selected using MTiOpenScreen. A total of 167 common DEGs, including 77 upregulated and 90 downregulated DEGs, were screened. The common DEGs were associated with the functions of plasma membrane, extracellular matrix, response to steroid hormone stimulus and cell adhesion, and the pathways of tyrosine metabolism and cell adhesion molecules were significantly enriched. A total of eight common DEGs (MET, SERPINA1, LGALS3, FN1, TNFRSF11B, LAMB3 and COL13A1) were involved in the subnetwork. The two drugs, lanoteplase and ocriplasmin, and four drugs, β‑mercaptoethanol, recombinant α 1‑antitrypsin, PPL‑100 and API, were found for FN1 and SERPINA1, respectively. The common DEGs identified may be potential biomarkers for PCT. FN1 and SERPINA1 may be involved in PTC by regulating epithelial‑to‑mesenchymal transition and responding to steroid hormone stimuli, respectively. Ocriplasmin, β‑mercaptoethanol and recombinant α 1‑antitrypsin may be potential drugs for the treatment of PTC.

  20. Proteomics and metabolomics for mechanistic insights and biomarker discovery in cardiovascular disease.

    Science.gov (United States)

    Barallobre-Barreiro, Javier; Chung, Yuen-Li; Mayr, Manuel

    2013-08-01

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of cardiovascular diseases. The unbiased assessment of pathophysiological processes without a priori assumptions complements other molecular biology techniques that are currently used in a reductionist approach. In this review, we highlight some of the "omics" methods used to assess protein and metabolite changes in cardiovascular disease. A discrete biological function is very rarely attributed to a single molecule; more often it is the combined input of many proteins. In contrast to the reductionist approach, in which molecules are studied individually, "omics" platforms allow the study of more complex interactions in biological systems. Combining proteomics and metabolomics to quantify changes in metabolites and their corresponding enzymes will advance our understanding of pathophysiological mechanisms and aid the identification of novel biomarkers for cardiovascular disease. Copyright © 2013 Sociedad Española de Cardiología. Published by Elsevier Espana. All rights reserved.

  1. Discovery and Validation of Biomarkers to Guide Clinical Management of Pneumonia in African Children

    Science.gov (United States)

    Huang, Honglei; Ideh, Readon C.; Gitau, Evelyn; Thézénas, Marie L.; Jallow, Muminatou; Ebruke, Bernard; Chimah, Osaretin; Oluwalana, Claire; Karanja, Henri; Mackenzie, Grant; Adegbola, Richard A.; Kwiatkowski, Dominic; Kessler, Benedikt M.; Berkley, James A.; Howie, Stephen R. C.; Casals-Pascual, Climent

    2014-01-01

    Background. Pneumonia is the leading cause of death in children globally. Clinical algorithms remain suboptimal for distinguishing severe pneumonia from other causes of respiratory distress such as malaria or distinguishing bacterial pneumonia and pneumonia from others causes, such as viruses. Molecular tools could improve diagnosis and management. Methods. We conducted a mass spectrometry–based proteomic study to identify and validate markers of severity in 390 Gambian children with pneumonia (n = 204) and age-, sex-, and neighborhood-matched controls (n = 186). Independent validation was conducted in 293 Kenyan children with respiratory distress (238 with pneumonia, 41 with Plasmodium falciparum malaria, and 14 with both). Predictive value was estimated by the area under the receiver operating characteristic curve (AUC). Results. Lipocalin 2 (Lpc-2) was the best protein biomarker of severe pneumonia (AUC, 0.71 [95% confidence interval, .64–.79]) and highly predictive of bacteremia (78% [64%–92%]), pneumococcal bacteremia (84% [71%–98%]), and “probable bacterial etiology” (91% [84%–98%]). These results were validated in Kenyan children with severe malaria and respiratory distress who also met the World Health Organization definition of pneumonia. The combination of Lpc-2 and haptoglobin distinguished bacterial versus malaria origin of respiratory distress with high sensitivity and specificity in Gambian children (AUC, 99% [95% confidence interval, 99%–100%]) and Kenyan children (82% [74%–91%]). Conclusions. Lpc-2 and haptoglobin can help discriminate the etiology of clinically defined pneumonia and could be used to improve clinical management. These biomarkers should be further evaluated in prospective clinical studies. PMID:24696240

  2. [Clinical validation of multiple biomarkers suspension array technology for ovarian cancer].

    Science.gov (United States)

    Zhao, B B; Yang, Z J; Wang, Q; Pan, Z M; Zhang, W; Li, L

    2017-01-25

    Objective: To investigates the diagnostic value of combined detection serum CCL18, CXCL1 antigen, C1D, TM4SF1, FXR1, TIZ IgG autoantibody by suspension array for ovarian cancer. Methods: Suspension array was used to detect CCL18, CXCL1 antigen, C1D, TM4SF1, FXR1, TIZ IgG autoantibody in 120 cases of healthy women, 204 cases of patients with benign pelvic tumors, 119 cases of pelvic malignant tumor patients, and 40 cases with breast cancer, lung cancer oroliver cancer, respectively. Constructed diagnosis model of combined detection six biomarkers for diagnosis of ovarian malignant tumor. Constructed diagnosis model of combined detection autoantibodies to diagnose epithelial ovarian cancer. Analysed the value of detecting six biomarkers for diagnosis of ovarian malignant tumor and detecting autoantibodies for diagnosis of epithelial ovarian cancer. Analysed diagnostic value of detecting six biomarkers to diagnose stage Ⅰ and Ⅱepithelial ovarian cancer. Compared diagnostic value of detecting six biomarkers in diagnosis of tissue types and pathologic grading with that of CA(125). Results: Model of combined detecting six biomarkers to diagnose ovarian malignant tumor was logit (P) =-11.151+0.008×C1D+0.011×TM4SF1+0.011×TIZ-0.008×FXR1+0.021×CCL18+0.200×CXCL1. Model of combined detection autoantibodies to diagnose epithelial ovarian cancer was logit (P) =-5.137+0.013×C1D+0.014×TM4SF1+0.060×TIZ-0.060×FXR1. Sensitivity and specificity of detecting six biomarker to diagnose ovarian malignant tumor was 90.6% and 98.7%. Sensitivity and specificity of detecting autoantibodies to diagnose epithelial ovarian cancer was 75.8% and 96.7%. Combined detection for six biomarkers to diagnose serous and mucinous ovarian cancer was statistically no better than those of CA(125) (P=0.196 and P=0.602, respectively); there was significantly difference in diagnosis of ovarian cancer (P=0.023), and there was no significantly difference in diagnosis of different pathological grading

  3. 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.

  4. Evaluation of Multi-Protein Immunoaffinity Subtraction for Plasma Proteomics and Candidate Biomarker Discovery Using Mass Spectrometry

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    Liu, Tao; Qian, Weijun; Mottaz, Heather M.; Gritsenko, Marina A.; Norbeck, Angela D.; Moore, Ronald J.; Purvine, Samuel O.; Camp, David G.; Smith, Richard D.

    2006-11-01

    The detection of low-abundance protein disease biomarkers from human blood poses significant challenges due to the high dynamic range of protein concentrations that span more than 10 orders of magnitude, as well as the extreme complexity of the serum/plasma proteome. Therefore, experimental strategies that include the removal of high-abundance proteins have been increasingly utilized in proteomic studies of serum, plasma, and other body fluids to enhance detection of low-abundance proteins and achieve broader proteome coverage. However, both the specificity and reproducibility of the high-abundance protein depletion process represent common concerns. Here, we report a detailed evaluation of the performance of two commercially available immunoaffinity subtraction systems commonly used in human serum/plasma proteome characterization by high resolution LC-MS/MS. One system uses mammalian IgG antibodies to remove six of the most abundant plasma proteins, and the other uses chicken immunoglobulin yolk (IgY) antibodies to remove twelve of the most abundant plasma proteins. Plasma samples were repeatedly processed using these two systems, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. Removal of target proteins by both immunoaffinity subtraction systems proved reproducible and efficient. Nontarget proteins, including spiked protein standards, were also observed to bind to the columns, but in a fairly reproducible manner. The results suggest that these multi-protein immunoaffinity subtraction systems are both highly effective and reproducible for removing high-abundance proteins and therefore, can be readily integrated into quantitative strategies to enhance detection of low-abundance proteins in biomarker discovery studies.

  5. Pre-analytical factors in clinical proteomics investigations: impact of ex vivo protein modifications for multiple sclerosis biomarker discovery.

    Science.gov (United States)

    Pieragostino, Damiana; Petrucci, Francesca; Del Boccio, Piero; Mantini, Dante; Lugaresi, Alessandra; Tiberio, Sara; Onofrj, Marco; Gambi, Domenico; Sacchetta, Paolo; Di Ilio, Carmine; Federici, Giorgio; Urbani, Andrea

    2010-01-03

    Serum proteome investigations have raised an incredible interest in the research of novel molecular biomarker, nevertheless few of the proposed evidences have been translated to the clinical practice. One of the limiting factors has been the lack of generally accepted guidelines for clinical proteomics studies and the lack of a robust analytical and pre-analytical ground for the proposed classification models. Pre-analytical issues may results in a deep impact for biomarker discovery campaign. In this study we present a systematic evaluation of sample storage and sampling conditions for clinical proteomics investigations. We have developed and validated a linear MALDI-TOF-MS protein profiling method to explore the low protein molecular weight region (5-20 kDa) of serum samples. Data normalization and processing was performed using optimise peak detection routine (LIMPIC) able to describe each group under investigation. Data were acquired either from healthy volunteers and from multiple sclerosis patients in order to highlight ex vivo protein profile alteration related to different physio-pathological conditions. Our data showed critical conditions for serum protein profiles depending on storage times and temperatures: 23 degrees C, 4 degrees C, -20 degrees C and -80 degrees C. We demonstrated that upon a -20 degrees C short term storage, characteristic degradation profiles are associated with different clinical groups. Protein signals were further identified after preparative HPLC separation by peptide sequencing on a nanoLC-Q-TOF TANDEM mass spectrometer. Apolipoprotein A-IV and complement C3 protein fragments, transthyretin and the oxidized isoforms in different apolipoprotein species represent the major molecular features of such a degradation pattern. (c) 2009 Elsevier B.V. All rights reserved.

