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Sample records for cancer biomarker discovery

  1. Using Aptamers for Cancer Biomarker Discovery

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    Yun Min Chang

    2013-01-01

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

  2. Computational and Experimental Approaches to Cancer Biomarker Discovery

    DEFF Research Database (Denmark)

    Krzystanek, Marcin

    with a purely biological, experimental approach where the effects of treatment with cytotoxic agents or defects in DNA repair mechanisms can be individually quantified and turned into mutational signatures.In the second part of the thesis I present work towards identification and improvement of the current......Effective cancer treatment requires good biomarkers: measurable indicators of some biological state or condition that constitute the cornerstone of personalized medicine. Prognostic biomarkers provide information about the likely course of the disease, while predictive biomarkers enable prediction...... of a patient’s response to a particular treatment, thus helping to avoid unnecessary treatment and unwanted side effects in non-responding individuals.Currently biomarker discovery is facilitated by recent advances in high-throughput technologies when association between a given biological phenotype...

  3. 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.

  4. 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.

  5. 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.

  6. Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery

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    Si, Qian

    Technological advances in proteomics have shown great potential in detecting cancer at the earliest stages. One way is to use the time of flight mass spectroscopy to identify biomarkers, or early disease indicators related to the cancer. Pattern analysis of time of flight mass spectra data from blood and tissue samples gives great hope for the identification of potential biomarkers among the complex mixture of biological and chemical samples for the early cancer detection. One of the keys issues is the pre-processing of raw mass spectra data. A lot of challenges need to be addressed: unknown noise character associated with the large volume of data, high variability in the mass spectroscopy measurements, and poorly understood signal background and so on. This dissertation focuses on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data. I have introduced an advanced accurate estimate of the noise model and a half-supervised method of mass spectrum data processing which requires little knowledge about the data.

  7. 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.

  8. Application of Glycoproteomics in the Discovery of Biomarkers for Lung Cancer

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    Li, Qing Kay; Gabrielson, Edward; Zhang, Hui

    2017-01-01

    Lung cancer is the leading cause of cancer-related deaths in the United States. Approximately 40–60% of lung cancer patients present with locally advanced or metastatic disease at the time of diagnosis. In order to improve the survival rate of lung cancer patients, the discovery of early diagnostic and prognostic biomarkers is urgently needed. Lung cancer development and progression are a multistep process which is characterized by abnormal gene and protein expressions ultimately leading to phenotypic change. In lung cancer, the expression of cellular glycoproteins directly reflects the physiological and/or pathological status of the lung parenchyma. Glycoproteins have long been recognized to play fundamental roles in many physiological and pathological processes, particularly in cancer genesis and progression. Although numerous papers have already acknowledged the importance of the discovery of cancer biomarkers, the systemic study of glycoproteins in lung cancer using glycoproteomic approaches is still suboptimal. Herein, we review the recent technological development of glycoproteomics in highlighting their utility and limitations for the discovery of glycoprotein biomarkers in lung cancer. PMID:22641610

  9. Biomarker discovery by proteomics-based approaches for early detection and personalized medicine in colorectal cancer.

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    Corbo, Claudia; Cevenini, Armando; Salvatore, Francesco

    2016-12-26

    About one million people per year develop colorectal cancer (CRC) and approximately half of them die. The extent of the disease (i.e. local invasion at the time of diagnosis) is a key prognostic factor. The 5-year survival rate is almost 90% in the case of delimited CRC and 10% in the case of metastasized CRC. Hence, one of the great challenges in the battle against CRC is to improve early diagnosis strategies. Large-scale proteomic approaches are widely used in cancer research to search for novel biomarkers. Such biomarkers can help in improving the accuracy of the diagnosis and in the optimization of personalized therapy. Herein, we provide an overview of studies published in the last 5 years on CRC that led to the identification of protein biomarkers suitable for clinical application by using proteomic approaches. We discussed these findings according to biomarker application, including also the role of protein phosphorylation and cancer stem cells in biomarker discovery. Our review provides a cross section of scientific approaches and can furnish suggestions for future experimental strategies to be used as reference by scientists, clinicians and researchers interested in proteomics for biomarker discovery.

  10. 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.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  12. Integrative Genomic Data Mining for Discovery of Potential Blood-Borne Biomarkers for Early Diagnosis of Cancer

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    Yongliang Yang; Pavel Pospisil; Iyer, Lakshmanan K.; S. James Adelstein; Amin I. Kassis

    2008-01-01

    BACKGROUND: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA) program to identify po...

  13. An integrated approach to blood-based cancer diagnosis and biomarker discovery.

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    Min, Martin Renqiang; Chowdhury, Salim; Qi, Yanjun; Stewart, Alex; Ostroff, Rachel

    2014-01-01

    Disrupted or abnormal biological processes responsible for cancers often quantitatively manifest as disrupted additive and multiplicative interactions of gene/protein expressions correlating with cancer progression. However, the examination of all possible combinatorial interactions between gene features in most case-control studies with limited training data is computationally infeasible. In this paper, we propose a practically feasible data integration approach, QUIRE (QUadratic Interactions among infoRmative fEatures), to identify discriminative complex interactions among informative gene features for cancer diagnosis and biomarker discovery directly based on patient blood samples. QUIRE works in two stages, where it first identifies functionally relevant gene groups for the disease with the help of gene functional annotations and available physical protein interactions, then it explores the combinatorial relationships among the genes from the selected informative groups. Based on our private experimentally generated data from patient blood samples using a novel SOMAmer (Slow Off-rate Modified Aptamer) technology, we apply QUIRE to cancer diagnosis and biomarker discovery for Renal Cell Carcinoma (RCC) and Ovarian Cancer (OVC). To further demonstrate the general applicability of our approach, we also apply QUIRE to a publicly available Colorectal Cancer (CRC) dataset that can be used to prioritize our SOMAmer design. Our experimental results show that QUIRE identifies gene-gene interactions that can better identify the different cancer stages of samples, as compared to other state-of-the-art feature selection methods. A literature survey shows that many of the interactions identified by QUIRE play important roles in the development of cancer.

  14. 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.

  15. 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.

  16. A comparison of methods for data-driven cancer outlier discovery, and an application scheme to semisupervised predictive biomarker discovery.

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    Karrila, Seppo; Lee, Julian Hock Ean; Tucker-Kellogg, Greg

    2011-04-18

    A core component in translational cancer research is biomarker discovery using gene expression profiling for clinical tumors. This is often based on cell line experiments; one population is sampled for inference in another. We disclose a semisupervised workflow focusing on binary (switch-like, bimodal) informative genes that are likely cancer relevant, to mitigate this non-statistical problem. Outlier detection is a key enabling technology of the workflow, and aids in identifying the focus genes.We compare outlier detection techniques MOST, LSOSS, COPA, ORT, OS, and t-test, using a publicly available NSCLC dataset. Removing genes with Gaussian distribution is computationally efficient and matches MOST particularly well, while also COPA and OS pick prognostically relevant genes in their top ranks. Also our stability assessment is in favour of both MOST and COPA; the latter does not pair well with prefiltering for non-Gaussianity, but can handle data sets lacking non-cancer cases.We provide R code for replicating our approach or extending it.

