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Sample records for cancer biomarker discovery

  1. Biological Networks for Cancer Candidate Biomarkers Discovery

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

    2016-01-01

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

  2. Biological Networks for Cancer Candidate Biomarkers Discovery.

    Science.gov (United States)

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

    2016-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. Cancer Stem Cell Biomarker Discovery Using Antibody Array Technology.

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    Burgess, Rob; Huang, Ruo-Pan

    2016-01-01

    Cancer is a complex disease involving hundreds of pathways and numerous levels of disease progression. In addition, there is a growing body of evidence that the origins and growth rates of specific types of cancer may involve "cancer stem cells," which are defined as "cells within a tumor that possess the capacity to self-renew and to cause the development of heterogeneous lineages of cancer cells that comprise the tumor.(1)" Many types of cancer are now thought to harbor cancer stem cells. These cells themselves are thought to be unique in comparison to other cells types present within the tumor and to exhibit characteristics that allow for the promotion of tumorigenesis and in some cases metastasis. In addition, it is speculated that each type of cancer stem cell exhibits a unique set of molecular and biochemical markers. These markers, alone or in combination, may act as a signature for defining not only the type of cancer but also the progressive state. These biomarkers may also double as signaling entities which act autonomously or upon neighboring cancer stem cells or other cells within the local microenvironment to promote tumorigenesis. This review describes the heterogeneic properties of cancer stem cells and outlines the identification and application of biomarkers and signaling molecules defining these cells as they relate to different forms of cancer. Other examples of biomarkers and signaling molecules expressed by neighboring cells in the local tumor microenvironment are also discussed. In addition, biochemical signatures for cancer stem cell autocrine/paracrine signaling, local site recruitment, tumorigenic potential, and conversion to a stem-like phenotype are described.

  7. Computational and Experimental Approaches to Cancer Biomarker Discovery

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    Krzystanek, Marcin

    Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... was sequenced, assembled and characterized, which is described in the thesis. We are currently using it as a model system in our framework for functional analysis study of DNA repair mechanisms and cytotoxic effects. We hope that the experimentally derived mutational signatures will be useful as a part...... are expected.This work, together with manifold of efforts being done all over the world, is hopefully a step towards implementation of personalized medicine and better treatments for cancer patients. ...

  8. 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.

  9. The Clinical Impact of Recent Advances in LC-MS for Cancer Biomarker Discovery and Verification

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

    2016-01-01

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

  10. 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.

  11. 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.

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

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    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-07-01

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

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

    Science.gov (United States)

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-01-01

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

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

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

    2014-01-01

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

  15. Integrated proteomic analysis of human cancer cells and plasma from tumor bearing mice for ovarian cancer biomarker discovery.

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    Sharon J Pitteri

    Full Text Available The complexity of the human plasma proteome represents a substantial challenge for biomarker discovery. Proteomic analysis of genetically engineered mouse models of cancer and isolated cancer cells and cell lines provide alternative methods for identification of potential cancer markers that would be detectable in human blood using sensitive assays. The goal of this work is to evaluate the utility of an integrative strategy using these two approaches for biomarker discovery.We investigated a strategy that combined quantitative plasma proteomics of an ovarian cancer mouse model with analysis of proteins secreted or shed by human ovarian cancer cells. Of 106 plasma proteins identified with increased levels in tumor bearing mice, 58 were also secreted or shed from ovarian cancer cells. The remainder consisted primarily of host-response proteins. Of 25 proteins identified in the study that were assayed, 8 mostly secreted proteins common to mouse plasma and human cancer cells were significantly upregulated in a set of plasmas from ovarian cancer patients. Five of the eight proteins were confirmed to be upregulated in a second independent set of ovarian cancer plasmas, including in early stage disease.Integrated proteomic analysis of cancer mouse models and human cancer cell populations provides an effective approach to identify potential circulating protein biomarkers.

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

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

    2015-07-01

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

  17. Translating discovery in zebrafish pancreatic development to human pancreatic cancer: biomarkers, targets, pathogenesis, and therapeutics.

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    Yee, Nelson S; Kazi, Abid A; Yee, Rosemary K

    2013-06-01

    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.

  18. 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.

  19. Glycoproteomics using so-called ‘fluid-biopsy’ specimens in the discovery of lung cancer biomarkers. Promise and challenge

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    Li, Qing Kay; Gabrielson, Ed; Askin, Frederic; Chan, Daniel W; Zhang, Hui

    2016-01-01

    Lung cancer is the number one cancer in the US and worldwide. In spite of the rapid progression in personalized treatments, the overall survival rate of lung cancer patients is still suboptimal. Over the past decade, tremendous efforts have been focused on the discovery of protein biomarkers to facilitate the early detection and monitoring lung cancer progression during treatment. In addition to tumor tissues and cancer cell lines, a variety of biological material has been studied. Particularly in recent years, studies using fluid-based specimen or so-called “fluid-biopsy” specimen have progressed rapidly. Fluid specimens are relatively easier to collect than tumor tissue, and they can be repeatedly sampled during the disease progression. Glycoproteins have long been recognized to play fundamental roles in many physiological and pathological processes. In this review, we focus the discussion on recent advances of glycoproteomics, particularly in the identification of potential protein biomarkers using so-called fluid-based specimens in lung cancer. The purpose of this review is to summarize current strategies, achievements and perspectives in the field. This insight will highlight the discovery of tumor-associated glycoprotein biomarkers in lung cancer and their potential clinical applications. PMID:23112109

  20. 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

    and healthy individuals to identify circulating O-glycoproteins with the STn glycoform. We identified 37 O-glycoproteins in the pool of cancer sera, and only 9 of these were also found in sera from healthy individuals. Two identified candidate O-glycoprotein biomarkers (CD44 and GalNAc-T5) circulating...

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

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    Choolani Mahesh

    2011-09-01

    Full Text Available Abstract 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.

  2. 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.

  3. Discovery and validation of DNA hypomethylation biomarkers for liver cancer using HRM-specific probes.

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    Barbara Stefanska

    Full Text Available Poor prognosis of hepatocellular carcinoma (HCC associated with late diagnosis necessitates the development of early diagnostic biomarkers. We have previously delineated the landscape of DNA methylation in HCC patients unraveling the importance of promoter hypomethylation in activation of cancer- and metastasis-driving genes. The purpose of the present study was to test the feasibility that genes that are hypomethylated in HCC could serve as candidate diagnostic markers. We use high resolution melting analysis (HRM as a simple translatable PCR-based method to define methylation states in clinical samples. We tested seven regions selected from the shortlist of genes hypomethylated in HCC and showed that HRM analysis of several of them distinguishes methylation states in liver cancer specimens from normal adjacent liver and chronic hepatitis in the Shanghai area. Such regions were identified within promoters of neuronal membrane glycoprotein M6-B (GPM6B and melanoma antigen family A12 (MAGEA12 genes. Differences in HRM in the immunoglobulin superfamily Fc receptor (FCRL1 separated invasive tumors from less invasive HCC. The identified biomarkers differentiated HCC from chronic hepatitis in another set of samples from Dhaka. Although the main thrust in DNA methylation diagnostics in cancer is on hypermethylated genes, our study for the first time illustrates the potential use of hypomethylated genes as markers for solid tumors. After further validation in a larger cohort, the identified DNA hypomethylated regions can become important candidate biomarkers for liver cancer diagnosis and prognosis, especially in populations with high risk for HCC development.

  4. Unlocking biomarker discovery: large scale application of aptamer proteomic technology for early detection of lung cancer.

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    Rachel M Ostroff

    Full Text Available BACKGROUND: Lung cancer is the leading cause of cancer deaths worldwide. New diagnostics are needed to detect early stage lung cancer because it may be cured with surgery. However, most cases are diagnosed too late for curative surgery. Here we present a comprehensive clinical biomarker study of lung cancer and the first large-scale clinical application of a new aptamer-based proteomic technology to discover blood protein biomarkers in disease. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a multi-center case-control study in archived serum samples from 1,326 subjects from four independent studies of non-small cell lung cancer (NSCLC in long-term tobacco-exposed populations. Sera were collected and processed under uniform protocols. Case sera were collected from 291 patients within 8 weeks of the first biopsy-proven lung cancer and prior to tumor removal by surgery. Control sera were collected from 1,035 asymptomatic study participants with ≥ 10 pack-years of cigarette smoking. We measured 813 proteins in each sample with a new aptamer-based proteomic technology, identified 44 candidate biomarkers, and developed a 12-protein panel (cadherin-1, CD30 ligand, endostatin, HSP90α, LRIG3, MIP-4, pleiotrophin, PRKCI, RGM-C, SCF-sR, sL-selectin, and YES that discriminates NSCLC from controls with 91% sensitivity and 84% specificity in cross-validated training and 89% sensitivity and 83% specificity in a separate verification set, with similar performance for early and late stage NSCLC. CONCLUSIONS/SIGNIFICANCE: This study is a significant advance in clinical proteomics in an area of high unmet clinical need. Our analysis exceeds the breadth and dynamic range of proteome interrogated of previously published clinical studies of broad serum proteome profiling platforms including mass spectrometry, antibody arrays, and autoantibody arrays. The sensitivity and specificity of our 12-biomarker panel improves upon published protein and gene expression panels

  5. 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.

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

    International Nuclear Information System (INIS)

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

  7. Glycoscience aids in biomarker discovery

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    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.

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

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    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.

  9. Profiling of circulating microRNAs for prostate cancer biomarker discovery

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

    2014-01-01

    Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary...... 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...

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

    Science.gov (United States)

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

    2010-03-01

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

  11. Biomarkers in precision therapy in colorectal cancer

    OpenAIRE

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

    2013-01-01

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

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

    OpenAIRE

    Jianwen She; Wei Zou; Vladimir V. Tolstikov

    2013-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

  14. Proteomic Approaches for Biomarker Panels in Cancer.

    Science.gov (United States)

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

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

  15. Stable Feature Selection for Biomarker Discovery

    CERN Document Server

    He, Zengyou

    2010-01-01

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

  16. Novel diagnostic biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Chikezie O. Madu, Yi Lu

    2010-01-01

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

  17. Novel diagnostic biomarkers for prostate cancer.

    Science.gov (United States)

    Madu, Chikezie O; Lu, Yi

    2010-10-06

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

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

    Science.gov (United States)

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

    2016-01-01

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

  19. Proteomics Discovery of Disease Biomarkers

    OpenAIRE

    Mamoun Ahram; Petricoin, Emanuel F.

    2008-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Wanling Yang; Dingge Ying; Yu-Lung Lau

    2009-01-01

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

  1. 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.

  2. 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.

  3. Biomarkers in Prostate Cancer Epidemiology

    Directory of Open Access Journals (Sweden)

    Mudit Verma

    2011-09-01

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

  4. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

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

    2015-01-01

    in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance...... of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before...

  5. Cancer Biomarkers | Division of Cancer Prevention

    Science.gov (United States)

    This group promotes research to identify, develop, and validate biological markers for early cancer detection and cancer risk assessment. | Research to identify, develop and validate biomarkers for early cancer detection and risk assessment.

  6. 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.

  7. Epigenetic biomarkers in liver cancer.

    Science.gov (United States)

    Banaudha, Krishna K; Verma, Mukesh

    2015-01-01

    Liver cancer (hepatocellular carcinoma or HCC) is a major cancer worldwide. Research in this field is needed to identify biomarkers that can be used for early detection of the disease as well as new approaches to its treatment. Epigenetic biomarkers provide an opportunity to understand liver cancer etiology and evaluate novel epigenetic inhibitors for treatment. Traditionally, liver cirrhosis, proteomic biomarkers, and the presence of hepatitis viruses have been used for the detection and diagnosis of liver cancer. Promising results from microRNA (miRNA) profiling and hypermethylation of selected genes have raised hopes of identifying new biomarkers. Some of these epigenetic biomarkers may be useful in risk assessment and for screening populations to identify who is likely to develop cancer. Challenges and opportunities in the field are discussed in this chapter.

  8. Current technological challenges in biomarker discovery and validation

    NARCIS (Netherlands)

    Horvatovich, Peter L.; Bischoff, Rainer

    2010-01-01

    In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It

  9. 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.

  10. Biomarkers in Prostate Cancer Epidemiology

    OpenAIRE

    Mudit Verma; Mukesh Verma; Payal Patel

    2011-01-01

    Understanding the etiology of a disease such as prostate cancer may help in identifying populations at high risk, timely intervention of the disease, and proper treatment. Biomarkers, along with exposure history and clinical data, are useful tools to achieve these goals. Individual risk and population incidence of prostate cancer result from the intervention of genetic susceptibility and exposure. Biochemical, epigenetic, genetic, and imaging biomarkers are used to identify people at high ris...

  11. Current and emerging breast cancer biomarkers

    Directory of Open Access Journals (Sweden)

    Maryam Sana

    2015-01-01

    Full Text Available Breast cancer treatment has experienced several advancements in the past few decades with the discovery of specific predictive and prognostic biomarkers that make possible the application of individualized therapies. In addition to traditional prognostic factors of breast carcinoma, molecular biomarkers have played a significant role in tumor prediction and treatment. The most frequent genetic alterations of breast cancer are gained along chromosome 1q, 8q, 17q, 20q, and 11q and losses along 8p, 13q, 16q, 18q, and 11q. Interestingly, many of these chromosomal fragments harbor known proto oncogenes or tumor suppressor genes such as BRCA1, BRCA2, p53, HER2-neu, cyclin D1, and cyclin E, which are briefly described in this review.

  12. Proteomics in Discovery of Hepatocellular Carcinoma Biomarkers

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  13. Serum Glycoprotein Biomarker Discovery and Qualification Pipeline Reveals Novel Diagnostic Biomarker Candidates for Esophageal Adenocarcinoma.

    Science.gov (United States)

    Shah, Alok K; Cao, Kim-Anh Lê; Choi, Eunju; Chen, David; Gautier, Benoît; Nancarrow, Derek; Whiteman, David C; Saunders, Nicholas A; Barbour, Andrew P; Joshi, Virendra; Hill, Michelle M

    2015-11-01

    We report an integrated pipeline for efficient serum glycoprotein biomarker candidate discovery and qualification that may be used to facilitate cancer diagnosis and management. The discovery phase used semi-automated lectin magnetic bead array (LeMBA)-coupled tandem mass spectrometry with a dedicated data-housing and analysis pipeline; GlycoSelector (http://glycoselector.di.uq.edu.au). The qualification phase used lectin magnetic bead array-multiple reaction monitoring-mass spectrometry incorporating an interactive web-interface, Shiny mixOmics (http://mixomics-projects.di.uq.edu.au/Shiny), for univariate and multivariate statistical analysis. Relative quantitation was performed by referencing to a spiked-in glycoprotein, chicken ovalbumin. We applied this workflow to identify diagnostic biomarkers for esophageal adenocarcinoma (EAC), a life threatening malignancy with poor prognosis in the advanced setting. EAC develops from metaplastic condition Barrett's esophagus (BE). Currently diagnosis and monitoring of at-risk patients is through endoscopy and biopsy, which is expensive and requires hospital admission. Hence there is a clinical need for a noninvasive diagnostic biomarker of EAC. In total 89 patient samples from healthy controls, and patients with BE or EAC were screened in discovery and qualification stages. Of the 246 glycoforms measured in the qualification stage, 40 glycoforms (as measured by lectin affinity) qualified as candidate serum markers. The top candidate for distinguishing healthy from BE patients' group was Narcissus pseudonarcissus lectin (NPL)-reactive Apolipoprotein B-100 (p value = 0.0231; AUROC = 0.71); BE versus EAC, Aleuria aurantia lectin (AAL)-reactive complement component C9 (p value = 0.0001; AUROC = 0.85); healthy versus EAC, Erythroagglutinin Phaseolus vulgaris (EPHA)-reactive gelsolin (p value = 0.0014; AUROC = 0.80). A panel of 8 glycoforms showed an improved AUROC of 0.94 to discriminate EAC from BE. Two biomarker candidates

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

    Science.gov (United States)

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

    2014-05-01

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

  15. Nanostructured optical microchips for cancer biomarker detection.

    Science.gov (United States)

    Zhang, Tianhua; He, Yuan; Wei, Jianjun; Que, Long

    2012-01-01

    Herein we report the label-free detection of a cancer biomarker using newly developed arrayed nanostructured Fabry-Perot interferometer (FPI) microchips. Specifically, the prostate cancer biomarker free prostate-specific antigen (f-PSA) has been detected with a mouse anti-human PSA monoclonal antibody (mAb) as the receptor. Experiments found that the limit-of-detection of current nanostructured FPI microchip for f-PSA is about 10 pg/mL and the upper detection range for f-PSA can be dynamically changed by varying the amount of the PSA mAb immobilized on the sensing surface. The control experiments have also demonstrated that the immunoassay protocol used in the experiments shows excellent specificity and selectivity, suggesting the great potential to detect the cancer biomarkers at trace levels in complex biofluids. In addition, given its nature of low cost, simple-to-operation and batch fabrication capability, the arrayed nanostructured FPI microchip-based platform could provide an ideal technical tool for point-of-care diagnostics application and anticancer drug screen and discovery.

  16. 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

  17. 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

    2013-12-01

    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.

  18. Novel technologies and emerging biomarkers for personalized cancer immunotherapy.

    Science.gov (United States)

    Yuan, Jianda; Hegde, Priti S; Clynes, Raphael; Foukas, Periklis G; Harari, Alexandre; Kleen, Thomas O; Kvistborg, Pia; Maccalli, Cristina; Maecker, Holden T; Page, David B; Robins, Harlan; Song, Wenru; Stack, Edward C; Wang, Ena; Whiteside, Theresa L; Zhao, Yingdong; Zwierzina, Heinz; Butterfield, Lisa H; Fox, Bernard A

    2016-01-01

    The culmination of over a century's work to understand the role of the immune system in tumor control has led to the recent advances in cancer immunotherapies that have resulted in durable clinical responses in patients with a variety of malignancies. Cancer immunotherapies are rapidly changing traditional treatment paradigms and expanding the therapeutic landscape for cancer patients. However, despite the current success of these therapies, not all patients respond to immunotherapy and even those that do often experience toxicities. Thus, there is a growing need to identify predictive and prognostic biomarkers that enhance our understanding of the mechanisms underlying the complex interactions between the immune system and cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) reconvened an Immune Biomarkers Task Force to review state of the art technologies, identify current hurdlers, and make recommendations for the field. As a product of this task force, Working Group 2 (WG2), consisting of international experts from academia and industry, assembled to identify and discuss promising technologies for biomarker discovery and validation. Thus, this WG2 consensus paper will focus on the current status of emerging biomarkers for immune checkpoint blockade therapy and discuss novel technologies as well as high dimensional data analysis platforms that will be pivotal for future biomarker research. In addition, this paper will include a brief overview of the current challenges with recommendations for future biomarker discovery.

  19. 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.

  20. 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

  1. PET Metabolic Biomarkers for Cancer

    Science.gov (United States)

    Croteau, Etienne; Renaud, Jennifer M.; Richard, Marie Anne; Ruddy, Terrence D.; Bénard, François; deKemp, Robert A.

    2016-01-01

    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 18F-fluorodeoxyglucose (18F-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.

  2. Biomarkers of HIV-associated Cancer

    OpenAIRE

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

    2014-01-01

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

  3. Exhaled Breath Condensate for Proteomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Sean W. Harshman

    2014-07-01

    Full Text Available Exhaled breath condensate (EBC has been established as a potential source of respiratory biomarkers. Compared to the numerous small molecules identified, the protein content of EBC has remained relatively unstudied due to the methodological and technical difficulties surrounding EBC analysis. In this review, we discuss the proteins identified in EBC, by mass spectrometry, focusing on the significance of those proteins identified. We will also review the limitations surrounding mass spectral EBC protein analysis emphasizing recommendations to enhance EBC protein identifications by mass spectrometry. Finally, we will provide insight into the future directions of the EBC proteomics field.

  4. MicroRNA signatures as clinical biomarkers in lung cancer

    Directory of Open Access Journals (Sweden)

    Markou A

    2015-05-01

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

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

    Science.gov (United States)

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

    2012-04-01

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

  6. 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

  7. Emerging concepts in biomarker discovery; the US-Japan Workshop on Immunological Molecular Markers in Oncology.

    Science.gov (United States)

    Tahara, Hideaki; Sato, Marimo; Thurin, Magdalena; Wang, Ena; Butterfield, Lisa H; Disis, Mary L; Fox, Bernard A; Lee, Peter P; Khleif, Samir N; Wigginton, Jon M; Ambs, Stefan; Akutsu, Yasunori; Chaussabel, Damien; Doki, Yuichiro; Eremin, Oleg; Fridman, Wolf Hervé; Hirohashi, Yoshihiko; Imai, Kohzoh; Jacobson, James; Jinushi, Masahisa; Kanamoto, Akira; Kashani-Sabet, Mohammed; Kato, Kazunori; Kawakami, Yutaka; Kirkwood, John M; Kleen, Thomas O; Lehmann, Paul V; Liotta, Lance; Lotze, Michael T; Maio, Michele; Malyguine, Anatoli; Masucci, Giuseppe; Matsubara, Hisahiro; Mayrand-Chung, Shawmarie; Nakamura, Kiminori; Nishikawa, Hiroyoshi; Palucka, A Karolina; Petricoin, Emanuel F; Pos, Zoltan; Ribas, Antoni; Rivoltini, Licia; Sato, Noriyuki; Shiku, Hiroshi; Slingluff, Craig L; Streicher, Howard; Stroncek, David F; Takeuchi, Hiroya; Toyota, Minoru; Wada, Hisashi; Wu, Xifeng; Wulfkuhle, Julia; Yaguchi, Tomonori; Zeskind, Benjamin; Zhao, Yingdong; Zocca, Mai-Britt; Marincola, Francesco M

    2009-06-17

    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 were recognized that

  8. 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.

  9. PROFILEing idiopathic pulmonary fibrosis: rethinking biomarker discovery.

    Science.gov (United States)

    Maher, Toby M

    2013-06-01

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

  10. 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.

  11. Early Detection Biomarkers for Ovarian Cancer

    Directory of Open Access Journals (Sweden)

    Sreeja Sarojini

    2012-01-01

    Full Text Available Despite the widespread use of conventional and contemporary methods to detect ovarian cancer development, ovarian cancer remains a common and commonly fatal gynecological malignancy. The identification and validation of early detection biomarkers highly specific to ovarian cancer, which would permit development of minimally invasive screening methods for detecting early onset of the disease, are urgently needed. Current practices for early detection of ovarian cancer include transvaginal ultrasonography, biomarker analysis, or a combination of both. In this paper we review recent research on novel and robust biomarkers for early detection of ovarian cancer and provide specific details on their contributions to tumorigenesis. Promising biomarkers for early detection of ovarian cancer include KLK6/7, GSTT1, PRSS8, FOLR1, ALDH1, and miRNAs.

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

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    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

  13. 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.

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2015-01-01

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

  16. New serum biomarkers for prostate cancer diagnosis

    OpenAIRE

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

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2013-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    He Qing-Yu; Chiu Jen-Fu

    2004-01-01

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

  19. 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.

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

    International Nuclear Information System (INIS)

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

  1. Role of proteomics in the discovery of autism biomarkers

    International Nuclear Information System (INIS)

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

  2. Nanomaterials based biosensors for cancer biomarker detection

    Science.gov (United States)

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

    2016-04-01

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

  3. 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.

  4. 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 va

  5. Proteome-based biomarkers in pancreatic cancer

    Institute of Scientific and Technical Information of China (English)

    Chen Sun; Ann H Rosendahl; Daniel Ansari; Roland Andersson

    2011-01-01

    Pancreatic cancer, as a highly malignant cancer and the fourth cause of cancer-related death in world, is characterized by dismal prognosis, due to rapid disease progression, highly invasive tumour phenotype, and resistance to chemotherapy. Despite significant advances in treatment of the disease during the past decade,the survival rate is little improved. A contributory factor to the poor outcome is the lack of appropriate sensitive and specific biomarkers for early diagnosis. Furthermore, biomarkers for targeting, directing and assessing therapeutic intervention, as well as for detection of residual or recurrent cancer are also needed. Thus, the identification of adequate biomarkers in pancreatic cancer is of extreme importance. Recently, accompanying the development of proteomic technology and devices, more and more potential biomarkers have appeared and are being reported. In this review, we provide an overview of the role of proteome-based biomarkers in pancreatic cancer, including tissue, serum, juice, urine and cell lines. We also discuss the possible mechanism and prospects in the future. That information hopefully might be helpful for further research in the field.

  6. DETECTION OF CANCER BIOMARKERS WITH NANOTECHNOLOGY

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Pia Davidsson

    2005-01-01

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

  8. Molecular Imaging of Biomarkers in Breast Cancer

    Science.gov (United States)

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

    2016-01-01

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

  9. The National Cancer Program: Driving Discovery

    Science.gov (United States)

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

  10. 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.

  11. Discovery – Methotrexate: Chemotherapy Treatment for Cancer

    Science.gov (United States)

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

  12. Identification of Biomarkers for Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Anna Meiliana

    2014-12-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  15. Using Aptamers for Cancer Biomarker Discovery

    OpenAIRE

    Yun Min Chang; Donovan, Michael J; Weihong Tan

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tsubouchi Hirohito

    2010-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Tatiana Altadill

    Full Text Available Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported using Exosomes-Like Vesicles (ELVs from different sources, exosomal metabolome characterization and its modulation in health and disease remains to be elucidated. Here we describe methodologies for UPLC-ESI-MS based small molecule profiling of ELVs from human plasma and cell culture media. In this study, we present evidence that indeed ELVs carry a rich metabolome that could not only augment the discovery of low abundance biomarkers but may also help explain the molecular basis of disease progression. This approach could be easily translated to other studies seeking to develop predictive biomarkers that can subsequently be used with simplified targeted approaches.

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

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

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

  19. 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.

  20. Biomarkers and Pharmacogenetics in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Xunhai Xu

    2011-07-01

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

  1. 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.

  2. Milestones in Cancer Research and Discovery

    Science.gov (United States)

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

  3. 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

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

    Science.gov (United States)

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

    2015-09-01

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

  5. 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...

  6. Translating colorectal cancer genetics into clinically useful biomarkers.

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

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

    2013-11-01

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

  8. New serum biomarkers for prostate cancer diagnosis

    Directory of Open Access Journals (Sweden)

    Kailash C Chadha

    2014-01-01

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

  9. 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

  10. Role of Systems Biology in Brain Injury Biomarker Discovery: Neuroproteomics Application.

    Science.gov (United States)

    Jaber, Zaynab; Aouad, Patrick; Al Medawar, Mohamad; Bahmad, Hisham; Abou-Abbass, Hussein; Ghandour, Hiba; Mondello, Stefania; Kobeissy, Firas

    2016-01-01

    Years of research in the field of neurotrauma have led to the concept of applying systems biology as a tool for biomarker discovery in traumatic brain injury (TBI). Biomarkers may lead to understanding mechanisms of injury and recovery in TBI and can be potential targets for wound healing, recovery, and increased survival with enhanced quality of life. The literature available on neurotrauma studies from both animal and clinical studies has provided rich insight on the molecular pathways and complex networks of TBI, elucidating the proteomics of this disease for the discovery of biomarkers. With such a plethora of information available, the data from the studies require databases with tools to analyze and infer new patterns and associations. The role of different systems biology tools and their use in biomarker discovery in TBI are discussed in this chapter. PMID:27604718

  11. Testicular cancer: biology and biomarkers.

    Science.gov (United States)

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

    2014-03-01

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

  12. 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...

  13. Hypermethylated DNA, a Biomarker for colorectal cancer

    DEFF Research Database (Denmark)

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

    2016-01-01

    AIM: In colorectal cancer (CRC), improved methods for early detection are essential for increasing survival. Hypermethylated DNA in blood or stool has been proposed as a biomarker for CRC. In recent years, biochemical methods have improved, and several hypermethylated genes that are sensitive....... In blood samples, hypermethylated P16, HLTF, TMEFF1, ALX4, VIM, and FBN2 were associated with poor prognosis, hypermethylated APC, TAC1, SEPT9, NEUROG1, RASSF1A, SDC2, and THBD were detected in early-stage CRC, and hypermethylated P16 and TFPI2 could detect CRC recurrence. In stool samples, hypermethylated...

  14. 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.

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

    Institute of Scientific and Technical Information of China (English)

    Yu Shi; Daoqing Dai; Chaochun Liu; Hong Yan

    2009-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  17. Colorectal Cancer Biomarkers: Where Are We Now?

    Directory of Open Access Journals (Sweden)

    Maria Gonzalez-Pons

    2015-01-01

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

  18. Methylated genes as new cancer biomarkers

    DEFF Research Database (Denmark)

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

    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 meas......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...

  19. Systems biology of cancer biomarker detection.

    Science.gov (United States)

    Mitra, Sanga; Das, Smarajit; Chakrabarti, Jayprokas

    2013-01-01

    Cancer systems-biology is an ever-growing area of research due to explosion of data; how to mine these data and extract useful information is the problem. To have an insight on carcinogenesis one need to systematically mine several resources, such as databases, microarray and next-generation sequences. This review encompasses management and analysis of cancer data, databases construction and data deposition, whole transcriptome and genome comparison, analysing results from high throughput experiments to uncover cellular pathways and molecular interactions, and the design of effective algorithms to identify potential biomarkers. Recent technical advances such as ChIP-on-chip, ChIP-seq and RNA-seq can be applied to get epigenetic information transformed into a high-throughput endeavour to which systems biology and bioinformatics are making significant inroads. The data from ENCODE and GENCODE projects available through UCSC genome browser can be considered as benchmark for comparison and meta-analysis. A pipeline for integrating next generation sequencing data, microarray data, and putting them together with the existing database is discussed. The understanding of cancer genomics is changing the way we approach cancer diagnosis and treatment. To give a better understanding of utilizing available resources' we have chosen oral cancer to show how and what kind of analysis can be done. This review is a computational genomic primer that provides a bird's eye view of computational and bioinformatics' tools currently available to perform integrated genomic and system biology analyses of several carcinoma.

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

    Directory of Open Access Journals (Sweden)

    William C. S. Cho

    2011-02-01

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

  1. Approach to cerebrospinal fluid (CSF) biomarker discovery and evaluation in HIV infection.

    Science.gov (United States)

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

    2013-12-01

    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. Previously-defined 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.