  6. Detection of cancer biomarkers in serum using a hybrid mechanical and optoplasmonic nanosensor

    Science.gov (United States)

    Kosaka, P. M.; Pini, V.; Ruz, J. J.; da Silva, R. A.; González, M. U.; Ramos, D.; Calleja, M.; Tamayo, J.

    2014-12-01

    Blood contains a range of protein biomarkers that could be used in the early detection of disease. To achieve this, however, requires sensors capable of detecting (with high reproducibility) biomarkers at concentrations one million times lower than the concentration of the other blood proteins. Here, we show that a sandwich assay that combines mechanical and optoplasmonic transduction can detect cancer biomarkers in serum at ultralow concentrations. A biomarker is first recognized by a surface-anchored antibody and then by an antibody in solution that identifies a free region of the captured biomarker. This second antibody is tethered to a gold nanoparticle that acts as a mass and plasmonic label; the two signatures are detected by means of a silicon cantilever that serves as a mechanical resonator for ‘weighing’ the mass of the captured nanoparticles and as an optical cavity that boosts the plasmonic signal from the nanoparticles. The capabilities of the approach are illustrated with two cancer biomarkers: the carcinoembryonic antigen and the prostate specific antigen, which are currently in clinical use for the diagnosis, monitoring and prognosis of colon and prostate cancer, respectively. A detection limit of 1 × 10-16 g ml-1 in serum is achieved with both biomarkers, which is at least seven orders of magnitude lower than that achieved in routine clinical practice. Moreover, the rate of false positives and false negatives at this concentration is extremely low, ˜10-4.

  7. Lab-on-a-Chip Platforms for Detection of Cardiovascular Disease and Cancer Biomarkers.

    Science.gov (United States)

    Wu, Jiandong; Dong, Meili; Santos, Susy; Rigatto, Claudio; Liu, Yong; Lin, Francis

    2017-12-17

    Cardiovascular disease (CVD) and cancer are two leading causes of death worldwide. CVD and cancer share risk factors such as obesity and diabetes mellitus and have common diagnostic biomarkers such as interleukin-6 and C-reactive protein. Thus, timely and accurate diagnosis of these two correlated diseases is of high interest to both the research and healthcare communities. Most conventional methods for CVD and cancer biomarker detection such as microwell plate-based immunoassay and polymerase chain reaction often suffer from high costs, low test speeds, and complicated procedures. Recently, lab-on-a-chip (LoC)-based platforms have been increasingly developed for CVD and cancer biomarker sensing and analysis using various molecular and cell-based diagnostic biomarkers. These new platforms not only enable better sample preparation, chemical manipulation and reaction, high-throughput and portability, but also provide attractive features such as label-free detection and improved sensitivity due to the integration of various novel detection techniques. These features effectively improve the diagnostic test speed and simplify the detection procedure. In addition, microfluidic cell assays and organ-on-chip models offer new potential approaches for CVD and cancer diagnosis. Here we provide a mini-review focusing on recent development of LoC-based methods for CVD and cancer diagnostic biomarker measurements, and our perspectives of the challenges, opportunities and future directions.

  8. cMRI-BED: A novel informatics framework for cardiac MRI biomarker extraction and discovery applied to pediatric cardiomyopathy classification

    Science.gov (United States)

    2015-01-01

    Background Pediatric cardiomyopathies are a rare, yet heterogeneous group of pathologies of the myocardium that are routinely examined clinically using Cardiovascular Magnetic Resonance Imaging (cMRI). This gold standard powerful non-invasive tool yields high resolution temporal images that characterize myocardial tissue. The complexities associated with the annotation of images and extraction of markers, necessitate the development of efficient workflows to acquire, manage and transform this data into actionable knowledge for patient care to reduce mortality and morbidity. Methods We develop and test a novel informatics framework called cMRI-BED for biomarker extraction and discovery from such complex pediatric cMRI data that includes the use of a suite of tools for image processing, marker extraction and predictive modeling. We applied our workflow to obtain and analyze a dataset of 83 de-identified cases and controls containing cMRI-derived biomarkers for classifying positive versus negative findings of cardiomyopathy in children. Bayesian rule learning (BRL) methods were applied to derive understandable models in the form of propositional rules with posterior probabilities pertaining to their validity. Popular machine learning methods in the WEKA data mining toolkit were applied using default parameters to assess cross-validation performance of this dataset using accuracy and percentage area under ROC curve (AUC) measures. Results The best 10-fold cross validation predictive performance obtained on this cMRI-derived biomarker dataset was 80.72% accuracy and 79.6% AUC by a BRL decision tree model, which is promising from this type of rare data. Moreover, we were able to verify that mycocardial delayed enhancement (MDE) status, which is known to be an important qualitative factor in the classification of cardiomyopathies, is picked up by our rule models as an important variable for prediction. Conclusions Preliminary results show the feasibility of our framework

  9. microRNA Biomarkers to Generate Sensitivity to Abiraterone-Resistant Prostate Cancer

    Science.gov (United States)

    2017-09-01

    AWARD NUMBER: W81XWH-15-1-0353 TITLE: microRNA Biomarkers to Generate Sensitivity to Abiraterone-Resistant Prostate Cancer PRINCIPAL...TITLE AND SUBTITLE microRNA Biomarkers to Generate Sensitivity to Abiraterone- Resistant Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER...15 8. Special Reporting Requirements……………………………………16 9. Appendices……………………………………………………………17 1. INTRODUCTION: Prostate cancer (PCa) is the most

  10. Exposure of mayfly Ephemera orientalis (Ephemeroptera) eggs to heavy metals and discovery of biomarkers.

    Science.gov (United States)

    Mo, Hyoung-ho; Lee, Sung-Eun; Son, Jino; Hwang, Jeong Mi; Bae, Yeon Jae; Cho, Kijong

    2013-11-01

    The objective of this study was to assess acute toxicity of heavy metals in eggs of mayfly Ephemera orientalis McLachlan, and to elucidate relationships between heavy metal toxicity and protein expression patterns determined using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Acute toxicity analysis was conducted using five heavy metals (cadmium, chromium, copper, lead, and mercury), and the toxicity endpoint was established from the egg hatching rate during a 14-day exposure period. Median hatching toxicity (HC₅₀) values were determined for each heavy metal, and the most toxic heavy metal was found to be mercury (0.11 mg/L), followed by copper (0.32 mg/L) and lead (4.39 mg/L). E. orientalis eggs were highly tolerant to cadmium and chromium (>120 mg/L). Proteinchip array analysis using a strong anion exchange proteinchip (Q10) in conjunction with SELDI-TOF-MS was used to assess the protein expression patterns after exposure to heavy metals at the EHC10 (prohibiting hatching concentration to 10% eggs), except for cadmium and chromium, which were used at concentrations of 1, 10, and 100mg/L. Three novel biomarker candidate proteins, i.e., 4269, 4283, and 4623 m/z, were identified for the detection of heavy metal toxicity in aquatic ecosystems at the level of HC₁₀ in E. orientalis eggs. SELDI-TOF MS analysis for detecting differential expression of proteins was found to be more effective than Q10 proteinchip separation in the mayfly eggs. Copyright © 2013 Elsevier B.V. All rights reserved.

  11. Isolation and characterization of urinary extracellular vesicles: implications for biomarker discovery.

    Science.gov (United States)

    Merchant, Michael L; Rood, Ilse M; Deegens, Jeroen K J; Klein, Jon B

    2017-12-01

    Urine is a valuable diagnostic medium and, with the discovery of urinary extracellular vesicles, is viewed as a dynamic bioactive fluid. Extracellular vesicles are lipid-enclosed structures that can be classified into three categories: exosomes, microvesicles (or ectosomes) and apoptotic bodies. This classification is based on the mechanisms by which membrane vesicles are formed: fusion of multivesicular bodies with the plasma membranes (exosomes), budding of vesicles directly from the plasma membrane (microvesicles) or those shed from dying cells (apoptotic bodies). During their formation, urinary extracellular vesicles incorporate various cell-specific components (proteins, lipids and nucleic acids) that can be transferred to target cells. The rigour needed for comparative studies has fueled the search for optimal approaches for their isolation, purification, and characterization. RNA, the newest extracellular vesicle component to be discovered, has received substantial attention as an extracellular vesicle therapeutic, and compelling evidence suggests that ex vivo manipulation of microRNA composition may have uses in the treatment of kidney disorders. The results of these studies are building the case that urinary extracellular vesicles act as mediators of renal pathophysiology. As the field of extracellular vesicle studies is burgeoning, this Review focuses on primary data obtained from studies of human urine rather than on data from studies of laboratory animals or cultured immortalized cells.

  12. MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

    Science.gov (United States)

    Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology.

  13. Adiposity, mediating biomarkers and risk of colon cancer in the european prospective investigation into cancer and nutrition study

    NARCIS (Netherlands)

    Aleksandrova, K.; Drogan, D.; Boeing, H.; Jenab, M.; Bueno de Mesquita, H.B.; Duijnhoven, van F.J.B.