  17. Integrative genomic data mining for discovery of potential blood-borne biomarkers for early diagnosis of cancer.

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    Yongliang Yang

    Full Text Available BACKGROUND: With the arrival of the postgenomic era, there is increasing interest in the discovery of biomarkers for the accurate diagnosis, prognosis, and early detection of cancer. Blood-borne cancer markers are favored by clinicians, because blood samples can be obtained and analyzed with relative ease. We have used a combined mining strategy based on an integrated cancer microarray platform, Oncomine, and the biomarker module of the Ingenuity Pathways Analysis (IPA program to identify potential blood-based markers for six common human cancer types. METHODOLOGY/PRINCIPAL FINDINGS: In the Oncomine platform, the genes overexpressed in cancer tissues relative to their corresponding normal tissues were filtered by Gene Ontology keywords, with the extracellular environment stipulated and a corrected Q value (false discovery rate cut-off implemented. The identified genes were imported to the IPA biomarker module to separate out those genes encoding putative secreted or cell-surface proteins as blood-borne (blood/serum/plasma cancer markers. The filtered potential indicators were ranked and prioritized according to normalized absolute Student t values. The retrieval of numerous marker genes that are already clinically useful or under active investigation confirmed the effectiveness of our mining strategy. To identify the biomarkers that are unique for each cancer type, the upregulated marker genes that are in common between each two tumor types across the six human tumors were also analyzed by the IPA biomarker comparison function. CONCLUSION/SIGNIFICANCE: The upregulated marker genes shared among the six cancer types may serve as a molecular tool to complement histopathologic examination, and the combination of the commonly upregulated and unique biomarkers may serve as differentiating markers for a specific cancer. This approach will be increasingly useful to discover diagnostic signatures as the mass of microarray data continues to grow in the

  18. Proteomic approaches to biomarker discovery in lung cancers by SELDI technology

    Institute of Scientific and Technical Information of China (English)

    肖雪媛; 卫秀平; 何大澄

    2003-01-01

    The purpose of the present work is to identify protein profiles that could be used to discover specific biomarkers in serum and discriminate lung cancer. Thirty serum samples from patients with lung cancer (15 cases of primary brochogenic carcinoma, 9 cases of metastasis lung cancer and 6 cases of lung cancer after chemotherapy) and twelve from healthy individuals were analyzed by SELDI (Surfaced Enhanced Laser Desorption/Ionization) technology. Anion-exchange columns were used to fractionate the sera with 6 designated pH washing solutions. Two types of protein chip arrays, IMAC-Cu and WCX2, were employed. Protein chips were examined in PBSII ProteinChip Reader (Ciphergen Biosystems Inc.) and the resulting profiles between cancer and normal were analyzed with Biomarker Wizard System. In total, 15 potential lung cancer biomarkers, of which 6 were up-regulated and 9 were down-regulated, were discovered in the serum samples from patients with lung cancer. 5 of 15 these biomarkers were able to be detected on both WCX2 and IMAC-Cu protein chips. The sensitivities provided by the individual markers range from 44.8% to 93.1% and the specificities were 85.0%-94.4%. Our results suggest that serum is a capable resource for detection of lung cancer with specific biomarkers. Moreover, protein chip array system was shown to be a useful tool for identification, as well as detection of disease biomarkers in sera.

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

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    Nodin Björn

    2012-01-01

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

  20. 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

  1. Comprehensive serum profiling for the discovery of epithelial ovarian cancer biomarkers.

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    Ping Yip

    Full Text Available FDA-cleared ovarian cancer biomarkers are limited to CA-125 and HE4 for monitoring and recurrence and OVA1, a multivariate panel consisting of CA-125 and four additional biomarkers, for referring patients to a specialist. Due to relatively poor performance of these tests, more accurate and broadly applicable biomarkers are needed. We evaluated the dysregulation of 259 candidate cancer markers in serum samples from 499 patients. Sera were collected prospectively at 11 monitored sites under a single well-defined protocol. All stages of ovarian cancer and common benign gynecological conditions were represented. To ensure consistency and comparability of biomarker comparisons, all measurements were performed on a single platform, at a single site, using a panel of rigorously calibrated, qualified, high-throughput, multiplexed immunoassays and all analyses were conducted using the same software. Each marker was evaluated independently for its ability to differentiate ovarian cancer from benign conditions. A total of 175 markers were dysregulated in the cancer samples. HE4 (AUC=0.933 and CA-125 (AUC=0.907 were the most informative biomarkers, followed by IL-2 receptor α, α1-antitrypsin, C-reactive protein, YKL-40, cellular fibronectin, CA-72-4 and prostasin (AUC>0.800. To improve the discrimination between cancer and benign conditions, a simple multivariate combination of markers was explored using logistic regression. When combined into a single panel, the nine most informative individual biomarkers yielded an AUC value of 0.950, significantly higher than obtained when combining the markers in the OVA1 panel (AUC 0.912. Additionally, at a threshold sensitivity of 90%, the combination of the top 9 markers gave 88.9% specificity compared to 63.4% specificity for the OVA1 markers. Although a blinded validation study has not yet been performed, these results indicate that alternative biomarker combinations might lead to significant improvements in the

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

    KAUST Repository

    Kaur, Mandeep

    2011-09-19

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

  3. 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.

  4. Morph-X-Select: Morphology-based tissue aptamer selection for ovarian cancer biomarker discovery

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    Wang, Hongyu; Li, Xin; Volk, David E.; Lokesh, Ganesh L.-R.; Elizondo-Riojas, Miguel-Angel; Li, Li; Nick, Alpa M.; Sood, Anil K.; Rosenblatt, Kevin P.; Gorenstein, David G.

    2016-01-01

    High affinity aptamer-based biomarker discovery has the advantage of simultaneously discovering an aptamer affinity reagent and its target biomarker protein. Here, we demonstrate a morphology-based tissue aptamer selection method that enables us to use tissue sections from individual patients and identify high-affinity aptamers and their associated target proteins in a systematic and accurate way. We created a combinatorial DNA aptamer library that has been modified with thiophosphate substitutions of the phosphate ester backbone at selected 5′dA positions for enhanced nuclease resistance and targeting. Based on morphological assessment, we used image-directed laser microdissection (LMD) to dissect regions of interest bound with the thioaptamer (TA) library and further identified target proteins for the selected TAs. We have successfully identified and characterized the lead candidate TA, V5, as a vimentin-specific sequence that has shown specific binding to tumor vasculature of human ovarian tissue and human microvascular endothelial cells. This new Morph-X-Select method allows us to select high-affinity aptamers and their associated target proteins in a specific and accurate way, and could be used for personalized biomarker discovery to improve medical decision-making and to facilitate the development of targeted therapies to achieve more favorable outcomes. PMID:27839510

  5. 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.

  6. The role of quantitative mass spectrometry in the discovery of pancreatic cancer biomarkers for translational science.