  2. Emerging Therapeutic Biomarkers in Endometrial Cancer

    Directory of Open Access Journals (Sweden)

    Peixin Dong

    2013-01-01

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

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

    OpenAIRE

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

    2012-01-01

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

  4. 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.

  5. 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.

  6. Identification of cancer protein biomarkers using proteomic techniques

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-02-23

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

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

    Directory of Open Access Journals (Sweden)

    Bonella F

    2015-07-01

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

  8. 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....

  9. Manifold Learning for Biomarker Discovery in MR Imaging

    Science.gov (United States)

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

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

  10. 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

    and III breast cancer therapy trials (Chemo-N0, NNBC-3 and Plan B), and introduces ongoing clinical trials targeting uPA in advanced cancers of the breast and pancreas, employing synthetic small-size drugs to counteract uPA activity (WX-UK1, Mesupron(®)). The therapeutic effect of a uPA-derived small......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......-type plasminogen activator (uPA) and its inhibitor plasminogen activator inhibitor type 1 (PAI-1) are two of the few tumor tissue-associated cancer biomarkers that have been evaluated successfully and extensively in many preclinical and clinical studies for their clinical utility. Most of the studies have been...

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

    OpenAIRE

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

    2016-01-01

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

  12. 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.

  13. Far Beyond the Usual Biomarkers in Breast Cancer: A Review

    Science.gov (United States)

    dos Anjos Pultz, Brunna; da Luz, Felipe Andrés Cordero; de Faria, Paulo Rogério; Oliveira, Ana Paula Lima; de Araújo, Rogério Agenor; Silva, Marcelo José Barbosa

    2014-01-01

    Research investigating biomarkers for early detection, prognosis and the prediction of treatment responses in breast cancer is rapidly expanding. However, no validated biomarker currently exists for use in routine clinical practice, and breast cancer detection and management remains dependent on invasive procedures. Histological examination remains the standard for diagnosis, whereas immunohistochemical and genetic tests are utilized for treatment decisions and prognosis determinations. Therefore, we conducted a comprehensive review of literature published in PubMed on breast cancer biomarkers between 2009 and 2013. The keywords that were used together were breast cancer, biomarkers, diagnosis, prognosis and drug response. The cited references of the manuscripts included in this review were also screened. We have comprehensively summarized the performance of several biomarkers for diagnosis, prognosis and predicted drug responses of breast cancer. Finally, we have identified 15 biomarkers that have demonstrated promise in initial studies and several miRNAs. At this point, such biomarkers must be rigorously validated in the clinical setting to be translated into clinically useful tests for the diagnosis, prognosis and prediction of drug responses of breast cancer. PMID:25057307

  14. 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.

  15. 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 rece

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

    NARCIS (Netherlands)

    Horvatovich, P.; Govorukhina, N.I; 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 rece

  17. A Critical Assessment of Feature Selection Methods for Biomarker Discovery in Clinical Proteomics

    NARCIS (Netherlands)

    Christin, Christin; Hoefsloot, Huub C. J.; Smilde, Age K.; Hoekman, B.; Suits, Frank; Bischoff, Rainer; Horvatovich, Peter

    2013-01-01

    In this paper, we compare the performance of six different feature selection methods for LC-MS-based proteomics and metabolomics biomarker discovery-t test, the Mann-Whitney-Wilcoxon test (mww test), nearest shrunken centroid (NSC), linear support vector machine-recursive features elimination (SVM-R

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2016-07-21

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

  20. 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.

  1. 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

  2. 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.

  3. Targeting autophagic pathways for cancer drug discovery

    Institute of Scientific and Technical Information of China (English)

    Bo Liu; Jin-Ku Bao; Jin-Ming Yang; Yan Cheng

    2013-01-01

    Autophagy,an evolutionarily conserved lysosomal degradation process,has drawn an increasing amount of attention in recent years for its role in a variety of human diseases,such as cancer.Notably,autophagy plays an important role in regulating several survival and death signaling pathways that determine cell fate in cancer.To date,substantial evidence has demonstrated that some key autophagic mediators,such as autophagy-related genes (ATGs),PI3K,mTOR,p53,and Beclin-1,may play crucial roles in modulating autophagic activity in cancer initiation and progression.Because autophagy-modulating agents such as rapamycin and chloroquine have already been used clinically to treat cancer,it is conceivable that targeting autophagic pathways may provide a new opportunity for discovery and development of more novel cancer therapeutics.With a deeper understanding of the regulatory mechanisms governing autophagy,we will have a better opportunity to facilitate the exploitation of autophagy as a target for therapeutic intervention in cancer.This review discusses the current status of targeting autophagic pathways as a potential cancer therapy.

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

    Directory of Open Access Journals (Sweden)

    Theresa L Whiteside

    2013-05-01

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

  5. 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.

  6. Prognostic and therapeutic value of mitochondrial serine hydroxyl-methyltransferase 2 as a breast cancer biomarker

    Science.gov (United States)

    Zhang, Lahong; Chen, Zhaojun; Xue, Dan; Zhang, Qi; Liu, Xiyong; Luh, Frank; Hong, Liquan; Zhang, Hang; Pan, Feng; Liu, Yuhua; Chu, Peiguo; Zheng, Shu; Lou, Guoqiang; Yen, Yun

    2016-01-01

    Mitochondrial serine hydroxylmethyltransferase 2 (SHMT2) is a key enzyme in the serine/glycine synthesis pathway. SHMT2 has been implicated as a critical component for tumor cell survival. The aim of the present study was to evaluate the prognostic value and efficiency of SHMT2 as a biomarker in patients with breast cancer. Individual and pooled survival analyses were performed on five independent breast cancer microarray datasets. Gene signatures enriched by SHMT2 were also analyzed in these datasets. SHMT2 protein expression was detected using immunohistochemistry (IHC) assay in 128 breast cancer cases. Gene set enrichment analysis revealed that SHMT2 was significantly associated with gene signatures of mitochondrial module, cancer invasion, metastasis and poor survival among breast cancer patients (paggressiveness (TNM staging and Elson grade) in a dose-dependent manner (p<0.05). The prognostic performance of SHMT2 mRNA was comparable to other gene signatures and proved superior to TNM staging. Further analysis results indicated that SHMT2 had better prognostic value for estrogen receptor (ER)-negative breast cancer patients, compared to ER-positive patients. In cases involving stage IIb breast cancer, chemotherapy significantly extended survival time among patients with high SHMT2 expression. These results indicate that SHMT2 may be a valuable prognostic biomarker in ER-negative breast cancer cases. Furthermore, SHMT2 may be a potential target for breast cancer treatment and drug discovery. PMID:27666119

  7. Development of urinary pseudotargeted LC-MS-based metabolomics method and its application in hepatocellular carcinoma biomarker discovery.

    Science.gov (United States)

    Shao, Yaping; Zhu, Bin; Zheng, Ruiyin; Zhao, Xinjie; Yin, Peiyuan; Lu, Xin; Jiao, Binghua; Xu, Guowang; Yao, Zhenzhen

    2015-02-01

    Hepatocellular carcinoma (HCC) is one of the pestilent malignancies leading to cancer-related death. Discovering effective biomarkers for HCC diagnosis is an urgent demand. To identify potential metabolite biomarkers, we developed a urinary pseudotargeted method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Compared with nontargeted method, the pseudotargeted method can achieve better data quality, which benefits differential metabolites discovery. The established method was applied to cirrhosis (CIR) and HCC investigation. It was found that urinary nucleosides, bile acids, citric acid, and several amino acids were significantly changed in liver disease groups compared with the controls, featuring the dysregulation of purine metabolism, energy metabolism, and amino metabolism in liver diseases. Furthermore, some metabolites such as cyclic adenosine monophosphate, glutamine, and short- and medium-chain acylcarnitines were the differential metabolites of HCC and CIR. On the basis of binary logistic regression, butyrylcarnitine (carnitine C4:0) and hydantoin-5-propionic acid were defined as combinational markers to distinguish HCC from CIR. The area under curve was 0.786 and 0.773 for discovery stage and validation stage samples, respectively. These data show that the established pseudotargeted method is a complementary one of targeted and nontargeted methods for metabolomics study.

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

    Science.gov (United States)

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

  9. Cancer Salivary Biomarkers for Tumours Distant to the Oral Cavity

    Directory of Open Access Journals (Sweden)

    Óscar Rapado-González

    2016-09-01

    Full Text Available The analysis of saliva as a diagnostic approach for systemic diseases was proposed just two decades ago, but recently great interest in the field has emerged because of its revolutionary potential as a liquid biopsy and its usefulness as a non-invasive sampling method. Multiple molecules isolated in saliva have been proposed as cancer biomarkers for diagnosis, prognosis, drug monitoring and pharmacogenetic studies. In this review, we focus on the current status of the salivary diagnostic biomarkers for different cancers distant to the oral cavity, noting their potential use in the clinic and their applicability in personalising cancer therapies.

  10. Cancer Salivary Biomarkers for Tumours Distant to the Oral Cavity

    Science.gov (United States)

    Rapado-González, Óscar; Majem, Blanca; Muinelo-Romay, Laura; López-López, Rafa; Suarez-Cunqueiro, María Mercedes

    2016-01-01

    The analysis of saliva as a diagnostic approach for systemic diseases was proposed just two decades ago, but recently great interest in the field has emerged because of its revolutionary potential as a liquid biopsy and its usefulness as a non-invasive sampling method. Multiple molecules isolated in saliva have been proposed as cancer biomarkers for diagnosis, prognosis, drug monitoring and pharmacogenetic studies. In this review, we focus on the current status of the salivary diagnostic biomarkers for different cancers distant to the oral cavity, noting their potential use in the clinic and their applicability in personalising cancer therapies. PMID:27626410

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

    OpenAIRE

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

    2013-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

  13. Strategies for discovery and validation of methylated and hydroxymethylated DNA biomarkers.

    Science.gov (United States)

    Olkhov-Mitsel, Ekaterina; Bapat, Bharati

    2012-10-01

    DNA methylation, consisting of the addition of a methyl group at the fifth-position of cytosine in a CpG dinucleotide, is one of the most well-studied epigenetic mechanisms in mammals with important functions in normal and disease biology. Disease-specific aberrant DNA methylation is a well-recognized hallmark of many complex diseases. Accordingly, various studies have focused on characterizing unique DNA methylation marks associated with distinct stages of disease development as they may serve as useful biomarkers for diagnosis, prognosis, prediction of response to therapy, or disease monitoring. Recently, novel CpG dinucleotide modifications with potential regulatory roles such as 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine have been described. These potential epigenetic marks cannot be distinguished from 5-methylcytosine by many current strategies and may potentially compromise assessment and interpretation of methylation data. A large number of strategies have been described for the discovery and validation of DNA methylation-based biomarkers, each with its own advantages and limitations. These strategies can be classified into three main categories: restriction enzyme digestion, affinity-based analysis, and bisulfite modification. In general, candidate biomarkers are discovered using large-scale, genome-wide, methylation sequencing, and/or microarray-based profiling strategies. Following discovery, biomarker performance is validated in large independent cohorts using highly targeted locus-specific assays. There are still many challenges to the effective implementation of DNA methylation-based biomarkers. Emerging innovative methylation and hydroxymethylation detection strategies are focused on addressing these gaps in the field of epigenetics. The development of DNA methylation- and hydroxymethylation-based biomarkers is an exciting and rapidly evolving area of research that holds promise for potential applications in diverse clinical

  14. 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.

  15. 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...

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

    Science.gov (United States)

    Wang, Dingzhi; DuBois, Raymond N

    2013-06-01

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

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

    Science.gov (United States)

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

  18. Biomarkers, Bundled Payments, and Colorectal Cancer Care

    OpenAIRE

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

    2012-01-01

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

  19. Pharmacogenomics: Biomarker-Directed Therapy for Bladder Cancer.

    Science.gov (United States)

    Jones, Robert T; Felsenstein, Kenneth M; Theodorescu, Dan

    2016-02-01

    The clinical management of bladder cancer has seen little change over the last three decades and there is pressing need to identify more effective treatments for advanced disease. Low clinical use of neoadjuvant therapies stems from historical limitations in the ability to predict patients most likely to respond to combination chemotherapies. This article focuses on recent molecular and genetic studies, highlighting promising clinical trials and retrospective studies, and discusses emerging trials that use predictive biomarkers to match patients with therapies to which they are most likely to respond. The implementation of predictive genomic and molecular biomarkers will revolutionize urologic oncology and the clinical management of bladder cancer.

  20. Exosomal miRNAs as biomarkers for prostate cancer

    Directory of Open Access Journals (Sweden)

    Nina Pettersen Hessvik

    2013-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Barbara Di Camillo

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

  2. Theoretical modeling of masking DNA application in aptamer-facilitated biomarker discovery.

    Science.gov (United States)

    Cherney, Leonid T; Obrecht, Natalia M; Krylov, Sergey N

    2013-04-16

    In aptamer-facilitated biomarker discovery (AptaBiD), aptamers are selected from a library of random DNA (or RNA) sequences for their ability to specifically bind cell-surface biomarkers. The library is incubated with intact cells, and cell-bound DNA molecules are separated from those unbound and amplified by the polymerase chain reaction (PCR). The partitioning/amplification cycle is repeated multiple times while alternating target cells and control cells. Efficient aptamer selection in AptaBiD relies on the inclusion of masking DNA within the cell and library mixture. Masking DNA lacks primer regions for PCR amplification and is typically taken in excess to the library. The role of masking DNA within the selection mixture is to outcompete any nonspecific binding sequences within the initial library, thus allowing specific DNA sequences (i.e., aptamers) to be selected more efficiently. Efficient AptaBiD requires an optimum ratio of masking DNA to library DNA, at which aptamers still bind specific binding sites but nonaptamers within the library do not bind nonspecific binding sites. Here, we have developed a mathematical model that describes the binding processes taking place within the equilibrium mixture of masking DNA, library DNA, and target cells. An obtained mathematical solution allows one to estimate the concentration of masking DNA that is required to outcompete the library DNA at a desirable ratio of bound masking DNA to bound library DNA. The required concentration depends on concentrations of the library and cells as well as on unknown cell characteristics. These characteristics include the concentration of total binding sites on the cell surface, N, and equilibrium dissociation constants, K(nsL) and K(nsM), for nonspecific binding of the library DNA and masking DNA, respectively. We developed a theory that allows the determination of N, K(nsL), and K(nsM) based on measurements of EC50 values for cells mixed separately with the library and masking DNA

  3. MicroRNA Machinery Genes as Novel Biomarkers for Cancer.

    Science.gov (United States)

    Huang, Jing-Tao; Wang, Jin; Srivastava, Vibhuti; Sen, Subrata; Liu, Song-Mei

    2014-01-01

    MicroRNAs (miRNAs) directly and indirectly affect tumorigenesis. To be able to perform their myriad roles, miRNA machinery genes, such as Drosha, DGCR8, Dicer1, XPO5, TRBP, and AGO2, must generate precise miRNAs. These genes have specific expression patterns, protein-binding partners, and biochemical capabilities in different cancers. Our preliminary analysis of data from The Cancer Genome Atlas consortium on multiple types of cancer revealed significant alterations in these miRNA machinery genes. Here, we review their biological structures and functions with an eye toward understanding how they could serve as cancer biomarkers.

  4. Facile Discovery of Cell-Surface Protein Targets of Cancer Cell Aptamers.

    Science.gov (United States)

    Bing, Tao; Shangguan, Dihua; Wang, Yinsheng

    2015-10-01

    Cancer biomarker discovery constitutes a frontier in cancer research. In recent years, cell-binding aptamers have become useful molecular probes for biomarker discovery. However, there are few successful examples, and the critical barrier resides in the identification of the cell-surface protein targets for the aptamers, where only a limited number of aptamer targets have been identified so far. Herein, we developed a universal SILAC-based quantitative proteomic method for target discovery of cell-binding aptamers. The method allowed for distinguishing specific aptamer-binding proteins from nonspecific proteins based on abundance ratios of proteins bound to aptamer-carrying bait and control bait. In addition, we employed fluorescently labeled aptamers for monitoring and optimizing the binding conditions. We were able to identify and validate selectin L and integrin α4 as the protein targets for two previously reported aptamers, Sgc-3b and Sgc-4e, respectively. This strategy should be generally applicable for the discovery of protein targets for other cell-binding aptamers, which will promote the applications of these aptamers.

  5. Risk factors and novel biomarkers in breast cancer

    OpenAIRE

    Fourkala, E.-O.

    2011-01-01

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

  6. 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.

  7. Prostate cancer biomarker profiles in urinary sediments and exosomes

    NARCIS (Netherlands)

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

    2014-01-01

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

  8. Identification of candidate epigenetic biomarkers for ovarian cancer detection

    NARCIS (Netherlands)

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

    2009-01-01

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

  9. Long Non-Coding RNAs As Potential Novel Prognostic Biomarkers in Colorectal Cancer.

    Science.gov (United States)

    Saus, Ester; Brunet-Vega, Anna; Iraola-Guzmán, Susana; Pegueroles, Cinta; Gabaldón, Toni; Pericay, Carles

    2016-01-01

    Colorectal cancer (CRC) is the fourth most common cause of death worldwide. Surgery is usually the first line of treatment for patients with CRC but many tumors with similar histopathological features show significantly different clinical outcomes. The discovery of robust prognostic biomarkers in patients with CRC is imperative to achieve more effective treatment strategies and improve patient's care. Recent progress in next generation sequencing methods and transcriptome analysis has revealed that a much larger part of the genome is transcribed into RNA than previously assumed. Collectively referred to as non-coding RNAs (ncRNAs), some of these RNA molecules such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been shown to be altered and to play critical roles in tumor biology. This discovery leads to exciting possibilities for personalized cancer diagnosis, and therapy. Many lncRNAs are tissue and cancer-type specific and have already revealed to be useful as prognostic markers. In this review, we focus on recent findings concerning aberrant expression of lncRNAs in CRC tumors and emphasize their prognostic potential in CRC. Further studies focused on the mechanisms of action of lncRNAs will contribute to the development of novel biomarkers for diagnosis and disease progression.

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

    OpenAIRE

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

    2016-01-01

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

  11. Antiangiogenic cancer treatment: The great discovery and greater complexity (Review)

    Science.gov (United States)

    Maj, Ewa; Papiernik, Diana; Wietrzyk, Joanna

    2016-01-01

    The discovery of tumor angiogenesis opened a new path in fighting cancer. The approval of different antiangiogenic agents, most targeting vascular endothelial growth factor (VEGF) signaling, has either increased the effectiveness of standard chemotherapy or even replaced it by offering better patient outcomes. However, an increasing number of preclinical and clinical observations have shown that the process of angiogenesis is far from clearly understood. Apart from targeting the VEGF pathway, novel strategies aim to influence other molecular factors that are involved in tumor angiogenesis. In addition, naturally occurring compounds seem to offer additional agents for influencing angiogenesis. The first concept of antiangiogenic therapy aimed to destroy tumor vessels, while it turned out that, paradoxically, antiangiogenic drugs normalized vasculature and as a result offered an improvement in chemotherapeutic delivery. In order to design an effective treatment schedule, methods for detecting the time window of normalization and biomarkers predicting patient response are needed. The initial idea that antiangiogenic therapy would be resistance-free failed to materialize and currently we still face the obstacle of resistance to antiangiogenic therapy.

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

    Directory of Open Access Journals (Sweden)

    Claire L. Tonry

    2016-07-01

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

  13. Biomarkers of Angiogenesis in Colorectal Cancer

    OpenAIRE

    Luay Mousa; Salem, Mohamed E.; Sameh Mikhail

    2015-01-01

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

  14. 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.

  15. 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.

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Michal Rihacek

    2015-01-01

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

  19. Aberrantly methylated DNA as a biomarker in breast cancer

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  20. 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.

  1. 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.

  2. Exosomal miRNAs as cancer biomarkers and therapeutic targets

    OpenAIRE

    Arron Thind; Clive Wilson

    2016-01-01

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

  3. Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

    International Nuclear Information System (INIS)

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

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Kramer Alon

    2009-01-01

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

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

    Science.gov (United States)

    Bauer, Chris; Glintschert, Alexander; Schuchhardt, Johannes

    2014-05-01

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

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

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    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

  8. 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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-10-31

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

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

    Directory of Open Access Journals (Sweden)

    Stefan eMereiter

    2016-03-01

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

  11. 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.

  12. 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

  13. 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.

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

    International Nuclear Information System (INIS)

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

  15. Identification of Gastric Cancer Biomarkers Using 1H Nuclear Magnetic Resonance Spectrometry.

    Science.gov (United States)

    Ramachandran, Gokula Krishnan; Yong, Wei Peng; Yeow, Chen Hua

    2016-01-01

    Existing gastric cancer diagnosing methods were invasive, hence, a reliable non-invasive gastric cancer diagnosing method is needed. As a starting point, we used 1H NMR for identifying gastric cancer biomarkers using a panel of gastric cancer spheroids and normal gastric spheroids. We were able to identify 8 chemical shift biomarkers for gastric cancer spheroids. Our data suggests that the cancerous and non-cancerous spheroids significantly differ in the lipid composition and energy metabolism. These results encourage the translation of these biomarkers into in-vivo gastric cancer detection methodology using MRI-MS. PMID:27611679

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

    Directory of Open Access Journals (Sweden)

    Cesare Malagù

    2014-10-01

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

  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. 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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

    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...

  20. Trace cancer biomarker quantification using polystyrene-functionalized gold nanorods

    Science.gov (United States)

    Wu, Jian; Li, Wei; Hajisalem, Ghazal; Lukach, Ariella; Kumacheva, Eugenia; Hof, Fraser; Gordon, Reuven

    2014-01-01

    We demonstrate the application of polystyrene-functionalized gold nanorods (AuNRs) as a platform for surface enhanced Raman scattering (SERS) quantification of the exogenous cancer biomarker Acetyl Amantadine (AcAm). We utilize the hydrophobicity of the polystyrene attached to the AuNR surface to capture the hydrophobic AcAm from solution, followed by drying and detection using SERS. We achieve a detection limit of 16 ng/mL using this platform. This result shows clinical potential for low-cost early cancer detection. PMID:25574423

  1. Biomarkers in the management of breast cancer: great expectations, hard times.

    Science.gov (United States)

    Bertelli, Gianfilippo; Nelmes, Daniel J; Al-Allak, Asmaa

    2013-12-01

    Progress in biomarkers research has resulted in increasing awareness of the heterogeneity of breast cancer. The identification of subtypes with different clinical behavior and the possibility of using targeted therapy in specific subgroup of patients (eg, those with tumors overexpressing HER2) raise expectations for increasing personalization of treatment. However, there is a widening gap between scientific discoveries and practical application in everyday practice: too many patients are still being managed based only on traditional clinical and pathologic parameters, because of lack of access to up to date technology-such as gene profiling, or cell proliferation assays-in many cancer centers in the United Kingdom. In this article, we provide some examples of this contrast, drawn from the literature and from our own clinical experience in South West Wales, and discuss possible solutions.

  2. Discovery and identification of serum biomarkers of Wilms' tumor in mice using proteomics technology

    Institute of Scientific and Technical Information of China (English)

    JIA Zhan-kui; WANG Jia-xiang; YANG Jin-jian; XUE Rui; ZHANG Da; WANG Guan-nan; MA Sheng-li; DUAN Zhen-feng

    2012-01-01

    Background Wilms' tumor (nephroblastoma) is a cancer of the kidneys that occurs typically in children and rarely in adults.Early diagnosis is very important for the treatment and prognosis of the disease.The aim of our study was to discover and identify potential non-invasive and convenient biomarkers for the diagnosis of Wilms' tumor.Methods Nude mice were used to construct a Wilms' tumor model by injecting nephroblastoma cells into their bilateral abdomen.We collected 94 serum samples from mice consisting of 45 samples with Wilms' tumor and 49 controls.The serum proteomic profiles of the samples were analyzed via surface-enhanced laser desorption/ionization time-of-flight mass spectrometry.The candidate biomarkers were purified by high-performance liquid chromatography,identified by liquid chromatography-mass spectrometry,and validated using ProteinChip immunoassays.Results We finally retrieved two differential proteins (m/z 4509.2; 6207.9),which were identified as apolipoprotein A-Ⅱ and polyubiquitin,respectively.The expression of apolipoprotein A-Ⅱ was higher in the Wilms' tumor group than in the control group (P<0.01).By contrast,the expression of polyubiquitin was lower in the Wilms' tumor group than in the control group.Conclusion Apolipoprotein A-Ⅱ and polyubiquitin may be used as potential biomarkers for nephroblastoma in children,and the analysis of apolipoprotein A-Ⅱ may help diagnose and treat Wilms' tumor.

  3. The Significance of Proteomic Biomarkers in Male Breast Cancer.

    Science.gov (United States)

    Zografos, Eleni; Gazouli, Maria; Tsangaris, Georgios; Marinos, Evangelos

    2016-01-01

    Breast cancer in men (MBC) is an uncommon malignancy and accounts for only 1% of all diagnosed breast cancers. By using genomic and transcriptomic approaches, researchers have been able to expand our insight into the genetic basis of breast cancer, by providing new biomarkers. We currently know that gene analysis by itself does not show the complete picture. Along with the genomic approach, proteomics are crucial for the improvement of breast cancer diagnosis, sub-classification, for predicting response to different treatment modalities and for predicting prognosis. There are great challenges in identifying discriminatory proteins and the use of specific techniques along with additional analytical tools is required. A number of techniques allow testing for proteins produced during specific diseases. In this review, an effort is made to summarize the studies and results linked to the implementation of proteomics in the field of MBC detection and diagnosis.

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

    Science.gov (United States)

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

    2013-01-01

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

  5. 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. PMID:27579980

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

    Science.gov (United States)

    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. PMID:27579980

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Yuesheng ZHANG; Li TANG

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Astrid Wachter

    2015-11-01

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

  10. 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...

  11. Novel Altered Region for Biomarker Discovery in Hepatocellular Carcinoma (HCC Using Whole Genome SNP Array

    Directory of Open Access Journals (Sweden)

    Esraa M. Hashem

    2016-04-01

    Full Text Available cancer represents one of the greatest medical causes of mortality. The majority of Hepatocellular carcinoma arises from the accumulation of genetic abnormalities, and possibly induced by exterior etiological factors especially HCV and HBV infections. There is a need for new tools to analysis the large sum of data to present relevant genetic changes that may be critical for both understanding how cancers develop and determining how they could ultimately be treated. Gene expression profiling may lead to new biomarkers that may help develop diagnostic accuracy for detecting Hepatocellular carcinoma. In this work, statistical technique (discrete stationary wavelet transform for detection of copy number alternations to analysis high-density single-nucleotide polymorphism array of 30 cell lines on specific chromosomes, which are frequently detected in Hepatocellular carcinoma have been proposed. The results demonstrate the feasibility of whole-genome fine mapping of copy number alternations via high-density single-nucleotide polymorphism genotyping, Results revealed that a novel altered chromosomal region is discovered; region amplification (4q22.1 have been detected in 22 out of 30-Hepatocellular carcinoma cell lines (73%. This region strike, AFF1 and DSPP, tumor suppressor genes. This finding has not previously reported to be involved in liver carcinogenesis; it can be used to discover a new HCC biomarker, which helps in a better understanding of hepatocellular carcinoma.

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

    Science.gov (United States)

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

    2011-05-01

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

  13. Biomarkers for pancreatic carcinogenesis

    OpenAIRE

    Hustinx, S.R.

    2007-01-01

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

  14. Midkine: A Novel Prognostic Biomarker for Cancer

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-04-20

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

  15. 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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    Cindy D DAVIS; John A MILNER

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Taysir Hassan A. Soliman

    2015-12-01

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

  19. Identification of prostate cancer biomarkers in urinary exosomes.

    Science.gov (United States)

    Øverbye, Anders; Skotland, Tore; Koehler, Christian J; Thiede, Bernd; Seierstad, Therese; Berge, Viktor; Sandvig, Kirsten; Llorente, Alicia

    2015-10-01

    Exosomes have recently appeared as a novel source of non-invasive cancer biomarkers since tumour-specific molecules can be found in exosomes isolated from biological fluids. We have here investigated the proteome of urinary exosomes by using mass spectrometry to identify proteins differentially expressed in prostate cancer patients compared to healthy male controls. In total, 15 control and 16 prostate cancer samples of urinary exosomes were analyzed. Importantly, 246 proteins were differentially expressed in the two groups. The majority of these proteins (221) were up-regulated in exosomes from prostate cancer patients. These proteins were analyzed according to specific criteria to create a focus list that contained 37 proteins. At 100% specificity, 17 of these proteins displayed individual sensitivities above 60%. Even though several of these proteins showed high sensitivity and specificity for prostate cancer as individual biomarkers, combining them in a multi-panel test has the potential for full differentiation of prostate cancer from non-disease controls. The highest sensitivity, 94%, was observed for transmembrane protein 256 (TM256; chromosome 17 open reading frame 61). LAMTOR proteins were also distinctly enriched with very high specificity for patient samples. TM256 and LAMTOR1 could be used to augment the sensitivity to 100%. Other prominent proteins were V-type proton ATPase 16 kDa proteolipid subunit (VATL), adipogenesis regulatory factor (ADIRF), and several Rab-class members and proteasomal proteins. In conclusion, this study clearly shows the potential of using urinary exosomes in the diagnosis and clinical management of prostate cancer.