    2014-01-01

    Adiposity is a risk factor for colon cancer, but underlying mechanisms are not well understood. We evaluated the extent to which 11 biomarkers with inflammatory and metabolic actions mediate the association of adiposity measures, waist circumference (WC) and body mass index (BMI), with colon cancer

  14. MicroRNA-196a Is a Putative Diagnostic Biomarker and Therapeutic Target for Laryngeal Cancer

    Science.gov (United States)

    Saito, Koichiro; Inagaki, Koji; Kamimoto, Takahiro; Ito, Yoko; Sugita, Toshiaki; Nakajo, Satoko; Hirasawa, Akira; Iwamaru, Arifumi; Ishikura, Takashi; Hanaoka, Hideki; Okubo, Keisuke; Onozaki, Tokio; Zama, Takeru

    2013-01-01

    Background MicroRNA (miRNA) is an emerging subclass of small non-coding RNAs that regulates gene expression and has a pivotal role for many physiological processes including cancer development. Recent reports revealed the role of miRNAs as ideal biomarkers and therapeutic targets due to their tissue- or disease-specific nature. Head and neck cancer (HNC) is a major cause of cancer-related mortality and morbidity, and laryngeal cancer has the highest incidence in it. However, the molecular mechanisms involved in laryngeal cancer development remain to be known and highly sensitive biomarkers and novel promising therapy is necessary. Methodology/Principal Findings To explore laryngeal cancer-specific miRNAs, RNA from 5 laryngeal surgical specimens including cancer and non-cancer tissues were hybridized to microarray carrying 723 human miRNAs. The resultant differentially expressed miRNAs were further tested by using quantitative real time PCR (qRT-PCR) on 43 laryngeal tissue samples including cancers, noncancerous counterparts, benign diseases and precancerous dysplasias. Significant expressional differences between matched pairs were reproduced in miR-133b, miR-455-5p, and miR-196a, among which miR-196a being the most promising cancer biomarker as validated by qRT-PCR analyses on additional 84 tissue samples. Deep sequencing analysis revealed both quantitative and qualitative deviation of miR-196a isomiR expression in laryngeal cancer. In situ hybridization confirmed laryngeal cancer-specific expression of miR-196a in both cancer and cancer stroma cells. Finally, inhibition of miR-196a counteracted cancer cell proliferation in both laryngeal cancer-derived cells and mouse xenograft model. Conclusions/Significance Our study provided the possibilities that miR-196a might be very useful in diagnosing and treating laryngeal cancer. PMID:23967217

  15. Multiplex detection of pancreatic cancer biomarkers using a SERS-based immunoassay

    Science.gov (United States)

    Banaei, Nariman; Foley, Anne; Houghton, Jean Marie; Sun, Yubing; Kim, Byung

    2017-11-01

    Early diagnosis of pancreatic cancer (PC) is critical to reduce the mortality rate of this disease. Current biological analysis approaches cannot robustly detect several low abundance PC biomarkers in sera, limiting the clinical application of these biomarkers. Enzyme linked immunosorbent assay and radioimmunoassay are two common platforms for detection of biomarkers; however, they suffer from some limitation. This study demonstrates a novel system for multiplex detection of pancreatic biomarkers CA19-9, MMP7 and MUC4 in sera samples with high sensitivity using surface enhanced Raman spectroscopy. Measuring the levels of these biomarkers in PC patients, pancreatitis patients, and healthy individuals reveals the unique expression pattern of these markers in PC patients, suggesting the great potential of using this approach for early diagnostics of PCs.

  16. Ensuring Sample Quality for Biomarker Discovery Studies - Use of ICT Tools to Trace Biosample Life-cycle.

    Science.gov (United States)

    Riondino, Silvia; Ferroni, Patrizia; Spila, Antonella; Alessandroni, Jhessica; D'Alessandro, Roberta; Formica, Vincenzo; Della-Morte, David; Palmirotta, Raffaele; Nanni, Umberto; Roselli, Mario; Guadagni, Fiorella

    2015-01-01

    The growing demand of personalized medicine marked the transition from an empirical medicine to a molecular one, aimed at predicting safer and more effective medical treatment for every patient, while minimizing adverse effects. This passage has emphasized the importance of biomarker discovery studies, and has led sample availability to assume a crucial role in biomedical research. Accordingly, a great interest in Biological Bank science has grown concomitantly. In biobanks, biological material and its accompanying data are collected, handled and stored in accordance with standard operating procedures (SOPs) and existing legislation. Sample quality is ensured by adherence to SOPs and sample whole life-cycle can be recorded by innovative tracking systems employing information technology (IT) tools for monitoring storage conditions and characterization of vast amount of data. All the above will ensure proper sample exchangeability among research facilities and will represent the starting point of all future personalized medicine-based clinical trials. Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.

  17. 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.

  18. Topoisomerase I copy number alterations as biomarker for irinotecan efficacy in metastatic colorectal cancer

    DEFF Research Database (Denmark)

    Palshof, Jesper Andreas; Hogdall, Estrid Vilma Solyom; Poulsen, Tim Svenstrup

    2017-01-01

    Background No biomarker exists to guide the optimal choice of chemotherapy for patients with metastatic colorectal cancer. We examined the copy numbers (CN) of topoisomerase I (TOP1) as well as the ratios of TOP1/CEN-20 and TOP1/CEN-2 as biomarkers for irinotecan efficacy in patients...... with metastatic colorectal cancer. Methods From a national cohort, we identified 163 patients treated every third week with irinotecan 350 mg/m2 as second-line therapy. Among these 108 were eligible for analyses and thus entered the study. Primary tumors samples were collected and tissue microarray (TMA) blocks...... in search of a biomarker driven patient stratification. Other biomarkers to be paired with TOP1 CN are therefore highly warranted....

  19. The Present and Future of Biomarkers in Prostate Cancer: Proteomics, Genomics, and Immunology Advancements

    Directory of Open Access Journals (Sweden)

    Pierre-Olivier Gaudreau

    2016-01-01

    Full Text Available Prostate cancer (PC is the second most common form of cancer in men worldwide. Biomarkers have emerged as essential tools for treatment and assessment since the variability of disease behavior, the cost and diversity of treatments, and the related impairment of quality of life have given rise to a need for a personalized approach. High-throughput technology platforms in proteomics and genomics have accelerated the development of biomarkers. Furthermore, recent successes of several new agents in PC, including immunotherapy, have stimulated the search for predictors of response and resistance and have improved the understanding of the biological mechanisms at work. This review provides an overview of currently established biomarkers in PC, as well as a selection of the most promising biomarkers within these particular fields of development.

  20. Stress proteins and cytokines are urinary biomarkers for diagnosis and staging of bladder cancer.

    Science.gov (United States)

    Margel, David; Pevsner-Fischer, Meirav; Pesvner-Fischer, Meirav; Baniel, Jack; Yossepowitch, Ofer; Cohen, Irun R

    2011-01-01

    Cancer often involves inflammatory processes. We hypothesized that immune mediators in urine may serve as biomarkers for bladder cancer (BCa). To investigate whether BCa might be marked by urinary levels of heat shock proteins (HSPs; HSP60, HSP70, or HSP90) or cytokines (interferon [IFN]-γ, tumor necrosis factor [TNF]-α, tumor growth factor [TGF]-β, interleukin [IL]-1β, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, or IL-13). This was a case-control study with a discovery and validation phase. We examined urine from 106 consecutive patients: healthy controls (n=18); hematuria with no evidence of BCa (n=20); non-muscle-invasive BCa (n=50); and muscle-invasive BCa (n=18). The concentrations of HSPs and cytokines were assessed by enzyme-linked immunosorbent assay. In the validation phase, independent urine samples from 40 patients were analyzed (controls [n=19] and BCa [n=21]). We used the area under the curve (AUC) of a receiver operating characteristic analysis to determine the ability of HSPs and cytokines to mark BCa and applied a multivariate logistic regression to create a formula able to diagnose BCa. The formula was applied to the validation set without recalculation, and positive and negative predictive values were calculated. Urinary concentrations of IL-8, IL-10, and IL-13 were significantly elevated in BCa; IL-13 was the most prominent marker (AUC: 0.93; 95% confidence interval [CI], 0.85-0.99). The multivariate regression analysis highlighted HSP60 (odds ratio [OR]: 1.206; 95% CI, 1.041-1.397, p=0.003) and IL-13 (OR: 1.020; 95% CI: 1.007-1.033, p=0.012). The validation assay was performed using HSP60 and IL-13. The overall positive predictive value was 74% (95% CI, 64-84%); and the negative predictive value was 76% (95% CI, 66-86%). Since we examined a small number of patients, the results need to be confirmed in a larger cohort. These results suggest that it might be possible to develop a urinary biomarker for BCa and raise the possibility that expression of

  1. 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

    BACKGROUND: Few studies have investigated the association between whole-grain intake and colorectal cancer. Because whole-grain intake estimation might be prone to measurement errors, more objective measures (eg, biomarkers) could assist in investigating such associations. METHODS: The association...... 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....... We included 1372 incident colorectal cancer case patients and 1372 individual matched control subjects and calculated the incidence rate ratios (IRRs) for overall and anatomical subsites of colorectal cancer using conditional logistic regression adjusted for potential confounders. Regional...

  2. Potential Biomarkers of Fat Loss as a Feature of Cancer Cachexia

    OpenAIRE

    Maryam Ebadi; Mazurak, Vera C.

    2015-01-01

    Fat loss is associated with shorter survival and reduced quality of life in cancer patients. Effective intervention for fat loss in cachexia requires identification of the condition using prognostic biomarkers for early detection and prevention of further depletion. No biomarkers of fat mass alterations have been defined for application to the neoplastic state. Several inflammatory cytokines have been implicated in mediating fat loss associated with cachexia; however, plasma levels may no...

  3. Exosomal proteins as prognostic biomarkers in non-small cell lung cancer

    DEFF Research Database (Denmark)

    Paulsen, Birgitte Sandfeld; Aggerholm-Pedersen, N; Bæk, R

    2016-01-01

    for optimal treatment. We here evaluate exosomes by protein phenotyping as a prognostic biomarker in NSCLC. METHODS: Exosomes from plasma of 276 NSCLC patients were phenotyped using the Extracellular Vesicle Array; 49 antibodies captured the proteins on the exosomes, and a cocktail of biotin......BACKGROUND: Use of exosomes as biomarkers in non-small cell lung cancer (NSCLC) is an intriguing approach in the liquid-biopsy era. Exosomes are nano-sized vesicles with membrane-bound proteins that reflect their originating cell. Prognostic biomarkers are needed to improve patient selection...