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    Ansari, Daniel; Aronsson, Linus; Sasor, Agata; Welinder, Charlotte; Rezeli, Melinda; Marko-Varga, György; Andersson, Roland

    2014-04-05

    In the post-genomic era, it has become evident that genetic changes alone are not sufficient to understand most disease processes including pancreatic cancer. Genome sequencing has revealed a complex set of genetic alterations in pancreatic cancer such as point mutations, chromosomal losses, gene amplifications and telomere shortening that drive cancerous growth through specific signaling pathways. Proteome-based approaches are important complements to genomic data and provide crucial information of the target driver molecules and their post-translational modifications. By applying quantitative mass spectrometry, this is an alternative way to identify biomarkers for early diagnosis and personalized medicine. We review the current quantitative mass spectrometric technologies and analyses that have been developed and applied in the last decade in the context of pancreatic cancer. Examples of candidate biomarkers that have been identified from these pancreas studies include among others, asporin, CD9, CXC chemokine ligand 7, fibronectin 1, galectin-1, gelsolin, intercellular adhesion molecule 1, insulin-like growth factor binding protein 2, metalloproteinase inhibitor 1, stromal cell derived factor 4, and transforming growth factor beta-induced protein. Many of these proteins are involved in various steps in pancreatic tumor progression including cell proliferation, adhesion, migration, invasion, metastasis, immune response and angiogenesis. These new protein candidates may provide essential information for the development of protein diagnostics and targeted therapies. We further argue that new strategies must be advanced and established for the integration of proteomic, transcriptomic and genomic data, in order to enhance biomarker translation. Large scale studies with meta data processing will pave the way for novel and unexpected correlations within pancreatic cancer, that will benefit the patient, with targeted treatment.

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

    Directory of Open Access Journals (Sweden)

    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

  8. Lectin chromatography/mass spectrometry discovery workflow identifies putative biomarkers of aggressive breast cancers.

    Science.gov (United States)

    Drake, Penelope M; Schilling, Birgit; Niles, Richard K; Prakobphol, Akraporn; Li, Bensheng; Jung, Kwanyoung; Cho, Wonryeon; Braten, Miles; Inerowicz, Halina D; Williams, Katherine; Albertolle, Matthew; Held, Jason M; Iacovides, Demetris; Sorensen, Dylan J; Griffith, Obi L; Johansen, Eric; Zawadzka, Anna M; Cusack, Michael P; Allen, Simon; Gormley, Matthew; Hall, Steven C; Witkowska, H Ewa; Gray, Joe W; Regnier, Fred; Gibson, Bradford W; Fisher, Susan J

    2012-04-06

    We used a lectin chromatography/MS-based approach to screen conditioned medium from a panel of luminal (less aggressive) and triple negative (more aggressive) breast cancer cell lines (n=5/subtype). The samples were fractionated using the lectins Aleuria aurantia (AAL) and Sambucus nigra agglutinin (SNA), which recognize fucose and sialic acid, respectively. The bound fractions were enzymatically N-deglycosylated and analyzed by LC-MS/MS. In total, we identified 533 glycoproteins, ∼90% of which were components of the cell surface or extracellular matrix. We observed 1011 glycosites, 100 of which were solely detected in ≥3 triple negative lines. Statistical analyses suggested that a number of these glycosites were triple negative-specific and thus potential biomarkers for this tumor subtype. An analysis of RNaseq data revealed that approximately half of the mRNAs encoding the protein scaffolds that carried potential biomarker glycosites were up-regulated in triple negative vs luminal cell lines, and that a number of genes encoding fucosyl- or sialyltransferases were differentially expressed between the two subtypes, suggesting that alterations in glycosylation may also drive candidate identification. Notably, the glycoproteins from which these putative biomarker candidates were derived are involved in cancer-related processes. Thus, they may represent novel therapeutic targets for this aggressive tumor subtype.

  9. Compact cancer biomarkers discovery using a swarm intelligence feature selection algorithm.

    Science.gov (United States)

    Martinez, Emmanuel; Alvarez, Mario Moises; Trevino, Victor

    2010-08-01

    Biomarker discovery is a typical application from functional genomics. Due to the large number of genes studied simultaneously in microarray data, feature selection is a key step. Swarm intelligence has emerged as a solution for the feature selection problem. However, swarm intelligence settings for feature selection fail to select small features subsets. We have proposed a swarm intelligence feature selection algorithm based on the initialization and update of only a subset of particles in the swarm. In this study, we tested our algorithm in 11 microarray datasets for brain, leukemia, lung, prostate, and others. We show that the proposed swarm intelligence algorithm successfully increase the classification accuracy and decrease the number of selected features compared to other swarm intelligence methods.

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

    Directory of Open Access Journals (Sweden)

    Lazar Iulia M

    2009-03-01

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

  11. Glycoscience aids in biomarker discovery

    Directory of Open Access Journals (Sweden)

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

    2012-06-01

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

  12. Blood biomarker levels to aid discovery of cancer-related single-nucleotide polymorphisms: kallikreins and prostate cancer.

    Science.gov (United States)

    Klein, Robert J; Halldén, Christer; Cronin, Angel M; Ploner, Alexander; Wiklund, Fredrik; Bjartell, Anders S; Stattin, Pär; Xu, Jianfeng; Scardino, Peter T; Offit, Kenneth; Vickers, Andrew J; Grönberg, Henrik; Lilja, Hans

    2010-05-01

    Polymorphisms associated with prostate cancer include those in three genes encoding major secretory products of the prostate: KLK2 (encoding kallikrein-related peptidase 2; hK2), KLK3 (encoding prostate-specific antigen; PSA), and MSMB (encoding beta-microseminoprotein). PSA and hK2, members of the kallikrein family, are elevated in sera of men with prostate cancer. In a comprehensive analysis that included sequencing of all coding, flanking, and 2 kb of putative promoter regions of all 15 kallikrein (KLK) genes spanning approximately 280 kb on chromosome 19q, we identified novel single-nucleotide polymorphisms (SNP) and genotyped 104 SNPs in 1,419 cancer cases and 736 controls in Cancer Prostate in Sweden 1, with independent replication in 1,267 cases and 901 controls in Cancer Prostate in Sweden 2. This verified prior associations of SNPs in KLK2 and in MSMB (but not in KLK3) with prostate cancer. Twelve SNPs in KLK2 and KLK3 were associated with levels of PSA forms or hK2 in plasma of control subjects. Based on our comprehensive approach, this is likely to represent all common KLK variants associated with these phenotypes. A T allele at rs198977 in KLK2 was associated with increased cancer risk and a striking decrease of hK2 levels in blood. We also found a strong interaction between rs198977 genotype and hK2 levels in blood in predicting cancer risk. Based on this strong association, we developed a model for predicting prostate cancer risk from standard biomarkers, rs198977 genotype, and rs198977 x hK2 interaction; this model had greater accuracy than did biomarkers alone (area under the receiver operating characteristic curve, 0.874 versus 0.866), providing proof in principle to clinical application for our findings.

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

    Directory of Open Access Journals (Sweden)

    Kooren Joel A

    2011-09-01

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

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions...... targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate...... cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal...

  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. Cellular Proteases as Cancer Biomarkers: A Review

    Directory of Open Access Journals (Sweden)

    Sarah R. Röthlisberger

    2010-12-01

    Full Text Available Over the past few decades a variety of biomolecules have been proposed as diagnostic biomarkers and predictors of severity for transmissible and nontransmissible diseases. Studies in a range of cancers have revealed many biomarkers with great potential in cancer diagnosis, in establishing tumor stage, progression, and response to therapies; such as the Kallikrein and Metalloproteinase families. Traditionally blood (serum and tissue have been the main biological sources of biomarker discovery, but in the past decade urine has emerged as a promising source of cancer biomarkers. In this review we will focus on two large families, the Kallikrein family of serine proteases discovered in serum, and the Metalloproteinase family of zinc proteases discovered in urine, as potential cancer biomarkers.