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

    Directory of Open Access Journals (Sweden)

    Rajeev Singhai

    2011-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2012-02-01

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

  3. Telomerase promoter mutations in cancer: an emerging molecular biomarker?

    Science.gov (United States)

    Vinagre, João; Pinto, Vasco; Celestino, Ricardo; Reis, Marta; Pópulo, Helena; Boaventura, Paula; Melo, Miguel; Catarino, Telmo; Lima, Jorge; Lopes, José Manuel; Máximo, Valdemar; Sobrinho-Simões, Manuel; Soares, Paula

    2014-08-01

    Cell immortalization has been considered for a long time as a classic hallmark of cancer cells. Besides telomerase reactivation, such immortalization could be due to telomere maintenance through the "alternative mechanism of telomere lengthening" (ALT) but the mechanisms underlying both forms of reactivation remained elusive. Mutations in the coding region of telomerase gene are very rare in the cancer setting, despite being associated with some degenerative diseases. Recently, mutations in telomerase (TERT) gene promoter were found in sporadic and familial melanoma and subsequently in several cancer models, notably in gliomas, thyroid cancer and bladder cancer. The importance of these findings has been reinforced by the association of TERT mutations in some cancer types with tumour aggressiveness and patient survival. In the first part of this review, we summarize the data on the biology of telomeres and telomerase, available methodological approaches and non-neoplastic diseases associated with telomere dysfunction. In the second part, we review the information on telomerase expression and genetic alterations in the most relevant types of cancer (skin, thyroid, bladder and central nervous system) on record, and discuss the value of telomerase as a new biomarker with impact on the prognosis and survival of the patients and as a putative therapeutic target. PMID:25048572

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  6. Circulating DNA as Potential Biomarker for Cancer Individualized Therapy

    Institute of Scientific and Technical Information of China (English)

    Yu Shaorong; Liu Baorui; Lu Jianwei; Feng Jifeng

    2013-01-01

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

  7. Exosomal Proteins as a Diagnostic Biomarkers in Lung Cancer

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  8. Oral cancer: Deregulated molecular events and their use as biomarkers.

    Science.gov (United States)

    Sinevici, Nicoleta; O'sullivan, Jeff

    2016-10-01

    Oral Cancer (OC) is a subset of head and neck cancer (HNC) with an annual worldwide incidence of 275,000 cases. OC remains a significant burden worldwide in terms of diagnosis, treatment and prognosis. Despite desirable outcomes in early diagnosed OCs and treatment advances most OCs are detected in advanced stages. The 5-year survival rate of early-stage disease is ∼80% and that of late-stage disease is only ∼20%. Recurrence and chemoresistance from a treatment point of view and pain and disfiguration are important factors contributing to the high morbidity and mortality of OC. Furthermore the process of oral carcinogenesis is complex and not yet fully understood. Consequently numerous potential biomarkers have been hypothesised though controversial results across the board hamper their clinical implementation. Of greatest advantage would be biomarkers signalling early events preceeding OC. Biomarker targets predominately involve deregulated molecular events that participate in cell signalling, growth, survival, motility, angiogenesis and cell cycle control but can also use changes in metabolic genes to discriminate healthy form disease state. Promising potential biomarkers include the growth signalling oncogenes, Epidermal Growth Factor Receptor and Cyclin D1, the anti-growth signalling components p53 and p21, apoptotic effectors such as Bcl-2 and also components involved in immortalisation, angiogenesis, invasion and metastasis processes. Translation of these potential biomakers to the patients is closer than ever though few issues remain to be resolved. Firstly large clinical trials are needed to validate their clinical applicability but also standardised methods of collection, storage and processing methods are needed to minimise variability. PMID:27688099

  9. Biomarkers along the continuum of care in lung cancer.

    Science.gov (United States)

    Holdenrieder, Stefan

    2016-01-01

    Blood-based biomarkers are valuable diagnostic tools for the management of lung cancer patients. They support not only differential diagnosis and histological subtyping, but are also applied for estimation of prognosis, stratification for specific therapies, monitoring of therapy response, surveillance monitoring and early detection of residual or progressive disease. Early diagnosis of lung cancer in high risk populations (screening) is a promising future indication but poses high medical and economic challenges to marker performance. The five mostly used classical 'tumor markers' show characteristic profiles of sensitivity and specificity for non-small cell lung cancer (NSCLC) like cytokeratin 19-fragments (CYFRA 21-1), carcino-embryonic antigen (CEA) and squamous cancer cell antigen (SCCA) as well as for small cell lung cancer (SCLC) like progastrin-releasing peptide (ProGRP) and neuron-specific enolase (NSE). Combined use and pattern recognition approaches enable highly accurate diagnosis, subtyping and therapy monitoring. For the interpretation of serial measurements on an individual level, marker-specific algorithms have to be developed. So-called companion diagnostics identify druggable molecular changes in signaling pathways of tumor tissue that can be addressed by targeted therapies. New highly sensitive technologies enable the convenient and serial molecular characterization on circulating tumor DNA (ctDNA) in the blood, too. This approach is helpful when biopsies are not available and to overcome tumor molecular heterogeneity and plasticity. As only a portion of patients have such druggable molecular changes, future strategies will imply the combined use of classical and new ctDNA-based biomarkers to optimize the management of lung cancer patients during the course of disease. PMID:27542002

  10. 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

  11. 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 ...

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

    OpenAIRE

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Amit V. Patil

    2011-03-01

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

  14. Towards discovery-driven translational research in breast cancer

    DEFF Research Database (Denmark)

    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. Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection

    CERN Document Server

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

    2015-01-01

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

  16. Circulating exosomal microRNAs as biomarkers of colon cancer.

    Directory of Open Access Journals (Sweden)

    Hiroko Ogata-Kawata

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

  17. 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

  18. Computational protein biomarker prediction: a case study for prostate cancer

    Directory of Open Access Journals (Sweden)

    Adam Bao-Ling

    2004-03-01

    Full Text Available Abstract Background Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates. Results Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained at the Eastern Virginia Medical School using SELDI-TOF mass spectrometry. We obtain average classification accuracies of 87% on a four-group classification problem using a two-stage linear SVM-based procedure and just 13 peaks, with other methods performing comparably. Conclusions Modern feature selection and classification methods are powerful techniques for both the identification of biomarker candidates and the related problem of building predictive models from protein mass spectrometric profiles. Cross-validation and randomization are essential tools that must be performed carefully in order not to bias the results unfairly. However, only a biological validation and identification of the underlying proteins will ultimately confirm the actual value and power of any computational predictions.

  19. 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

  20. 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

    2013-01-01

    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 < 0.004) in HCC relative to HCV. Differential expression quantified via two-dimensional difference gel electrophoresis was confirmed by means of 18O/16O 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 18O/16O-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

  1. Colon Cancer Biomarkers To Identify Patients Suitable For Therapeutic Intervention | NCI Technology Transfer Center | TTC

    Science.gov (United States)

    The National Cancer Institute's Laboratory of Human Carcinogenesis is seeking statements of capability or interest from parties interested in collaborative research to further develop, evaluate, or commercialize cancer biomarkers and therapeutic targets.

  2. Exosomal miRNAs as cancer biomarkers and therapeutic targets.

    Science.gov (United States)

    Thind, Arron; Wilson, Clive

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-10-15

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

  4. Circulating protein and antibody biomarker for personalized cancer immunotherapy.

    Science.gov (United States)

    Yuan, Jianda

    2016-01-01

    Immune checkpoint blockade therapies are revolutionizing standard cancer treatments. Immune checkpoint inhibitors likely function to enhance the tumor specific antigen response in order to achieve favorable clinical outcomes. Thus, continuous efforts to identify the common tumor-specific antigens are essential for the broad clinical application of these therapies. Several immunoproteomics approaches have been used in order to screen for this specificity. In a recent article from Jhaveri and colleagues published in the February issue of Cancer Immunology Research, antibody biomarkers were screened in pancreatic cancer patients who received allogeneic, granulocyte-macrophage colony stimulating factor-secreting pancreatic cancer vaccine (GVAX) by using a serum antibody-based SILAC immunoprecipitation (SASI) approach. Using this assay, several new tumor antigens (MYPT1, PSMC5 and TRFR) were identified that were found to have significantly different expression in tumors compared with normal tissue. Moreover, patients with detectable antibodies showed improved disease-free survival after GVAX therapy. These targets need to be further validated to determine the full spectrum of tumor antigen immunogencity and their potential clinical application. In addition to antibodies, circulating protein, DNA and RNA in peripheral blood are under clinical investigation as liquid biopsies and have the potential to provide guidance for future personalized cancer immunotherapy.

  5. Epigenetic Alterations in Colorectal Cancer: Emerging Biomarkers.

    Science.gov (United States)

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

    2015-10-01

    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 colonic 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, are 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.

  6. 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.

  7. 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.

  8. 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

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

    OpenAIRE

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2003-01-01

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

  12. Weighted gene co-expression based biomarker discovery for psoriasis detection.

    Science.gov (United States)

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

    Psoriasis is a chronic inflammatory disease of the skin with an unknown aetiology. The disease manifests itself as red and silvery scaly plaques distributed over the scalp, lower back and extensor aspects of the limbs. After receiving scant consideration for quite a few years, psoriasis has now become a prominent focus for new drug development. A group of closely connected and differentially co-expressed genes may act in a network and may serve as molecular signatures for an underlying phenotype. A weighted gene coexpression network analysis (WGCNA), a system biology approach has been utilized for identification of new molecular targets for psoriasis. Gene coexpression relationships were investigated in 58 psoriatic lesional samples resulting in five gene modules, clustered based on the gene coexpression patterns. The coexpression pattern was validated using three psoriatic datasets. 10 highly connected and informative genes from each module was selected and termed as psoriasis specific hub signatures. A random forest based binary classifier built using the expression profiles of signature genes robustly distinguished psoriatic samples from the normal samples in the validation set with an accuracy of 0.95 to 1. These signature genes may serve as potential candidates for biomarker discovery leading to new therapeutic targets. WGCNA, the network based approach has provided an alternative path to mine out key controllers and drivers of psoriasis. The study principle from the current work can be extended to other pathological conditions.

  13. 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.

  14. Bioinformatics for cancer immunotherapy target discovery

    DEFF Research Database (Denmark)

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

    2014-01-01

    cancer immunotherapies has yet to be fulfilled. The insufficient efficacy of existing treatments can be attributed to a number of biological and technical issues. In this review, we detail the current limitations of immunotherapy target selection and design, and review computational methods to streamline...

  15. Discovery and validation of breast cancer subtypes

    OpenAIRE

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

    2006-01-01

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

  16. Validation of methylation biomarkers that distinguish normal colon mucosa of cancer patients from normal colon mucosa of patients without cancer.

    Science.gov (United States)

    Cesaroni, Matteo; Powell, Jasmine; Sapienza, Carmen

    2014-07-01

    We have validated differences in DNA methylation levels of candidate genes previously reported to discriminate between normal colon mucosa of patients with colon cancer and normal colon mucosa of individuals without cancer. Here, we report that CpG sites in 16 of the 30 candidate genes selected show significant differences in mean methylation level in normal colon mucosa of 24 patients with cancer and 24 controls. A support vector machine trained on these data and data for an additional 66 CpGs yielded an 18-gene signature, composed of ten of the validated candidate genes plus eight additional candidates. This model exhibited 96% sensitivity and 100% specificity in a 40-sample training set and classified all eight samples in the test set correctly. Moreover, we found a moderate-strong correlation (Pearson coefficients r = 0.253-0.722) between methylation levels in colon mucosa and methylation levels in peripheral blood for seven of the 18 genes in the support vector model. These seven genes, alone, classified 44 of the 48 patients in the validation set correctly and five CpGs selected from only two of the seven genes classified 41 of the 48 patients in the discovery set correctly. These results suggest that methylation biomarkers may be developed that will, at minimum, serve as useful objective and quantitative diagnostic complements to colonoscopy as a cancer-screening tool. These data also suggest that it may be possible to monitor biomarker methylation levels in tissues collected much less invasively than by colonoscopy. PMID:24806665

  17. Prediction of breast cancer survival through knowledge discovery in databases.

    Science.gov (United States)

    Lotfnezhad Afshar, Hadi; Ahmadi, Maryam; Roudbari, Masoud; Sadoughi, Farahnaz

    2015-01-26

    The collection of large volumes of medical data has offered an opportunity to develop prediction models for survival by the medical research community. Medical researchers who seek to discover and extract hidden patterns and relationships among large number of variables use knowledge discovery in databases (KDD) to predict the outcome of a disease. The study was conducted to develop predictive models and discover relationships between certain predictor variables and survival in the context of breast cancer. This study is Cross sectional. After data preparation, data of 22,763 female patients, mean age 59.4 years, stored in the Surveillance Epidemiology and End Results (SEER) breast cancer dataset were analyzed anonymously. IBM SPSS Statistics 16, Access 2003 and Excel 2003 were used in the data preparation and IBM SPSS Modeler 14.2 was used in the model design. Support Vector Machine (SVM) model outperformed other models in the prediction of breast cancer survival. Analysis showed SVM model detected ten important predictor variables contributing mostly to prediction of breast cancer survival. Among important variables, behavior of tumor as the most important variable and stage of malignancy as the least important variable were identified. In current study, applying of the knowledge discovery method in the breast cancer dataset predicted the survival condition of breast cancer patients with high confidence and identified the most important variables participating in breast cancer survival.

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

    Science.gov (United States)

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

    2016-01-01

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

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Grate Leslie R

    2005-04-01

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

  1. 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

    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 pla...

  2. Advances in Gas Chromatographic Methods for the Identification of Biomarkers in Cancer

    Directory of Open Access Journals (Sweden)

    Konstantinos A. Kouremenos, Mikael Johansson, Philip J. Marriott

    2012-01-01

    Full Text Available Screening complex biological specimens such as exhaled air, tissue, blood and urine to identify biomarkers in different forms of cancer has become increasingly popular over the last decade, mainly due to new instruments and improved bioinformatics. However, despite some progress, the identification of biomarkers has shown to be a difficult task with few new biomarkers (excluding recent genetic markers being considered for introduction to clinical analysis. This review describes recent advances in gas chromatographic methods for the identification of biomarkers in the detection, diagnosis and treatment of cancer. It presents a general overview of cancer metabolism, the current biomarkers used for cancer diagnosis and treatment, a background to metabolic changes in tumors, an overview of current GC methods, and collectively presents the scope and outlook of GC methods in oncology.

  3. Discovery and validation of breast cancer subtypes

    Directory of Open Access Journals (Sweden)

    Bukholm Ida RK

    2006-09-01

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

  4. MicroRNAs as biomarkers for CNS cancer and other disorders.

    Science.gov (United States)

    De Smaele, Enrico; Ferretti, Elisabetta; Gulino, Alberto

    2010-06-18

    The use of miRNAs as biomarkers has gained growing interest in the last few years. Their role in regulating a great variety of targets and, as a consequence, multiple pathways, makes their use in diagnostics a powerful tool to be exploited for early detection of disease, risk assessment and prognosis and for the design of innovative therapeutic strategies. While still not fully validated, profiling of blood cells, exosomes or body fluid miRNAs would represent a tremendous and promising advance in non-invasive diagnostics of CNS disorders. A major challenge is represented by technological aspects of miRNA detection and discovery aiming to genome-wide high throughput, sensitive and accurate analysis. Although there is much to be learned in the field, this review will highlight the potential role of miRNA as a new class of biomarkers in several CNS disorders, including neurodegenerative diseases such as Alzheimer, Huntington and Parkinson diseases, schizophrenia and autism as well as different types of cancer (e.g. gliomas and medulloblastomas).

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

    OpenAIRE

    2015-01-01

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

  6. Circulating MicroRNAs as Biomarkers in Biliary Tract Cancers

    Science.gov (United States)

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

    2016-01-01

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

  7. Role of MGMT as biomarker in colorectal cancer

    Science.gov (United States)

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

    2014-01-01

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

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    Yinhai Wang

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

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

    Science.gov (United States)

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

    2016-04-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  12. Knowledge based cluster ensemble for cancer discovery from biomolecular data.

    Science.gov (United States)

    Yu, Zhiwen; Wongb, Hau-San; You, Jane; Yang, Qinmin; Liao, Hongying

    2011-06-01

    The adoption of microarray techniques in biological and medical research provides a new way for cancer diagnosis and treatment. In order to perform successful diagnosis and treatment of cancer, discovering and classifying cancer types correctly is essential. Class discovery is one of the most important tasks in cancer classification using biomolecular data. Most of the existing works adopt single clustering algorithms to perform class discovery from biomolecular data. However, single clustering algorithms have limitations, which include a lack of robustness, stability, and accuracy. In this paper, we propose a new cluster ensemble approach called knowledge based cluster ensemble (KCE) which incorporates the prior knowledge of the data sets into the cluster ensemble framework. Specifically, KCE represents the prior knowledge of a data set in the form of pairwise constraints. Then, the spectral clustering algorithm (SC) is adopted to generate a set of clustering solutions. Next, KCE transforms pairwise constraints into confidence factors for these clustering solutions. After that, a consensus matrix is constructed by considering all the clustering solutions and their corresponding confidence factors. The final clustering result is obtained by partitioning the consensus matrix. Comparison with single clustering algorithms and conventional cluster ensemble approaches, knowledge based cluster ensemble approaches are more robust, stable and accurate. The experiments on cancer data sets show that: 1) KCE works well on these data sets; 2) KCE not only outperforms most of the state-of-the-art single clustering algorithms, but also outperforms most of the state-of-the-art cluster ensemble approaches.

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    Jakob Vasehus Schou

    2016-06-01

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

  15. Current advances in biomarkers for targeted therapy in triple-negative breast cancer

    Directory of Open Access Journals (Sweden)

    Fleisher B

    2016-10-01

    Full Text Available Brett Fleisher,1 Charlotte Clarke,2 Sihem Ait-Oudhia1 1Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, FL, 2Department of Translational Research, UT MD Anderson Cancer Center, Houston, TX, USA Abstract: Triple-negative breast cancer (TNBC is a complex heterogeneous disease characterized by the absence of three hallmark receptors: human epidermal growth factor receptor 2, estrogen receptor, and progesterone receptor. Compared to other breast cancer subtypes, TNBC is more aggressive, has a higher prevalence in African-Americans, and more frequently affects younger patients. Currently, TNBC lacks clinically accepted targets for tailored therapy, warranting the need for candidate biomarkers. BiomarkerBase, an online platform used to find biomarkers reported in clinical trials, was utilized to screen all potential biomarkers for TNBC and select only the ones registered in completed TNBC trials through clinicaltrials.gov. The selected candidate biomarkers were classified as surrogate, prognostic, predictive, or pharmacodynamic (PD and organized by location in the blood, on the cell surface, in the cytoplasm, or in the nucleus. Blood biomarkers include vascular endothelial growth factor/vascular endothelial growth factor receptor and interleukin-8 (IL-­8; cell surface biomarkers include EGFR, insulin-like growth factor binding protein, c-Kit, c-Met, and PD-L1; cytoplasm biomarkers include PIK3CA, pAKT/S6/p4E-BP1, PTEN, ALDH1, and the PIK3CA/AKT/mTOR-related metabolites; and nucleus biomarkers include BRCA1, the glucocorticoid receptor, TP53, and Ki67. Candidate biomarkers were further organized into a “cellular protein network” that demonstrates potential connectivity. This review provides an inventory and reference point for promising biomarkers for breakthrough targeted therapies in TNBC. Keywords: anti-cancer directed pharmacotherapy, difficult

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

    Science.gov (United States)

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

    2016-03-01

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

  17. Urinary APE1/Ref-1: A Potential Bladder Cancer Biomarker.

    Science.gov (United States)

    Choi, Sunga; Shin, Ju Hyun; Lee, Yu Ran; Joo, Hee Kyoung; Song, Ki Hak; Na, Yong Gil; Chang, Seok Jong; Lim, Jae Sung; Jeon, Byeong Hwa

    2016-01-01

    Bladder cancer (BCa) is one of the most common urothelial cancers with still noticeable incidence rate. Early detection of BCa is highly correlated with successful therapeutic outcomes. We previously showed that apurinic/apyrimidinic endonuclease 1/redox factor-1 (APE1/Ref-1) was expressed at an increased level in the serum of BCa patients when compared to the level in healthy controls. In this study, we investigated whether urinary APE1/Ref-1 was also elevated in patients with BCa. In this case-control study, voided urine was collected from 277 subjects including 169 BCa patients and 108 non-BCa controls. Urinary APE1/Ref-1 level was assessed by enzyme-linked immunosorbent assay (ELISA). APE1/Ref-1 levels were significantly elevated in BCa patients relative to levels in non-BCa controls and were correlated with tumor grade and stage. Urinary APE1/Ref-1 levels were also higher in patients with recurrence history of BCa. The receiver operating characteristics (ROC) curve of APE1/Ref-1 showed an area under the curve of 0.83, indicating the reliability and validity of this biomarker. The optimal combination of sensitivity and specificity was determined to be 82% and 80% at a cut-off value of 0.376 ng/100 μL for detection of APE1/Ref-1 in urine. In conclusion, urinary APE1/Ref-1 levels measured from noninvasively obtained body fluids would be clinically applicable for diagnosis of BCa.

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

    International Nuclear Information System (INIS)

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

  2. 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

  3. RNA Editing and Drug Discovery for Cancer Therapy

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    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.

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

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    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.

  5. HER2: An emerging biomarker in non-breast and non-gastric cancers

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    Norhayati Omar

    2015-08-01

    Conclusion: Moving forward, the rigorous evaluation of HER2 (protein and genomic status as a predictive biomarker will be necessary to bring anti-HER2 therapeutics for non-breast and non-gastric cancers to the clinic.

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

    Science.gov (United States)

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

    2016-08-18

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

  7. Telomere and Telomerase: From Discovery to Cancer Treatment

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    Eskandari-Nasab

    2015-07-01

    Full Text Available Context Cancer is a major cause of death worldwide. It was estimated that 7.6 million people died during 2008 due to cancer and this figure is expected to double by 2030. To conquer this disease, discovery of validated targets and new drugs is a necessity. Evidence Acquisition Telomeres are terminal structures of linear chromosomes in eukaryotes and consist of multiple repetitive sequences. Their main function is to protect and confer stability to chromosome ends and prevent their breakage, end-to-end fusion, and degeneration. Polymerases responsible for replication of DNA in eukaryotes are not able to replicate chromosome ends and, during cell division, chromosomes continuously become shorter from the telomere ends. This shortening will eventually stop cell division. In cancer cells, there is a ribonucleoprotein enzyme called telomerase that allows compensation of telomere shortening and continuation of the cell multiplication process. Results About 90% of cancers need a high level of this enzyme to continue cell multiplication. Since this enzyme set is absent in normal cells, or present at a very low level, use of telomerase inhibitors cannot have significant effects on normal cells. Conclusions Since telomerase is expressed in 90% of cancer cells, its inhibition can be considered as a goal of cancer treatment.

  8. Identification of plasma lipid biomarkers for prostate cancer by lipidomics and bioinformatics.

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    Xinchun Zhou

    Full Text Available BACKGROUND: Lipids have critical functions in cellular energy storage, structure and signaling. Many individual lipid molecules have been associated with the evolution of prostate cancer; however, none of them has been approved to be used as a biomarker. The aim of this study is to identify lipid molecules from hundreds plasma apparent lipid species as biomarkers for diagnosis of prostate cancer. METHODOLOGY/PRINCIPAL FINDINGS: Using lipidomics, lipid profiling of 390 individual apparent lipid species was performed on 141 plasma samples from 105 patients with prostate cancer and 36 male controls. High throughput data generated from lipidomics were analyzed using bioinformatic and statistical methods. From 390 apparent lipid species, 35 species were demonstrated to have potential in differentiation of prostate cancer. Within the 35 species, 12 were identified as individual plasma lipid biomarkers for diagnosis of prostate cancer with a sensitivity above 80%, specificity above 50% and accuracy above 80%. Using top 15 of 35 potential biomarkers together increased predictive power dramatically in diagnosis of prostate cancer with a sensitivity of 93.6%, specificity of 90.1% and accuracy of 97.3%. Principal component analysis (PCA and hierarchical clustering analysis (HCA demonstrated that patient and control populations were visually separated by identified lipid biomarkers. RandomForest and 10-fold cross validation analyses demonstrated that the identified lipid biomarkers were able to predict unknown populations accurately, and this was not influenced by patient's age and race. Three out of 13 lipid classes, phosphatidylethanolamine (PE, ether-linked phosphatidylethanolamine (ePE and ether-linked phosphatidylcholine (ePC could be considered as biomarkers in diagnosis of prostate cancer. CONCLUSIONS/SIGNIFICANCE: Using lipidomics and bioinformatic and statistical methods, we have identified a few out of hundreds plasma apparent lipid molecular

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

    Science.gov (United States)

    Hao, Wenrui; Friedman, Avner

    2016-01-01

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

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

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    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.

  11. A novel approach to the discovery of survival biomarkers in glioblastoma using a joint analysis of DNA methylation and gene expression.

    Science.gov (United States)

    Smith, Ashley A; Huang, Yen-Tsung; Eliot, Melissa; Houseman, E Andres; Marsit, Carmen J; Wiencke, John K; Kelsey, Karl T

    2014-06-01

    Glioblastoma multiforme (GBM) is the most aggressive of all brain tumors, with a median survival of less than 1.5 years. Recently, epigenetic alterations were found to play key roles in both glioma genesis and clinical outcome, demonstrating the need to integrate genetic and epigenetic data in predictive models. To enhance current models through discovery of novel predictive biomarkers, we employed a genome-wide, agnostic strategy to specifically capture both methylation-directed changes in gene expression and alternative associations of DNA methylation with disease survival in glioma. Human GBM-associated DNA methylation, gene expression, IDH1 mutation status, and survival data were obtained from The Cancer Genome Atlas. DNA methylation loci and expression probes were paired by gene, and their subsequent association with survival was determined by applying an accelerated failure time model to previously published alternative and expression-based association equations. Significant associations were seen in 27 unique methylation/expression pairs with expression-based, alternative, and combinatorial associations observed (10, 13, and 4 pairs, respectively). The majority of the predictive DNA methylation loci were located within CpG islands, and all but three of the locus pairs were negatively correlated with survival. This finding suggests that for most loci, methylation/expression pairs are inversely related, consistent with methylation-associated gene regulatory action. Our results indicate that changes in DNA methylation are associated with altered survival outcome through both coordinated changes in gene expression and alternative mechanisms. Furthermore, our approach offers an alternative method of biomarker discovery using a priori gene pairing and precise targeting to identify novel sites for locus-specific therapeutic intervention.

  12. Integrative discovery of epigenetically derepressed cancer testis antigens in NSCLC.

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    Chad A Glazer

    Full Text Available BACKGROUND: Cancer/testis antigens (CTAs were first discovered as immunogenic targets normally expressed in germline cells, but differentially expressed in a variety of human cancers. In this study, we used an integrative epigenetic screening approach to identify coordinately expressed genes in human non-small cell lung cancer (NSCLC whose transcription is driven by promoter demethylation. METHODOLOGY/PRINCIPAL FINDINGS: Our screening approach found 290 significant genes from the over 47,000 transcripts incorporated in the Affymetrix Human Genome U133 Plus 2.0 expression array. Of the top 55 candidates, 10 showed both differential overexpression and promoter region hypomethylation in NSCLC. Surprisingly, 6 of the 10 genes discovered by this approach were CTAs. Using a separate cohort of primary tumor and normal tissue, we validated NSCLC promoter hypomethylation and increased expression by quantitative RT-PCR for all 10 genes. We noted significant, coordinated coexpression of multiple target genes, as well as coordinated promoter demethylation, in a large set of individual tumors that was associated with the SCC subtype of NSCLC. In addition, we identified 2 novel target genes that exhibited growth-promoting effects in multiple cell lines. CONCLUSIONS/SIGNIFICANCE: Coordinated promoter demethylation in NSCLC is associated with aberrant expression of CTAs and potential, novel candidate protooncogenes that can be identified using integrative discovery techniques. These findings have significant implications for discovery of novel CTAs and CT antigen directed immunotherapy.

  13. 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

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

    Directory of Open Access Journals (Sweden)

    Nelson S. Yee

    2012-01-01

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

  15. Urinary tobacco smoke-constituent biomarkers for assessing risk of lung cancer.

    Science.gov (United States)

    Yuan, Jian-Min; Butler, Lesley M; Stepanov, Irina; Hecht, Stephen S

    2014-01-15

    Tobacco-constituent biomarkers are metabolites of specific compounds present in tobacco or tobacco smoke. Highly reliable analytic methods, based mainly on mass spectrometry, have been developed for quantitation of these biomarkers in both urine and blood specimens. There is substantial interindividual variation in smoking-related lung cancer risk that is determined in part by individual variability in the uptake and metabolism of tobacco smoke carcinogens. Thus, by incorporating these biomarkers in epidemiologic studies, we can potentially obtain a more valid and precise measure of in vivo carcinogen dose than by using self-reported smoking history, ultimately improving the estimation of smoking-related lung cancer risk. Indeed, we have demonstrated this by using a prospective study design comparing biomarker levels in urine samples collected from smokers many years before their development of cancer versus those in their smoking counterparts without a cancer diagnosis. The following urinary metabolites were associated with lung cancer risk, independent of smoking intensity and duration: cotinine plus its glucuronide, a biomarker of nicotine uptake; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides (total NNAL), a biomarker of the tobacco carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK); and r-1-,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene (PheT), a biomarker of polycyclic aromatic hydrocarbons (PAH). These results provide several possible new directions for using tobacco smoke-constituent biomarkers in lung cancer prevention, including improved lung cancer risk assessment, intermediate outcome determination in prevention trials, and regulation of tobacco products.

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

    Directory of Open Access Journals (Sweden)

    Peter E. Barker

    2009-11-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

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

    Science.gov (United States)

    Tan, M H 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

  19. 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

    -glycopeptide microarray was developed that detected IgG antibodies to aberrant O-glycopeptide epitopes in patients vaccinated with a keyhole limpet hemocyanin-conjugated truncated MUC1 peptide. We detected cancer-associated IgG autoantibodies in sera from breast, ovarian, and prostate cancer patients against different...... 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......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...

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

    Institute of Scientific and Technical Information of China (English)

    Norihisa; Uemura; Tadashi; Kondo

    2014-01-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

  2. Discovery of specific metastasis-related N-glycan alterations in epithelial ovarian cancer based on quantitative glycomics.