  4. CCNA2 Is a Prognostic Biomarker for ER+ Breast Cancer and Tamoxifen Resistance

    OpenAIRE

    Gao, Tian; Han, Yong; Yu, Ling; Ao, Sheng; Li, Ziyu; Ji, Jiafu

    2014-01-01

    Identification of effective prognostic biomarkers and targets are of crucial importance to the management of estrogen receptor positive (ER+) breast cancer. CCNA2 (also known as CyclinA2) belongs to the highly conserved cyclin family and is significantly overexpressed in various cancer types. In this study, we demonstrated that CCNA2 had significant predictive power in distant metastasis free survival, disease free survival, recurrence free survival and overall survival of ER+ breast cancer p...

  5. Urinary long noncoding RNAs in nonmuscle-invasive bladder cancer: new architects in cancer prognostic biomarkers.

    Science.gov (United States)

    Terracciano, Daniela; Ferro, Matteo; Terreri, Sara; Lucarelli, Giuseppe; D'Elia, Carolina; Musi, Gennaro; de Cobelli, Ottavio; Mirone, Vincenzo; Cimmino, Amelia

    2017-06-01

    Several reports over the last 10 years provided evidence that long noncoding RNAs (lncRNAs) are often altered in bladder cancers. lncRNAs are longer than 200 nucleotides and function as important regulators of gene expression, interacting with the major pathways of cell growth, proliferation, differentiation, and survival. A large number of lncRNAs has oncogenic function and is more expressed in tumor compared with normal tissues. Their overexpression may be associated with tumor formation, progression, and metastasis in a variety of tumors including bladder cancer. Although lncRNAs have been shown to have critical regulatory roles in cancer biology, the biological functions and prognostic values in nonmuscle-invasive bladder cancer remain largely unknown. Nevertheless, a growing body of evidence suggests that several lncRNAs expression profiles in bladder malignancies are associated with poor prognosis, and they can be detected in biological fluids, such as urines. Here, we review current progress in the biology and the implication of lncRNAs associated with bladder cancer, and we discuss their potential use as diagnosis and prognosis biomarkers in bladder malignancies with a focus on their role in high-risk nonmuscle-invasive tumors. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. 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 of ...

  7. MIP-Based Sensors: Promising New Tools for Cancer Biomarker Determination

    Directory of Open Access Journals (Sweden)

    Giulia Selvolini

    2017-03-01

    Full Text Available Detecting cancer disease at an early stage is one of the most important issues for increasing the survival rate of patients. Cancer biomarker detection helps to provide a diagnosis before the disease becomes incurable in later stages. Biomarkers can also be used to evaluate the progression of therapies and surgery treatments. In recent years, molecularly imprinted polymer (MIP based sensors have been intensely investigated as promising analytical devices in several fields, including clinical analysis, offering desired portability, fast response, specificity, and low cost. The aim of this review is to provide readers with an overview on recent important achievements in MIP-based sensors coupled to various transducers (e.g., electrochemical, optical, and piezoelectric for the determination of cancer biomarkers by selected publications from 2012 to 2016.

  8. [Predictive biomarkers of efficacy of checkpoint blockade inhibitors in cancer treatment].

    Science.gov (United States)

    Duruisseaux, Michaël; Lize-Dufranc, Cécile; Badoual, Céline; Bibeau, Frédéric

    2017-02-01

    The remarkable efficacy of PD-1/PD-L1 and CTLA4 immune checkpoint inhibitors has led to numerous approvals in melanoma, non-small cell lung cancer, kidney cancer and several other cancers. Nevertheless, a response is observed in a variable proportion of patients, emphasizing the need for predictive biomarkers of efficacy of immune checkpoint inhibitors effectiveness. Several predictive biomarkers of efficacy are of interest: companion tests such PD-L1 immunohistochemistry, the mutational load, the immune status of the tumor and its molecular profile. They do not allow a perfect selection of the patients, but standardization procedures for certain techniques are ongoing. Moreover the emergence of new approaches, such as the multiplex in situ techniques and the microbiote analysis, may offer the opportunity to better select patients who really benefit from immunotherapy. The goal of this article is to discuss available and promising predictive biomarkers of efficacy for immunotherapy strategies. Copyright © 2016. Published by Elsevier Masson SAS.

  9. Discovery of biomarkers that reflect the intake of sodium selenate by nutritional proteomics.

    Science.gov (United States)

    Mahn, Andrea V; Muñoz, M Cristina; Zamorano, Mauricio J

    2009-10-01

    Selenium offers important health benefits, including the prevention of some types of cancer. The traditional selenium indexes, such as selenium concentration, do not account for the metabolic status of this element regarding its chemoprotective effect. Then, the knowledge of a group of proteins that respond to selenium supplementation could be useful in the assessment of the metabolic status of selenium. The effect of dietary supplementation of rats with sodium-selenate on the blood plasma proteome is investigated. A group composed of six rats is fed a basic diet supplemented with sodium-selenate at 1.9 microg of Selenium per g of food, and a control group is fed a diet that covers the minimum selenium requirements, each for ten weeks. A proteomic approach is used to both quantify the changes in the abundance of some plasmatic proteins and to identify them. Fibrinogen, apolipoproteins, haptoglobin, and transthyretin changed significantly their abundance due to selenium administration. Those proteins are indirectly related to selenium metabolism. Then, the change in the proteomic profile due to selenium supplementation could probably be considered as a new index to assess the metabolic status of selenium. This index might help in the prevention of some diseases by nutritional diagnosis and, consequently, the adequate dietary recommendation.

  10. Diagnostic, Predictive, Prognostic, and Therapeutic Molecular Biomarkers in Third Millennium: A Breakthrough in Gastric Cancer.

    Science.gov (United States)

    Carlomagno, Nicola; Incollingo, Paola; Tammaro, Vincenzo; Peluso, Gaia; Rupealta, Niccolò; Chiacchio, Gaetano; Sandoval Sotelo, Maria Laura; Minieri, Gianluca; Pisani, Antonio; Riccio, Eleonora; Sabbatini, Massimo; Bracale, Umberto Marcello; Calogero, Armando; Dodaro, Concetta Anna; Santangelo, Michele

    2017-01-01

    Gastric cancer is the fifth most common cancer and the third cause of cancer death. The clinical outcomes of the patients are still not encouraging with a low rate of 5 years' survival. Often the disease is diagnosed at advanced stages and this obviously negatively affects patients outcomes. A deep understanding of molecular basis of gastric cancer can lead to the identification of diagnostic, predictive, prognostic, and therapeutic biomarkers. This paper aims to give a global view on the molecular classification and mechanisms involved in the development of the tumour and on the biomarkers for gastric cancer. We discuss the role of E-cadherin, HER2, fibroblast growth factor receptor (FGFR), MET, human epidermal growth factor receptor (EGFR), hepatocyte growth factor receptor (HGFR), mammalian target of rapamycin (mTOR), microsatellite instability (MSI), PD-L1, and TP53. We have also considered in this manuscript new emerging biomarkers as matrix metalloproteases (MMPs), microRNAs, and long noncoding RNAs (lncRNAs). Identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers will have a huge impact on patients outcomes as they will allow early detection of tumours and also guide the choice of a targeted therapy based on specific molecular features of the cancer.

  11. Diagnostic, Predictive, Prognostic, and Therapeutic Molecular Biomarkers in Third Millennium: A Breakthrough in Gastric Cancer

    Directory of Open Access Journals (Sweden)

    Nicola Carlomagno

    2017-01-01

    Full Text Available Introduction. Gastric cancer is the fifth most common cancer and the third cause of cancer death. The clinical outcomes of the patients are still not encouraging with a low rate of 5 years’ survival. Often the disease is diagnosed at advanced stages and this obviously negatively affects patients outcomes. A deep understanding of molecular basis of gastric cancer can lead to the identification of diagnostic, predictive, prognostic, and therapeutic biomarkers. Main Body. This paper aims to give a global view on the molecular classification and mechanisms involved in the development of the tumour and on the biomarkers for gastric cancer. We discuss the role of E-cadherin, HER2, fibroblast growth factor receptor (FGFR, MET, human epidermal growth factor receptor (EGFR, hepatocyte growth factor receptor (HGFR, mammalian target of rapamycin (mTOR, microsatellite instability (MSI, PD-L1, and TP53. We have also considered in this manuscript new emerging biomarkers as matrix metalloproteases (MMPs, microRNAs, and long noncoding RNAs (lncRNAs. Conclusions. Identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers will have a huge impact on patients outcomes as they will allow early detection of tumours and also guide the choice of a targeted therapy based on specific molecular features of the cancer.

  12. 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.

  13. Autoantibodies against stress-induced phosphoprotein-1 as a novel biomarker candidate for ovarian cancer.

    Science.gov (United States)

    Kim, Sunghoon; Cho, Hanbyoul; Nam, Eun Ji; Kim, Sang Wun; Kim, Young Tae; Park, Yong Won; Kim, Bo Wook; Kim, Jae-Hoon

    2010-07-01

    Detection of autoantibodies against tumor-associated antigens (TAA) has recently been shown to be a powerful tool for early detection of various cancers. The aim of this study was to investigate the possibility of using autoantibodies against TAA as novel biomarkers by a proteomics-based approach in patients with ovarian cancer. We used two-dimensional differential gel electrophoresis analysis of immuno-precipitated tumor antigens (2D-DITA) to compare the levels of autoantibodies in pretreatment and posttreatment sera of patients with ovarian cancers. The identified autoantibodies were validated by SYBR Green real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC). We further evaluated the level of autoantibody in sera of 68 ovarian cancer patients by an enzyme-linked immunosorbent assay (ELISA). The autoantibody directed against stress-induced phosphoprotein-1 (STIP-1) emerged as a novel biomarker candidate for ovarian cancer. SYBR Green PCR and IHC confirmed that the STIP-1 mRNA and protein expression levels were significantly up-regulated in ovarian cancers compared with normal and benign tumors (P = 0.003 and P ovarian cancer patients compared with healthy controls (P = 0.03). The results suggest that 2D-DITA is a useful tool to detect autoantibodies and that STIP-1 is a potential biomarker candidate for ovarian cancers. (c) 2010 Wiley-Liss, Inc.