  17. 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

  18. 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

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

    Directory of Open Access Journals (Sweden)

    Tong Zhang

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

  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. Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology.

    Science.gov (United States)

    Ogino, S; Lochhead, P; Giovannucci, E; Meyerhardt, J A; Fuchs, C S; Chan, A T

    2014-06-05

    Regular use of aspirin reduces incidence and mortality of various cancers, including colorectal cancer. Anticancer effect of aspirin represents one of the 'Provocative Questions' in cancer research. Experimental and clinical studies support a carcinogenic role for PTGS2 (cyclooxygenase-2), which is an important enzymatic mediator of inflammation, and a target of aspirin. Recent 'molecular pathological epidemiology' (MPE) research has shown that aspirin use is associated with better prognosis and clinical outcome in PIK3CA-mutated colorectal carcinoma, suggesting somatic PIK3CA mutation as a molecular biomarker that predicts response to aspirin therapy. The PI3K (phosphatidylinositol-4,5-bisphosphonate 3-kinase) enzyme has a pivotal role in the PI3K-AKT signaling pathway. Activating PIK3CA oncogene mutations are observed in various malignancies including breast cancer, ovarian cancer, brain tumor, hepatocellular carcinoma, lung cancer and colon cancer. The prevalence of PIK3CA mutations increases continuously from rectal to cecal cancers, supporting the 'colorectal continuum' paradigm, and an important interplay of gut microbiota and host immune/inflammatory reaction. MPE represents an interdisciplinary integrative science, conceptually defined as 'epidemiology of molecular heterogeneity of disease'. As exposome and interactome vary from person to person and influence disease process, each disease process is unique (the unique disease principle). Therefore, MPE concept and paradigm can extend to non-neoplastic diseases including diabetes mellitus, cardiovascular diseases, metabolic diseases, and so on. MPE research opportunities are currently limited by paucity of tumor molecular data in the existing large-scale population-based studies. However, genomic, epigenomic and molecular pathology testings (for example, analyses for microsatellite instability, MLH1 promoter CpG island methylation, and KRAS and BRAF mutations in colorectal tumors) are becoming routine

  2. Validation of New Cancer Biomarkers

    DEFF Research Database (Denmark)

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

    2015-01-01

    BACKGROUND: Biomarkers are playing increasingly important roles in the detection and management of patients with cancer. Despite an enormous number of publications on cancer biomarkers, few of these biomarkers are in widespread clinical use. CONTENT: In this review, we discuss the key steps...... in advancing a newly discovered cancer candidate biomarker from pilot studies to clinical application. Four main steps are necessary for a biomarker to reach the clinic: analytical validation of the biomarker assay, clinical validation of the biomarker test, demonstration of clinical value from performance...... of the biomarker test, and regulatory approval. In addition to these 4 steps, all biomarker studies should be reported in a detailed and transparent manner, using previously published checklists and guidelines. Finally, all biomarker studies relating to demonstration of clinical value should be registered before...

  3. 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.

  4. 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.

  5. As if Biomarker Discovery Isn't Hard Enough: the Consequences of Poorly Characterized Reagents

    Energy Technology Data Exchange (ETDEWEB)

    Rodland, Karin D.

    2014-02-04

    The advent of high throughput omic technologies over the past two decades has driven a vast expansion in the search for clinical biomarkers, as manifested by the plethora of publications on biomarker discovery (over 8,600) listed on PubMed since 2000. Unfortunately, the same time period has seen a relative dearth of clinically validated biomarkers that have received FDA approval; only 10 new cancer biomarkers have been approved by the FDA in the same time period [1].

  6. 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.

  7. Cancer Biomarkers | Division of Cancer Prevention

    Science.gov (United States)

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

  8. The Process Chain for Peptidomic Biomarker Discovery

    Directory of Open Access Journals (Sweden)

    Michael Schrader

    2006-01-01

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

  9. 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.

  10. 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.

  11. 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

  12. Auto-fluorescent intracellular sink - A novel Inherent biomarker for drug discovery in pancreatic cancer stem cells

    OpenAIRE

    Miranda Lorenzo, Irene

    2013-01-01

    Tesis doctoral inédita, leída en Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de lectura: 20/09/2013. Pancreatic adenocarcinoma (PDAC), the fourth leading cause of cancer-­‐ related death world-­‐wide, is a malignant neoplasm of the exocrine pancreas. It has been hypothesized that a subset of tumor cells with stem-­‐like properties, termed ...

  13. Colorectal cancer biomarker discovery and validation using LC-MS/MS-based proteomics in blood: truth or dare?

    Science.gov (United States)

    Reumer, Ank; Maes, Evelyne; Mertens, Inge; Cho, William C S; Landuyt, Bart; Valkenborg, Dirk; Schoofs, Liliane; Baggerman, Geert

    2014-08-01

    Globally, colorectal cancer (CRC) is the third most common malignant neoplasm. However, highly sensitive, specific, noninvasive tests that allow CRC diagnosis at an early stage are still needed. As circulatory blood reflects the physiological status of an individual and/or the disease status for several disorders, efforts have been undertaken to identify candidate diagnostic CRC markers in plasma and serum. In this review, the challenges, bottlenecks and promising properties of mass spectrometry (MS)-based proteomics in blood are discussed. More specifically, important aspects in clinical design, sample retrieval, sample preparation, and MS analysis are presented. The recent developments in targeted MS approaches in plasma or serum are highlighted as well.

  14. Coherent pipeline for biomarker discovery using mass spectrometry and bioinformatics

    Directory of Open Access Journals (Sweden)

    Al-Shahib Ali

    2010-08-01

    Full Text Available Abstract Background Robust biomarkers are needed to improve microbial identification and diagnostics. Proteomics methods based on mass spectrometry can be used for the discovery of novel biomarkers through their high sensitivity and specificity. However, there has been a lack of a coherent pipeline connecting biomarker discovery with established approaches for evaluation and validation. We propose such a pipeline that uses in silico methods for refined biomarker discovery and confirmation. Results The pipeline has four main stages: Sample preparation, mass spectrometry analysis, database searching and biomarker validation. Using the pathogen Clostridium botulinum as a model, we show that the robustness of candidate biomarkers increases with each stage of the pipeline. This is enhanced by the concordance shown between various database search algorithms for peptide identification. Further validation was done by focusing on the peptides that are unique to C. botulinum strains and absent in phylogenetically related Clostridium species. From a list of 143 peptides, 8 candidate biomarkers were reliably identified as conserved across C. botulinum strains. To avoid discarding other unique peptides, a confidence scale has been implemented in the pipeline giving priority to unique peptides that are identified by a union of algorithms. Conclusions This study demonstrates that implementing a coherent pipeline which includes intensive bioinformatics validation steps is vital for discovery of robust biomarkers. It also emphasises the importance of proteomics based methods in biomarker discovery.

  15. 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...

  16. Proteomics in Discovery of Hepatocellular Carcinoma Biomarkers

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

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

  17. Clinical states model for biomarkers in bladder cancer.

    Science.gov (United States)

    Apolo, Andrea B; Milowsky, Matthew; Bajorin, Dean F

    2009-09-01

    Bladder cancer is a significant healthcare problem in the USA, with a high recurrence rate, the need for expensive continuous surveillance and limited treatment options for patients with advanced disease. Research has contributed to an understanding of the molecular pathways involved in the development and progression of bladder cancer, and that understanding has led to the discovery of potentially diagnostic, predictive and prognostic biomarkers. In this review, a clinical states model of bladder cancer is introduced and integrated into a paradigm for biomarker development. Biomarkers are systematically incorporated with predefined end points to aid in clinical management.