    Directory of Open Access Journals (Sweden)

    Xingwang Zhang

    Full Text Available Generally, most of ovarian cancer cannot be detected until large scale and remote metastasis occurs, which is the major cause of high mortality in ovarian cancer. Therefore, it is urgent to discover metastasis-related biomarkers for the detection of ovarian cancer in its occult metastasis stage. Altered glycosylation is a universal feature of malignancy and certain types of glycan structures are well-known markers for tumor progressions. Thus, this study aimed to reveal specific changes of N-glycans in the secretome of the metastatic ovarian cancer. We employed a quantitative glycomics approach based on metabolic stable isotope labeling to compare the differential N-glycosylation of secretome between an ovarian cancer cell line SKOV3 and its high metastatic derivative SKOV3-ip. Intriguingly, among total 17 N-glycans identified, the N-glycans with bisecting GlcNAc were all significantly decreased in SKOV3-ip in comparison to SKOV3. This alteration in bisecting GlcNAc glycoforms as well as its corresponding association with ovarian cancer metastatic behavior was further validated at the glycotransferase level with multiple techniques including real-time PCR, western blotting, transwell assay, lectin blotting and immunohistochemistry analysis. This study illustrated metastasis-related N-glycan alterations in ovarian cancer secretome in vitro for the first time, which is a valuable source for biomarker discovery as well. Moreover, N-glycans with bisecting GlcNAc shed light on the detection of ovarian cancer in early peritoneal metastasis stage which may accordingly improve the prognosis of ovarian cancer patients.

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

    Science.gov (United States)

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

    2014-10-15

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

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

    OpenAIRE

    Trivedi, Mahendra Kumar

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Takayuki Goto

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

  6. Review: US Spelling Colorectal cancer models for novel drug discovery

    Science.gov (United States)

    Golovko, Daniel; Kedrin, Dmitriy; Yilmaz, Omer H.; Roper, Jatin

    2016-01-01

    Introduction Despite increased screening rates and advances in targeted therapy, colorectal cancer (CRC) remains the third leading cause of cancer-related mortality. CRC models that recapitulate key features of human disease are essential to the development of novel and effective therapeutics. Classic methods of modeling CRC such as human cell lines and xenograft mice, while useful for many applications, carry significant limitations. Recently developed in vitro and in vivo models overcome some of these deficiencies and thus can be utilized to better model CRC for mechanistic and translational research. Areas Covered The authors review established models of in vitro cell culture and describe advances in organoid culture for studying normal and malignant intestine. They also discuss key features of classic xenograft models and describe other approaches for in vivo CRC research, including patient-derived xenograft, carcinogen-induced, orthotopic transplantation, and transgenic mouse models. We also describe mouse models of metastatic CRC. Expert opinion No single model is optimal for drug discovery in CRC. Genetically engineered models overcome many limitations of xenograft models. Three-dimensional organoids can be efficiently derived from both normal and malignant tissue for large-scale in vitro and in vivo (transplantation) studies, and are thus a significant advance in CRC drug discovery. PMID:26295972

  7. Knowledge discovery for pancreatic cancer using inductive logic programming.

    Science.gov (United States)

    Qiu, Yushan; Shimada, Kazuaki; Hiraoka, Nobuyoshi; Maeshiro, Kensei; Ching, Wai-Ki; Aoki-Kinoshita, Kiyoko F; Furuta, Koh

    2014-08-01

    Pancreatic cancer is a devastating disease and predicting the status of the patients becomes an important and urgent issue. The authors explore the applicability of inductive logic programming (ILP) method in the disease and show that the accumulated clinical laboratory data can be used to predict disease characteristics, and this will contribute to the selection of therapeutic modalities of pancreatic cancer. The availability of a large amount of clinical laboratory data provides clues to aid in the knowledge discovery of diseases. In predicting the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer, using the ILP model, three rules are developed that are consistent with descriptions in the literature. The rules that are identified are useful to detect the differentiation of tumour and the status of lymph node metastasis in pancreatic cancer and therefore contributed significantly to the decision of therapeutic strategies. In addition, the proposed method is compared with the other typical classification techniques and the results further confirm the superiority and merit of the proposed method.

  8. Systematic Discovery of Complex Indels in Human Cancers

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jonghwan Lee

    2015-04-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-10-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

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

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

    OpenAIRE

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

    2013-01-01

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

  17. Application of systems biology principles to protein biomarker discovery: Urinary exosomal proteome in renal transplantation

    Science.gov (United States)

    Das, Samarjit; Knepper, Mark A.; Bagnasco, Serena M.

    2013-01-01

    Purpose In MS-based studies to discover urinary protein biomarkers, an important question is how to analyze the data to find the most promising potential biomarkers to be advanced to large-scale validation studies. Here, we describe a ‘systems biology-based’ approach to address this question. Experimental design We analyzed large-scale LC-MS/MS data of urinary exosomes from renal allograft recipients with biopsy-proven evidence of immunological rejection or tubular injury. We asked whether bioinformatic analysis of urinary exosomal proteins can identify protein groups that correlate with biopsy findings and whether the protein groups fit with general knowledge of the pathophysiological mechanisms involved. Results LC-MS/MS analysis of urinary exosomal proteomes identified more than 1000 proteins in each pathologic group. These protein lists were analyzed computationally to identify Biological Process and KEGG Pathway terms that are significantly associated with each pathological group. Among the most informative terms for each group were: “sodium ion transport” for tubular injury; “immune response” for all rejection; “epithelial cell differentiation” for cell-mediated rejection; and “acute inflammatory response” for antibody-mediated rejection. Based on these terms, candidate biomarkers were identified using a novel strategy to allow a dichotomous classification between different pathologic categories. Conclusions and clinical relevance The terms and candidate biomarkers identified make rational connections to pathophysiological mechanisms, suggesting that the described bioinformatic approach will be useful in advancing large-scale biomarker identification studies toward a validation phase. PMID:22641613

  18. 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

  19. Candidate serological biomarkers for cancer identified from the secretomes of 23 cancer cell lines and the human protein atlas.

    Science.gov (United States)

    Wu, Chih-Ching; Hsu, Chia-Wei; Chen, Chi-De; Yu, Chia-Jung; Chang, Kai-Ping; Tai, Dar-In; Liu, Hao-Ping; Su, Wen-Hui; Chang, Yu-Sun; Yu, Jau-Song

    2010-06-01

    Although cancer cell secretome profiling is a promising strategy used to identify potential body fluid-accessible cancer biomarkers, questions remain regarding the depth to which the cancer cell secretome can be mined and the efficiency with which researchers can select useful candidates from the growing list of identified proteins. Therefore, we analyzed the secretomes of 23 human cancer cell lines derived from 11 cancer types using one-dimensional SDS-PAGE and nano-LC-MS/MS performed on an LTQ-Orbitrap mass spectrometer to generate a more comprehensive cancer cell secretome. A total of 31,180 proteins was detected, accounting for 4,584 non-redundant proteins, with an average of 1,300 proteins identified per cell line. Using protein secretion-predictive algorithms, 55.8% of the proteins appeared to be released or shed from cells. The identified proteins were selected as potential marker candidates according to three strategies: (i) proteins apparently secreted by one cancer type but not by others (cancer type-specific marker candidates), (ii) proteins released by most cancer cell lines (pan-cancer marker candidates), and (iii) proteins putatively linked to cancer-relevant pathways. We then examined protein expression profiles in the Human Protein Atlas to identify biomarker candidates that were simultaneously detected in the secretomes and highly expressed in cancer tissues. This analysis yielded 6-137 marker candidates selective for each tumor type and 94 potential pan-cancer markers. Among these, we selectively validated monocyte differentiation antigen CD14 (for liver cancer), stromal cell-derived factor 1 (for lung cancer), and cathepsin L1 and interferon-induced 17-kDa protein (for nasopharyngeal carcinoma) as potential serological cancer markers. In summary, the proteins identified from the secretomes of 23 cancer cell lines and the Human Protein Atlas represent a focused reservoir of potential cancer biomarkers.

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

  2. Cell-specific biomarkers and targeted biopharmaceuticals for breast cancer treatment.

    Science.gov (United States)

    Liu, Mei; Li, Zhiyang; Yang, Jingjing; Jiang, Yanyun; Chen, Zhongsi; Ali, Zeeshan; He, Nongyue; Wang, Zhifei

    2016-08-01

    Breast cancer is the second leading cause of cancer death among women, and its related treatment has been attracting significant attention over the past decades. Among the various treatments, targeted therapy has shown great promise as a precision treatment, by binding to cancer cell-specific biomarkers. So far, great achievements have been made in targeted therapy of breast cancer. In this review, we first discuss cell-specific biomarkers, which are not only useful for classification of breast cancer subtyping but also can be utilized as goals for targeted therapy. Then, the innovative and generic-targeted biopharmaceuticals for breast cancer, including monoclonal antibodies, non-antibody proteins and small molecule drugs, are reviewed. Finally, we provide our outlook on future developments of biopharmaceuticals, and provide solutions to problems in this field. PMID:27312135

  3. Cell-specific biomarkers and targeted biopharmaceuticals for breast cancer treatment.

    Science.gov (United States)

    Liu, Mei; Li, Zhiyang; Yang, Jingjing; Jiang, Yanyun; Chen, Zhongsi; Ali, Zeeshan; He, Nongyue; Wang, Zhifei

    2016-08-01

    Breast cancer is the second leading cause of cancer death among women, and its related treatment has been attracting significant attention over the past decades. Among the various treatments, targeted therapy has shown great promise as a precision treatment, by binding to cancer cell-specific biomarkers. So far, great achievements have been made in targeted therapy of breast cancer. In this review, we first discuss cell-specific biomarkers, which are not only useful for classification of breast cancer subtyping but also can be utilized as goals for targeted therapy. Then, the innovative and generic-targeted biopharmaceuticals for breast cancer, including monoclonal antibodies, non-antibody proteins and small molecule drugs, are reviewed. Finally, we provide our outlook on future developments of biopharmaceuticals, and provide solutions to problems in this field.

  4. 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 poly

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

  7. TOFwave: reproducibility in biomarker discovery from time-of-flight mass spectrometry data.

    Science.gov (United States)

    Chierici, Marco; Albanese, Davide; Franceschi, Pietro; Furlanello, Cesare

    2012-11-01

    Many are the sources of variability that can affect reproducibility of disease biomarkers from time-of-flight (TOF) Mass Spectrometry (MS) data. Here we present TOFwave, a complete software pipeline for TOF-MS biomarker identification, that limits the impact of parameter tuning along the whole chain of preprocessing and model selection modules. Peak profiles are obtained by a preprocessing based on Continuous Wavelet Transform (CWT), coupled with a machine learning protocol aimed at avoiding selection bias effects. Only two parameters (minimum peak width and a signal to noise cutoff) have to be explicitly set. The TOFwave pipeline is built on top of the mlpy Python package. Examples on Matrix-Assisted Laser Desorption and Ionization (MALDI) TOF datasets are presented. Software prototype, datasets and details to replicate results in this paper can be found at http://mlpy.sf.net/tofwave/. PMID:22875362

  8. 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

    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...... 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...

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

  13. 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. PMID:26543078

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

    OpenAIRE

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

    2010-01-01

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

  15. 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 ...

  16. Single-band upconversion nanoprobes for multiplexed simultaneous in situ molecular mapping of cancer biomarkers

    Science.gov (United States)

    Zhou, Lei; Wang, Rui; Yao, Chi; Li, Xiaomin; Wang, Chengli; Zhang, Xiaoyan; Xu, Congjian; Zeng, Aijun; Zhao, Dongyuan; Zhang, Fan

    2015-04-01

    The identification of potential diagnostic markers and target molecules among the plethora of tumour oncoproteins for cancer diagnosis requires facile technology that is capable of quantitatively analysing multiple biomarkers in tumour cells and tissues. Diagnostic and prognostic classifications of human tumours are currently based on the western blotting and single-colour immunohistochemical methods that are not suitable for multiplexed detection. Herein, we report a general and novel method to prepare single-band upconversion nanoparticles with different colours. The expression levels of three biomarkers in breast cancer cells were determined using single-band upconversion nanoparticles, western blotting and immunohistochemical technologies with excellent correlation. Significantly, the application of antibody-conjugated single-band upconversion nanoparticle molecular profiling technology can achieve the multiplexed simultaneous in situ biodetection of biomarkers in breast cancer cells and tissue specimens and produce more accurate results for the simultaneous quantification of proteins present at low levels compared with classical immunohistochemical technology.

  17. Improving low-level plasma protein mass spectrometry-based detection for candidate biomarker discovery and validation

    Energy Technology Data Exchange (ETDEWEB)

    Page, Jason S.; Kelly, Ryan T.; Camp, David G.; Smith, Richard D.

    2008-09-01

    Methods. To improve the detection of low abundance protein candidate biomarker discovery and validation, particularly in complex biological fluids such as blood plasma, increased sensitivity is desired using mass spectrometry (MS)-based instrumentation. A key current limitation on the sensitivity of electrospray ionization (ESI) MS is due to the fact that many sample molecules in solution are never ionized, and the vast majority of the ions that are created are lost during transmission from atmospheric pressure to the low pressure region of the mass analyzer. Two key technologies, multi-nanoelectrospray emitters and the electrodynamic ion funnel have recently been developed and refined at Pacific Northwest National Laboratory (PNNL) to greatly improve the ionization and transmission efficiency of ESI MS based analyses. Multi-emitter based ESI enables the flow from a single source (typically a liquid chromatography [LC] column) to be divided among an array of emitters (Figure 1). The flow rate delivered to each emitter is thus reduced, allowing the well-documented benefits of nanoelectrospray 1 for both sensitivity and quantitation to be realized for higher flow rate separations. To complement the increased ionization efficiency afforded by multi-ESI, tandem electrodynamic ion funnels have also been developed at PNNL, and shown to greatly improve ion transmission efficiency in the ion source interface.2, 3 These technologies have been integrated into a triple quadrupole mass spectrometer for multiple reaction monitoring (MRM) of probable biomarker candidates in blood plasma and show promise for the identification of new species even at low level concentrations.

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

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

    2015-11-17

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

  20. Aberrant Crypt Foci: The Case for Inclusion as a Biomarker for Colon Cancer

    Directory of Open Access Journals (Sweden)

    Jay Morris

    2010-09-01

    Full Text Available Aberrant crypt foci (ACF are one of the earliest histopathological manifestations of colon cancer. In this review, we critically present the molecular, cellular, histopathological, and chemopreventive evidence that ACF are relevant biomarkers for colon cancer. The laboratory and clinical evidence are highly suggestive that ACF are in the pathway leading to colon cancer, but not all ACF will do so. The possible fate and outcome of ACF in the progression toward colon cancer may be dependent on a number of features that define their predictive power for the prevention or progression of cancer.

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

    Directory of Open Access Journals (Sweden)

    Erika Larrea

    2016-04-01

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

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

    Science.gov (United States)

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

    2016-05-01

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

  3. 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

  4. 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.

  5. 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.

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

    Science.gov (United States)

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

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

    OpenAIRE

    Ian Collins; Jones, Alan M.

    2014-01-01

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

  8. [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.

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

    Directory of Open Access Journals (Sweden)

    Michael Phillips

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

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

    Science.gov (United States)

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

    2015-01-01

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

  11. 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

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    Natalie Turner

    2014-03-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Steven M. Lucas

    2012-01-01

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

  16. Potential Biomarker of L type Amino Acid Transporter 1 in Breast Cancer Progression

    Energy Technology Data Exchange (ETDEWEB)

    Liang, Zhongxing; Cho, Heidi T.; Williams, Larry; Zhu, Aizhi; Liang, Ke; Huang, Ke; Wu, Hui; Jiang, Chunsu; Hong, Samuel; Crowe, Ronald; Goodman, Mark M.; Shim, Hyunsuk [Emory Univ. School of Medicine, Atlanta (United States)

    2011-06-15

    L type amino acid transporter 1 (LAT1) is essential for the transport of large neutral amino acids. However, its role in breast cancer growth remains largely unknown. The purpose of the study is to investigate whether LAT1 is a potential biomarker for the diagnosis and treatment of breast cancer. LAT1 mRNA and protein levels in breast cancer cell lines and tissues were analyzed. In addition, the effects of targeting LAT1 for the inhibition of breast cancer cell tumorigenesis were assessed with soft agar assay. The imaging of xenograft with 1 amino 3 [{sup 18F}]fluorocyclo butane 1 carboxylic acid ([{sup 18F}]FACBC) PET was assessed for its diagnostic biomarker potential. Normal breast tissue or low malignant cell lines expressed low levels of LAT1 mRNA and protein, while highly malignant cancer cell lines and high grade breast cancer tissue expressed high levels of LAT1. In addition, higher expression levels of LAT1 in breast cancer tissues were consistent with advanced stage breast cancer. Furtermore, the blockade of LAT1 with its inhibitor, 2 amino bicyclo[2.2.1]heptane 2 carboxylic acid (BCH), or the knockdown of LAT1 with siRNA, inhibited proliferation and tumorigenesis of breast cancer cells. A leucine analog, [{sup 18F}]FACBC, has been demonstrated to be an excellent PET tracer for the non invasive imaging og malignant breast cancer using an orthotopic animal model. The overexpression of LAT1 is required for the progression of breast cancer. LAT1 represents a potential biomarker for therapy and diagnosis of breast cancer. [{sup 18F}]FACBC that correlates with LAT1 function is a potential PET tracer for malignant breast tumor imaging.

  17. Prediagnostic serum biomarkers as early detection tools for pancreatic cancer in a large prospective cohort study.

    Directory of Open Access Journals (Sweden)

    Brian M Nolen

    Full Text Available BACKGROUND: The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. METHODS: Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO. RESULTS: The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively associated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN levels of 32.4% and 29.7% in samples collected 1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. CONCLUSIONS: Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combinations offered advantage over CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis. However, the efficacy of biomarker-based tools remains limited at present. Several biomarkers demonstrated significant velocity related to time to diagnosis, an observation which may offer considerable potential for enhancements in early detection.

  18. Molecular biomarker set for early detection of ovarian cancer

    KAUST Repository

    Bajic, Vladimir B.

    2015-06-16

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

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

    OpenAIRE

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-01-01

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

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

    OpenAIRE

    Brown, Janet E.; Sim, Sheryl

    2010-01-01

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

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

    OpenAIRE

    Brown, Janet E.; Sheryl Sim

    2010-01-01

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

  2. 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.

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

    OpenAIRE

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-01-01

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

  4. 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.

  5. Blood diagnostic biomarkers for major depressive disorder using multiplex DNA methylation profiles: discovery and validation.

    Science.gov (United States)

    Numata, Shusuke; Ishii, Kazuo; Tajima, Atsushi; Iga, Jun-ichi; Kinoshita, Makoto; Watanabe, Shinya; Umehara, Hidehiro; Fuchikami, Manabu; Okada, Satoshi; Boku, Shuken; Hishimoto, Akitoyo; Shimodera, Shinji; Imoto, Issei; Morinobu, Shigeru; Ohmori, Tetsuro

    2015-01-01

    Aberrant DNA methylation in the blood of patients with major depressive disorder (MDD) has been reported in several previous studies. However, no comprehensive studies using medication-free subjects with MDD have been conducted. Furthermore, the majority of these previous studies has been limited to the analysis of the CpG sites in CpG islands (CGIs) in the gene promoter regions. The main aim of the present study is to identify DNA methylation markers that distinguish patients with MDD from non-psychiatric controls. Genome-wide DNA methylation profiling of peripheral leukocytes was conducted in two set of samples, a discovery set (20 medication-free patients with MDD and 19 controls) and a replication set (12 medication-free patients with MDD and 12 controls), using Infinium HumanMethylation450 BeadChips. Significant diagnostic differences in DNA methylation were observed at 363 CpG sites in the discovery set. All of these loci demonstrated lower DNA methylation in patients with MDD than in the controls, and most of them (85.7%) were located in the CGIs in the gene promoter regions. We were able to distinguish patients with MDD from the control subjects with high accuracy in the discriminant analysis using the top DNA methylation markers. We also validated these selected DNA methylation markers in the replication set. Our results indicate that multiplex DNA methylation markers may be useful for distinguishing patients with MDD from non-psychiatric controls.

  6. 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...

  7. 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.

  8. 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.)

  9. AGR3 in Breast Cancer: Prognostic Impact and Suitable Serum-Based Biomarker for Early Cancer Detection

    Science.gov (United States)

    Garczyk, Stefan; von Stillfried, Saskia; Antonopoulos, Wiebke; Hartmann, Arndt; Schrauder, Michael G.; Fasching, Peter A.; Anzeneder, Tobias; Tannapfel, Andrea; Ergönenc, Yavuz; Knüchel, Ruth

    2015-01-01

    Blood-based early detection of breast cancer has recently gained novel momentum, as liquid biopsy diagnostics is a fast emerging field. In this study, we aimed to identify secreted proteins which are up-regulated both in tumour tissue and serum samples of breast cancer patients compared to normal tissue and sera. Based on two independent tissue cohorts (n = 75 and n = 229) and one serum cohort (n = 80) of human breast cancer and healthy serum samples, we characterised AGR3 as a novel potential biomarker both for breast cancer prognosis and early breast cancer detection from blood. AGR3 expression in breast tumours is significantly associated with oestrogen receptor α (P<0.001) and lower tumour grade (P<0.01). Interestingly, AGR3 protein expression correlates with unfavourable outcome in low (G1) and intermediate (G2) grade breast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, P<0.05) indicating an independent prognostic impact. In sera analysed by ELISA technique, AGR3 protein concentration was significantly (P<0.001) elevated in samples from breast cancer patients (n = 40, mainly low stage tumours) compared to healthy controls (n = 40). To develop a suitable biomarker panel for early breast cancer detection, we measured AGR2 protein in human serum samples in parallel. The combined AGR3/AGR2 biomarker panel achieved a sensitivity of 64.5% and a specificity of 89.5% as shown by receiver operating characteristic (ROC) curve statistics. Thus our data clearly show the potential usability of AGR3 and AGR2 as biomarkers for blood-based early detection of human breast cancer. PMID:25875093

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

    Science.gov (United States)

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

    2014-10-01

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

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

    Science.gov (United States)

    Herreros-Villanueva, Marta; Bujanda, Luis

    2016-04-01

    Pancreatic cancer (PC) is probably the most lethal tumor being forecast as the second most fatal cancer by 2020 in developed countries. Only the earliest forms of the disease are a curable disease but it has to be diagnosed before symptoms starts. Detection at curable phase demands screening intervention for early detection and differential diagnosis. Unfortunately, no successful strategy or image technique has been concluded as effective approach and currently non-invasive biomarkers are the hope. Multiple translational research studies have explored minimally or non-invasive biomarkers in biofluids-blood, urine, stool, saliva or pancreatic juice, but diagnostic performance has not been validated yet. Nowadays no biomarker, alone or in combination, has been superior to carbohydrate antigen 19-9 (CA19-9) in sensitivity and specificity. Although the number of novel biomarkers for early diagnosis of PC has been increasing during the last couple of years, no molecular signature is ready to be implemented in clinical routine. Under the uncertain future, miRNAs profiling and methylation status seem to be the most promising biomarkers. However, good results in larger validations are urgently needed before application. Industry efforts through biotech and pharmaceutical companies are urgently required to demonstrate accuracy and validate promising results from basic and translational results. PMID:27162784

  12. Fucose: A biomarker in grading of oral cancer

    OpenAIRE

    Kumar, Satish; Saxena, Mona; Srinivas, Kandakurtis; Singh, Vinod Kumar

    2015-01-01

    Introduction: Early diagnosis of cancer helps a great deal in the management of oral cancer patients. Number of proteinous markers have been employed for this purpose. Majority of them are not specific. Recently conjugated oligosaccharide with proteins and lipids have gained considerable importance in the present postgenomics and postproteomic period in the diagnostic and prognostics of cancer cases. Materials and Methods: In this study, serum fucose levels were estimated in 50 control cases ...

  13. 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.

  14. Serial Patterns of Ovarian Cancer Biomarkers in a Prediagnosis Longitudinal Dataset.

    Science.gov (United States)

    Blyuss, Oleg; Gentry-Maharaj, Alex; Fourkala, Evangelia-Orania; Ryan, Andy; Zaikin, Alexey; Menon, Usha; Jacobs, Ian; Timms, John F

    2015-01-01

    Early detection of ovarian cancer through screening may have impact on mortality from the disease. Approaches based on CA125 cut-off have not been effective. Longitudinal algorithms such as the Risk of Ovarian Cancer Algorithm (ROCA) to interpret CA125 have been shown to have higher sensitivity and specificity than a single cut-off. The aim of this study was to investigate whether other ovarian cancer-related biomarkers, Human Epididymis 4 (HE4), glycodelin, mesothelin, matrix metalloproteinase 7 (MMP7), and cytokeratin 19 fragment (CYFRA 21-1), could improve the performance of CA125 in detecting ovarian cancer earlier. Serum samples (single and serial) predating diagnosis from 47 women taking part in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) who went on to develop primary invasive ovarian, fallopian tube, or peritoneal cancer (index cancer) (170 samples) and 179 matched controls (893 samples) were included in the study. A multiplex immunobased assay platform (Becton Dickinson) allowing simultaneous measurement of the six serum markers was used. The area under the ROC curve for the panel of three biomarkers (CA125, HE4, and glycodelin) was higher than for CA125 alone for all analysed time groups, indicating that these markers can improve on sensitivity of CA125 alone for ovarian cancer detection. PMID:26819954

  15. Serial Patterns of Ovarian Cancer Biomarkers in a Prediagnosis Longitudinal Dataset

    Directory of Open Access Journals (Sweden)

    Oleg Blyuss

    2015-01-01

    Full Text Available Early detection of ovarian cancer through screening may have impact on mortality from the disease. Approaches based on CA125 cut-off have not been effective. Longitudinal algorithms such as the Risk of Ovarian Cancer Algorithm (ROCA to interpret CA125 have been shown to have higher sensitivity and specificity than a single cut-off. The aim of this study was to investigate whether other ovarian cancer-related biomarkers, Human Epididymis 4 (HE4, glycodelin, mesothelin, matrix metalloproteinase 7 (MMP7, and cytokeratin 19 fragment (CYFRA 21-1, could improve the performance of CA125 in detecting ovarian cancer earlier. Serum samples (single and serial predating diagnosis from 47 women taking part in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS who went on to develop primary invasive ovarian, fallopian tube, or peritoneal cancer (index cancer (170 samples and 179 matched controls (893 samples were included in the study. A multiplex immunobased assay platform (Becton Dickinson allowing simultaneous measurement of the six serum markers was used. The area under the ROC curve for the panel of three biomarkers (CA125, HE4, and glycodelin was higher than for CA125 alone for all analysed time groups, indicating that these markers can improve on sensitivity of CA125 alone for ovarian cancer detection.

  16. Xenograft assessment of predictive biomarkers for standard head and neck cancer therapies.

    Science.gov (United States)

    Stein, Andrew P; Swick, Adam D; Smith, Molly A; Blitzer, Grace C; Yang, Robert Z; Saha, Sandeep; Harari, Paul M; Lambert, Paul F; Liu, Cheng Z; Kimple, Randall J

    2015-05-01

    Head and neck squamous cell carcinoma (HNSCC) remains a challenging cancer to treat with overall 5-year survival on the order of 50-60%. Therefore, predictive biomarkers for this disease would be valuable to provide more effective and individualized therapeutic approaches for these patients. While prognostic biomarkers such as p16 expression correlate with outcome; to date, no predictive biomarkers have been clinically validated for HNSCC. We generated xenografts in immunocompromised mice from six established HNSCC cell lines and evaluated response to cisplatin, cetuximab, and radiation. Tissue microarrays were constructed from pre- and posttreatment tumor samples derived from each xenograft experiment. Quantitative immunohistochemistry was performed using a semiautomated imaging and analysis platform to determine the relative expression of five potential predictive biomarkers: epidermal growth factor receptor (EGFR), phospho-EGFR, phospho-Akt, phospho-ERK, and excision repair cross-complementation group 1 (ERCC1). Biomarker levels were compared between xenografts that were sensitive versus resistant to a specific therapy utilizing a two-sample t-test with equal standard deviations. Indeed the xenografts displayed heterogeneous responses to each treatment, and we linked a number of baseline biomarker levels to response. This included low ERCC1 being associated with cisplatin sensitivity, low phospho-Akt correlated with cetuximab sensitivity, and high total EGFR was related to radiation resistance. Overall, we developed a systematic approach to identifying predictive biomarkers and demonstrated several connections between biomarker levels and treatment response. Despite these promising initial results, this work requires additional preclinical validation, likely involving the use of patient-derived xenografts, prior to moving into the clinical realm for confirmation among patients with HNSCC.

  17. 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.

  18. DNA methylome and the complexity of discovering prostate cancer biomarkers

    Institute of Scientific and Technical Information of China (English)

    Shahriar Koochekpour

    2011-01-01

    @@ Prostate cancer (PCa) remains the most common malignancy and a leading cause of cancer-related deaths in men.Molecular discrimination at an early stage between indolent and aggressive primary tumors in pathologically confirmed PCa is required to develop personalized therapeutic interventions.

  19. Chromosomal aberrations and SCEs as biomarkers of cancer risk

    DEFF Research Database (Denmark)

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

    2006-01-01

    of xenobiotic metabolism, DNA repair, and folate metabolism affect the level of CAs and might collectively contribute to the cancer predictivity of CAs. Other factors that may influence the association between CAs and cancer include, e.g., exposure to genotoxic carcinogens and internal generation of genotoxic...

  20. Collections of simultaneously altered genes as biomarkers of cancer cell drug response.

    Science.gov (United States)

    Masica, David L; Karchin, Rachel

    2013-03-15

    Computational analysis of cancer pharmacogenomics data has resulted in biomarkers predictive of drug response, but the majority of response is not captured by current methods. Methods typically select single biomarkers or groups of related biomarkers but do not account for response that is strictly dependent on many simultaneous genetic alterations. This shortcoming reflects the combinatorics and multiple-testing problem associated with many-body biologic interactions. We developed a novel approach, Multivariate Organization of Combinatorial Alterations (MOCA), to partially address these challenges. Extending on previous work that accounts for pairwise interactions, the approach rapidly combines many genomic alterations into biomarkers of drug response, using Boolean set operations coupled with optimization; in this framework, the union, intersection, and difference Boolean set operations are proxies of molecular redundancy, synergy, and resistance, respectively. The algorithm is fast, broadly applicable to cancer genomics data, is of immediate use for prioritizing cancer pharmacogenomics experiments, and recovers known clinical findings without bias. Furthermore, the results presented here connect many important, previously isolated observations.