  14. Long non-coding RNA PVT1: Emerging biomarker in digestive system cancer.

    Science.gov (United States)

    Zhou, Dan-Dan; Liu, Xiu-Fen; Lu, Cheng-Wei; Pant, Om Prakash; Liu, Xiao-Dong

    2017-12-01

    The digestive system cancers are leading cause of cancer-related death worldwide, and have high risks of morbidity and mortality. More and more long non-coding RNAs (lncRNAs) have been studied to be abnormally expressed in cancers and play a key role in the process of digestive system tumour progression. Plasmacytoma variant translocation 1 (PVT1) seems fairly novel. Since 1984, PVT1 was identified to be an activator of MYC in mice. Its role in human tumour initiation and progression has long been a subject of interest. The expression of PVT1 is elevated in digestive system cancers and correlates with poor prognosis. In this review, we illustrate the various functions of PVT1 during the different stages in the complex process of digestive system tumours (including oesophageal cancer, gastric cancer, colorectal cancer, hepatocellular carcinoma and pancreatic cancer). The growing evidence shows the involvement of PVT1 in both proliferation and differentiation process in addition to its involvement in epithelial to mesenchymal transition (EMT). These findings lead us to conclude that PVT1 promotes proliferation, survival, invasion, metastasis and drug resistance in digestive system cancer cells. We will also discuss PVT1's potential in diagnosis and treatment target of digestive system cancer. There was a great probability PVT1 could be a novel biomarker in screening tumours, prognosis biomarkers and future targeted therapy to improve the survival rate in cancer patients. © 2017 John Wiley & Sons Ltd.

  15. Identification of Biomarkers for Predicting Lymph Node Metastasis of Stomach Cancer Using Clinical DNA Methylation Data.

    Science.gov (United States)

    Wu, Jun; Xiao, Yawen; Xia, Chao; Yang, Fan; Li, Hua; Shao, Zhifeng; Lin, Zongli; Zhao, Xiaodong

    2017-01-01

    Lymph node (LN) metastasis was an independent risk factor for stomach cancer recurrence, and the presence of LN metastasis has great influence on the overall survival of stomach cancer patients. Thus, accurate prediction of the presence of lymph node metastasis can provide guarantee of credible prognosis evaluation of stomach cancer patients. Recently, increasing evidence demonstrated that the aberrant DNA methylation first appears before symptoms of the disease become clinically apparent. Selecting key biomarkers for LN metastasis presence prediction for stomach cancer using clinical DNA methylation based on a machine learning method. To reduce the overfitting risk of prediction task, we applied a three-step feature selection method according to the property of DNA methylation data. The feature selection procedure extracted several cancer-related and lymph node metastasis-related genes, such as TP73, PDX1, FUT8, HOXD1, NMT1, and SEMA3E. The prediction performance was evaluated on the public DNA methylation dataset. The results showed that the three-step feature procedure can largely improve the prediction performance and implied the reliability of the biomarkers selected. With the selected biomarkers, the prediction method can achieve higher accuracy in detecting LN metastasis and the results also proved the reliability of the selected biomarkers indirectly.

  16. Identification of Biomarkers for Predicting Lymph Node Metastasis of Stomach Cancer Using Clinical DNA Methylation Data

    Directory of Open Access Journals (Sweden)

    Jun Wu

    2017-01-01

    Full Text Available Background. Lymph node (LN metastasis was an independent risk factor for stomach cancer recurrence, and the presence of LN metastasis has great influence on the overall survival of stomach cancer patients. Thus, accurate prediction of the presence of lymph node metastasis can provide guarantee of credible prognosis evaluation of stomach cancer patients. Recently, increasing evidence demonstrated that the aberrant DNA methylation first appears before symptoms of the disease become clinically apparent. Objective. Selecting key biomarkers for LN metastasis presence prediction for stomach cancer using clinical DNA methylation based on a machine learning method. Methods. To reduce the overfitting risk of prediction task, we applied a three-step feature selection method according to the property of DNA methylation data. Results. The feature selection procedure extracted several cancer-related and lymph node metastasis-related genes, such as TP73, PDX1, FUT8, HOXD1, NMT1, and SEMA3E. The prediction performance was evaluated on the public DNA methylation dataset. The results showed that the three-step feature procedure can largely improve the prediction performance and implied the reliability of the biomarkers selected. Conclusions. With the selected biomarkers, the prediction method can achieve higher accuracy in detecting LN metastasis and the results also proved the reliability of the selected biomarkers indirectly.

  17. [The level of evidence for the use of biomarkers in the early detection of prostate cancer].

    Science.gov (United States)

    Lamy, Pierre-Jean; Gauchez, Anne-Sophie; Salomon, Laurent; Haugh, Margaret; Ceraline, Jocelyn; Fulla, Yvonne; Georges, Agnès; Larré, Stéphane; Loric, Sylvain; Luporsi, Elisabeth; Martin, Pierre-Marie; Mazerolles, Catherine; Molinié, Vincent; Mongiat-Artus, Pierre; Piffret, Jacques; Thuillier, François; Perrin, Paul; Rebillard, Xavier

    2016-01-01

    To systematically review the evidence for the use of PSA and other biomarkers in the early detection of prostate cancer, we searched PubMed for clinical trials and studies assessing PSA and other biomarkers in the early detection of prostate cancer, published between 2000 and May 2013 that included >200 subjects. The level of evidence (LOE) for clinical utility was evaluated using the tumor marker utility grading system. A total of 84 publications, corresponding to 70 trials and studies were selected for inclusion in this review. We attributed a level of evidence (LoE) of IA to PSA for early PCa detection, but we do not recommend its use in mass screening. Emerging biomarkers were assessed in prospective case-control and cohort studies: PCA3 (n=3); kallikreins (n=3); [-2]proPSA (n=5); fusion oncogenes (n=2). These studies used biopsy results for prostate cancer to determine specificity and sensitivity, but they did not assess the effect on PCa mortality. The LoE attributed was III-C. PSA can be used for early prostate cancer detection but mass screening is not recommended. Studies on other biomarkers suggest that they could be used, individually or in combination, to improve the selection of patients with elevated PSA levels for biopsy, but RCTs assessing their impact on prostate cancer management and mortality are needed. A better use of available tests is possible for men at risk in order to maximize the risk-benefit ratio.

  18. Biomarkers for pancreatic cancer: promising new markers and options beyond CA 19-9.

    Science.gov (United States)

    Ballehaninna, Umashankar K; Chamberlain, Ronald S

    2013-12-01

    Pancreatic adenocarcinoma accounts for nearly 90-95% of exocrine malignant tumors of the pancreas. Traditionally, overexpressed proteins/epitopes such as CA 19-9, CA-50, CEA, and many others were being used as pancreatic cancer tumor markers. The main utility of these biomarkers was in the diagnosis of pancreatic cancer as well as to assess response to chemotherapy and to determine prognosis and to predict tumor recurrence. However, these markers had significant limitations such as lack of sensitivity, false-negative results in certain blood groups, as well as false-positive elevation in the presence of obstructive jaundice. To circumvent these limitations, an extraordinary amount of research is being performed to identify an accurate tumor marker or a panel of markers that could aid in the management of the pancreatic cancer. Although this research has identified a large number and different variety of biomarkers, few hold future promise as a preferred marker for pancreatic cancer. This review provides an insight into exciting new areas of pancreatic biomarker research such as salivary, pancreatic juice, and stool markers that can be used as a noninvasive test to identify pancreatic cancer. This manuscript also provides a discussion on newer biomarkers, the role of microRNAs, and pancreatic cancer proteomics, which have the potential to identify a preferred tumor marker for pancreatic adenocarcinoma. This review further elaborates on important genetic changes associated with the development and progression of pancreatic cancer that holds the key for the identification of a sensitive biomarker and which could also serve as a therapeutic target.

  19. Utilizing Existing Clinical and Population Biospecimen Resources for Discovery or Validation of Markers for Early Cancer Detection

    Science.gov (United States)

    Utilizing Existing Clinical and Population Biospecimen Resources for Discovery or Validation of Markers for Early Cancer Detection, a 2013 workshop sponsored by the Epidemiology and Genomics Research Program.

  20. Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

    Directory of Open Access Journals (Sweden)

    Srivastava Mousami

    2012-11-01

    Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

  1. Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

    Science.gov (United States)

    Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

    2012-11-02

    The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated

  2. LiverCancerMarkerRIF: a liver cancer biomarker interactive curation system combining text mining and expert annotations.