  18. 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

  19. 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.

  20. Maximizing biomarker discovery by minimizing gene signatures

    Directory of Open Access Journals (Sweden)

    Chang Chang

    2011-12-01

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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

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

    NARCIS (Netherlands)

    Aye, T.T.

    2010-01-01

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

  7. 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.

  8. Galectins as Cancer Biomarkers

    Science.gov (United States)

    Balan, Vitaly; Nangia-Makker, Pratima; Raz, Avraham

    2010-01-01

    Galectins are a group of proteins that bind β-galactosides through evolutionarily conserved sequence elements of the carbohydrate recognition domain (CRD). Proteins similar to galectins can be found in very primitive animals such as sponges. Each galectin has an individual carbohydrate binding preference and can be found in cytoplasm as well as in the nucleus. They also can be secreted through non-classical pathways and function extra-cellularly. Experimental and clinical data demonstrate a correlation between galectin expression and tumor progression and metastasis, and therefore, galectins have the potential to serve as reliable tumor markers. In this review, we describe the expression and role of galectins in different cancers and their clinical applications for diagnostic use. PMID:23658855

  9. Galectins as Cancer Biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Balan, Vitaly; Nangia-Makker, Pratima; Raz, Avraham, E-mail: raza@karmanos.org [Karmanos Cancer Institute, Wayne State University, 110 E. Warren Avenue, Detroit, MI 48201 (United States)

    2010-04-20

    Galectins are a group of proteins that bind β-galactosides through evolutionarily conserved sequence elements of the carbohydrate recognition domain (CRD). Proteins similar to galectins can be found in very primitive animals such as sponges. Each galectin has an individual carbohydrate binding preference and can be found in cytoplasm as well as in the nucleus. They also can be secreted through non-classical pathways and function extra-cellularly. Experimental and clinical data demonstrate a correlation between galectin expression and tumor progression and metastasis, and therefore, galectins have the potential to serve as reliable tumor markers. In this review, we describe the expression and role of galectins in different cancers and their clinical applications for diagnostic use.

  10. Galectins as Cancer Biomarkers

    Directory of Open Access Journals (Sweden)

    Vitaly Balan

    2010-04-01

    Full Text Available Galectins are a group of proteins that bind β-galactosides through evolutionarily conserved sequence elements of the carbohydrate recognition domain (CRD. Proteins similar to galectins can be found in very primitive animals such as sponges. Each galectin has an individual carbohydrate binding preference and can be found in cytoplasm as well as in the nucleus. They also can be secreted through non-classical pathways and function extra-cellularly. Experimental and clinical data demonstrate a correlation between galectin expression and tumor progression and metastasis, and therefore, galectins have the potential to serve as reliable tumor markers. In this review, we describe the expression and role of galectins in different cancers and their clinical applications for diagnostic use.

  11. 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.

  12. 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

  13. 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

  14. 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

  15. 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.

  16. Quantitative imaging as cancer biomarker

    Science.gov (United States)

    Mankoff, David A.

    2015-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Larry Gold

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

  18. 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.

  19. Data mining of spectroscopic data for biomarker discovery.

    Science.gov (United States)

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

    2001-05-01

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

  20. 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.

  1. Molecular biology tools: proteomics techniques in biomarker discovery.

    Science.gov (United States)

    Lottspeich, Friedrich; Kellermann, Josef; Keidel, Eva-Maria

    2010-01-01

    Despite worldwide efforts biomarker discovery by plasma proteomics was not successful so far. Several reasons for this failure are obvious. Mainly, proteome diversity is remarkable between different individuals and is caused by genetic, environmental and life style parameters. To recognize disease related proteins that could serve as potential biomarkers is only feasible by investigating a non realizable large number of patients. Furthermore, plasma proteomics comprises enormous technical hurdles for quantitative analysis. High reproducibility of blood sampling in clinical routine is hard to achieve. Quantitative proteome analysis has to struggle with the complexity of millions of protein species comprising typical plasma proteins, cellular leakage proteins and antibodies and concentration differences of more than 1011 between high and low abundant proteins. Therefore, no successful quantitative and comprehensive plasma proteome analysis is reported so far. A novel proteomics strategy is proposed for biomarker discovery in plasma. Instead of comparing the plasma proteome of different individuals it is recommended to analyze the proteomes of different time points of a single individual during the development of a disease. This strategy is realized by the use of plasma of the Bavarian Red Cross Blood Bank, were three million samples are stored under standardized conditions. To achieve reliable data the isotope coded protein labelling proteomics technology was used.

  2. 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.

  3. 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

  4. Cancer and molecular biomarkers of phase 2

    DEFF Research Database (Denmark)

    Dalhoff, Kim; Enghusen Poulsen, Henrik

    2005-01-01

    as molecular genetic biomarkers of risk. GSTM(my)1 has been associated with an increased risk of colorectal cancer, lung cancer, and bladder cancer and GSTP(pi)1 with prostate cancer. UGT1A1*28 and *37 are both associated with an increased risk of breast cancer as is SULT1A1*2. The presence of UGT1A1...

  5. Using MALDI-IMS and MRM to stablish a pipeline for discovery and validation of tumor neovasculature biomarker candidates. — EDRN Public Portal

    Science.gov (United States)

    In an effort to circumvent the limitations associated with biomarker discovery workflows involving cell lines and cell cultures, histology-directed MALDI protein profiling and imaging mass spectrometry will be used for identification of vascular endothelial biomarkers suitable for early prostate cancer detection by CEUS targeted molecular imaging

  6. Lung cancer biomarkers in exhaled breath.

    Science.gov (United States)

    Amann, Anton; Corradi, Massimo; Mazzone, Peter; Mutti, Antonio

    2011-03-01

    Lung cancer is the leading cause of cancer-related mortality worldwide. Methods for early detection of lung cancer, such as computerized tomography scanning technology, often discover a large number of small lung nodules, posing a new problem to radiologists and chest physicians. The vast majority of these nodules will be benign, but there is currently no easy way to determine which nodules represent very early lung cancer. Adjuvant testing with PET imaging and nonsurgical biopsies has a low yield for these small indeterminate nodules, carries potential morbidity and is costly. Indeed, purely morphological criteria seem to be insufficient for distinguishing lung cancer from benign nodules at early stages with sufficient confidence, therefore false positives undergoing surgical resection frequently occur. A molecular approach to the diagnosis of lung cancer through the analysis of exhaled breath could greatly improve the specificity of imaging procedures. A biomarker-driven approach to signs or symptoms possibly due to lung cancer would represent a complementary tool aimed at ruling out (with known error probability) rather than diagnosing lung cancer. Volatile and nonvolatile components of the breath are being studied as biomarkers of lung cancer. Breath testing is noninvasive and potentially inexpensive. There is promise that an accurate lung cancer breath biomarker, capable of being applied clinically, will be developed in the near future. In this article, we summarize some of the rationale for breath biomarker development, review the published literature in this field and provide thoughts regarding future directions.

  7. Novel biomarkers for cancer detection and prognostication

    NARCIS (Netherlands)

    Mehra, N.