  1. The Progress and Prospects of Putative Biomarkers for Liver Cancer Stem Cells in Hepatocellular Carcinoma.

    Science.gov (United States)

    Xiang, Yan; Yang, Ting; Pang, Bing-Yao; Zhu, Ying; Liu, Yong-Ning

    2016-01-01

    Accumulating evidence suggests that hepatocellular carcinoma (HCC) is organized by liver cancer stem cells (LCSCs), which are a subset of cells with "stem-like" characteristics. Identification of the LCSCs is a fundamental and important problem in HCC research. LCSCs have been investigated by various stem cell biomarkers. There is still lack of consensus regarding the existence of a "global" marker for LCSCs in HCC. In this review article, we summarize the progress and prospects of putative biomarkers for LCSCs in the past decades, which is essential to develop future therapies targeting CSCs and to predict prognosis and curative effect of these therapies. PMID:27610139

  2. 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.

  3. Circulating microRNAs: Novel biomarkers for esophageal cancer

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Esophageal carcinogenesis is a multi-stage process, involving a variety of changes in gene expression and physiological structure change. MicroRNAs (miRNAs) are a class of small non-coding endogenous RNA molecules. Recent innovation in miRNAs profiling technology have shed new light on the pathology of esophageal carcinoma (EC), and also heralded great potential for exploring novel biomarkers for both EC diagnosis and treatment. Frequent dysregulation of miRNA in malignancy highlights the study of molecular...

  4. Personalization of prostate cancer prevention and therapy: are clinically qualified biomarkers in the horizon?

    Directory of Open Access Journals (Sweden)

    Yap Timothy A

    2012-01-01

    Full Text Available Abstract Prostate cancer remains the most common malignancy among men and the second leading cause of male cancer-related mortality. Death from this disease is invariably due to resistance to androgen deprivation therapy. Our improved understanding of the biology of prostate cancer has heralded a new era in molecular anticancer drug development, with multiple novel anticancer drugs for castration resistant prostate cancer now entering the clinic. These include the taxane cabazitaxel, the vaccine sipuleucel-T, the CYP17 inhibitor abiraterone, the novel androgen receptor antagonist MDV-3100 and the radionuclide alpharadin. The management and therapeutic landscape of prostate cancer has now been transformed with this growing armamentarium of effective antitumor agents. This review discusses strategies for the prevention and personalization of prostate cancer therapy, with a focus on the development of predictive and intermediate endpoint biomarkers, as well as novel clinical trial designs that will be crucial for the optimal development of such anticancer therapeutics.

  5. Human Papilloma Virus as a Biomarker for Personalized Head and Neck Cancer Radiotherapy

    DEFF Research Database (Denmark)

    Eriksen, Jesper Grau; Lassen, Pernille

    2016-01-01

    A dramatic increase in the incidence of HPV-related oropharyngeal cancer has been reported in some parts of the western world over the past 30 years. They constitute a clinically distinct subgroup of cancers in terms of molecular biology, patient characteristics, and treatment outcome. This chapter...... describes the molecular characteristics, epidemiology, and demographics of the HPV-related head and neck cancers and discuss available methods to detect HPV-related tumours. The impact of HPV-related biomarkers in clinical studies on radiotherapy only, altered fractionation, modulation of hypoxia...

  6. Multi-transcript profiling in archival diagnostic prostate cancer needle biopsies to evaluate biomarkers in non-surgically treated men

    OpenAIRE

    Kachroo, Naveen; Warren, Anne Y; Gnanapragasam, Vincent J.

    2014-01-01

    Background Most biomarkers in prostate cancer have only been evaluated in surgical cohorts. The value of these biomarkers in a different therapy context remains unclear. Our objective was to test a panel of surgical biomarkers for prognostic value in men treated by external beam radiotherapy (EBRT) and primary androgen deprivation therapy (PADT). Methods The Fluidigm® PCR array was used for multi-transcript profiling of laser microdissected tumours from archival formalin-fixed diagnostic biop...

  7. AGE metabolites: a biomarker linked to cancer disparity?

    Science.gov (United States)

    Foster, Dion; Spruill, Laura; Walter, Katherine R; Nogueira, Lourdes M; Fedarovich, Hleb; Turner, Ryan Y; Ahmed, Mahtabuddin; Salley, Judith D; Ford, Marvella E; Findlay, Victoria J; Turner, David P

    2014-10-01

    Socioeconomic and environmental influences are established factors promoting cancer disparity, but the contribution of biologic factors is not clear. We report a mechanistic link between carbohydrate-derived metabolites and cancer that may provide a biologic consequence of established factors of cancer disparity. Glycation is the nonenzymatic glycosylation of carbohydrates to macromolecules, which produces reactive metabolites called advanced glycation end products (AGE). A sedentary lifestyle and poor diet all promote disease and the AGE accumulation pool in our bodies and also increase cancer risk. We examined AGE metabolites in clinical specimens of African American and European American patients with prostate cancer and found a higher AGE concentration in these specimens among African American patients when compared with European American patients. Elevated AGE levels corresponded with expression of the receptor for AGE (RAGE or AGER). We show that AGE-mediated increases in cancer-associated processes are dependent upon RAGE. Aberrant AGE accumulation may represent a metabolic susceptibility difference that contributes to cancer disparity. PMID:25053712

  8. Potentials of plasma NGAL and MIC-1 as biomarker(s in the diagnosis of lethal pancreatic cancer.

    Directory of Open Access Journals (Sweden)

    Sukhwinder Kaur

    Full Text Available Pancreatic cancer (PC is lethal malignancy with very high mortality rate. Absence of sensitive and specific marker(s is one of the major factors for poor prognosis of PC patients. In pilot studies using small set of patients, secreted acute phase proteins neutrophil gelatinase associated lipocalin (NGAL and TGF-β family member macrophage inhibitory cytokine-1 (MIC-1 are proposed as most potential biomarkers specifically elevated in the blood of PC patients. However, their performance as diagnostic markers for PC, particularly in pre-treatment patients, remains unknown. In order to evaluate the diagnostic efficacy of NGAL and MIC-1, their levels were measured in plasma samples from patients with pre-treatment PC patients (n = 91 and compared it with those in healthy control (HC individuals (n = 24 and patients with chronic pancreatitis (CP, n = 23. The diagnostic performance of these two proteins was further compared with that of CA19-9, a tumor marker commonly used to follow PC progression. The levels of all three biomarkers were significantly higher in PC compared to HCs. The mean (± standard deviation, SD plasma NGAL, CA19-9 and MIC-1 levels in PC patients was 111.1 ng/mL (2.2, 219.2 U/mL (7.8 and 4.5 ng/mL (4.1, respectively. In comparing resectable PC to healthy patients, all three biomarkers were found to have comparable sensitivities (between 64%-81% but CA19-9 and NGAL had a higher specificity (92% and 88%, respectively. For distinguishing resectable PC from CP patients, CA19-9 and MIC-1 were most specific (74% and 78% respectively. CA19-9 at an optimal cut-off of 54.1 U/ml is highly specific in differentiating resectable (stage 1/2 pancreatic cancer patients from controls in comparison to its clinical cut-off (37.1 U/ml. Notably, the addition of MIC-1 to CA19-9 significantly improved the ability to distinguish resectable PC cases from CP (p = 0.029. Overall, MIC-1 in combination with CA19-9 improved the diagnostic

  9. Biomarkers of ambient air pollution and lung cancer

    DEFF Research Database (Denmark)

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

    2012-01-01

    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...... 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...

  10. Direct cancer tissue proteomics: a method to identify candidate cancer biomarkers from formalin-fixed paraffin-embedded archival tissues.

    Science.gov (United States)

    Hwang, S-I; Thumar, J; Lundgren, D H; Rezaul, K; Mayya, V; Wu, L; Eng, J; Wright, M E; Han, D K

    2007-01-01

    Successful treatment of multiple cancer types requires early detection and identification of reliable biomarkers present in specific cancer tissues. To test the feasibility of identifying proteins from archival cancer tissues, we have developed a methodology, termed direct tissue proteomics (DTP), which can be used to identify proteins directly from formalin-fixed paraffin-embedded prostate cancer tissue samples. Using minute prostate biopsy sections, we demonstrate the identification of 428 prostate-expressed proteins using the shotgun method. Because the DTP method is not quantitative, we employed the absolute quantification method and demonstrate picogram level quantification of prostate-specific antigen. In depth bioinformatics analysis of these expressed proteins affords the categorization of metabolic pathways that may be important for distinct stages of prostate carcinogenesis. Furthermore, we validate Wnt-3 as an upregulated protein in cancerous prostate cells by immunohistochemistry. We propose that this general strategy provides a roadmap for successful identification of critical molecular targets of multiple cancer types.

  11. The Role of Epigenomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools.

    Science.gov (United States)

    Verma, Mukesh

    2015-01-01

    Epigenetics plays a key role in cancer development. Genetics alone cannot explain sporadic cancer and cancer development in individuals with no family history or a weak family history of cancer. Epigenetics provides a mechanism to explain the development of cancer in such situations. Alterations in epigenetic profiling may provide important insights into the etiology and natural history of cancer. Because several epigenetic changes occur before histopathological changes, they can serve as biomarkers for cancer diagnosis and risk assessment. Many cancers may remain asymptomatic until relatively late stages; in managing the disease, efforts should be focused on early detection, accurate prediction of disease progression, and frequent monitoring. This chapter describes epigenetic biomarkers as they are expressed during cancer development and their potential use in cancer diagnosis and prognosis. Based on epigenomic information, biomarkers have been identified that may serve as diagnostic tools; some such biomarkers also may be useful in identifying individuals who will respond to therapy and survive longer. The importance of analytical and clinical validation of biomarkers is discussed, along with challenges and opportunities in this field.

  12. Molecular profiling of childhood cancer: Biomarkers and novel therapies

    Directory of Open Access Journals (Sweden)

    Federica Saletta

    2014-06-01

    General significance: The increasing recognition of the heterogeneity of molecular causes of cancer favors the continued development of molecularly targeted agents, and their transfer to pediatric and adolescent populations.

  13. Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response

    Science.gov (United States)

    Giedt, Randy J.; Fumene Feruglio, Paolo; Pathania, Divya; Yang, Katherine S.; Kilcoyne, Aoife; Vinegoni, Claudio; Mitchison, Timothy J.; Weissleder, Ralph

    2016-09-01

    Mitochondria, which are essential organelles in resting and replicating cells, can vary in number, mass and shape. Past research has primarily focused on short-term molecular mechanisms underlying fission/fusion. Less is known about longer-term mitochondrial behavior such as the overall makeup of cell populations’ morphological patterns and whether these patterns can be used as biomarkers of drug response in human cells. We developed an image-based analytical technique to phenotype mitochondrial morphology in different cancers, including cancer cell lines and patient-derived cancer cells. We demonstrate that (i) cancer cells of different origins, including patient-derived xenografts, express highly diverse mitochondrial phenotypes; (ii) a given phenotype is characteristic of a cell population and fairly constant over time; (iii) mitochondrial patterns correlate with cell metabolic measurements and (iv) therapeutic interventions can alter mitochondrial phenotypes in drug-sensitive cancers as measured in pre- versus post-treatment fine needle aspirates in mice. These observations shed light on the role of mitochondrial dynamics in the biology and drug response of cancer cells. On the basis of these findings, we propose that image-based mitochondrial phenotyping can provide biomarkers for assessing cancer phenotype and drug response.

  14. Computational imaging reveals mitochondrial morphology as a biomarker of cancer phenotype and drug response

    Science.gov (United States)

    Giedt, Randy J.; Fumene Feruglio, Paolo; Pathania, Divya; Yang, Katherine S.; Kilcoyne, Aoife; Vinegoni, Claudio; Mitchison, Timothy J.; Weissleder, Ralph

    2016-01-01

    Mitochondria, which are essential organelles in resting and replicating cells, can vary in number, mass and shape. Past research has primarily focused on short-term molecular mechanisms underlying fission/fusion. Less is known about longer-term mitochondrial behavior such as the overall makeup of cell populations’ morphological patterns and whether these patterns can be used as biomarkers of drug response in human cells. We developed an image-based analytical technique to phenotype mitochondrial morphology in different cancers, including cancer cell lines and patient-derived cancer cells. We demonstrate that (i) cancer cells of different origins, including patient-derived xenografts, express highly diverse mitochondrial phenotypes; (ii) a given phenotype is characteristic of a cell population and fairly constant over time; (iii) mitochondrial patterns correlate with cell metabolic measurements and (iv) therapeutic interventions can alter mitochondrial phenotypes in drug-sensitive cancers as measured in pre- versus post-treatment fine needle aspirates in mice. These observations shed light on the role of mitochondrial dynamics in the biology and drug response of cancer cells. On the basis of these findings, we propose that image-based mitochondrial phenotyping can provide biomarkers for assessing cancer phenotype and drug response. PMID:27609668

  15. Cell division cycle associated 1 as a novel prognostic biomarker and therapeutic target for oral cancer.

    Science.gov (United States)

    Thang, Phung Manh; Takano, Atsushi; Yoshitake, Yoshihiro; Shinohara, Masanori; Murakami, Yoshinori; Daigo, Yataro

    2016-10-01

    Oral cavity carcinoma (OCC) is one of the most common causes of cancer-related death worldwide and has poor clinical outcome after standard therapies. Therefore, new prognostic biomarkers and therapeutic targets for OCC are urgently needed. We selected cell division cycle associated 1 (CDCA1) as a candidate OCC biomarker. Immunohistochemical analysis confirmed that CDCA1 protein was expressed in 67 of 99 OCC tissues (67.7%), but not in healthy oral epithelia. CDCA1 expression was significantly associated with poor prognosis in OCC patients (P=0.0244). Knockdown of CDCA1 by siRNAs significantly increased apoptosis of tumor cells. These data suggest that CDCA1 represents a novel prognostic biomarker and therapeutic target for OCC. PMID:27499128

  16. A new device for liver cancer biomarker detection with high accuracy

    Directory of Open Access Journals (Sweden)

    Shuaipeng Wang

    2015-06-01

    Full Text Available A novel cantilever array-based bio-sensor was batch-fabricated with IC compatible MEMS technology for precise liver cancer bio-marker detection. A micro-cavity was designed in the free end of the cantilever for local antibody-immobilization, thus adsorption of the cancer biomarker is localized in the micro-cavity, and the adsorption-induced k variation can be dramatically reduced with comparison to that caused by adsorption of the whole lever. The cantilever is pizeoelectrically driven into vibration which is pizeoresistively sensed by Wheatstone bridge. These structural features offer several advantages: high sensitivity, high throughput, high mass detection accuracy, and small volume. In addition, an analytical model has been established to eliminate the effect of adsorption-induced lever stiffness change and has been applied to precise mass detection of cancer biomarker AFP, the detected AFP antigen mass (7.6 pg/ml is quite close to the calculated one (5.5 pg/ml, two orders of magnitude better than the value by the fully antibody-immobilized cantilever sensor. These approaches will promote real application of the cantilever sensors in early diagnosis of cancer.

  17. miRNAs as potential biomarkers in early breast cancer detection following mammography.

    Science.gov (United States)

    Fu, Sidney W; Lee, Woojin; Coffey, Caitrin; Lean, Alexa; Wu, Xiaoling; Tan, Xiaohui; Man, Yan-Gao; Brem, Rachel F

    2016-01-01

    Breast cancer is the most common cancer among American women, except for skin cancers. About 12 % women in the United States will develop invasive breast cancer during their lifetime. Currently one of the most accepted model/theories is that ductal breast cancer (most common type of breast cancer) follows a linear progression: from normal breast epithelial cells to ductal hyperplasia to atypical ductal hyperplasia (ADH) to ductal carcinoma in situ (DCIS), and finally to invasive ductal carcinoma (IDC). Distinguishing pure ADH diagnosis from DCIS and/or IDC on mammography, and even combined with follow-up core needle biopsy (CNB) is still a challenge. Therefore subsequent surgical excision cannot be avoided to make a definitive diagnosis. MicroRNAs (miRNAs) are a highly abundant class of endogenous non-coding RNAs, which contribute to cancer initiation and progression, and are differentially expressed between normal and cancer tissues. They can function as either tumor suppressors or oncogenes. With accumulating evidence of the role of miRNAs in breast cancer progression, including our own studies, we sought to summarize the nature of early breast lesions and the potential use of miRNA molecules as biomarkers in early breast cancer detection. In particular, miRNA biomarkers may potentially serve as a companion tool following mammography screening and CNB. In the long-term, a better understanding of the molecular mechanisms underlying the miRNA signatures associated with breast cancer development could potentially result in the development of novel strategies for disease prevention and therapy. PMID:26819702

  18. TFF3 is a valuable predictive biomarker of endocrine response in metastatic breast cancer.

    Science.gov (United States)

    May, Felicity E B; Westley, Bruce R

    2015-06-01

    The stratification of breast cancer patients for endocrine therapies by oestrogen or progesterone receptor expression is effective but imperfect. The present study aims were to validate microarray studies that demonstrate TFF3 regulation by oestrogen and its association with oestrogen receptors in breast cancer, to evaluate TFF3 as a biomarker of endocrine response, and to investigate TFF3 function. Microarray data were validated by quantitative RT-PCR and northern and western transfer analyses. TFF3 was induced by oestrogen, and its induction was inhibited by antioestrogens, tamoxifen, 4-hydroxytamoxifen and fulvestrant in oestrogen-responsive breast cancer cells. The expression of TFF3 mRNA was associated with oestrogen receptor mRNA in breast tumours (Pearson's coefficient=0.762, P=0.000). Monoclonal antibodies raised against the TFF3 protein detected TFF3 by immunohistochemistry in oesophageal submucosal glands, intestinal goblet and neuroendocrine cells, Barrett's metaplasia and intestinal metaplasia. TFF3 protein expression was associated with oestrogen receptor, progesterone receptor and TFF1 expression in malignant breast cells. TFF3 is a specific and sensitive predictive biomarker of response to endocrine therapy, degree of response and duration of response in unstratified metastatic breast cancer patients (P=0.000, P=0.002 and P=0.002 respectively). Multivariate binary logistic regression analysis demonstrated that TFF3 is an independent biomarker of endocrine response and degree of response, and this was confirmed in a validation cohort. TFF3 stimulated migration and invasion of breast cancer cells. In conclusion, TFF3 expression is associated with response to endocrine therapy, and outperforms oestrogen receptor, progesterone receptor and TFF1 as an independent biomarker, possibly because it mediates the malign effects of oestrogen on invasion and metastasis.

  19. Circulating biomarkers to monitor cancer progression and treatment.

    Science.gov (United States)

    Rapisuwon, Suthee; Vietsch, Eveline E; Wellstein, Anton

    2016-01-01

    Tumor heterogeneity is a major challenge and the root cause of resistance to treatment. Still, the standard diagnostic approach relies on the analysis of a single tumor sample from a local or metastatic site that is obtained at a given time point. Due to intratumoral heterogeneity and selection of subpopulations in diverse lesions this will provide only a limited characterization of the makeup of the disease. On the other hand, recent developments of nucleic acid sequence analysis allows to use minimally invasive serial blood samples to assess the mutational status and altered gene expression patterns for real time monitoring in individual patients. Here, we focus on cell-free circulating tumor-specific mutant DNA and RNA (including mRNA and non-coding RNA), as well as current limitations and challenges associated with circulating nucleic acids biomarkers. PMID:27358717

  20. Exploring the role of molecular biomarkers as a potential weapon against gastric cancer: A review of the literature

    Science.gov (United States)

    Matboli, Marwa; El-Nakeep, Sarah; Hossam, Nourhan; Habieb, Alaa; Azazy, Ahmed E M; Ebrahim, Ali E; Nagy, Ziad; Abdel-Rahman, Omar

    2016-01-01

    Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management.

  1. Exploring the role of molecular biomarkers as a potential weapon against gastric cancer: A review of the literature.

    Science.gov (United States)

    Matboli, Marwa; El-Nakeep, Sarah; Hossam, Nourhan; Habieb, Alaa; Azazy, Ahmed E M; Ebrahim, Ali E; Nagy, Ziad; Abdel-Rahman, Omar

    2016-07-14

    Gastric cancer (GC) is a global health problem and a major cause of cancer-related death with high recurrence rates ranging from 25% to 40% for GC patients staging II-IV. Unfortunately, while the majority of GC patients usually present with advanced tumor stage; there is still limited evidence-based therapeutic options. Current approach to GC management consists mainly of; endoscopy followed by, gastrectomy and chemotherapy or chemo-radiotherapy. Recent studies in GC have confirmed that it is a heterogeneous disease. Many molecular characterization studies have been performed in GC. Recent discoveries of the molecular pathways underlying the disease have opened the door to more personalized treatment and better predictable outcome. The identification of molecular markers is a useful tool for clinical managementin GC patients, assisting in diagnosis, evaluation of response to treatment and development of novel therapeutic modalities. While chemotherapeutic agents have certain physiological effects on the tumor cells, the prediction of the response is different from one type of tumor to the other. The specificity of molecular biomarkers is a principal feature driving their application in anticancer therapies. Here we are trying to focus on the role of molecular pathways of GC and well-established molecular markers that can guide the therapeutic management. PMID:27468184

  2. The use of MYBL2 as a novel candidate biomarker of cervical cancer.

    Science.gov (United States)

    Martin, Cara M; Astbury, Katharine; Kehoe, Louise; O'Crowley, Jacqueline Barry; O'Toole, Sharon; O'Leary, John J

    2015-01-01

    Cervical cancer is the third most common cancer affecting women worldwide. It is characterized by chromosomal aberrations and alteration in the expression levels of many cell cycle regulatory proteins, driven primarily by transforming human papillomavirus (HPV) infection. MYBL2 is a member of the MYB proto-oncogene family that encodes DNA binding proteins. These proteins are involved in cell proliferation and control of cellular differentiation. We have previously demonstrated the utility of MYBL2 as a putative biomarker for cervical pre-cancer and cancer. In this chapter we describe the methodological approach for testing MYBL2 protein expression in tissue biopsies from cases of cervical intraepithelial neoplasia (CIN) and cervical cancer, using immunohistochemistry techniques on the automated immunostaining platform, the Ventana BenchMark LT. The protocol outlines the various steps in the procedure from cutting tissue sections, antibody optimization, antigen retrieval, immunostaining, and histological review.

  3. Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening

    Science.gov (United States)

    Williams, Alex C.; Hitt, Austin; Voisin, Sophie; Tourassi, Georgia

    2013-03-01

    The biological concept of bilateral symmetry as a marker of developmental stability and good health is well established. Although most individuals deviate slightly from perfect symmetry, humans are essentially considered bilaterally symmetrical. Consequently, increased fluctuating asymmetry of paired structures could be an indicator of disease. There are several published studies linking bilateral breast size asymmetry with increased breast cancer risk. These studies were based on radiologists' manual measurements of breast size from mammographic images. We aim to develop a computerized technique to assess fluctuating breast volume asymmetry in screening mammograms and investigate whether it correlates with the presence of breast cancer. Using a large database of screening mammograms with known ground truth we applied automated breast region segmentation and automated breast size measurements in CC and MLO views using three well established methods. All three methods confirmed that indeed patients with breast cancer have statistically significantly higher fluctuating asymmetry of their breast volumes. However, statistically significant difference between patients with cancer and benign lesions was observed only for the MLO views. The study suggests that automated assessment of global bilateral asymmetry could serve as a breast cancer risk biomarker for women undergoing mammographic screening. Such biomarker could be used to alert radiologists or computer-assisted detection (CAD) systems to exercise increased vigilance if higher than normal cancer risk is suspected.

  4. Automated assessment of bilateral breast volume asymmetry as a breast cancer biomarker during mammographic screening

    Energy Technology Data Exchange (ETDEWEB)

    Williams, Alex C [ORNL; Hitt, Austin N [ORNL; Voisin, Sophie [ORNL; Tourassi, Georgia [ORNL

    2013-01-01

    The biological concept of bilateral symmetry as a marker of developmental stability and good health is well established. Although most individuals deviate slightly from perfect symmetry, humans are essentially considered bilaterally symmetrical. Consequently, increased fluctuating asymmetry of paired structures could be an indicator of disease. There are several published studies linking bilateral breast size asymmetry with increased breast cancer risk. These studies were based on radiologists manual measurements of breast size from mammographic images. We aim to develop a computerized technique to assess fluctuating breast volume asymmetry in screening mammograms and investigate whether it correlates with the presence of breast cancer. Using a large database of screening mammograms with known ground truth we applied automated breast region segmentation and automated breast size measurements in CC and MLO views using three well established methods. All three methods confirmed that indeed patients with breast cancer have statistically significantly higher fluctuating asymmetry of their breast volumes. However, statistically significant difference between patients with cancer and benign lesions was observed only for the MLO views. The study suggests that automated assessment of global bilateral asymmetry could serve as a breast cancer risk biomarker for women undergoing mammographic screening. Such biomarker could be used to alert radiologists or computer-assisted detection (CAD) systems to exercise increased vigilance if higher than normal cancer risk is suspected.

  5. Serum Circulating microRNA Profiling for Identification of Potential Breast Cancer Biomarkers

    Directory of Open Access Journals (Sweden)

    Fermín Mar-Aguilar

    2013-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small, non-coding RNA molecules that can regulate gene expression, thereby affecting crucial processes in cancer development. miRNAs offer great potential as biomarkers for cancer detection because of their remarkable stability in blood and their characteristic expression in different diseases. We investigated whether quantitative RT-PCR miRNA profiling on serum could discriminate between breast cancer patients and healthy controls. We performed miRNA profiling on serum from breast cancer patients, followed by construction of ROC (Receiver Operating Characteristic curves to determine the sensitivity and specificity of the assay. We found that seven miRNAs (miR-10b, miR-21, miR-125b, miR-145, miR-155 miR-191 and miR-382 had different expression patterns in serum of breast cancer patients compared to healthy controls. ROC curve analyses revealed that three serum miRNAs could be valuable biomarkers for distinguishing BC from normal controls. Additionally, a combination of ROC curve analyses of miR-145, miR-155 and miR-382 showed better sensitivity and specificity of our assay. miRNA profiling in serum has potential as a novel method for breast cancer detection in the Mexican population.

  6. Biomarkers of endometrial cancer and related gynaecological malignancies

    NARCIS (Netherlands)

    Seeber, L.M.S.

    2010-01-01

    In the Western World, endometrial cancer is the most common malignancy of the female genital tract. Endometrioid endometrial carcinoma (EEC or Type I tumour), accounts for approximately 75% of cases. Type II tumours, of which uterine papillary serous carcinoma (UPSC) is the most common subtype, are

  7. Radiotherapy diagnostic biomarkers in radioresistant human H460 lung cancer stem-like cells

    OpenAIRE

    Yun, Hong Shik; Baek, Jeong-Hwa; Yim, Ji-Hye; Um, Hong-Duck; Park, Jong Kuk; Song, Jie-Young; Park, In-Chul; KIM, JAE-SUNG; Lee, Su-Jae; Lee, Chang-Woo; Hwang, Sang-Gu

    2016-01-01

    ABSTRACT Tumor cell radioresistance is a major contributor to radiotherapy failure, highlighting the importance of identifying predictive biomarkers for radioresistance. In this work, we established a radioresistant H460 (RR-H460) cell line from parental radiosensitive H460 lung cancer cells by exposure to fractionated radiation. The radiation-resistant, anti-apoptotic phenotype of RR-H460 cell lines was confirmed by their enhanced clonogenic survival and increased expression of the radioresi...

  8. Tissue Biomarkers in Prognostication of Serous Ovarian Cancer following Neoadjuvant Chemotherapy

    OpenAIRE

    Binny Khandakar; Sandeep R Mathur; Lalit Kumar; Sunesh Kumar; Siddhartha Datta Gupta; Venkateswaran K Iyer; Kalaivani, M.

    2014-01-01

    Serous ovarian cancer (SOC) is a significant cause of morbidity and mortality in females with poor prognosis because of advanced stage at presentation. Recently, neoadjuvant chemotherapy (NACT) is being used for management of advanced SOC, but role of tissue biomarkers in prognostication following NACT is not well established. The study was conducted on advanced stage SOC patients (n = 100) that were treated either conventionally (n = 50) or with NACT (n = 50), followed by surgery. In order t...

  9. Identification of Novel Epithelial Ovarian Cancer Biomarkers by Cross-laboratory Microarray Analysis

    Institute of Scientific and Technical Information of China (English)

    蒋学锋; 朱涛; 杨洁; 李双; 叶双梅; 廖书杰; 孟力; 卢运萍; 马丁

    2010-01-01

    The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers.Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data,then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes(DEGs),followed by clustering and pathway analysis for these ...

  10. Composite Biomarkers For Non-invasive Screening, Diagnosis And Prognosis Of Colorectal Cancer

    KAUST Repository

    Mansour, Hicham

    2014-09-11

    The present invention concerns particular biomarkers for diagnosing and/or prognosticating colorectal cancer, in particular in a non-invasive manner. The methods and compositions concern analysis of methylation patterns of one or more genes from a set of 29 genes identified as described herein. In certain embodiments, the gene set includes at least P15.INK4b, SST, GAS7, CNRIP1, and PIK3CG.

  11. Computational discovery of pathway-level genetic vulnerabilities in non-small-cell lung cancer | Office of Cancer Genomics

    Science.gov (United States)

    Novel approaches are needed for discovery of targeted therapies for non-small-cell lung cancer (NSCLC) that are specific to certain patients. Whole genome RNAi screening of lung cancer cell lines provides an ideal source for determining candidate drug targets. Unsupervised learning algorithms uncovered patterns of differential vulnerability across lung cancer cell lines to loss of functionally related genes. Such genetic vulnerabilities represent candidate targets for therapy and are found to be involved in splicing, translation and protein folding.

  12. Chromosomal aberrations in lymphocytes predict human cancer: a report from the European Study Group on Cytogenetic Biomarkers and Health (ESCH)

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U;

    1998-01-01

    . No association was seen between the SCEs or the MN frequencies and subsequent cancer incidence/mortality. The present study further supports our previous observation on the cancer predictivity of the CA biomarker, which seems to be independent of age at test, gender, and time since test. The risk patterns were...... similar within each national cohort. This result suggests that the frequency of CAs in peripheral blood lymphocytes is a relevant biomarker for cancer risk in humans, reflecting either early biological effects of genotoxic carcinogens or individual cancer susceptibility....