    Science.gov (United States)

    Dai, Hong-Jie; Wu, Johnny Chi-Yang; Lin, Wei-San; Reyes, Aaron James F; Dela Rosa, Mira Anne C; Syed-Abdul, Shabbir; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2014-01-01

    Biomarkers are biomolecules in the human body that can indicate disease states and abnormal biological processes. Biomarkers are often used during clinical trials to identify patients with cancers. Although biomedical research related to biomarkers has increased over the years and substantial effort has been expended to obtain results in these studies, the specific results obtained often contain ambiguities, and the results might contradict each other. Therefore, the information gathered from these studies must be appropriately integrated and organized to facilitate experimentation on biomarkers. In this study, we used liver cancer as the target and developed a text-mining-based curation system named LiverCancerMarkerRIF, which allows users to retrieve biomarker-related narrations and curators to curate supporting evidence on liver cancer biomarkers directly while browsing PubMed. In contrast to most of the other curation tools that require curators to navigate away from PubMed and accommodate distinct user interfaces or Web sites to complete the curation process, our system provides a user-friendly method for accessing text-mining-aided information and a concise interface to assist curators while they remain at the PubMed Web site. Biomedical text-mining techniques are applied to automatically recognize biomedical concepts such as genes, microRNA, diseases and investigative technologies, which can be used to evaluate the potential of a certain gene as a biomarker. Through the participation in the BioCreative IV user-interactive task, we examined the feasibility of using this novel type of augmented browsing-based curation method, and collaborated with curators to curate biomarker evidential sentences related to liver cancer. The positive feedback received from curators indicates that the proposed method can be effectively used for curation. A publicly available online database containing all the aforementioned information has been constructed at http

  3. Urothelial cancer of the upper urinary tract: emerging biomarkers and integrative models for risk stratification.

    Science.gov (United States)

    Mathieu, Romain; Vartolomei, Mihai D; Mbeutcha, Aurélie; Karakiewicz, Pierre I; Briganti, Alberto; Roupret, Morgan; Shariat, Shahrokh F

    2016-08-01

    The aim of this review was to provide an overview of current biomarkers and risk stratification models in urothelial cancer of the upper urinary tract (UTUC). A non-systematic Medline/PubMed literature search was performed using the terms "biomarkers", "preoperative models", "postoperative models", "risk stratification", together with "upper tract urothelial carcinoma". Original articles published between January 2003 and August 2015 were included based on their clinical relevance. Additional references were collected by cross referencing the bibliography of the selected articles. Various promising predictive and prognostic biomarkers have been identified in UTUC thanks to the increasing knowledge of the different biological pathways involved in UTUC tumorigenesis. These biomarkers may help identify tumors with aggressive biology and worse outcomes. Current tools aim at predicting muscle invasive or non-organ confined disease, renal failure after radical nephroureterectomy and survival outcomes. These models are still mainly based on imaging and clinicopathological feature and none has integrated biomarkers. Risk stratification in UTUC is still suboptimal, especially in the preoperative setting due to current limitations in staging and grading. Identification of novel biomarkers and external validation of current prognostic models may help improve risk stratification to allow evidence-based counselling for kidney-sparing approaches, perioperative chemotherapy and/or risk-based surveillance. Despite growing understanding of the biology underlying UTUC, management of this disease remains difficult due to the lack of validated biomarkers and the limitations of current predictive and prognostic tools. Further efforts and collaborations are necessaryry to allow their integration in daily practice.

  4. Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.

    Science.gov (United States)

    Fortner, Renée T; Hüsing, Anika; Kühn, Tilman; Konar, Meric; Overvad, Kim; Tjønneland, Anne; Hansen, Louise; Boutron-Ruault, Marie-Christine; Severi, Gianluca; Fournier, Agnès; Boeing, Heiner; Trichopoulou, Antonia; Benetou, Vasiliki; Orfanos, Philippos; Masala, Giovanna; Agnoli, Claudia; Mattiello, Amalia; Tumino, Rosario; Sacerdote, Carlotta; Bueno-de-Mesquita, H B As; Peeters, Petra H M; Weiderpass, Elisabete; Gram, Inger T; Gavrilyuk, Oxana; Quirós, J Ramón; Maria Huerta, José; Ardanaz, Eva; Larrañaga, Nerea; Lujan-Barroso, Leila; Sánchez-Cantalejo, Emilio; Butt, Salma Tunå; Borgquist, Signe; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Allen, Naomi E; Rinaldi, Sabina; Dossus, Laure; Gunter, Marc; Merritt, Melissa A; Tzoulaki, Ioanna; Riboli, Elio; Kaaks, Rudolf

    2017-03-15

    Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

  5. 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.

  6. A review of molecular biomarkers for bladder cancer

    African Journals Online (AJOL)

    McRoy

    diagnosis, guide treatment and provide accurate prognostication.[2-5]. A biomarker is a molecular compound .... is substantially reduced in the presence of inflammation, infectious diseases, urinary calculi, foreign body, ... conclude that p53 is a good prognostic marker.[25] Similarly, a recent trail has shown that there was no ...

  7. Guidelines for Biomarker of Food Intake Reviews (BFIRev: how to conduct an extensive literature search for biomarker of food intake discovery

    Directory of Open Access Journals (Sweden)

    Giulia Praticò

    2018-02-01

    Full Text Available Abstract Identification of new biomarkers of food and nutrient intake has developed fast over the past two decades and could potentially provide important new tools for compliance monitoring and dietary intake assessment in nutrition and health science. In recent years, metabolomics has played an important role in identifying a large number of putative biomarkers of food intake (BFIs. However, the large body of scientific literature on potential BFIs outside the metabolomics area should also be taken into account. In particular, we believe that extensive literature reviews should be conducted and that the quality of all suggested biomarkers should be systematically evaluated. In order to cover the literature on BFIs in the most appropriate and consistent manner, there is a need for appropriate guidelines on this topic. These guidelines should build upon guidelines in related areas of science while targeting the special needs of biomarker methodology. This document provides a guideline for conducting an extensive literature search on BFIs, which will provide the basis to systematically validate BFIs. This procedure will help to prioritize future work on the identification of new potential biomarkers and on validating these as well as other biomarker candidates, thereby providing better tools for future studies in nutrition and health.

  8. Skp1: Implications in cancer and SCF-oriented anti-cancer drug discovery.

    Science.gov (United States)

    Hussain, Muzammal; Lu, Yongzhi; Liu, Yong-Qiang; Su, Kai; Zhang, Jiancun; Liu, Jinsong; Zhou, Guang-Biao

    2016-09-01

    In the last decade, the ubiquitin proteasome system (UPS), in general, and E3 ubiquitin ligases, in particular, have emerged as valid drug targets for the development of novel anti-cancer therapeutics. Cullin RING Ligases (CRLs), which can be classified into eight groups (CRL1-8) and comprise approximately 200 members, represent the largest family of E3 ubiquitin ligases which facilitate the ubiquitination-derived proteasomal degradation of a myriad of functionally and structurally diverse substrates. S phase kinase-associated protein 1 (Skp1)-Cullin1-F-Box protein (SCF) complexes are the best characterized among CRLs, which play crucial roles in numerous cellular processes and physiological dysfunctions, such as in cancer biology. Currently, there is growing interest in developing SCF-targeting anti-cancer therapies for clinical application. Indeed, the research in this field has seen some progress in the form of cullin neddylation- and Skp2-inhibitors. However, it still remains an underdeveloped area and needs to design new strategies for developing improved form of therapy. In this review, we venture a novel strategy that rational pharmacological targeting of Skp1, a central regulator of SCF complexes, may provide a novel avenue for SCF-oriented anti-cancer therapy, expected: (i) to simultaneously address the critical roles that multiple SCF oncogenic complexes play in cancer biology, (ii) to selectively target cancer cells with minimal normal cell toxicity, and (iii) to offer multiple chemical series, via therapeutic interventions at the Skp1 binding interfaces in SCF complex, thereby maximizing chances of success for drug discovery. In addition, we also discuss the challenges that might be posed regarding rational pharmacological interventions against Skp1. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Inflammatory biomarkers and cancer: CRP and suPAR as markers of incident cancer in patients with serious nonspecific symptoms and signs of cancer.

    Science.gov (United States)

    Rasmussen, Line Jee Hartmann; Schultz, Martin; Gaardsting, Anne; Ladelund, Steen; Garred, Peter; Iversen, Kasper; Eugen-Olsen, Jesper; Helms, Morten; David, Kim Peter; Kjaer, Andreas; Lebech, Anne-Mette; Kronborg, Gitte

    2017-07-01

    In Denmark, patients with serious nonspecific symptoms and signs of cancer (NSSC) are referred to the diagnostic outpatient clinics (DOCs) where an accelerated cancer diagnostic program is initiated. Various immunological and inflammatory biomarkers have been associated with cancer, including soluble urokinase plasminogen activator receptor (suPAR) and the pattern recognition receptors (PRRs) pentraxin-3, mannose-binding lectin, ficolin-1, ficolin-2 and ficolin-3. We aimed to evaluate these biomarkers and compare their diagnostic ability to classical biomarkers for diagnosing cancer in patients with NSSC. Patients were included from the DOC, Department of Infectious Diseases, Copenhagen University Hospital Hvidovre. Patients were given a final diagnosis based on the combined results from scans, blood work and physical examination. Weight loss, Charlson score and previous cancer were registered on admission, and plasma concentrations of biomarkers were measured. The primary outcome was incident cancer within 1 year. Out of 197 patients included, 39 patients (19.8%) were diagnosed with cancer. Patients with cancer were significantly older and had a higher burden of comorbidities and previous cancer diagnoses compared to patients who were not diagnosed with cancer. Previous cancer, C-reactive protein (CRP) and suPAR were significantly associated with newly diagnosed cancer during follow-up in multiple logistic regression analyses adjusted for age, sex and CRP. Neither any of the PRRs investigated nor self-reported weight loss was associated with cancer. In this study, previous cancer, CRP and suPAR were significantly associated with cancer diagnosis in patients with NSSC. Ficolin-1-3, MBL and pentraxin-3 were not associated with cancer. © 2017 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of Union for International Cancer Control.

  10. The Role of Metabolomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools.

    Science.gov (United States)

    Trezzi, Jean-Pierre; Vlassis, Nikos; Hiller, Karsten

    2015-01-01

    This chapter introduces the emerging field of metabolomics and its application in the context of cancer biomarker research. Taking advantage of modern high-throughput technologies, and enhanced computational power, metabolomics has a high potential for cancer biomarker identification and the development of diagnostic tools. This chapter describes current metabolomics technologies used in cancer research, starting with metabolomics sample preparation, elaborating on current analytical methodologies for metabolomics measurement and introducing existing software for data analysis. The last part of this chapter deals with the statistical analysis of very large metabolomics datasets and their relevance for cancer biomarker identification.