    2007-01-01

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

  8. Targeted discovery and validation of plasma biomarkers of Parkinson's disease.

    Science.gov (United States)

    Pan, Catherine; Zhou, Yong; Dator, Romel; Ginghina, Carmen; Zhao, Yanchun; Movius, James; Peskind, Elaine; Zabetian, Cyrus P; Quinn, Joseph; Galasko, Douglas; Stewart, Tessandra; Shi, Min; Zhang, Jing

    2014-11-07

    Despite extensive research, an unmet need remains for protein biomarkers of Parkinson's disease (PD) in peripheral body fluids, especially blood, which is easily accessible clinically. The discovery of such biomarkers is challenging, however, due to the enormous complexity and huge dynamic range of human blood proteins, which are derived from nearly all organ systems, with those originating specifically from the central nervous system (CNS) being exceptionally low in abundance. In this investigation of a relatively large cohort (∼300 subjects), selected reaction monitoring (SRM) assays (a targeted approach) were used to probe plasma peptides derived from glycoproteins previously found to be altered in the CNS based on PD diagnosis or severity. Next, the detected peptides were interrogated for their diagnostic sensitivity and specificity as well as the correlation with PD severity, as determined by the Unified Parkinson's Disease Rating Scale (UPDRS). The results revealed that 12 of the 50 candidate glycopeptides were reliably and consistently identified in plasma samples, with three of them displaying significant differences among diagnostic groups. A combination of four peptides (derived from PRNP, HSPG2, MEGF8, and NCAM1) provided an overall area under curve (AUC) of 0.753 (sensitivity: 90.4%; specificity: 50.0%). Additionally, combining two peptides (derived from MEGF8 and ICAM1) yielded significant correlation with PD severity, that is, UPDRS (r = 0.293, p = 0.004). The significance of these results is at least two-fold: (1) it is possible to use a targeted approach to identify otherwise very difficult to detect CNS related biomarkers in peripheral blood and (2) the novel biomarkers, if validated in independent cohorts, can be employed to assist with clinical diagnosis of PD as well as monitoring disease progression.

  9. Random glycopeptide bead libraries for seromic biomarker discovery

    DEFF Research Database (Denmark)

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

    2010-01-01

    Identification of disease-specific biomarkers is important to address early diagnosis and management of disease. Aberrant post-translational modifications (PTM) of proteins such as O-glycosylations (O-PTMs) are emerging as triggers of autoantibodies that can serve as sensitive biomarkers. Here we...... have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I(2)/NaBH(4) and TFA......) for release of glycopeptides and sequence determination by ESI-Orbitrap-MS(n). As proof-of-principle, tumor -specific glycopeptide reporter epitopes were built-in into the libraries and were detected by tumor-specific monoclonal antibodies and autoantibodies from cancer patients. Sequenced and identified...

  10. 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.

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection...... inhibitor. Through the analysis of tumour tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumour-derived genomic data with personalised tumour-derived shRNA and high throughput si......, reducing ineffective therapy in drug resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate...

  12. 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.

  13. 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.

  14. Novel automated biomarker discovery work flow for urinary peptidomics

    DEFF Research Database (Denmark)

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

    2009-01-01

    eluted peptides using MALDI-TOF, Fourier transform ion cyclotron resonance, and liquid chromatography-iontrap mass spectrometry. We determined qualitative and quantitative reproducibility of the system and robustness of the method using BSA digests and urine samples, and we used a selected set of urine...... numbers of urine samples, resulting in a broad spectrum of native peptides, as a tool to be used for biomarker discovery. METHODS: Peptide samples were trapped, desalted, pH-normalized, and fractionated on a miniaturized automatic reverse-phase strong cation exchange (RP-SCX) cartridge system. We analyzed...... samples from Schistosoma haematobium-infected individuals to evaluate clinical applicability. RESULTS: The automated RP-SCX sample cleanup and fractionation system exhibits a high qualitative and quantitative reproducibility, with both BSA standards and urine samples. Because of the relatively high...

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    and utilization of such a resource is an important step in the development of blood-based biomarker tests for colorectal cancer.Methods: We have created a subject data and biological sample resource, Endoscopy II, which is based on 4698 individuals referred for diagnostic colonoscopy in Denmark between May 2010...

  16. Novel avenues of drug discovery and biomarkers for diabetes mellitus.

    Science.gov (United States)

    Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Hou, Jinling

    2011-02-01

    Globally, developed nations spend a significant amount of their resources on health care initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes 16% of its gross domestic product to health care, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase life span with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus becomes increasingly critical given that the number of diabetic people will increase exponentially over the next 20 years. This article discusses the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in diabetes mellitus for new treatment strategies. Pathways that involve wingless, β-nicotinamide adenine dinucleotide (NAD(+)) precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during diabetes mellitus and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for diabetes mellitus to provide focused clinical care with limited or absent long-term complications.

  17. 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.

  18. Genetic and Epigenetic Biomarkers for Recurrent Prostate Cancer After Radiotherapy

    Science.gov (United States)

    2015-07-01

    Award Number: W81XWH-12-1-0113 TITLE: Genetic and epigenetic biomarkers for recurrent prostate cancer after radiotherapy PRINCIPAL INVESTIGATOR...Beadchip microarray, high density beadchip, for this study. This array includes 485,577 CpG sites and covers CpGs in 99% of genes and 96% of CpG ...differentially methylated CpG sites in 17 genes between recurrent and non-recurrent tumor tissues, with a false discovery rate (FDR) [12] q-value less than

  19. Current early diagnostic biomarkers of prostate cancer

    Directory of Open Access Journals (Sweden)

    Min Qu

    2014-08-01

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

  20. Biomarkers for Basal-like Breast Cancer

    OpenAIRE

    Choo, Jennifer R.; Torsten O. Nielsen

    2010-01-01

    Initially recognized through microarray-based gene expression profiling, basal-like breast cancer, for which we lack effective targeted therapies, is an aggressive form of carcinoma with a predilection for younger women. With some success, immunohistochemical studies have attempted to reproduce the expression profile classification of breast cancer through identification of subtype-specific biomarkers. This review aims to present an in depth summary and analysis of the current status of basal...

  1. Lung cancer biomarkers: State of the art

    Directory of Open Access Journals (Sweden)

    Sangeetha Subramaniam

    2013-01-01

    Full Text Available Lung cancer is one of the deadliest cancers worldwide, with the highest incidence and mortality amongst all cancers. While the prognosis of lung cancer is generally grim, with 5-year survival rates of only 15%, there is hope, and evidence, that early detection of lung cancer can reduce mortality. Today, only computed tomography screening has shown to lead to early detection and reduction in mortality, but is limited by being anatomic in nature, unable to differentiate between inflammatory and neoplastic pathways, and therefore, susceptible to false positives. There is increasing interest in biomarkers for lung cancer, especially those that predict metastatic risk. Some biomarkers like DNA mutations and epigenetic changes potentially require tissue from the at-risk site; some like serum proteins and miRNAs are minimally invasive, but may not be specific to the lung. In comparison, emerging biomarkers from exhaled breath, like volatile organic compounds (VOC, and exhaled breath condensate, e.g., small molecules and nucleic acids, have the potential to combine the best of both. This mini review is intended to provide an overview of the field, briefly discussing the potential of what is known and highlighting the exciting recent developments, particularly with miRNAs and VOCs.