  13. The novel prostate cancer antigen 3 (PCA3 biomarker

    Directory of Open Access Journals (Sweden)

    Andreas Bourdoumis

    2010-12-01

    Full Text Available PCA3 is a prostate specific, nonprotein coding RNA that is significantly over expressed in prostate cancer, without any correlation to prostatic volume and/or other prostatic diseases (e.g. prostatitis. It can now easily be measured in urine with a novel transcription-mediated amplification based test. Quantification of PCA3 mRNA levels can predict the outcome of prostatic biopsies with a higher specificity rate in comparison to PSA. Several studies have demonstrated that PCA3 can be used as a prognostic marker of prostate cancer, especially in conjunction with other predictive markers. Novel PCA3-based nomograms have already been introduced into clinical practice. PCA3 test may be of valuable help in several PSA quandary situations such as negative prostatic biopsies, concomitant prostatic diseases, and active surveillance. Results from relevant clinical studies, comparative with PSA, are warranted in order to confirm the perspective of PCA3 to substitute PSA.

  14. Exosomes: Emerging biomarkers and targets for ovarian cancer.

    Science.gov (United States)

    Tang, Maggie K S; Wong, Alice S T

    2015-10-10

    The limitations of current chemotherapies have motivated research in developing new treatments. Growing evidence shows that interaction between tumors and their microenvironment, but not tumor cells per se, is the key factor in tumor progression and therefore of obvious scientific interest and therapeutic value. Exosomes are small (30-100 nm) extracellular vesicles which have emerged as key mediators of intercellular communication between tumor cells and major cell types in the tumor microenvironment such as fibroblasts, endothelial cells, and immune cells as well as noncellular extracellular matrices through paracrine mechanisms. This review is to highlight the emerging role of exosomes in particular types of cancer, such as ovarian cancer, owing to its unique route of metastasis, which is capable of rapidly translating exosome research for clinical applications in diagnosis, prognosis, and potential treatment.

  15. Annexin A9 (ANXA9) biomarker and therapeutic target in epithelial cancer

    Science.gov (United States)

    Hu, Zhi; Kuo, Wen-Lin; Neve, Richard M.; Gray, Joe W.

    2012-06-12

    Amplification of the ANXA9 gene in human chromosomal region 1q21 in epithelial cancers indicates a likelihood of both in vivo drug resistance and metastasis, and serves as a biomarker indicating these aspects of the disease. ANXA9 can also serve as a therapeutic target. Interfering RNAs (iRNAs) (such as siRNA and miRNA) and shRNA adapted to inhibit ANXA9 expression, when formulated in a therapeutic composition, and delivered to cells of the tumor, function to treat the epithelial cancer.

  16. Plasma levels of the MMP-9:TIMP-1 complex as prognostic biomarker in breast cancer

    DEFF Research Database (Denmark)

    Thorsen, Stine Buch; Christensen, Sarah Louise T; Würtz, Sidse Ørnbjerg;

    2013-01-01

    Worldwide more than one million women are annually diagnosed with breast cancer. A considerable fraction of these women receive systemic adjuvant therapy; however, some are cured by primary surgery and radiotherapy alone. Prognostic biomarkers guide stratification of patients into different risk...... groups and hence improve management of breast cancer patients. Plasma levels of Matrix Metalloproteinase-9 (MMP-9) and its natural inhibitor Tissue inhibitor of metalloproteinase-1 (TIMP-1) have previously been associated with poor patient outcome and resistance to certain forms of chemotherapy. To...

  17. Role of MGMT as biomarker in colorectal cancer

    OpenAIRE

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

    2014-01-01

    O6-methylguanine DNA methyltransferase (MGMT) gene promoter methylation plays an important role in colorectal carcinogenesis, occurring in about 30%-40% of metastatic colorectal cancer. Its prognostic role has not been defined yet, but loss of expression of MGMT, which is secondary to gene promoter methylation, results in an interesting high response to alkylating agents such as dacarbazine and temozolomide. In a phase 2 study on heavily pre-treated patients with MGMT methylated metastatic co...

  18. Biomarkers of endometrial cancer and related gynaecological malignancies

    OpenAIRE

    Seeber, L.M.S.

    2010-01-01

    In the Western World, endometrial cancer is the most common malignancy of the female genital tract. Endometrioid endometrial carcinoma (EEC or Type I tumour), accounts for approximately 75% of cases. Type II tumours, of which uterine papillary serous carcinoma (UPSC) is the most common subtype, are less common. Since classification as EEC or UPSC has therapeutic and prognostic implications, it is important to make the proper diagnosis. UPSC share their aggressive clinical behaviour and their ...

  19. Cancer Research from Molecular Discovery to Global Health

    Science.gov (United States)

    A science writers' seminar to discuss the latest research in cancer genetics and global health efforts, including talks from leaders of NCI’s new centers of cancer genomics and global health will be held Dec. 13, 2011, at NCI.

  20. Glioblastoma cancer stem cells: Biomarker and therapeutic advances.

    Science.gov (United States)

    Pointer, Kelli B; Clark, Paul A; Zorniak, Michael; Alrfaei, Bahauddeen M; Kuo, John S

    2014-05-01

    Glioblastoma multiforme (GBM) is the most common and aggressive primary brain tumor in humans. It accounts for fifty-two percent of primary brain malignancies in the United States and twenty percent of all primary intracranial tumors. Despite the current standard therapies of maximal safe surgical resection followed by temozolomide and radiotherapy, the median patient survival is still less than 2 years due to inevitable tumor recurrence. Glioblastoma cancer stem cells (GSCs) are a subgroup of tumor cells that are radiation and chemotherapy resistant and likely contribute to rapid tumor recurrence. In order to gain a better understanding of the many GBM-associated mutations, analysis of the GBM cancer genome is on-going; however, innovative strategies to target GSCs and overcome tumor resistance are needed to improve patient survival. Cancer stem cell biology studies reveal basic understandings of GSC resistance patterns and therapeutic responses. Membrane proteomics using phage and yeast display libraries provides a method to identify novel antibodies and surface antigens to better recognize, isolate, and target GSCs. Altogether, basic GBM and GSC genetics and proteomics studies combined with strategies to discover GSC-targeting agents could lead to novel treatments that significantly improve patient survival and quality of life.

  1. Dietary Associations with a Breast Cancer Risk Biomarker Depend on Menopause Status.

    Science.gov (United States)

    Hidaka, Brandon H; Carlson, Susan E; Kimler, Bruce F; Fabian, Carol J

    2016-10-01

    We investigated how timing influences the role of diet in breast cancer risk with a cross-sectional study of pre-malignant change in breast tissue. Women with an elevated risk of developing breast cancer (33 premenopausal and 32 postmenopausal) completed the National Cancer Institute's food frequency questionnaire and underwent random periareolar fine-needle aspiration for evaluation of cytologic atypia, an established risk biomarker. Fatty acid composition of breast adipose was measured in 32 (49%) subjects. We found that premenopausal and postmenopausal women had similar diets, but the associations between atypia and intake of total n-3 polyunsaturated fatty acids (PUFA) and soy differed by menopause status (both P interaction soy (P = 0.0003 and P = 0.48, respectively). This pattern of dietary interaction with menopause was mirrored in tissue fatty acids (P interaction 0.37). Dietary associations with breast cancer risk are stronger prior to menopause. PMID:27618149

  2. Biomarker-specific conjugated nanopolyplexes for the active coloring of stem-like cancer cells

    Science.gov (United States)

    Hong, Yoochan; Lee, Eugene; Choi, Jihye; Haam, Seungjoo; Suh, Jin-Suck; Yang, Jaemoon

    2016-06-01

    Stem-like cancer cells possess intrinsic features and their CD44 regulate redox balance in cancer cells to survive under stress conditions. Thus, we have fabricated biomarker-specific conjugated polyplexes using CD44-targetable hyaluronic acid and redox-sensible polyaniline based on a nanoemulsion method. For the most sensitive recognition of the cellular redox at a single nanoparticle scale, a nano-scattering spectrum imaging analyzer system was introduced. The conjugated polyplexes showed a specific targeting ability toward CD44-expressing cancer cells as well as a dramatic change in its color, which depended on the redox potential in the light-scattered images. Therefore, these polyaniline-based conjugated polyplexes as well as analytical processes that include light-scattering imaging and measurements of scattering spectra, clearly establish a systematic method for the detection and monitoring of cancer microenvironments.

  3. Circulating Cancer Biomarkers: The Macro-revolution of the Micro-RNA.

    Science.gov (United States)

    Montani, Francesca; Bianchi, Fabrizio

    2016-03-01

    MicroRNAs (miRNAs) are small non-coding RNAs that act as master regulators of many cellular processes. The expression of miRNAs is often deregulated in human tumors, causing the alteration of molecular mechanisms relevant for cancer progression. Importantly, miRNAs are detectable in the blood and their quantity fluctuations are the hallmark of pathogenic conditions, including cancer. Several groups reported the identification of circulating cell-free miRNAs (cf-miRNAs) in the human serum and plasma and demonstrated their diagnostic and prognostic utility. Other studies also shown that it may be feasible to apply such cf-miRNA signatures within screening programs in order to improve cancer early detection. Circulating cf-miRNAs therefore appear to be excellent candidates for blood-borne cancer biomarkers.

  4. SurvExpress: an online biomarker validation tool and database for cancer gene expression data using survival analysis.

    Directory of Open Access Journals (Sweden)

    Raul Aguirre-Gamboa

    Full Text Available Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included. The website was implemented in JSP, JavaScript, MySQL, and R.

  5. Screening for colorectal cancer risk biomarkers related to diet

    OpenAIRE

    Da Pieve, Chiara; Moore, Sharon; Velasco, Maria

    2010-01-01

    Background: Red and processed meat are associated with high risks of colorectal cancer due to the endogenous formation of O6-carboxymethyl guanine (O6CMG), a potent carcinogen. The aim of our research is to develop liquid chromatography tandem mass spectrometry (LC-MS/MS) analytical methods for the measurement of the DNA adducts, such as O6CMG and its nucleoside O6-carboxymethyl deoxyguanosine (O6CMdG), in urine samples and correlate it to different diets. Methods: Urine samples were coll...

  6. PTRF/Cavin-1 and MIF Proteins Are Identified as Non-Small Cell Lung Cancer Biomarkers by Label-Free Proteomics

    Science.gov (United States)

    Gámez-Pozo, Angelo; Sánchez-Navarro, Iker; Calvo, Enrique; Agulló-Ortuño, María Teresa; López-Vacas, Rocío; Díaz, Esther; Camafeita, Emilio; Nistal, Manuel; Madero, Rosario; Espinosa, Enrique; López, Juan Antonio; Vara, Juan Ángel Fresno

    2012-01-01

    With the completion of the human genome sequence, biomedical sciences have entered in the “omics” era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer. PMID:22461895

  7. Aberrant p16 promoter hypermethylation in bronchial mucosae as a biomarker for the early detection of lung cancer

    Institute of Scientific and Technical Information of China (English)

    XIE Guang-shun; HOU Ai-rong; LI Long-yun; GAO Yan-ning; CHENG Shu-jun

    2006-01-01

    @@ Lung cancer is the leading cause of cancer related death in the world and its mortality could be greatly reduced by diagnosis and treatment in its early stages. Effective tools for the early detection of lung cancer and its high risk factors remain a major challenge. Biomarkers that detect lung cancer in its early stages or identify its pretumour lesions,enabling early therapeutic intervention, would be invaluable to improve its dismal prognosis.

  8. [New opportunities, MRI biomarkers in the evaluation of gynaecological cancer].

    Science.gov (United States)

    Horváth, Katalin; Gõdény, Mária

    2015-09-01

    the case of parametrial tumour invasion the accuracy of the clinical examination is 78%, while that of CT and MRI are 70% and 92%, respectively. DCE-MRI and DWMRI are promising imaging biomarkers in the early assessment of the effectiveness of the therapy and also in detecting residual as well as recurrent tumours. PMID:26339911

  9. A targeted proteomic strategy for the measurement of oral cancer candidate biomarkers in human saliva.

    Science.gov (United States)

    Kawahara, Rebeca; Bollinger, James G; Rivera, César; Ribeiro, Ana Carolina P; Brandão, Thaís Bianca; Paes Leme, Adriana F; MacCoss, Michael J

    2016-01-01

    Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC.

  10. Emerging treatments in management of prostate cancer: biomarker validation and endpoints for immunotherapy clinical trial design

    Directory of Open Access Journals (Sweden)

    Slovin SF

    2013-12-01

    Full Text Available Susan F SlovinGenitourinary Oncology Service, Sidney Kimmel Center for Prostate and Urologic Cancers, Memorial Sloan-Kettering Cancer Center, New York, NY, USAAbstract: The rapidly emerging field of immunotherapy and the development of novel immunologic agents that have been approved in melanoma and successfully studied in lung cancer, kidney cancer, and prostate cancer have mandated that there be uniformity in clinical trial analysis beyond conventional survival endpoints and imaging. This includes some measure of determining whether the immunologic target is hit and how the treatment has impacted on the immune system in toto. While melanoma is leading the field towards these ends, there is some doubt that not all of the recent successes with immune therapies, for example, checkpoint inhibitors, will be effective for every cancer, and that the toxicities may also be different depending on the malignancy. This review serves to elucidate the current issues facing clinical investigators who perform immunologic trials targeted at patients with prostate cancer and discusses the challenges in assessing the right immunologic endpoints to demonstrate biologic/immunologic targeting leading to clinical benefit.Keywords: sipuleucel-T, prostate-specific antigen, prostate cancer, biomarkers, monoclonal antibodies, vaccines, cellular therapy

  11. The ADAMs family of proteases: new biomarkers and therapeutic targets for cancer?

    LENUS (Irish Health Repository)

    Duffy, Michael J

    2011-06-09

    Abstract The ADAMs are transmembrane proteins implicated in proteolysis and cell adhesion. Forty gene members of the family have been identified, of which 21 are believed to be functional in humans. As proteases, their main substrates are the ectodomains of other transmembrane proteins. These substrates include precursor forms of growth factors, cytokines, growth factor receptors, cytokine receptors and several different types of adhesion molecules. Although altered expression of specific ADAMs has been implicated in different diseases, their best-documented role is in cancer formation and progression. ADAMs shown to play a role in cancer include ADAM9, ADAM10, ADAM12, ADAM15 and ADAM17. Two of the ADAMs, i.e., ADAM10 and 17 appear to promote cancer progression by releasing HER\\/EGFR ligands. The released ligands activate HER\\/EGFR signalling that culminates in increased cell proliferation, migration and survival. Consistent with a causative role in cancer, several ADAMs are emerging as potential cancer biomarkers for aiding cancer diagnosis and predicting patient outcome. Furthermore, a number of selective ADAM inhibitors, especially against ADAM10 and ADAM17, have been shown to have anti-cancer effects. At least one of these inhibitors is now undergoing clinical trials in patients with breast cancer.

  12. Deep-sequencing of microRNA associated with Alzheimer’s disease in biological fluids: From biomarker discovery to diagnostic practice

    Directory of Open Access Journals (Sweden)

    Lesley eCheng

    2013-08-01

    Full Text Available Diagnostic tools for neurodegenerative diseases such as Alzheimer's disease (AD currently involve subjective neuropsychological testing and specialised brain imaging techniques. While definitive diagnosis requires a pathological brain evaluation at autopsy, neurodegenerative changes are believed to begin years before the clinical presentation of cognitive decline. Therefore, there is an essential need for reliable biomarkers to aid in the early detection of disease in order to implement preventative strategies. microRNAs (miRNA are small non-coding RNA species that are involved in post-transcriptional gene regulation. Expression levels of miRNA’s have potential as diagnostic biomarkers as they are known to circulate and tissue specific profiles can be identified in a number of bodily fluids such as plasma, CSF and urine. Recent developments in deep sequencing technology present a viable approach to develop biomarker discovery pipelines in order to profile microRNA signatures in bodily fluids specific to neurodegenerative diseases. Here we review the potential use of microRNA deep sequencing in biomarker identification from biological fluids and its translation into clinical practice.

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

    OpenAIRE

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

    2014-01-01

    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 ...

  14. Noncoding Genomics in Gastric Cancer and the Gastric Precancerous Cascade: Pathogenesis and Biomarkers

    Directory of Open Access Journals (Sweden)

    Alejandra Sandoval-Bórquez

    2015-01-01

    Full Text Available Gastric cancer is the fifth most common cancer and the third leading cause of cancer-related death, whose patterns vary among geographical regions and ethnicities. It is a multifactorial disease, and its development depends on infection by Helicobacter pylori (H. pylori and Epstein-Barr virus (EBV, host genetic factors, and environmental factors. The heterogeneity of the disease has begun to be unraveled by a comprehensive mutational evaluation of primary tumors. The low-abundance of mutations suggests that other mechanisms participate in the evolution of the disease, such as those found through analyses of noncoding genomics. Noncoding genomics includes single nucleotide polymorphisms (SNPs, regulation of gene expression through DNA methylation of promoter sites, miRNAs, other noncoding RNAs in regulatory regions, and other topics. These processes and molecules ultimately control gene expression. Potential biomarkers are appearing from analyses of noncoding genomics. This review focuses on noncoding genomics and potential biomarkers in the context of gastric cancer and the gastric precancerous cascade.

  15. Cytochrome P450 1A1 genetic polymorphisms as cancer biomarkers

    Directory of Open Access Journals (Sweden)

    A Bag

    2015-01-01

    Full Text Available Phase I metabolic enzyme CYP1A1 plays an important role in xenobiotics metabolism and has been extensively studied as a cancer risk biomarker. CYP1A1 is polymorphic and its four variants, e.g., CYP1A1* 2 A, CYP1A1* 2C, CYP1A1* 3 and CYP1A1* 4 with trivial names m1, m2, m3, and m4 respectively, are most commonly studied for cancer link. Gene- gene interaction studies combining polymorphisms of this enzyme with those of phase II detoxifying enzymes, especially glutathione S- transferases (GSTs revealed greater risk for cancer susceptibility. Variants of CYP1A1 have also been found to be associated with chemotherapeutic adverse- effects. Results of these studies, however, remained largely contradictory mainly because of lack of statistical power due to involvement of small sample size. Strongly powered experimental designs involving gene- gene, gene- environment interactions are required in order to validate CYP1A1 as reliable cancer- biomarker.

  16. Biomarker and animal models for assessment of retinoid efficacy in cancer chemoprevention

    Institute of Scientific and Technical Information of China (English)

    Richard M NILES

    2007-01-01

    Vitamin A is essential for normal growth and development. Epidemiology and laboratory studies suggest that decreased vitamin A levels and defective metabo-lisrn/action may contribute to the genesis of certain cancers. Based on this information, natural and synthetic derivatives of vitamin A (retinoids) have been used for chemoprevention of cancer. Retinoids have had some success in the chemoprevention of leukoplakia and in the decreased incidence of second prima-ties in head and neck cancer. There is little information on biomarkers that can be used to assess the efficacy of the chemopreventive activity of retinoids. The ability of retinoids to induce RARb has been consistently shown to correlate with the response of cells and tissues to retinoic acid, but few other biomarkers have been certified as indicators of retinoid activity. In light of the failure of the ATBC and CARET clinical intervention trials for chemoprevention of lung cancer, greater use of animal models for chemoprevention studies is necessary. The potential combination of phytochemicals that inhibit DNA methyltransferase activity with retinoids holds promise for more effective chemoprevention of retinoid-unrespon-sive premalignant lesions.

  17. Novel Biomarker Candidates for Colorectal Cancer Metastasis: A Meta-analysis of In Vitro Studies.

    Science.gov (United States)

    Long, Nguyen Phuoc; Lee, Wun Jun; Huy, Nguyen Truong; Lee, Seul Ji; Park, Jeong Hill; Kwon, Sung Won

    2016-01-01

    Colorectal cancer (CRC) is one of the most common and lethal cancers. Although numerous studies have evaluated potential biomarkers for early diagnosis, current biomarkers have failed to reach an acceptable level of accuracy for distant metastasis. In this paper, we performed a gene set meta-analysis of in vitro microarray studies and combined the results from this study with previously published proteomic data to validate and suggest prognostic candidates for CRC metastasis. Two microarray data sets included found 21 significant genes. Of these significant genes, ALDOA, IL8 (CXCL8), and PARP4 had strong potential as prognostic candidates. LAMB2, MCM7, CXCL23A, SERPINA3, ABCA3, ALDH3A2, and POLR2I also have potential. Other candidates were more controversial, possibly because of the biologic heterogeneity of tumor cells, which is a major obstacle to predicting metastasis. In conclusion, we demonstrated a meta-analysis approach and successfully suggested ten biomarker candidates for future investigation. PMID:27688707

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

    Institute of Scientific and Technical Information of China (English)

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

    2012-01-01

    Breast cancer is a major health problem that affects more than 24% of women in Bangladesh.Furthermore,among low-income countries including Bangladesh,individuals have a high risk for developing breast cancer.This study aimed to identify candidate mitochondrial DNA (mtDNA) biomarkers for breast cancer diagnosis in Bangladeshi women to be used as a preventive approach.We screened the blood samples from 24 breast cancer patients and 20 healthy controls to detect polymorphisms in the D-loop and the ND3- and ND4-coding regions of mtDNA by direct sequencing.Among 14 distinct mutations,10 polymorphisms were found in the D-loop,3 were found in the ND3-coding region,and 1 was found in the ND4-coding region.The frequency of two novel polymorphisms in the D-loop,one at position 16290 (T-ins) and the other at position 16293 (A-del),was higher in breast cancer patients than in control subjects (position 16290:odds ratio =6.011,95% confidence interval =1.2482 to 28.8411,P =0.002; position 16293:odds ratio =5.6028,95% confidence interval =1.4357 to 21.8925,P =0.010).We also observed one novel mutation in the ND3-coding region at position 10316 (A > G) in 69% of breast cancer patients but not in control subjects.The study suggests that two novel polymorphisms in the D-loop may be candidate biomarkers for breast cancer diagnosis in Bangladeshi women.

  19. Exosomes are fingerprints of originating cells: potential biomarkers for ovarian cancer

    Directory of Open Access Journals (Sweden)

    Kobayashi M

    2015-03-01

    Full Text Available Miharu Kobayashi, Gregory E Rice, Jorge Tapia, Murray D Mitchell, Carlos Salomon Exosome Biology Laboratory, Centre for Clinical Diagnostics, University of Queensland Centre for Clinical Research, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia. Abstract: The past decade has seen an extraordinary explosion of research in the field of extracellular vesicles, especially in a specific type of extracellular vesicles originating from endosomal compartments, called exosomes. Exosomes are a specific subtype of secreted vesicles that are defined as small (~30–120 nm but very stable membrane vesicles that are released from a wide range of cells, including normal and cancer cells. As the content of exosomes is cell type specific, it is believed that they are a "fingerprint" of the releasing cell and its metabolic status. We hypothesized that the exosomes and their specific exosomal content (eg, microribonucleic acid represent a precious biomedical tool and may be used as biomarkers for the diagnosis and prognosis of malignant tumors. In addition, exosomes may modify the phenotype of the parent and/or target cell by transferring pro-oncogenic molecules to induce cancerous phenotype of recipient cells and contribute to the formation of the premetastatic niche. The mechanism involved in these phenomena remains unclear; however, inclusion of signaling mediators into exosomes or exosome release may reduce their intracellular bioavailability in the parent cell, thereby altering cell phenotype and their metastatic potential. The aim of this review therefore is to analyze the biogenesis and role of exosomes from tumor cells, focusing primarily on ovarian cancer. Ovarian cancer is the most lethal gynecologic cancer, and an effective early diagnosis has the potential to improve patient survival. Ovarian cancer currently lacks a reliable method for early detection, however, exosomes have received great attention as potential biomarkers and mediators

  20. Identification of biomarkers for cervical cancer in peripheral blood lymphocytes using oligonucleotide microarrays

    Institute of Scientific and Technical Information of China (English)

    SHENG Jie; ZHANG Wei-yuan

    2010-01-01

    Background Oligonucleotide microarrays are increasingly being used to identify gene expression profiles that associated with complex genetic diseases. Peripheral lymphocytes communicate with cells and extracellular matrixes in almost all tissues and organs in human body, suggesting that the gene expression profiles in peripheral lymphocytes may reflect the presence of disease in the body. This study aimed to identify molecular biomarkers for cervical cancer in peripheral blood lymphocytes by using oligonucleotide microarrays.Methods Total RNA was extracted from peripheral blood lymphocytes of 24 early stage cervical cancer patients and 18 healthy controls. We used 22K Human Genome microarrays to profile peripheral blood lymphocytes from 4 early stage cervical cancer patients and compared their gene expression profiles with those from 3 healthy controls. Differentially expressed genes would be identified if they had adjusted P values of less than 0.05 and a groupwise average fold change greater than 1.5 or less than 0.67. Then the selected 5 genes were validated in the remaining 20 early stage cervical cancer patients and the 15 healthy controls by using real-time reverse-transcription polymerase chain reaction (RT-PCR).Results Genes identified by the gene selection program expressed differently between the blood samples of the early stage cervical cancer patients and those of the healthy controls. To validate the gene expression data, 5 genes were analyzed by real-time RT-PCR. In three of the 5 identified genes, tenasin-c (TNC), nuceolin (NCL), and enolase 2 (ENO2) showed a significant up-regulation in the blood samples of the early stage cervical cancer patients versus that of the healthy controls.Conclusions The up-regulation of TNC, NCL, and ENO2 in peripheral blood may be used to identify novel blood biomarkers for detecting cervical cancer in a clinically accessible surrogate tissue, and thus to provide a possibility to develop a noninvasive and predictive

  1. Biomarkers for cervical cancer screening: the role of p16(INK4a) to highlight transforming HPV infections.

    Science.gov (United States)

    von Knebel Doeberitz, Magnus; Reuschenbach, Miriam; Schmidt, Dietmar; Bergeron, Christine

    2012-04-01

    Biomarkers indicating the initiation of neoplastic transformation processes in human papillomavirus (HPV)-infected epithelial cells are moving into the focus of cancer prevention research, particularly for anogenital cancer, including cancer of the uterine cervix. Based on the in-depth understanding of the molecular events leading to neoplastic transformation of HPV-infected human cells, the cyclin-dependent kinase inhibitor p16(INK4a) turned out to be substantially overexpressed in virtually all HPV-transformed cells. This finding opened novel avenues in diagnostic histopathology to substantially improve the diagnostic accuracy of cervical cancer and its precursor lesions. Furthermore, it provides a novel technical platform to substantially improve the accuracy of cytology-based cancer early-detection programs. Here, we review the molecular background and the current evidence for the clinical utility of the p16(INK4a) biomarker for HPV-related cancers, and cervical cancer prevention in particular.

  2. Transposons for cancer gene discovery: Sleeping Beauty and beyond

    OpenAIRE

    Collier, Lara S.; Largaespada, David A

    2007-01-01

    The use of Sleeping Beauty transposons as somatic mutagens to discover cancer genes in hematopoietic tumors and sarcomas has been documented. Here, we discuss the future of Sleeping Beauty for cancer genetic studies and the potential use of additional transposable elements for somatic mutagenesis.

  3. Synthesis and characterization of a HAp-based biomarker with controlled drug release for breast cancer.

    Science.gov (United States)

    González, Maykel; Merino, Ulises; Vargas, Susana; Quintanilla, Francisco; Rodríguez, Rogelio

    2016-04-01

    A biocompatible hybrid porous polymer-ceramic material was synthesized to be used as a biomarker in the treatment of breast cancer. This device was equipped with the capacity to release medicaments locally in a controlled manner. The biomaterial was Hydroxyapatite(HAp)-based and had a controlled pore size and pore volume fraction. It was implemented externally using a sharp end and a pair of barbed rings placed opposite each other to prevent relative movement once implanted. The biomarker was impregnated with cis-diamine dichloride platinum (II) [Cl2-Pt-(NH3)2]; the rate of release was obtained using inductively coupled plasma atomic emission spectroscopy (ICP-AES), and release occurred over the course of three months. Different release profiles were obtained as a function of the pore volume fraction. The biomaterial was characterized using scanning electron microscopy (SEM) and Raman spectroscopy. PMID:26838911

  4. 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.

  5. Ultrasensitive, multiplexed detection of cancer biomarkers directly in serum by using a quantum dot-based microfluidic protein chip.