  11. Serum biomarker screening for the diagnosis of early gastric cancer using SELDI-TOF-MS.

    Science.gov (United States)

    Li, Ping; Zhang, Dianliang; Guo, Chunbao

    2012-06-01

    In this study, we performed a proteomic analysis of sera from stage I gastric cancer patients using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) and established a diagnostic model for the early diagnosis of stage I gastric cancer. Serum samples from 169 gastric cancer patients and 83 age- and gender-matched healthy individuals were analyzed by SELDI-TOF-MS ProteinChip array technology. The SELDI-TOF-MS spectral data were analyzed using the Biomarker Wizard™ and Biomarker Patterns™ software to find differential proteins and develop a classification tree for gastric cancer. A total of 34 mass peaks were identified. Six peaks at a mass-to-charge ratio (m/z) of 2873, 3163, 4526, 5762, 6121 and 7778 were used to construct the diagnostic model. The model effectively distinguished gastric cancer samples from control samples, achieving a sensitivity and specificity of 93.49 and 91.57%, respectively. In addition, we identified 3 of the 6 protein peaks at 2873, 6121 and 7778 m/z, which distinguished between stage I and stage II/III/IV gastric cancer. The model had an accuracy of 88.89% for the identification of stage I gastric cancer. In conclusion, the diagnostic model for the detection of serum proteins by SELDI-TOF-MS ProteinChip array technology correctly distinguishes gastric cancer from healthy samples, and has the ability to screen and distinguish between early gastric cancer from advanced gastric cancer.

  12. 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.

  13. Mining for Lung Cancer Biomarkers in Plasma Metabolomics Data

    OpenAIRE

    Johnsson, Anna

    2010-01-01

    Lung cancer is the cancer form that has the highest mortality worldwide and inaddition the survival of lung cancer is very low. Only 15% of the patients are alivefive years from set diagnosis. More research is needed to understand the biologyof lung cancer and thus make it possible to discover the disease at an early stage.Early diagnosis leads to an increased chance of survival. In this thesis 179 lungcancer- and 116 control samples of blood serum were analyzed for identificationof metabolom...

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

    NARCIS (Netherlands)

    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,

  15. Changes in inflammatory endometrial cancer risk biomarkers in individuals undergoing surgical weight loss.

    Science.gov (United States)

    Linkov, Faina; Goughnour, Sharon L; Ma, Tianzhou; Xu, Zhongying; Edwards, Robert P; Lokshin, Anna E; Ramanathan, Ramesh C; Hamad, Giselle G; McCloskey, Carol; Bovbjerg, Dana H

    2017-10-01

    Obesity has been strongly linked to endometrial cancer (EC) risk. A number of potential EC risk biomarkers have been proposed, including heightened pro-inflammatory cytokines and adipokines. To evaluate if bariatric surgery can serve as a means for altering levels of such EC risk biomarkers, we investigated changes in these biomarkers after weight loss. Blood samples were collected pre-operatively and 6months post-operatively in 107 female bariatric surgery patients aged 18-72years. Wilcoxon signed-rank tests were used to compare biomarker levels (measured using xMAP immunoassays) pre- and post-surgery. Normative comparisons were implemented to contrast 6-month post-surgery biomarker levels to levels in a sample of 74 age-matched non-obese women. Linear regression was used to evaluate the relationship between biomarker expression at baseline and 6months post-surgery and the relationship between race and biomarker levels. On average, participants lost 30.15kg (SD: 12.26) after the bariatric intervention. Levels of C-peptide, insulin, CRP, leptin, IL-1Rα, and IL-6 significantly decreased, while levels of SHBG, IGFBP1, and adiponectin significantly increased with weight loss. Normative comparisons showed the levels of SHBG, C-peptide, insulin, IGFBP1, adiponectin, CRP, and TNFα after bariatric intervention approached the level of markers in comparison group. Multiple regression analyses revealed significant relationships between changes in BMI and changes in biomarker levels. The changes in IL-1Rα were significantly associated with race. Our findings demonstrate that normalization of EC risk biomarkers can be achieved with bariatric surgery. Improved understanding of biological mechanisms associated with weight loss may inform preventive strategies for EC. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Identification of microRNAs in Nipple Discharge as Potential Diagnostic Biomarkers for Breast Cancer.

    Science.gov (United States)

    Zhang, Kai; Zhao, Song; Wang, Qing; Yang, Hsin-Sheng; Zhu, Jiang; Ma, Rong

    2015-12-01

    Intraductal breast cancer is generally difficult to diagnose because of a lack of an efficient method for detection. The purpose of this study was to reveal and validate the differential expression of microRNAs (miRNAs) in nipple discharge from intraductal papilloma patients and identify miRNAs as novel potential biomarkers for primary breast cancer. Nipple discharge samples were collected from three intraductal carcinoma breast cancer patients and three intraductal papilloma patients. The initial screening of miRNA expression was performed with an Axon GenePix 4000B microarray scanner using a novel approach to label miRNAs. The expression levels of the miRNAs selected from the initial screening were further examined by quantitative real-time polymerase chain reaction (qRT-PCR) in 21 validation samples (8 carcinomas and 13 benign tumors). An independent t test was used to detect significant correlations between the miRNA expression levels and breast cancer. Microarray profiling demonstrated that three miRNAs were markedly up-regulated and three miRNAs were down-regulated in the intraductal carcinoma breast cancer patients compared to the papilloma group. The qRT-PCR analysis further verified that four miRNAs (miR-4484, miR-K12-5-5p, miR-3646, and miR-4732-5p) might serve as potential tumor biomarkers for breast cancer detection. The novel approach of using a microarray scanner is applicable for studying biomarkers in nipple discharge containing small amounts of miRNA. miRNAs could serve as potential tumor biomarkers that can assist in breast cancer screening. Up-regulation of miR-4484, miR-K12-5-5p, and miR-3646 in nipple discharge may be a predictor of malignant breast cancer.

  17. 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.

  18. 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.

  19. Microfluidic Electrochemical Immunoarray for Ultrasensitive Detection of Two Cancer Biomarker Proteins in Serum

    Science.gov (United States)

    Chikkaveeraiah, Bhaskara V.; Mani, Vigneshwaran; Patel, Vyomesh; Gutkind, J. Silvio; Rusling, James F.

    2011-01-01

    A microfluidic electrochemical immunoassay system for multiplexed detection of protein cancer biomarkers was fabricated using a molded polydimethylsiloxane channel and routine machined parts interfaced with a pump and sample injector. Using off-line capture of analytes by heavily-enzyme-labeled 1 μm superparamagnetic particle (MP)-antibody bioconjugates and capture antibodies attached to an 8-electrode measuring chip, simultaneous detection of cancer biomarker proteins prostate specific antigen (PSA) and interleukin-6 (IL-6) in serum was achieved at sub-pg mL−1 levels. MPs were conjugated with ~90,000 antibodies and ~200,000 horseradish peroxidase (HRP) labels to provide efficient off-line capture and high sensitivity. Measuring electrodes feature a layer of 5 nm glutathione-decorated gold nanoparticles to attach antibodies that capture MP-analyte bioconjugates. Detection limits of 0.23 pg mL−1 for PSA and 0.30 pg mL−1 for IL-6 were obtained in diluted serum mixtures. PSA and IL-6 biomarkers were measured in serum of prostate cancer patients in total assay time 1.15 h and sensor array results gave excellent correlation with standard enzyme-linked immunosorbent assays (ELISA). These microfluidic immunosensors employing nanostructured surfaces and off-line analyte capture with heavily-labeled paramagnetic particles hold great promise for accurate, sensitive multiplexed detection of diagnostic cancer biomarkers. PMID:21632234

  20. 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.

  1. Association between changes in fat distribution and biomarkers for breast cancer

    NARCIS (Netherlands)

    van Gemert, Willemijn A.M.; Monninkhof, Evelyn M.; May, Anne M.; Elias, Sjoerd G.; Van Der Palen, Job; Veldhuis, Wouter B.; Stapper, Maaike; Stellato, Rebecca K.; Schuit, Jantine A.; Peeters, Petra H.

    2017-01-01

    We assessed the associations between changes in total and abdominal fat and changes in biomarkers for breast cancer risk using data of the SHAPE-2 trial. In the SHAPE-2 trial, 243 postmenopausal overweight women were included. The intervention in this trial consisted of 5-6 kg weight loss either by

  2. Association between changes in fat distribution and biomarkers for breast cancer

    NARCIS (Netherlands)

    van Gemert, Willemijn A; Monninkhof, Evelyn M; May, Anne M; Elias, Sjoerd G; van der Palen, Job; Veldhuis, Wouter; Stapper, Maaike; Stellato, Rebecca K; Schuit, A.J.; Peeters, Petra H

    We assessed the associations between changes in total and abdominal fat and changes in biomarkers for breast cancer risk using data of the SHAPE-2 trial. In the SHAPE-2 trial, 243 postmenopausal overweight women were included. The intervention in this trial consisted of 5-6 kg weight loss either by

  3. Early diagnostic protein biomarkers for breast cancer: how far have we come?

    NARCIS (Netherlands)

    Opstal - van Winden, A.W.J.|info:eu-repo/dai/nl/355613239; Vermeulen, R.C.H.|info:eu-repo/dai/nl/216532620; Peeters, P.H.M.; Beijnen, J.H.|info:eu-repo/dai/nl/071919570; van Gils, C.H.