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

    Directory of Open Access Journals (Sweden)

    Joy eGuingab-Cagmat

    2013-05-01

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

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Vilém Guryča

    2014-03-01

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

  5. Disease Classification and Biomarker Discovery Using ECG Data

    Directory of Open Access Journals (Sweden)

    Rong Huang

    2015-01-01

    Full Text Available In the recent decade, disease classification and biomarker discovery have become increasingly important in modern biological and medical research. ECGs are comparatively low-cost and noninvasive in screening and diagnosing heart diseases. With the development of personal ECG monitors, large amounts of ECGs are recorded and stored; therefore, fast and efficient algorithms are called for to analyze the data and make diagnosis. In this paper, an efficient and easy-to-interpret procedure of cardiac disease classification is developed through novel feature extraction methods and comparison of classifiers. Motivated by the observation that the distributions of various measures on ECGs of the diseased group are often skewed, heavy-tailed, or multimodal, we characterize the distributions by sample quantiles which outperform sample means. Three classifiers are compared in application both to all features and to dimension-reduced features by PCA: stepwise discriminant analysis (SDA, SVM, and LASSO logistic regression. It is found that SDA applied to dimension-reduced features by PCA is the most stable and effective procedure, with sensitivity, specificity, and accuracy being 89.68%, 84.62%, and 88.52%, respectively.

  6. Discovery and validation of prostate cancer biomarkers

    NARCIS (Netherlands)

    F.H. Jansen (Flip)

    2013-01-01

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

  7. Current Status of Biomarkers for Prostate Cancer

    Directory of Open Access Journals (Sweden)

    Vicki M. Velonas

    2013-05-01

    Full Text Available Prostate cancer (PCa is a leading cause of cancer-related death of men globally. Since its introduction, there has been intense debate as to the effectiveness of the prostate specific antigen (PSA test as a screening tool for PCa. It is now evident that the PSA test produces unacceptably high rates of false positive results and is not prognostic. Here we review the current status of molecular biomarkers that promise to be prognostic and that might inform individual patient management. It highlights current efforts to identify biomarkers obtained by minimally invasive methods and discusses current knowledge with regard to gene fusions, mRNA and microRNAs, immunology, and cancer-associated microparticles.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-12-13

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

  9. 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.

  10. Urinary biomarkers for prostate cancer: a review

    Institute of Scientific and Technical Information of China (English)

    Daphne Hessels; Jack A Schalken

    2013-01-01

    Although the routine use of serum prostate-specific antigen (PSA) testing has undoubtedly increased prostate cancer (PCa) detection,one of its main drawbacks is its lack of specificity.As a consequence,many men undergo unnecessary biopsies or treatments for indolent tumours.PCa-specific markers are needed for the early detection of the disease and the prediction of aggressiveness of a prostate tumour.Since PCa is a heterogeneous disease,a panel of tumour markers is fundamental for a more precise diagnosis.Several biomarkers are promising due to their specificity for the disease in tissue.However,tissue is unsuitable as a possible screening tool.Since urine can be easily obtained in a non-invasive manner,it is a promising substrate for biomarker testing.This article reviews the biomarkers for the non-invasive testing of PCa in urine.

  11. Imaging biomarker roadmap for cancer studies

    Science.gov (United States)

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

    2017-01-01

    Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing ‘translational gaps’ through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored ‘roadmap’. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use. PMID:27725679

  12. 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

  13. Discovery Radiomics for Computed Tomography Cancer Detection

    OpenAIRE

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

    2015-01-01

    Objective: Lung cancer is the leading cause for cancer related deaths. As such, there is an urgent need for a streamlined process that can allow radiologists to provide diagnosis with greater efficiency and accuracy. A powerful tool to do this is radiomics. Method: In this study, we take the idea of radiomics one step further by introducing the concept of discovery radiomics for lung cancer detection using CT imaging data. Rather than using pre-defined, hand-engineered feature models as with ...

  14. 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

  15. 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...

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

    Science.gov (United States)

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

    2017-01-01

    Reviews on circulating biomarkers in breast cancer usually focus on one single biomarker or a selective group of biomarkers. An overview summarizing the discovery and evaluation of all blood-based biomarkers in metastatic breast cancer is lacking. This systematic review aims to identify the available evidence of known blood-based biomarkers in metastatic breast cancer, regarding their clinical utility and state-of-the-art position in the validation process. The initial search yielded 1078 original studies, of which 420 were assessed for eligibility. A total of 320 studies were included in the final synthesis. A Development, Evaluation and Application Chart (DEAC) of all biomarkers was developed. Most studies focus on identifying new biomarkers and search for relations between these biomarkers and traditional molecular characteristics. Biomarkers are usually investigated in only one study (68.8%). Only 9.8% of all biomarkers was investigated in more than five studies. Circulating tumor cells, gene expression within tumor cells and the concentration of secreted proteins are the most frequently investigated biomarkers in liquid biopsies. However, there is a lack of studies focusing on identifying the clinical utility of these biomarkers, by which the additional value still seems to be limited according to the investigated evidence. PMID:28208771

  17. 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

  18. 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.

  19. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  20. Identifying module biomarkers from gastric cancer by differential correlation network

    Directory of Open Access Journals (Sweden)

    Liu X

    2016-09-01

    Full Text Available Xiaoping Liu,1–3,* Xiao Chang1,3,* 1College of Statistics and Applied Mathematics, Anhui University of Finance and Economics, Bengbu, Anhui Province, People’s Republic of China; 2Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, People’s Republic of China; 3Collaborative Research Center for Innovative Mathematical Modeling, Institute of Industrial Science, University of Tokyo, Tokyo, Japan *These authors contributed equally to this work Abstract: Gastric cancer (stomach cancer is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. Keywords: biomarkers, gastric cancer, stomach cancer, differential network

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

    Science.gov (United States)

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

    2013-02-01

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

  3. 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.

  4. 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.

  5. Discovery of biomarkers for oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Wang, Ningli; Wei, Jianteng; Liu, Yewei; Pei, Dong; Hu, Qingping; Wang, Yu; Di, Duolong

    2016-07-01

    Oxidative stress has a close relationship with various pathologic physiology phenomena and the potential biomarkers of oxidative stress may provide evidence for clinical diagnosis or disease prevention. Metabolomics was employed to identify the potential biomarkers of oxidative stress. High-performance liquid chromatography-diode array detector, mass spectrometry and partial least squares discriminate analysis were used in this study. The 10, 15 and 13 metabolites were considered to discriminate the model group, vitamin E-treated group and l-glutathione-treated group, respectively. Some of them have been identified, namely, malic acid, vitamin C, reduced glutathione and tryptophan. Identification of other potential biomarkers should be conducted and their physiological significance also needs to be elaborated.

  6. 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...

  7. 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.