    Science.gov (United States)

    Hu, Mei; Yan, Juan; He, Yao; Lu, Haoting; Weng, Lixing; Song, Shiping; Fan, Chunhai; Wang, Lianhui

    2010-01-26

    Sensitive and selective detection for cancer biomarkers are critical in cancer clinical diagnostics. Here we developed a microfluidic protein chip for an ultrasensitive and multiplexed assay of cancer biomarkers. Aqueous-phase-synthesized CdTe/CdS quantum dots (aqQDs) were employed as fluorescent signal amplifiers to improve the detection sensitivity. Secondary antibodies (goat anti-mouse IgG) were conjugated to luminescent CdTe/CdS QDs to realize a versatile fluorescent probe that could be used for multiplexed detection in both sandwich and reverse phase immunoassays. We found that our microfluidic protein chip not only possessed ultrahigh femtomolar sensitivity for cancer biomarkers, but was selective enough to be directly used in serum. This protein chip thus combines the high-throughput capabilities of a microfluidic network with the high sensitivity and multicolor imaging ability offered by highly fluorescent QDs, which can become a promising diagnostic tool in clinical applications. PMID:20041634

  6. Assessment of biomarkers in asbestos-exposed workers as indicators of cancer risk.

    Science.gov (United States)

    Amati, Monica; Tomasetti, Marco; Mariotti, Laura; Tarquini, Lucia Miria; Valentino, Matteo; Santarelli, Lory

    2008-01-01

    Epidemiological studies have shown that mortality from malignant mesothelioma (MM) and lung cancer have increased with increasing cumulative exposure to asbestos. To investigate whether tumour-related biomarkers can contribute towards the evaluation of the carcinogenic risk in populations exposed to asbestos, the DNA adduct 8-hydroxy-2'-deoxyguanosine (80HdG), interleukine-6 (IL-6), platelet-derived growth factor (PDGF-BB), hepatocyte growth factor (HGF), basic fibroblast growth factor (bFGF), vascular endothelial growth factor (VEGFbeta) and soluble mesothelin-related peptides (SMRPs) were analysed in a cohort of workers differently exposed to asbestos fibres at the workplace. To document biomarker levels in an unexposed population, 54 age-matched subjects were enrolled. A total of 119 subjects with a history of occupational exposure to asbestos underwent clinical examination and were interviewed by trained personnel, responding to a detailed questionnaire related to duration of asbestos exposure, smoking, and occupational task. According to the occupational tasks, asbestos-exposed subjects were analysed for their asbestos cumulative dose and the association with the biomarkers was evaluated. Among the occupational groups, maintenance workers, pipe fitters and electricians were exposed to a higher cumulative dose of asbestos fibres. Exposure to asbestos significantly increased the steady-state content of 80HdG in DNA. Elevated levels of 80HdG and IL-6 best reflected a high level of SMRPs, which is related to cell transformation. Subjects heavily exposed to asbestos [> 60(ff/cm3) x years] showed also a higher level of angiogenic factors. A combination of angiogenic biomarkers with a specific mesothelioma-biomarker such as SMRPs could be used for close surveillance of workers with a history of asbestos exposure. PMID:18638565

  7. Mining novel biomarkers for prognosis of gastric cancer with serum proteomics

    Directory of Open Access Journals (Sweden)

    Sui Mei-Hua

    2009-09-01

    Full Text Available Abstract Background Although gastric caner (GC remains the second cause of cancer-related death, useful biomarkers for prognosis are still unavailable. We present here the attempt of mining novel biomarkers for GC prognosis by using serum proteomics. Methods Sera from 43 GC patients and 41 controls with gastritis as Group 1 and 11 GC patients as Group 2 was successively detected by Surface Enhanced Laser Desorption/ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS with Q10 chip. Peaks were acquired by Ciphergen ProteinChip Software 3.2.0 and analyzed by Zhejiang University-ProteinChip Data Analysis System (ZJU-PDAS. CEA level were evaluated by chemiluminescence immunoassay. Results After median follow-up periods of 33 months, Group 1 with 4 GC patients lost was divided into 20 good-prognosis GC patients (overall survival more than 24 months and 19 poor-prognosis GC patients (no more than 24 months. The established prognosis pattern consisted of 5 novel prognosis biomarkers with 84.2% sensitivity and 85.0% specificity, which were significantly higher than those of carcinoembryonic antigen (CEA and TNM stage. We also tested prognosis pattern blindly in Group 2 with 66.7% sensitivity and 80.0% specificity. Moreover, we found that 4474-Da peak elevated significantly in GC and was associated with advanced stage (III+IV and short survival (p Conclusion We have identified a number of novel biomarkers for prognosis prediction of GC by using SELDI-TOF-MS combined with sophisticated bioinformatics. Particularly, elevated expression of 4474-Da peak showed very promising to be developed into a novel biomarker associated with biologically aggressive features of GC.

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

    DEFF Research Database (Denmark)

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

    2012-01-01

    to PARP-1i. Here we addressed these issues using PARP-1i on 20 human cell lines from carcinomas of the breast, prostate, colon, pancreas and ovary. Aberrations of the Mre11-Rad50-Nbs1 (MRN) complex sensitized cancer cells to PARP-1i, while p53 status was less predictive, even in response to PARP-1i......Impaired DNA damage response pathways may create vulnerabilities of cancer cells that can be exploited therapeutically. One such selective vulnerability is the sensitivity of BRCA1- or BRCA2-defective tumors (hence defective in DNA repair by homologous recombination, HR) to inhibitors of the poly......(ADp-ribose) polymerase-1 (PARP-1), an enzyme critical for repair pathways alternative to HR. While promising, treatment with PARP-1 inhibitors (PARP-1i) faces some hurdles, including (1) acquired resistance, (2) search for other sensitizing, non-BRCA1/2 cancer defects and (3) lack of biomarkers to predict response...

  9. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune

    2010-01-01

    The structure and dynamics of protein signalling networks governs cell decision processes and the formation of tissue boundaries. Complex diseases such as cancer and diabetes are diseases of such networks. Therefore approaches that can give insight into how these networks change during disease...... associated technologies. We then focus on the multivariate nature of cellular networks and how this has implications for biomarker and drug discovery using cancer metastasis as an example....

  10. Biomarker discovery from the top down: Protein biomarkers for efficient virus transmission by insects (Homoptera: Aphididae) discovered by coupling genetics and 2-D DIGE.

    Science.gov (United States)

    Cilia, Michelle; Howe, Kevin; Fish, Tara; Smith, Dawn; Mahoney, Jaclyn; Tamborindeguy, Cecilia; Burd, John; Thannhauser, Theodore W; Gray, Stewart

    2011-06-01

    Yellow dwarf viruses cause the most economically important virus diseases of cereal crops worldwide and are vectored by aphids. The identification of vector proteins mediating virus transmission is critical to develop sustainable virus management practices and to understand viral strategies for circulative movement in all insect vectors. Previously, we applied 2-D DIGE to an aphid filial generation 2 population to identify proteins correlated with the transmission phenotype that were stably inherited and expressed in the absence of the virus. In the present study, we examined the expression of the DIGE candidates in previously unstudied, field-collected aphid populations. We hypothesized that the expression of proteins involved in virus transmission could be clinically validated in unrelated, virus transmission-competent, field-collected aphid populations. All putative biomarkers were expressed in the field-collected biotypes, and the expression of nine of these aligned with the virus transmission-competent phenotype. The strong conservation of the expression of the biomarkers in multiple field-collected populations facilitates new and testable hypotheses concerning the genetics and biochemistry of virus transmission. Integration of these biomarkers into current aphid-scouting methodologies will enable rational strategies for vector control aimed at judicious use and development of precision pest control methods that reduce plant virus infection. PMID:21648087

  11. Development of micro immunosensors to study genomic and proteomic biomarkers related to cancer and Alzheimer's disease

    Science.gov (United States)

    Prabhulkar, Shradha

    A report from the National Institutes of Health defines a disease biomarker as a "characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention." Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer's disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with biorecognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0--100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Abeta) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Abeta1-40/42 (or Abeta ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Abeta1-40 and Abeta1-42 in

  12. Transforming Discovery into Health (Cancer Therapy and Obesity)

    Science.gov (United States)

    ... genetic profile of each patient's cancer." Taking on Obesity More than one-third of adults in the ... may face an even greater struggle. Since 1980, obesity has more than doubled among U.S. children ages ...

  13. PiggyBac Transposon Mutagenesis: A Tool for Cancer Gene Discovery in Mice

    OpenAIRE

    Rad, Roland; Rad, Lena; Wang, Wei; Cadinanos, Juan; Vassiliou, George; Rice, Stephen; Campos, Lia S.; Yusa, Kosuke; Banerjee, Ruby; Li, Meng Amy; de la Rosa, Jorge; Strong, Alexander; Lu, Dong; Ellis, Peter; Conte, Nathalie

    2010-01-01

    Transposons are mobile DNA segments that can disrupt gene function by inserting in or near genes. Here we show that insertional mutagenesis by the PiggyBac transposon can be used for cancer gene discovery in mice. PiggyBac transposition in genetically engineered transposon/transposase mice induced cancers whose type (hematopoietic versus solid) and latency were dependent on the regulatory elements introduced into transposons. Analysis of 63 hematopoietic tumors revealed the unique qualities o...

  14. Label-free electrical detection of ovarian cancer biomarker CA-125 with a novel nanoscale coaxial array

    Science.gov (United States)

    Archibald, Michelle; Rizal, Binod; Cai, Dong; Connolly, Timothy; Burns, Michael; Naughton, Michael; Chiles, Thomas

    2013-03-01

    Technologies to detect early stage cancer would provide significant benefit to cancer disease patients. Clinical measurement of biomarkers offers the promise of a noninvasive and cost effective screening for early stage detection. We have developed a novel 3-dimensional nanocavity array for the detection of human cancer biomarkers. This all-electronic diagnostic sensor is based on a nanoscale coaxial array architecture that enables molecular-level detection. Each individual sensor in the array is a vertically-oriented coaxial capacitor, whose capacitance is measurably changed when target molecules enter the coax annulus. The coaxial array facilitates electrical-based detection in response to antibody or molecular imprint based recognition of a specific cancer biomarker, thereby providing a label-free, non-optical measurement. Here, we describe this nanoscale 3D architecture and its application to the detection of the ovarian cancer biomarker CA-125. We report our efforts on the development of molecular detection of CA-125 based on antibody-functionalized nanocoax arrays as well as molecular imprints. The results demonstrate the feasibility of using these arrays as ultrasensitive devices to detect a wide range of molecular targets, including disease biomarkers. Supported by the NIH grants NCI CA137681 and NIAID AI100216.

  15. Sparse multi-block PLSR for biomarker discovery when integrating data from LC-MS and NMR metabolomics

    DEFF Research Database (Denmark)

    Karaman, Ibrahim; Nørskov, Natalja; Yde, Christian Clement;

    2015-01-01

    The objective of this study was to implement a multivariate method which analyzes multi-block metabolomics data and performs variable selection in order to discover potential biomarkers, simultaneously. We call this method sparse multi-block partial least squares regression (Sparse MBPLSR...... the measurement variables of this multi-block data set. The results showed that Sparse MBPLSR with CMV is a useful tool for analyzing multi-block metabolomics data with a good prediction and for identifying potential biomarkers....

  16. Molecular Biomarkers in Bladder Cancer: Novel Potential Indicators of Prognosis and Treatment Outcomes

    Directory of Open Access Journals (Sweden)

    Masayoshi Nagata

    2016-01-01

    Full Text Available Although many clinical and molecular markers for predicting outcomes in bladder cancer (BC have been reported, their application in clinical practice remains unclear. Bladder carcinogenesis has two distinct molecular pathways that direct the development of BC. FGFR3 mutations are common in low-grade BC, while TP53 mutation or loss of RB1 is associated with muscle-invasive BC. However, no tissue-based gene markers confirmed by prospective large-scale trials in BC have been used in clinical practice. Micro-RNA analyses of BC tissue revealed that miR-145 and miR-29c⁎ function as tumor suppressors, whereas miR-183 and miR-17-5p function as oncogenic miRNAs. In liquid biopsy, circulating tumor cells (CTC, exosomes, or cell-free RNA is extracted from the peripheral blood samples of cancer patients to analyze cancer prognosis. It was reported that detection of CTC was associated with poor prognostic factors. However, application of liquid biopsy in BC treatment is yet to be explored. Although several cell-free RNAs, such as miR-497 in plasma or miR-214 in urine, could be promising novel circulating biomarkers, they are used only for diagnosing BC as the case that now stands. Here, we discuss the application of novel biomarkers in evaluating and measuring BC outcomes.

  17. Long noncoding RNAs as auxiliary biomarkers for gastric cancer screening: A pooled analysis of individual studies

    Science.gov (United States)

    Cui, Zhaolei; Chen, Yan; Xiao, Zhenzhou; Hu, Minhua; Lin, Yingying; Chen, Yansong; Zheng, Yuhong

    2016-01-01

    Background Long non-coding RNAs (lncRNAs) are highlighted as novel cancer biomarkers with great promise. Herein, we focused on summarizing the overall diagnostic performance of lncRNAs for gastric cancer (GC). Methods Publications fulfilling the search criteria were selected from the online databases. Study quality was assessed according to the Quality Assessment for Studies of Diagnostic Accuracy (QUADAS) checklist. The summary receiver operator characteristic (SROC) curve was plotted using a bivariate meta-analysis model. Statistical analysis was performed based on the platforms of STATA 12.0 and Meta-Disc 1.4 software. Results Fifteen studies with 1252 patients and 1283 matched controls were included. The pooled sensitivity and specificity for lncRNA expression profile in differentiating GC patients from cancer-free individuals were 0.68 (95%CI: 0.61-0.74) and 0.79 (95%CI: 0.72-0.84), respectively, corresponding to an area under curve (AUC) of 0.80. Moreover, the stratified analyses demonstrated that plasma-based lncRNA profiling harbored higher accuracy than that tissue-based assay (specificity: 0.80 versus 0.75; AUC: 0.84 versus 0.77). Conclusions LncRNA profiling hallmarks a moderate diagnostic value in the management of GC and that lncRNA expression patterns may potentially be utilized as auxiliary biomarkers in confirming GC. PMID:27015554

  18. Molecular biomarkers in extrahepatic bile duct cancer patients undergoing chemoradiotherapy for gross residual disease after surgery

    Energy Technology Data Exchange (ETDEWEB)

    Koh, Hyeon Kang; Kim, Kyu Bo; Chie, Eui Kyu; Ha, Sung W. [Seoul National University College of Medicine, Seoul (Korea, Republic of); Park, Hae Jin [Dept. of Radiation Oncology, Soonchunhyang University Hospital, Seoul (Korea, Republic of)

    2012-12-15

    To analyze the outcomes of chemoradiotherapy for extrahepatic bile duct (EHBD) cancer patients who underwent R2 resection or bypass surgery and to identify prognostic factors affecting clinical outcomes, especially in terms of molecular biomarkers. Medical records of 21 patients with EHBD cancer who underwent R2 resection or bypass surgery followed by chemoradiotherapy from May 2001 to June 2010 were retrospectively reviewed. All surgical specimens were re-evaluated by immunohistochemical staining using phosphorylated protein kinase B (pAKT), CD24, matrix metalloproteinase 9 (MMP9), survivin, and {beta}-catenin antibodies. The relationship between clinical outcomes and immunohistochemical results was investigated. At a median follow-up of 20 months, the actuarial 2-year locoregional progression-free, distant metastasis-free and overall survival were 37%, 56%, and 54%, respectively. On univariate analysis using clinicopathologic factors, there was no significant prognostic factor. In the immunohistochemical staining, cytoplasmic staining, and nuclear staining of pAKT was positive in 10 and 6 patients, respectively. There were positive CD24 in 7 patients, MMP9 in 16 patients, survivin in 8 patients, and {beta}-catenin in 3 patients. On univariate analysis, there was no significant value of immunohistochemical results for clinical outcomes. There was no significant association between clinical outcomes of patients with EHBD cancer who received chemoradiotherapy after R2 resection or bypass surgery and pAKT, CD24, MMP9, survivin, and {beta}-catenin. Future research is needed on a larger data set or with other molecular biomarkers.

  19. Approaches of targeting Rho GTPases in cancer drug discovery

    Science.gov (United States)

    Lin, Yuan; Zheng, Yi

    2016-01-01

    Introduction Rho GTPases are master regulators of actomyosin structure and dynamics and play pivotal roles in a variety of cellular processes including cell morphology, gene transcription, cell cycle progression and cell adhesion. Because aberrant Rho GTPase signaling activities are widely associated with human cancer, key components of Rho GTPase signaling pathways have attracted increasing interest as potential therapeutic targets. Similar to Ras, Rho GTPases themselves were, until recently, deemed “undruggable” because of structure-function considerations. Several approaches to interfere with Rho GTPase signaling have been explored and show promise as new ways for tackling cancer cells. Areas covered This review focuses on the recent progress in targeting the signaling activities of three prototypical Rho GTPases, i.e. RhoA, Rac1, and Cdc42. The authors describe the involvement of these Rho GTPases, their key regulators and effectors in cancer. Furthermore, the authors discuss the current approaches for rationally targeting aberrant Rho GTPases along their signaling cascades, upstream and downstream of Rho GTPases and posttranslational modifications at a molecular level. Expert opinion To date, while no clinically effective drugs targeting Rho GTPase signaling for cancer treatment are available, tool compounds and lead drugs that pharmacologically inhibit Rho GTPase pathways have shown promise. Small molecule inhibitors targeting Rho GTPase signaling may add new treatment options for future precision cancer therapy, particularly in combination with other anti-cancer agents. PMID:26087073

  20. Single-walled carbon nanotube based transparent immunosensor for detection of a prostate cancer biomarker osteopontin

    Energy Technology Data Exchange (ETDEWEB)

    Sharma, Abhinav; Hong, Seongkyeol; Singh, Renu [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); Jang, Jaesung, E-mail: jjang@unist.ac.kr [School of Mechanical and Nuclear Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); Department of Biomedical Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of); School of Materials Science and Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 689-798 (Korea, Republic of)

    2015-04-15

    Highlights: • A transparent CNT immunosensor is presented for detection of a prostate cancer biomarker osteopontin. • This immunosensor showed a highly linear and reproducible behavior from 1 pg mL{sup −1} to 1 μg mL{sup −1}. • The limit of detection of the immunosensor was 0.3 pg mL{sup −1}. • This immunosensor demonstrated high selectivity against bovine serum albumin and human serum. - Abstract: Osteopontin (OPN) is involved in almost all steps of cancer development, and it is being investigated as a potential biomarker for a diagnosis and prognosis of prostate cancer. Here, we report a label-free, highly sensitive and transparent immunosensor based on single-walled carbon nanotubes (SWCNTs) for detection of OPN. A high density of −COOH functionalized SWCNTs was deposited between two gold/indium tin oxide electrodes on a glass substrate by dielectrophoresis. Monoclonal antibodies specific to OPN were covalently immobilized on the SWCNTs. Relative resistance change of the immunosensors was measured as the concentration of OPN in phosphate buffer saline (PBS) and human serum was varied from 1 pg mL{sup −1} to 1 μg mL{sup −1} for different channel lengths of 2, 5, and 10 μm, showing a highly linear and reproducible behavior (R{sup 2} > 97%). These immunosensors were also specific to OPN against another test protein, bovine serum albumin, PBS and human serum, showing that a limit of detection for OPN was 0.3 pg mL{sup −1}. This highly sensitive and transparent immunosensor has a great potential as a simple point-of-care test kit for various protein biomarkers.

  1. Clinical relevance of breast cancer-related genes as potential biomarkers for oral squamous cell carcinoma

    International Nuclear Information System (INIS)

    Squamous cell carcinoma of the oral cavity (OSCC) is a common cancer form with relatively low 5-year survival rates, due partially to late detection and lack of complementary molecular markers as targets for treatment. Molecular profiling of head and neck cancer has revealed biological similarities with basal-like breast and lung carcinoma. Recently, we showed that 16 genes were consistently altered in invasive breast tumors displaying varying degrees of aggressiveness. To extend our findings from breast cancer to another cancer type with similar characteristics, we performed an integrative analysis of transcriptomic and proteomic data to evaluate the prognostic significance of the 16 putative breast cancer-related biomarkers in OSCC using independent microarray datasets and immunohistochemistry. Predictive models for disease-specific (DSS) and/or overall survival (OS) were calculated for each marker using Cox proportional hazards models. We found that CBX2, SCUBE2, and STK32B protein expression were associated with important clinicopathological features for OSCC (peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumor size). Consequently, SCUBE2 and STK32B are involved in the hedgehog signaling pathway which plays a pivotal role in metastasis and angiogenesis in cancer. In addition, CNTNAP2 and S100A8 protein expression were correlated with DSS and OS, respectively. Taken together, these candidates and the hedgehog signaling pathway may be putative targets for drug development and clinical management of OSCC patients

  2. Telling the story of childhood cancer: an evaluation of the Discovery Interview methodology conducted within the Queensland Children's Cancer Centre

    Directory of Open Access Journals (Sweden)

    Slater PJ

    2016-05-01

    Full Text Available Penelope J Slater,1 Shoni P Philpot2 1Queensland Children's Cancer Centre, Lady Cilento Children's Hospital, Children's Health Queensland, 2Queensland Cancer Control Analysis Team, Princess Alexandra Hospital, Brisbane, QLD, Australia Abstract: This paper evaluates the process and impact of the Discovery Interview methodology developed in the National Health Service and applied in the Queensland Children's Cancer Centre. It shows how this methodology supports the family-centered care philosophy of the organization and gives staff insight into the experience of the families they care for. In total, 17 Discovery Interviews recorded during 2012–2014 were transcribed, deidentified, condensed, and read back to 222 staff in 20 different meetings. Families and staff involved in the process provided positive feedback. Over 53% of staff found these sessions extremely valuable, and 46% rated them as valuable. Discovery Interviews were shown to be a powerful tool to engage with families and staff to improve the experience of families in the Queensland Children's Cancer Centre. The sessions where Discovery Interviews were read to clinical teams raised their awareness of the perspectives of families and impacted on the way they delivered care and interacted with families. Staff described the stories as insightful and valued hearing them and discussing ways to improve service, including individual clinical practice, service processes, and family supports. Keywords: family experience, family-centered care, consumer engagement, service improvement, narratives

  3. A Comprehensive Review on miR-200c, A Promising Cancer Biomarker with Therapeutic Potential.

    Science.gov (United States)

    Kumar, Suresh; Nag, Alo; Mandal, Chandi C

    2015-01-01

    MicroRNAs (miRNAs) are small single stranded non coding RNA molecules (~22 nucleotides) which impede protein production by directly interacting with 3'untranslated regions of the target mRNAs. Interestingly, miR-200c is often dysregulated in various cancers that normally exhibits tumor suppressive behavior by blocking epithelial to mesenchymal transition (EMT) of cancer cells. However, elevation of miR-200c in various cancer tissues contradicts the tumor suppressive role of this microRNA. This review addresses the molecular mechanisms involved in the regulation of the endogenous level of miR-200c in various cancers such as breast, ovarian, prostate, endometrial, lungs, colon, pancreatic, etc. and its differential role in regulation of proliferation and EMT phenotype of cancer cells. Further, this review discusses whether abnormal level of miR-200c in cancer tissues or in blood circulation can be used as a biomarker. Importantly, how the level of miR-200c can be used to predict the effectiveness of the cancer therapy is also discussed. Accumulating evidences suggest that use of miR-200c alone may not be sufficient for treatment of cancer patients, but the combination of miR-200c with an anti-proliferating drug could be a better choice to prevent invasiveness of cancers as well as tumor growth both in primary and in metastatic sites. This article also proposes that the tumor microenvironment may have a role in influencing epigenetic silencing of miR-200c expression.

  4. Spermine and citrate as metabolic biomarkers for assessing prostate cancer aggressiveness.

    Directory of Open Access Journals (Sweden)

    Guro F Giskeødegård

    Full Text Available Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients with a high cancer content (mean: 61.8% were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS. Multivariate analysis (PLS, PLS-DA and absolute quantification (LCModel were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30 and high grade (GS≥7, n = 81 cancer with normal adjacent tissue (n = 47. High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044 and citrate (p = 7.73·10(-4, and an increase in the clinically applied (total choline+creatine+polyamines/citrate (CCP/C ratio (p = 2.17·10(-4. The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71, and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.

  5. Extracellular vesicles – biomarkers and effectors of the cellular interactome in cancer

    Directory of Open Access Journals (Sweden)

    Janusz eRak

    2013-03-01

    Full Text Available In multicellular organisms both health and disease are defined by patterns of communications between the constituent cells. In addition to networks of soluble mediators, cells are also programmed to exchange complex messages pre-assembled as multimolecular cargo of membraneous structures known extracellular vesicles (EV. Several biogenetic pathways produce EVs with different properties and known as exosomes, ectosomes and apoptotic bodies. In cancer, EVs carry molecular signatures and effectors of the disease, such as mutant oncoproteins, oncogenic transcripts, microRNA and DNA sequences. Intercellular trafficking of such EVs (oncosomes may contribute to horizontal cellular transformation, phenotypic reprogramming and functional re-education of recipient cells, both locally and systemically. The EV-mediated, reciprocal molecular exchange also includes tumor suppressors, phosphoproteins, proteases, growth factors and bioactive lipids, all of which participate in the functional integration of multiple cells and their collective involved in tumor angiogenesis, inflammation, immunity, coagulopathy, mobilization of bone marrow derived effectors, metastasis, drug resistance or cellular stemness. In cases where the EV involvement is rate limiting their production and uptake may represent and unexplored anticancer therapy target. Moreover, oncosomes circulating in biofluids of cancer patients offer an unprecedented, remote and non-invasive access to crucial molecular information about cancer cells, including their driver mutations, classifiers, molecular subtypes, therapeutic targets and biomarkers of drug resistance. New nanotechnologies are being developed to exploit this unique biomarker platform. Indeed, embracing the notion that human cancers are defined not only by processes occurring within cancer cells, but also between them, and amidst the altered tumor and systemic microenvironment may open new diagnostic and therapeutic opportunities.

  6. Histone Methylation Marks on Circulating Nucleosomes as Novel Blood-Based Biomarker in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Ugur Gezer

    2015-12-01

    Full Text Available Circulating nucleic acids (CNAs are under investigation as a liquid biopsy in cancer as potential non-invasive biomarkers, as stable structure in circulation nucleosomes could be valuable sources for detection of cancer-specific alterations in histone modifications. Our interest is in histone methylation marks with a focus on colorectal cancer, one of the leading cancers respective the incidence and mortality. Our previous work included the analysis of trimethylations of lysine 9 on histone 3 (H3K9me3 and of lysine 20 on histone 4 (H4K20me3 by chromatin immuno- precipitation-related PCR in circulating nucleosomes. Here we asked whether global immunologic measurement of histone marks in circulation could be a suitable approach to show their potential as biomarkers. In addition to H3K9me3 and H4K20me3 we also measured H3K27me3 in plasma samples from CRC patients (n = 63 and cancer free individuals (n = 40 by ELISA-based methylation assays. Our results show that of three marks, the amounts of H3K27me3 (p = 0.04 and H4K20me3 (p < 0.001 were significantly lower in CRC patients than in healthy controls. For H3K9me3 similar amounts were measured in both groups. Areas under the curve (AUC in receiver operating characteristic (ROC curves indicating the power of CRC detection were 0.620 for H3K27me3, 0.715 for H4K20me3 and 0.769 for the combination of both markers. In conclusion, findings of this preliminary study reveal the potential of blood-based detection of CRC by quantification of histone methylation marks and the additive effect of the marker combination.

  7. Targeted biomarker profiling of matched primary and metastatic estrogen receptor positive breast cancers.

    Directory of Open Access Journals (Sweden)

    Erica B Schleifman

    Full Text Available Patients with newly diagnosed, early stage estrogen receptor positive (ER+ breast cancer often show disease free survival in excess of five years following surgery and systemic adjuvant therapy. An important question is whether diagnostic tumor tissue from the primary lesion offers an accurate molecular portrait of the cancer post recurrence and thus may be used for predictive diagnostic purposes for patients with relapsed, metastatic disease. As the class I phosphatidylinositol 3' kinase (PI3K pathway is frequently activated in ER+ breast cancer and has been linked to acquired resistance to hormonal therapy, we hypothesized pathway status could evolve over time and treatment. Biomarker analyses were conducted on matched, asynchronous primary and metastatic tumors from 77 patients with ER+ breast cancer. We examined whether PIK3CA and AKT1 alterations or PTEN and Ki67 levels showed differences between primary and metastatic samples. We also sought to look more broadly at gene expression markers reflective of proliferation, molecular subtype, and key receptors and signaling pathways using an mRNA analysis platform developed on the Fluidigm BioMark™ microfluidics system to measure the relative expression of 90 breast cancer related genes in formalin-fixed paraffin-embedded (FFPE tissue. Application of this panel of biomarker assays to matched tumor pairs showed a high concordance between primary and metastatic tissue, with generally few changes in mutation status, proliferative markers, or gene expression between matched samples. The collection of assays described here has been optimized for FFPE tissue and may have utility in exploratory analyses to identify patient subsets responsive to targeted therapies.

  8. Recent discoveries concerning the involvement of transcription factors from the Grainyhead-like family in cancer.

    Science.gov (United States)

    Mlacki, Michal; Kikulska, Agnieszka; Krzywinska, Ewa; Pawlak, Magdalena; Wilanowski, Tomasz

    2015-11-01

    The Grainyhead-like (GRHL) family of transcription factors has three mammalian members, which are currently termed Grainyhead-like 1 (GRHL1), Grainyhead-like 2 (GRHL2), and Grainyhead-like 3 (GRHL3). These factors adopt a DNA-binding immunoglobulin fold homologous to the DNA-binding domain of key tumor suppressor p53. Their patterns of expression are tissue and developmentally specific. Earlier studies of the GRHL proteins focused on their functions in mammalian development. In recent years, these factors have been linked to many different types of cancer: squamous cell carcinoma of the skin, breast cancer, gastric cancer, hepatocellular carcinoma, colorectal cancer, clear cell renal cell carcinoma, neuroblastoma, prostate cancer, and cervical cancer. The roles of GRHL proteins in these various types of cancer are complex, and in some cases appear to be contradictory: they can serve to promote cancer development, or they may act as tumor suppressors, depending on the particular GRHL protein involved and on the cancer type. The reasons for obvious discrepancies in results from different studies remain unclear. At the molecular level, the GRHL transcription factors regulate the expression of genes whose products are involved in cellular proliferation, differentiation, adhesion, and polarity. We herein review the roles of GRHL proteins in cancer development, and we critically examine relevant molecular mechanisms, which were proposed by different authors. We also discuss the significance of recent discoveries implicating the involvement of GRHL transcription factors in cancer and highlight potential future applications of this knowledge in cancer treatment. PMID:26069269

  9. Psychoneuroimmunology and cancer: a decade of discovery, paradigm shifts, and methodological innovations.

    Science.gov (United States)

    Green McDonald, Paige; O'Connell, Mary; Lutgendorf, Susan K

    2013-03-01

    This article introduces the supplement Advances in Cancer and Brain, Behavior, and Immunity and outlines important discoveries, paradigm shifts, and methodological innovations that have emerged in the past decade to advance mechanistic and translational understanding of biobehavioral influences on tumor biology, cancer treatment-related sequelae, and cancer outcomes. We offer a heuristic framework for research on biobehavioral pathways in cancer. The shifting survivorship landscape is highlighted, and we propose that the changing demographics suggest prudent adoption of a life course perspective of cancer and cancer survivorship. We note opportunities for psychoneuroimmunology (PNI) research to ameliorate the long-term, unintended consequences of aggressive curative intent and call attention to the critical role of reciprocal translational pathways between animal and human studies. Lastly, we briefly summarize the articles included in this compilation and offer our perspectives on future research directions.