    2012-01-01

    Many studies have used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry or matrix-assisted laser desorption/ionization time-of-flight mass spectrometry to search for blood-based proteins that are related to the presence of breast cancer. We review the biomarkers

  4. Antibody imaging as biomarker in early cancer drug development and treatment

    NARCIS (Netherlands)

    Lamberts, Laetitia Elisabeth

    2016-01-01

    Over the last decades many key pathways in cancer were identified, which raised interest in development of targeted drugs including antibodies. This process benefits of reliable companion biomarkers to enrich the patient population that may benefit of these drugs and to determine drug effects

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

    NARCIS (Netherlands)

    Kyrø, Cecilie; Olsen, Anja; Landberg, Rikard; Skeie, Guri; Loft, Steffen; Åman, Per; Leenders, Max; Dik, Vincent K.; Siersema, Peter D.; Pischon, Tobias; Christensen, Jane; Overvad, Kim; Boutron-Ruault, Marie Christine; Fagherazzi, Guy; Cottet, Vanessa; Kühn, Tilman; Chang-Claude, Jenny; Boeing, Heiner; Trichopoulou, Antonia; Bamia, Christina; Trichopoulos, Dimitrios; Palli, Domenico; Krogh, Vittorio; Tumino, Rosario; Vineis, Paolo; Panico, Salvatore; Peeters, Petra H.; Weiderpass, Elisabete; Bakken, Toril; Åsli, Lene Angell; Argüelles, Marcial; Jakszyn, Paula; Sánchez, María José; Amiano, Pilar; Huerta, José María; Barricarte, Aurelio; Ljuslinder, Ingrid; Palmqvist, Richard; Khaw, Kay Tee; Wareham, Nick; Key, Timothy J.; Travis, Ruth C.; Ferrari, Pietro; Freisling, Heinz; Jenab, Mazda; Gunter, Marc J.; Murphy, Neil; Riboli, Eilo; Tjønneland, Anne; Bueno-De-Mesquita, H. B.

    2014-01-01

    BackgroundFew studies have investigated the association between whole-grain intake and colorectal cancer. Because whole-grain intake estimation might be prone to measurement errors, more objective measures (eg, biomarkers) could assist in investigating such associations.MethodsThe association

  6. miRNA profiling of circulating EpCAM(+) extracellular vesicles: promising biomarkers of colorectal cancer

    DEFF Research Database (Denmark)

    Ostenfeld, Marie Stampe; Jensen, Steffen Grann; Jeppesen, Dennis Kjølhede

    2016-01-01

    Cancer cells secrete small membranous extracellular vesicles (EVs) into their microenvironment and circulation. These contain biomolecules, including proteins and microRNAs (miRNAs). Both circulating EVs and miRNAs have received much attention as biomarker candidates for non-invasive diagnostics...

  7. Tissue inhibitor of metalloproteinase 1 (TIMP-1) as a biomarker in gastric cancer

    DEFF Research Database (Denmark)

    Grunnet, Mie; Mau-Sørensen, Morten; Brünner, Nils

    2013-01-01

    The value of Tissue Inhibitor of MetalloProteinase-1 (TIMP-1) as a biomarker in patients with gastric cancer (GC) is widely debated. The aim of this review is to evaluate available literature describing the association between levels of TIMP-1 in tumor tissue and/or blood and the prognosis...

  8. The recently suggested intestinal cancer stem cell marker DCLK1 is an epigenetic biomarker for colorectal cancer.

    Science.gov (United States)

    Vedeld, Hege Marie; Skotheim, Rolf I; Lothe, Ragnhild A; Lind, Guro E

    2014-03-01

    Recently, Dclk1 expression was identified to be an intestinal cancer stem cell specific biomarker in mouse models, implicating a potential role for targeting the DCLK1-postive cancer cells as a treatment for colorectal cancer. Using quantitative methylation specific PCR (qMSP) we here demonstrated that the DCLK1 promoter is hypermethylated in the vast majority of colorectal cancers (134/164; 82%), with no methylation in the normal mucosa samples (0/106). We further showed by Affymetrix exon arrays that DCLK1 is significantly downregulated in human colorectal cancer (n = 125) compared with normal colonic mucosa (n = 15), which was further confirmed by real-time RT-PCR of a subgroup of the samples. Additionally, a significant negative correlation was observed between methylation and DCLK1 expression in 74 cancer cell lines derived from 15 different tissues, and gene expression increased significantly after epigenetic drug treatment of initially methylated cancer cell lines. These findings underscore the potential of DCLK1 as a colorectal cancer biomarker for early detection, but may also have clinical implications regarding the previously proposed therapy toward DCLK1-positive cancer cells. This therapy would at best affect the cancer stem cell population, but will, based on the present results, not be efficient to treat the bulk of the tumor.

  9. 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.

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

    Science.gov (United States)

    Schmidt, Kamila; Podmore, Ian

    2015-01-01

    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. PMID:26317039

  11. 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.)

  12. Biomarkers in the Detection of Prostate Cancer in African Americans

    Science.gov (United States)

    2015-09-01

    actionable alterations in genes that control PrCa lipid processing and metabolism that may reveal links between diet, obesity and aggressive forms prostate...EN Tables 1-6. Differential Expression of Prostate Biomarkers Associated with Lipid Transport, Syntheses, and metabolism . Previously, Dr. Gaston...and fatty acid binding protein 4 (FABP4) are increased in metabolic syndrome, which is a disorder which includes central obesity and elevated glucose

  13. Microparticles as Biomarkers of Blood Coagulation in Cancer

    Directory of Open Access Journals (Sweden)

    Shosaku Nomura

    2015-01-01

    Full Text Available Cancer is associated with hypercoagulopathy and increased risk of thrombosis. This negatively influences patient morbidity and mortality. Cancer is also frequently complicated by the development of venous thromboembolism (VTE. Tumor-derived tissue factor (TF-bearing microparticles (MPs are associated with VTE events in malignancy. MPs are small membrane vesicles released from many different cell types by exocytic budding of the plasma membrane in response to cellular activation or apoptosis. MPs may also be involved in clinical diseases through expression of procoagulative phospholipids. The detection of TF-expressing MPs in cancer patients may be clinically useful. In lung and breast cancer patients, MPs induce metastasis and angiogenesis and may be indicators of vascular complications. Additionally, MPs in patients with various types of cancer possess adhesion proteins and bind target cells to promoting cancer progression or metastasis. Overexpression of TF by cancer cells is closely associated with tumor progression, and shedding of TF-expressing MPs by cancer cells correlates with the genetic status of cancer. Consequently, TF-expressing MPs represent important markers to consider in the prevention of and therapy for VTE complications in cancer patients.

  14. Fluorous Drug-Affinity Proteomics for Cancer Drug Discovery

    OpenAIRE

    Herzberg, Benjamin

    2015-01-01

    Identifying the intracellular targets of small molecules – target ID – is a major problem in chemical biology with broad application to the discovery and development of novel therapies. Traditional target ID studies have relied on drug-affinity chromatography to separate biological mixtures combined with mass spectrometry shotgun sequencing for peptide identification. This workflow is limited, however, by low specificity for unique peptides, high demand for cellular material, unknown depth of...

  15. 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.

  16. Molecular lipid species in urinary exosomes as potential prostate cancer biomarkers.

    Science.gov (United States)

    Skotland, Tore; Ekroos, Kim; Kauhanen, Dimple; Simolin, Helena; Seierstad, Therese; Berge, Viktor; Sandvig, Kirsten; Llorente, Alicia

    2017-01-01

    Exosomes have recently appeared as a novel source of noninvasive cancer biomarkers, since these nanovesicles contain molecules from cancer cells and can be detected in biofluids. We have here investigated the potential use of lipids in urinary exosomes as prostate cancer biomarkers. A high-throughput mass spectrometry quantitative lipidomic analysis was performed to reveal the lipid composition of urinary exosomes in prostate cancer patients and healthy controls. Control samples were first analysed to characterise the lipidome of urinary exosomes and test the reproducibility of the method. In total, 107 lipid species were quantified in urinary exosomes. Several differences, for example, in cholesterol and phosphatidylcholine, were found between urinary exosomes and exosomes derived from cell lines, thus showing the importance of in vivo studies for biomarker analysis. The 36 most abundant lipid species in urinary exosomes were then quantified in 15 prostate cancer patients and 13 healthy controls. Interestingly, the levels of nine lipids species were found to be significantly different when the two groups were compared. The highest significance was shown for phosphatidylserine (PS) 18:1/18:1 and lactosylceramide (d18:1/16:0), the latter also showed the highest patient-to-control ratio. Furthermore, combinations of these lipid species and PS 18:0-18:2 distinguished the two groups with 93% sensitivity and 100% specificity. Finally, in agreement with the reported dysregulation of sphingolipid metabolism in cancer cells, alteration in specific sphingolipid lipid classes were observed. This study shows for the first time the potential use of exosomal lipid species in urine as prostate cancer biomarkers. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Release of Tissue-specific Proteins into Coronary Perfusate as a Model for Biomarker Discovery in Myocardial Ischemia/Reperfusion Injury

    DEFF Research Database (Denmark)

    Cordwell, Stuart; Edwards, Alistair; Liddy, Kiersten

    2012-01-01

    reperfusion post-15I. Proteins released during irreversible I/R (60I/60R) were profiled using gel-based (2-DE and one-dimensional gel electrophoresis coupled to liquid chromatography and tandem mass spectrometry; geLC–MS) and gel-free (LC–MS/MS) methods. A total of 192 tissue-specific proteins were identified......Diagnosis of acute coronary syndromes is based on protein biomarkers, such as the cardiac troponins (cTnI/cTnT) and creatine kinase (CK-MB) that are released into the circulation. Biomarker discovery is focused on identifying very low abundance tissue-derived analytes from within albumin......-rich plasma, in which the wide dynamic range of the native protein complement hinders classical proteomic investigations. We employed an ex vivo rabbit model of myocardial ischemia/reperfusion (I/R) injury using Langendorff buffer perfusion. Nonrecirculating perfusate was collected over a temporal profile...

  18. Pathway-based discovery of genetic interactions in breast cancer.

    Directory of Open Access Journals (Sweden)

    Wen Wang

    2017-09-01

    Full Text Available Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does

  19. 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.

  20. 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.