  10. Circulating Fibroblast Growth Factor 21 (Fgf21) as Diagnostic and Prognostic Biomarker in Renal Cancer

    Science.gov (United States)

    Knott, ME; Minatta, JN; Roulet, L; Gueglio, G; Pasik, L; Ranuncolo, SM; Nuñez, M; Puricelli, L; De Lorenzo, MS

    2016-01-01

    Background The finding of new biomarkers is needed to have a better sub-classification of primary renal tumors (RCC) as well as more reliable predictors of outcome and therapy response. In this study, we evaluated the role of circulating FGF21, an endocrine factor, as a diagnostic and prognostic biomarker for ccRCC. Materials and Methods Serum samples from healthy controls (HC), clear cell and chromophobe RCC cancer patients were obtained from the serum biobank “Biobanco Público de Muestras Séricas Oncológicas” (BPMSO) of the “Instituto de Oncología “Ángel H. Roffo”. Serum FGF21 and leptin were measured by ELISA while other metabolic markers were measured following routinely clinical procedures. Results One of our major findings was that FGF21 levels were significantly increased in ccRCC patients compared with HC. Moreover, we showed an association between the increased serum FGF21 levels and the shorter disease free survival in a cohort of 98 ccRCC patients, after adjustment for other predictors of outcome. Conclusion Our results suggest that higher FGF21 serum level is an independent prognostic biomarker, associated with worse free-disease survival. PMID:27358750

  11. Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

    Directory of Open Access Journals (Sweden)

    Shen Hu

    2010-09-01

    Full Text Available Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC. A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B. We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients.

  12. Osteopontin as potential biomarker and therapeutic target in gastric and liver cancers

    Institute of Scientific and Technical Information of China (English)

    Dong-Xing Cao; Zhi-Jie Li; Xiao-Ou Jiang; Yick Liang Lum; Ester Khin; Nikki P Lee; Guo-Hao Wu; John M Luk

    2012-01-01

    Gastric cancer and liver cancer are among the most common malignancies and the leading causes of death worldwide,due to late detection and high recurrence rates.Today,these cancers have a heavy socioeconomic burden,for which a full understanding of their pathophysiological features is warranted to search for promising biomarkers and therapeutic targets.Osteopontin (OPN) is overexpressed in most patients with gastric and liver cancers.Over the past decade,emerging evidence has revealed a correlation of OPN level and clinicopathological features and prognosis in gastric and liver cancers,indicating its potential as an independent prognostic indicator in such patients.Functional studies have verified the potential of OPN knockdown as a therapeutic approach in vitro and in vivo.Furthermore,OPN mediates multifaceted roles in the interaction between cancer cells and the tumor microenvironment,in which many details need further exploration.OPN signaling results in various functions,including prevention of apoptosis,modulation of angiogenesis,malfunction of tumor-associated macrophages,degradation of extracellular matrix,activation of phosphoinositide 3-kinase-Akt and nuclear factor-κB pathways,which lead to tumor formation and progression,particularly in gastric and liver cancers.This editorial aims to review recent findings on alteration in OPN expression and its clinicopathological associations with tumor progression,its potential as a therapeutic target,and putative mechanisms in gastric and liver cancers.Better understanding of the implications of OPN in tumorigenesis might facilitate development of therapeutic regimens to benefit patients with these deadly malignancies.

  13. Cancer Biomarkers from Genome-Scale DNA Methylation: Comparison of Evolutionary and Semantic Analysis Methods

    Directory of Open Access Journals (Sweden)

    Ioannis Valavanis

    2015-11-01

    Full Text Available DNA methylation profiling exploits microarray technologies, thus yielding a wealth of high-volume data. Here, an intelligent framework is applied, encompassing epidemiological genome-scale DNA methylation data produced from the Illumina’s Infinium Human Methylation 450K Bead Chip platform, in an effort to correlate interesting methylation patterns with cancer predisposition and, in particular, breast cancer and B-cell lymphoma. Feature selection and classification are employed in order to select, from an initial set of ~480,000 methylation measurements at CpG sites, predictive cancer epigenetic biomarkers and assess their classification power for discriminating healthy versus cancer related classes. Feature selection exploits evolutionary algorithms or a graph-theoretic methodology which makes use of the semantics information included in the Gene Ontology (GO tree. The selected features, corresponding to methylation of CpG sites, attained moderate-to-high classification accuracies when imported to a series of classifiers evaluated by resampling or blindfold validation. The semantics-driven selection revealed sets of CpG sites performing similarly with evolutionary selection in the classification tasks. However, gene enrichment and pathway analysis showed that it additionally provides more descriptive sets of GO terms and KEGG pathways regarding the cancer phenotypes studied here. Results support the expediency of this methodology regarding its application in epidemiological studies.

  14. Respiratory Toxicity Biomarkers

    Science.gov (United States)

    The advancement in high throughput genomic, proteomic and metabolomic techniques have accelerated pace of lung biomarker discovery. A recent growth in the discovery of new lung toxicity/disease biomarkers have led to significant advances in our understanding of pathological proce...

  15. N-Acetylgalactosaminyltransferase-14 as a potential biomarker for breast cancer by immunohistochemistry

    Directory of Open Access Journals (Sweden)

    Ma Sisi

    2010-04-01

    Full Text Available Abstract Background The post-translational modification of proteins, including glycosylation, differs between normal and tumor cells. The UDP-N-acetyl-D-galactosamine polypeptide N-acetylgalactosaminyltransferases (GalNAc-Tases family of enzymes regulates the initial steps of mucin O-glycosylation and is responsible for the altered glycosylation state observed in cancer cells. Recently it was found that GalNAc-T14 mRNA is heterogeneously expressed in breast carcinomas compared to normal tissue, however the expression profile of GalNAc-T14 protein in breast carcinomas compared to normal tissue is still unknown. In this study, we assessed the expression profile of GalNAc-T14 protein in malignant and non-malignant breast tissues by immunohistochemistry to evaluate whether GalNAc-T14 might be a potential biomarker for breast cancer. Methods In formalin-fixed tissues, the expression level of GalNAc-T14 protein was evaluated by immunohistochemistry assay in breast tissues. Expression profiles were assessed in normal tissues, benign fibroadenomas and several types of carcinomas. Results Our results showed that GalNAc-T14 was heterogeneously expressed in breast carcinomas compared to non-malignant tissue. GalNAc-T14 expression was observed in 47/56 (83.9% carcinoma samples, 7/48 (14.6% non-malignant breast tissue samples. GalNAc-T14 expression level was associated with histological grade. For this enzyme a significant association with invasive ductal type, mucinous adenocarcinoma and ductal carcinoma in situ (DCIS type was found. Conclusion Our results provide evidence that GalNAc-T14 may be a potential biomarker for breast cancer by immunohistochemistry. GalNAc-T14 expression level was associated with histological grade. GalNAc-T14 expression can provide new insights about breast cancer glycobiology.

  16. miRNA profiling of circulating EpCAM+ extracellular vesicles: promising biomarkers of colorectal cancer

    Science.gov (United States)

    Ostenfeld, Marie Stampe; Jensen, Steffen Grann; Jeppesen, Dennis Kjølhede; Christensen, Lise-Lotte; Thorsen, Stine Buch; Stenvang, Jan; Hvam, Michael Lykke; Thomsen, Anni; Mouritzen, Peter; Rasmussen, Mads Heilskov; Nielsen, Hans Jørgen; Ørntoft, Torben Falck; Andersen, Claus Lindbjerg

    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. Here we describe a sensitive analytical method for isolation and subsequent miRNA profiling of epithelial-derived EVs from blood samples of patients with colorectal cancer (CRC). The epithelial-derived EVs were isolated by immunoaffinity-capture using the epithelial cell adhesion molecule (EpCAM) as marker. This approach mitigates some of the specificity issues observed in earlier studies of circulating miRNAs, in particular the negative influence of miRNAs released by erythrocytes, platelets and non-epithelial cells. By applying this method to 2 small-scale patient cohorts, we showed that blood plasma isolated from CRC patients prior to surgery contained elevated levels of 13 EpCAM+-EV miRNAs compared with healthy individuals. Upon surgical tumour removal, the plasma levels of 8 of these were reduced (miR-16-5p, miR-23a-3p, miR-23b-3p, miR-27a-3p, miR-27b-3p, miR-30b-5p, miR-30c-5p and miR-222-3p). These findings indicate that the miRNAs are of tumour origin and may have potential as non-invasive biomarkers for detection of CRC. This work describes a non-invasive blood-based method for sensitive detection of cancer with potential for clinical use in relation to diagnosis and screening. We used the method to study CRC; however, it is not restricted to this disease. It may in principle be used to study any cancer that release epithelial-derived EVs into circulation. PMID:27576678

  17. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    Science.gov (United States)

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  18. Tumor budding as a potential histopathological biomarker in colorectal cancer: Hype or hope?

    Institute of Scientific and Technical Information of China (English)

    Fabio Grizzi; Giuseppe Celesti; Gianluca Basso; Luigi Laghi

    2012-01-01

    Colorectal cancer (CRC),the third most commonly diagnosed type of cancer in men and women worldwide is recognized as a complex multi-pathway disease,an observation sustained by the fact that histologically identical tumors may have different outcome,including various response to therapy.Therefore,particularly in early and intermediate stage (stages Ⅱ and Ⅲ,respectively) CRC,there is a compelling need for biomarkers helpful of selecting patients with aggressive disease that might benefit from adjuvant and targeted therapy.Histopathological examination shows that likely other solid tumors the development and progression of human CRC is not only determined by genetically abnormal cells,but also by intricate interactions between malignant cells and the surrounding microenvironment.This has led to reconsider the features of tumor microenvironment as potential predictive and prognostic biomarkers.Among the histopathological biomarkers,tumor budding (i.e.,the presence of individual cells and small clusters of tumor cells at the tumor invasive front)has received much recent attention,particularly in the setting of CRC.Although its acceptance as a reportable factor has been held back by a lack of uniformity with respect to qualitative and quantitative aspects,tumor budding is now considered as an independent adverse prognostic factor in CRC that may allow for stratification of patients into risk categories more meaningful than those defined by tumor-node-metastasis staging alone,and also potentially guide treatment decisions,especially in T2-T3 NO (stage Ⅱ) CRCs.

  19. Urinary Polyamines: A Pilot Study on Their Roles as Prostate Cancer Detection Biomarkers.

    Science.gov (United States)

    Tsoi, Tik-Hung; Chan, Chi-Fai; Chan, Wai-Lun; Chiu, Ka-Fung; Wong, Wing-Tak; Ng, Chi-Fai; Wong, Ka-Leung

    2016-01-01

    Current screening methods towards prostate cancer (PCa) are not without limitations. Research work has been on-going to assess if there are other better tests suitable for primary or secondary screening of PCa to supplement the serum prostate specific antigen (PSA) test, which fails to work accurately in a grey zone of 4-10ng/ml. In this pilot study, the potential roles of urinary polyamines as prostate cancer biomarkers were evaluated. PCa, benign prostatic hyperplasia (BPH) patients and healthy controls (HC) showing PSA>4.0ng/ml were enrolled in the study. Their urine samples were obtained, and the urinary levels of putrescine (Put), spermidine (Spd) and spermine (Spm) were determined by ultra-high performance liquid chromatography coupled with triple quadrupole mass spectrometer (UPLC-MS/MS). Receiver operating characteristics (ROC) curve and Student's t-test were used to evaluate their diagnostic accuracies. Among the three biogenic polyamines, Spm had demonstrated a good diagnostic performance when comparing their levels in PCa patients with BPH patients (1.47 in PCa vs 5.87 in BPH; pprostatic biopsy (TRUSPB) results, with an area under curve (AUC) value of 0.83±0.03. Therefore urinary Spm shows potential to serve as a novel PCa diagnostic biomarker, which in turn can help to address the limited sensitivity and specificity problem of serum PSA test. PMID:27598335

  20. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    Energy Technology Data Exchange (ETDEWEB)

    Schultz, Nicolai A. [Departments of Surgical Gastroenterology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark); Johansen, Julia S., E-mail: julia.johansen@post3.tele.dk [Departments of Oncology, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark); Departments of Medicine, Herlev Hospital, University of Copenhagen, Herlev Ringvej 75, DK-2730 Herlev (Denmark)

    2010-07-12

    YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer.

  1. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    Directory of Open Access Journals (Sweden)

    Julia S. Johansen

    2010-07-01

    Full Text Available YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer.

  2. YKL-40—A Protein in the Field of Translational Medicine: A Role as a Biomarker in Cancer Patients?

    International Nuclear Information System (INIS)

    YKL-40 is a 40 kDa glycoprotein produced by cancer cells, inflammatory cells and stem cells. It probably has a role in cell proliferation and differentiation, inflammation, protection against apoptosis, stimulation of angiogenesis, and regulation of extracellular tissue remodelling. Plasma levels of YKL-40 are often elevated in patients with localized or advanced cancer compared to age-matched healthy subjects. Several studies have demonstrated that high plasma YKL-40 is an independent prognostic biomarker of short survival in patients with different types of cancer. However, there is not yet sufficient data to support determination of plasma YKL-40 outside research projects as a biomarker for screening of gastrointestinal cancer and determination of treatment response and poor prognosis before or during treatment and follow-up. Plasma YKL-40 is also elevated in patients with other diseases than cancer, e.g., severe infections, cardiovascular disease, diabetes, chronic obstructive lung disease, asthma, liver fibrosis and rheumatoid arthritis. Co-morbidity should therefore always be considered in patients with cancer, since other sources than cancer cells can increase plasma YKL-40 levels. Future focused translational research projects combining basic and clinical research are needed in a joint effort to answer questions of the complex function and regulation of YKL-40 and the question if plasma YKL-40 is a clinical useful biomarker in patients with cancer

  3. Biomarker candidate discovery in Atlantic cod (Gadus morhua) continuously exposed to North Sea produced water from egg to fry

    DEFF Research Database (Denmark)

    Bohne-Kjersem, Anneli; Bache, Nicolai; Meier, Sonnich;

    2010-01-01

    In this study Atlantic cod (Gadus morhua) were exposed to different levels of North Sea produced water (PW) and 17beta-oestradiol (E(2)), a natural oestrogen, from egg to fry stage (90 days). By comparing changes in protein expression following E(2) exposure to changes induced by PW treatment, we...... changes that may be useful as biomarker candidates of produced water (PW) and oestradiol exposure in Atlantic cod fry. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring exposure and effects of discharges from the petroleum...

  4. Transcriptome analysis of recurrently deregulated genes across multiple cancers identifies new pan-cancer biomarkers

    DEFF Research Database (Denmark)

    Kaczkowski, Bogumil; Tanaka, Yuji; Kawaji, Hideya;

    2016-01-01

    RNAs which are upregulated in cancer, defining promoters which overlap with repetitive elements (especially SINE/Alu and LTR/ERV1 elements) that are often upregulated in cancer. Lastly, we documented for the first time upregulation of multiple copies of the REP522 interspersed repeat in cancer. Overall...

  5. Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

    Directory of Open Access Journals (Sweden)

    Fan Zhang

    2013-01-01

    Full Text Available Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.

  6. Emerging Glycolysis Targeting and Drug Discovery from Chinese Medicine in Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Zhiyu Wang

    2012-01-01

    Full Text Available Molecular-targeted therapy has been developed for cancer chemoprevention and treatment. Cancer cells have different metabolic properties from normal cells. Normal cells mostly rely upon the process of mitochondrial oxidative phosphorylation to produce energy whereas cancer cells have developed an altered metabolism that allows them to sustain higher proliferation rates. Cancer cells could predominantly produce energy by glycolysis even in the presence of oxygen. This alternative metabolic characteristic is known as the “Warburg Effect.” Although the exact mechanisms underlying the Warburg effect are unclear, recent progress indicates that glycolytic pathway of cancer cells could be a critical target for drug discovery. With a long history in cancer treatment, traditional Chinese medicine (TCM is recognized as a valuable source for seeking bioactive anticancer compounds. A great progress has been made to identify active compounds from herbal medicine targeting on glycolysis for cancer treatment. Herein, we provide an overall picture of the current understanding of the molecular targets in the cancer glycolytic pathway and reviewed active compounds from Chinese herbal medicine with the potentials to inhibit the metabolic targets for cancer treatment. Combination of TCM with conventional therapies will provide an attractive strategy for improving clinical outcome in cancer treatment.

  7. Salivary microRNAs as promising biomarkers for detection of esophageal cancer.

    Directory of Open Access Journals (Sweden)

    Zijun Xie

    Full Text Available BACKGROUND AND PURPOSE: Tissue microRNAs (miRNAs can detect cancers and predict prognosis. Several recent studies reported that tissue, plasma, and saliva miRNAs share similar expression profiles. In this study, we investigated the discriminatory power of salivary miRNAs (including whole saliva and saliva supernatant for detection of esophageal cancer. MATERIALS AND METHODS: By Agilent microarray, six deregulated miRNAs from whole saliva samples from seven patients with esophageal cancer and three healthy controls were selected. The six selected miRNAs were subjected to validation of their expression levels by RT-qPCR using both whole saliva and saliva supernatant samples from an independent set of 39 patients with esophageal cancer and 19 healthy controls. RESULTS: Six miRNAs (miR-10b*, miR-144, miR-21, miR-451, miR-486-5p, and miR-634 were identified as targets by Agilent microarray. After validation by RT-qPCR, miR-10b*, miR-144, and miR-451 in whole saliva and miR-10b*, miR-144, miR-21, and miR-451 in saliva supernatant were significantly upregulated in patients, with sensitivities of 89.7, 92.3, 84.6, 79.5, 43.6, 89.7, and 51.3% and specificities of 57.9, 47.4, 57.9%, 57.9, 89.5, 47.4, and 84.2%, respectively. CONCLUSIONS: We found distinctive miRNAs for esophageal cancer in both whole saliva and saliva supernatant. These miRNAs possess discriminatory power for detection of esophageal cancer. Because saliva collection is noninvasive and convenient, salivary miRNAs show great promise as biomarkers for detection of esophageal cancer in areas at high risk.

  8. Clinical utility of certain biomarkers as predictors of breast cancer with or without metastasis among Egyptian females.

    Science.gov (United States)

    Ahmed, Samia A; Hamed, Manal A; Omar, Omar S

    2015-02-01

    The objective of this study is to explore and correlate the value of certain biomarkers in breast cancer (BC) females with and without metastasis after undergoing the surgical treatment protocol in the National Cancer Institute in Egypt. Thirty females (33-69 years), diagnosed as early breast cancer patients with or without metastasis, and 20 healthy individuals were selected for this study. The biomarkers under investigation were vascular endothelial growth factor (VEGF), C-reactive protein (CRP), interleukin-6 (IL-6), and interleukin-8 (IL-8). The correlation between these markers and the tumor grade was also evaluated. The results revealed a significant increase (p IL-8 in breast cancer patients with or without metastasis as compared to the healthy group. Surgical treatment of metastatic BC females showed a significant reduction of those parameters by variable degrees, whereas BC females without metastasis recorded the most inhibition levels. Also, there was positive correlation (p IL-8 as well as CRP and IL-6. In conclusion, the selected biomarkers may be beneficial for the prognosis of breast cancer and seem to be a diagnostic tool to differentiate between BC with or without metastasis. The descried surgical treatment protocol succeeded to attenuate the elevated biomarker levels and improve patient survival which deserves more extensive studies.

  9. Biomarker discovery with SELDI-TOF MS in human urine associated with early renal injury : evaluation with computational analytical tools.

    NARCIS (Netherlands)

    Houtte, K.J.A. van; Laarakkers, C.; Marchiori, E.; Pickkers, P.; Wetzels, J.F.M.; Willems, J.L.; Heuvel, L.P.W.J. van den; Russel, F.G.M.; Masereeuw, R.

    2007-01-01

    BACKGROUND: Urine proteomics is one of the key emerging technologies to discover new biomarkers for renal disease, which may be used in the early diagnosis, prognosis and treatment of patients. In the present study, we validated surface-enhanced laser desorption/ionization time-of-flight mass spectr

  10. Regulatory Forum Opinion Piece*: Veterinary Pathologists in Translational Pharmacology and Biomarker Integration in Drug Discovery and Development.

    Science.gov (United States)

    Ramaiah, Shashi K; Walker, Dana B

    2016-02-01

    This article highlights emerging roles for veterinary pathologists outside of traditional functions and in line with the translational research (TR) approach. Veterinary pathologists offer unique and valuable expertise toward addressing particular TR and associated translational pharmacology questions, identifying gaps and risks in biomarker and pathology strategies, and advancing TR team decision making. Veterinary pathologists' attributes that are integral to the TR approach include (i) well-developed understanding of comparative physiology, pathology, and disease; (ii) extensive experience in interpretation and integration of complex data sets on whole-body responses and utilizing this for deciphering pathogenesis and translating events between laboratory species and man; (iii) proficiency in recognizing differences in disease end points among individuals, animal species and strains, and assessing correlations between these differences and other investigative (including biomarker) findings; and (iv) strong background in a wide spectrum of research technologies that can address pathomechanistic questions and biomarker needs. Some of the more evident roles in which veterinary pathologists can offer their greatest contributions to address questions and strategies of TR and biomarker integration will be emphasized. PMID:26839329

  11. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    Science.gov (United States)

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  12. An evaluation of logic regression-based biomarker discovery across multiple intergenic regions for predicting host specificity in Escherichia coli.

    Science.gov (United States)

    Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Banting, Graham; Edge, Thomas A; Topp, Edward; McAllister, Tim A; Neumann, Norman F

    2016-10-01

    Several studies have demonstrated that E. coli appears to display some level of host adaptation and specificity. Recent studies in our laboratory support these findings as determined by logic regression modeling of single nucleotide polymorphisms (SNP) in intergenic regions (ITGRs). We sought to determine the degree of host-specific information encoded in various ITGRs across a library of animal E. coli isolates using both whole genome analysis and a targeted ITGR sequencing approach. Our findings demonstrated that ITGRs across the genome encode various degrees of host-specific information. Incorporating multiple ITGRs (i.e., concatenation) into logic regression model building resulted in greater host-specificity and sensitivity outcomes in biomarkers, but the overall level of polymorphism in an ITGR did not correlate with the degree of host-specificity encoded in the ITGR. This suggests that distinct SNPs in ITGRs may be more important in defining host-specificity than overall sequence variation, explaining why traditional unsupervised learning phylogenetic approaches may be less informative in terms of revealing host-specific information encoded in DNA sequence. In silico analysis of 80 candidate ITGRs from publically available E. coli genomes was performed as a tool for discovering highly host-specific ITGRs. In one ITGR (ydeR-yedS) we identified a SNP biomarker that was 98% specific for cattle and for which 92% of all E. coli isolates originating from cattle carried this unique biomarker. In the case of humans, a host-specific biomarker (98% specificity) was identified in the concatenated ITGR sequences of rcsD-ompC, ydeR-yedS, and rclR-ykgE, and for which 78% of E. coli originating from humans carried this biomarker. Interestingly, human-specific biomarkers were dominant in ITGRs regulating antibiotic resistance, whereas in cattle host-specific biomarkers were found in ITGRs involved in stress regulation. These data suggest that evolution towards host

  13. Circulating plasma MiR-141 is a novel biomarker for metastatic colon cancer and predicts poor prognosis.

    Directory of Open Access Journals (Sweden)

    Hanyin Cheng

    Full Text Available BACKGROUND: Colorectal cancer (CRC remains one of the major cancer types and cancer related death worldwide. Sensitive, non-invasive biomarkers that can facilitate disease detection, staging and prediction of therapeutic outcome are highly desirable to improve survival rate and help to determine optimized treatment for CRC. The small non-coding RNAs, microRNAs (miRNAs, have recently been identified as critical regulators for various diseases including cancer and may represent a novel class of cancer biomarkers. The purpose of this study was to identify and validate circulating microRNAs in human plasma for use as such biomarkers in colon cancer. METHODOLOGY/PRINCIPAL FINDINGS: By using quantitative reverse transcription-polymerase chain reaction, we found that circulating miR-141 was significantly associated with stage IV colon cancer in a cohort of 102 plasma samples. Receiver operating characteristic (ROC analysis was used to evaluate the sensitivity and specificity of candidate plasma microRNA markers. We observed that combination of miR-141 and carcinoembryonic antigen (CEA, a widely used marker for CRC, further improved the accuracy of detection. These findings were validated in an independent cohort of 156 plasma samples collected at Tianjin, China. Furthermore, our analysis showed that high levels of plasma miR-141 predicted poor survival in both cohorts and that miR-141 was an independent prognostic factor for advanced colon cancer. CONCLUSIONS/SIGNIFICANCE: We propose that plasma miR-141 may represent a novel biomarker that complements CEA in detecting colon cancer with distant metastasis and that high levels of miR-141 in plasma were associated with poor prognosis.

  14. Circulating Plasma MiR-141 Is a Novel Biomarker for Metastatic Colon Cancer and Predicts Poor Prognosis

    Science.gov (United States)

    Cogdell, David E.; Zheng, Hong; Schetter, Aaron J.; Nykter, Matti; Harris, Curtis C.; Chen, Kexin; Hamilton, Stanley R.; Zhang, Wei

    2011-01-01

    Background Colorectal cancer (CRC) remains one of the major cancer types and cancer related death worldwide. Sensitive, non-invasive biomarkers that can facilitate disease detection, staging and prediction of therapeutic outcome are highly desirable to improve survival rate and help to determine optimized treatment for CRC. The small non-coding RNAs, microRNAs (miRNAs), have recently been identified as critical regulators for various diseases including cancer and may represent a novel class of cancer biomarkers. The purpose of this study was to identify and validate circulating microRNAs in human plasma for use as such biomarkers in colon cancer. Methodology/Principal Findings By using quantitative reverse transcription-polymerase chain reaction, we found that circulating miR-141 was significantly associated with stage IV colon cancer in a cohort of 102 plasma samples. Receiver operating characteristic (ROC) analysis was used to evaluate the sensitivity and specificity of candidate plasma microRNA markers. We observed that combination of miR-141 and carcinoembryonic antigen (CEA), a widely used marker for CRC, further improved the accuracy of detection. These findings were validated in an independent cohort of 156 plasma samples collected at Tianjin, China. Furthermore, our analysis showed that high levels of plasma miR-141 predicted poor survival in both cohorts and that miR-141 was an independent prognostic factor for advanced colon cancer. Conclusions/Significance We propose that plasma miR-141 may represent a novel biomarker that complements CEA in detecting colon cancer with distant metastasis and that high levels of miR-141 in plasma were associated with poor prognosis. PMID:21445232

  15. Circulating cell-free mitochondrial DNA as a novel cancer biomarker: opportunities and challenges.

    Science.gov (United States)

    Yu, Man

    2012-10-01

    The unique characteristics of the mitochondrial genome, such as short length, simple molecular structure, and high copy number, have made monitoring aberrant changes of mitochondrial DNA (mtDNA) quantity an interesting molecular tool for early tumor detection with many advantages over the nuclear genome-based methods. Recently, circulating cell-free (ccf) mtDNA in blood has emerged on the platform as a non-invasive diagnostic and prognostic biomarker for many forms of solid tumors. Accumulating evidence demonstrate that plasma or serum ccf mtDNA levels are significantly different between cancer patients and healthy individuals. Furthermore, quantification of ccf mtDNA levels in circulation may assist in identifying patients from cancer-free healthy population. This minireview attempts to summarize our recent findings in this very promising field of cancer research. The potential technical challenges that we have encountered during the quantitative analysis of ccf mtDNA and mtDNA in general are also briefly discussed. Prospective studies with a larger cohort of patients in various cancer entities are beneficial to precisely define the clinical importance of assessing the ccf mtDNA amount for diagnosing and tracking malignant diseases and their progression.

  16. Viral and Cellular Biomarkers in the Diagnosis of Cervical Intraepithelial Neoplasia and Cancer

    Directory of Open Access Journals (Sweden)

    Maria Lina Tornesello

    2013-01-01

    Full Text Available Cervical cancer arises from cells localized in the ectoendocervical squamocolumnar junction of the cervix persistently infected with one of about 13 human papillomavirus (HPV genotypes. The majority of HPV infections induces low grade squamous epithelial lesions that in more than 90% of cases spontaneously regress and in about 10% eventually progress to high grade lesions and even less frequently evolve to invasive cancer. Tumor progression is characterized by (1 increased expression of E6 and E7 genes of high risk HPVs, known to bind to and inactivate p53 and pRb oncosuppressors, respectively; (2 integration of viral DNA into host genome, with disruption of E2 viral genes and host chromosomal loci; and (3 molecular alterations of key regulators of cell cycle. Molecular markers with high sensitivity and specificity in differentiating viral infections associated with cellular abnormalities with high risk of progression are strongly needed for cervical cancer screening and triage. This review will focus on the analysis of clinical validated or candidate biomarkers, such as HPV DNA, HPV E6/E7 mRNA, HPV proteins, p16(INK4a and Ki67, TOP2A and MCM2 cellular factors, and DNA methylation profiles, which will likely improve the identification of premalignant lesions that have a high risk to evolve into invasive cervical cancer.

  17. Predictive and Prognostic Protein Biomarkers in Epithelial Ovarian Cancer: Recommendation for Future Studies

    Directory of Open Access Journals (Sweden)

    Cécile Le Page

    2010-05-01

    Full Text Available Epithelial ovarian cancer is the most lethal gynecological malignancy. Due to its lack of symptoms, this disease is diagnosed at an advanced stage when the cancer has already spread to secondary sites. While initial rates of response to first treatment is >80%, the overall survival rate of patients is extremely low, mainly due to development of drug resistance. To date, there are no reliable clinical factors that can properly stratify patients for suitable chemotherapy strategies. Clinical parameters such as disease stage, tumor grade and residual disease, although helpful in the management of patients after their initial surgery to establish the first line of treatment, are not efficient enough. Accordingly, reliable markers that are independent and complementary to clinical parameters are needed for a better management of these patients. For several years, efforts to identify prognostic factors have focused on molecular markers, with a large number having been investigated. This review aims to present a summary of the recent advances in the identification of molecular biomarkers in ovarian cancer patient tissues, as well as an overview of the need and importance of molecular markers for personalized medicine in ovarian cancer.

  18. TMPRSS2-ERG -specific transcriptional modulation is associated with prostate cancer biomarkers and TGF-β signaling

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