  8. Biomarkers for predicting complete debulking in ovarian cancer

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  9. Protein Biomarkers for the Early Detection of Breast Cancer

    Directory of Open Access Journals (Sweden)

    David E. Misek

    2011-01-01

    Full Text Available Advances in breast cancer control will be greatly aided by early detection so as to diagnose and treat breast cancer in its preinvasive state prior to metastasis. For breast cancer, the second leading cause of cancer-related death among women in the United States, early detection does allow for increased treatment options, including surgical resection, with a corresponding better patient response. Unfortunately, however, many patients' tumors are diagnosed following metastasis, thus making it more difficult to successfully treat the malignancy. There are, at present, no existing validated plasma/serum biomarkers for breast cancer. Only a few biomarkers (such as HER-2/neu, estrogen receptor, and progesterone receptor have utility for diagnosis and prognosis. Thus, there is a great need for new biomarkers for breast cancer. This paper will focus on the identification of new serum protein biomarkers with utility for the early detection of breast cancer.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

    OBJECTIVE: To present an update of the European Group on Tumor Markers guidelines for serum markers in epithelial ovarian cancer. METHODS: Systematic literature survey from 2008 to 2013. The articles were evaluated by level of evidence and strength of recommendation. RESULTS: Because of its low...... 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...

  15. 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

  16. 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

  17. 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....

  18. Biomarkers in the Detection of Prostate Cancer in African Americans

    Science.gov (United States)

    2015-09-01

    establish ELISA and multiplex immunoassays using samples of serum which are less than 1 year old. The ELISA will focus on FABP5. The multiplex immunoassay ...prostate as “suspicious” for prostate cancer and molecular prostate cancer field effects. September 2015 16. Book Chapter in Press Burke HB , Grizzle WE...Burke HB , Grizzle WE. Clinical Validation ofMolecular Biomarkers in Translational Medicine in Biomarkers in Cancer Screening and Early Detection, Sudhir

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

    DEFF Research Database (Denmark)

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

    2016-01-01

    BACKGROUND: Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. METHODS...... AND RESULTS: 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 HFr.......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. CONCLUSION: CE-MS based urine proteome analysis served as a sensitive tool...

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

    Science.gov (United States)

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

    2016-06-02

    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 analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Endometrial cancer risk prediction including serum-based biomarkers

    DEFF Research Database (Denmark)

    Fortner, Renée T; Hüsing, Anika; Kühn, Tilman;

    2017-01-01

    Endometrial cancer risk prediction models including lifestyle, anthropometric, and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case......-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum...... concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines, and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at pdiscrimination was assessed using...

  7. 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

  8. Mapping ethical and social aspects of cancer biomarkers.

    Science.gov (United States)

    Blanchard, Anne

    2016-12-25

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

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

    Science.gov (United States)

    Kondo, Tadashi

    2014-05-01

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

  10. A flexible integration and visualisation system for biomarker discovery.

    Science.gov (United States)

    Gaylord, Mary; Calley, John; Qiang, Huahong; Su, Eric W; Liao, Birong

    2006-01-01

    Biological data have accumulated at an unprecedented pace as a result of improvements in molecular technologies. However, the translation of data into information, and subsequently into knowledge, requires the intricate interplay of data access, visualisation and interpretation. Biological data are complex and are organised either hierarchically or non-hierarchically. For non-hierarchically organised data, it is difficult to view relationships among biological facts. In addition, it is difficult to make changes in underlying data storage without affecting the visualisation interface. Here, we demonstrate a platform where non-hierarchically organised data can be visualised through the application of a customised hierarchy incorporating medical subject headings (MeSH) classifications. This platform gives users flexibility in updating and manipulation. It can also facilitate fresh scientific insight by highlighting biological impacts across different hierarchical branches. An example of the integration of biomarker information from the curated Proteome database using MeSH and the StarTree visualisation tool is presented.

  11. Aptamer-based detection of disease biomarkers in mouse models for chagas drug discovery.

    Directory of Open Access Journals (Sweden)

    Fernanda Fortes de Araujo

    2015-01-01

    Full Text Available Drug discovery initiatives, aimed at Chagas treatment, have been hampered by the lack of standardized drug screening protocols and the absence of simple pre-clinical assays to evaluate treatment efficacy in animal models. In this study, we used a simple Enzyme Linked Aptamer (ELA assay to detect T. cruzi biomarker in blood and validate murine drug discovery models of Chagas disease. In two mice models, Apt-29 ELA assay demonstrated that biomarker levels were significantly higher in the infected group compared to the control group, and upon Benznidazole treatment, their levels reduced. However, biomarker levels in the infected treated group did not reduce to those seen in the non-infected treated group, with 100% of the mice above the assay cutoff, suggesting that parasitemia was reduced but cure was not achieved. The ELA assay was capable of detecting circulating biomarkers in mice infected with various strains of T. cruzi parasites. Our results showed that the ELA assay could detect residual parasitemia in treated mice by providing an overall picture of the infection in the host. They suggest that the ELA assay can be used in drug discovery applications to assess treatment efficacy in-vivo.

  12. Aptamer-based detection of disease biomarkers in mouse models for chagas drug discovery.

    Science.gov (United States)

    de Araujo, Fernanda Fortes; Nagarkatti, Rana; Gupta, Charu; Marino, Ana Paula; Debrabant, Alain

    2015-01-01

    Drug discovery initiatives, aimed at Chagas treatment, have been hampered by the lack of standardized drug screening protocols and the absence of simple pre-clinical assays to evaluate treatment efficacy in animal models. In this study, we used a simple Enzyme Linked Aptamer (ELA) assay to detect T. cruzi biomarker in blood and validate murine drug discovery models of Chagas disease. In two mice models, Apt-29 ELA assay demonstrated that biomarker levels were significantly higher in the infected group compared to the control group, and upon Benznidazole treatment, their levels reduced. However, biomarker levels in the infected treated group did not reduce to those seen in the non-infected treated group, with 100% of the mice above the assay cutoff, suggesting that parasitemia was reduced but cure was not achieved. The ELA assay was capable of detecting circulating biomarkers in mice infected with various strains of T. cruzi parasites. Our results showed that the ELA assay could detect residual parasitemia in treated mice by providing an overall picture of the infection in the host. They suggest that the ELA assay can be used in drug discovery applications to assess treatment efficacy in-vivo.

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

    Science.gov (United States)

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

    2017-02-01

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

  14. Review:Proteomic technology for biomarker profiling in cancer: an update

    Institute of Scientific and Technical Information of China (English)

    ALAOUI-JAMALI Moulay A.; XU Ying-jie

    2006-01-01

    The progress in the understanding of cancer progression and early detection has been slow and frustrating due to the complex multifactorial nature and heterogeneity of the cancer syndrome. To date, no effective treatment is available for advanced cancers, which remain a major cause of morbidity and mortality. Clearly, there is urgent need to unravel novel biomarkers for early detection.Most of the functional information of the cancer-associated genes resides in the proteome. The later is an exceptionally complex biological system involving several proteins that function through posttranslational modifications and dynamic intermolecular collisions with partners. These protein complexes can be regulated by signals emanating from cancer cells, their surrounding tissue microenvironment, and/or from the host. Some proteins are secreted and/or cleaved into the extracellular milieu and may represent valuable serum biomarkers for diagnosis purpose. It is estimated that the cancer proteome may include over 1.5million proteins as a result of posttranslational processing and modifications. Such complexity clearly highlights the need for ultra-high resolution proteomic technology for robust quantitative protein measurements and data acquisition. This review is to update the current research efforts in high-resolution proteomic technology for discovery and monitoring cancer biomarkers.

  15. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were...... the relationships between data-blocks and their contribution to predictive models. Among many variable selection techniques, we compared Sparse PLSR and Jack-knife PLSR according to the stability of the variable selection and the predictive ability. Further we used cross model validation (CMV) for assessing...... the importance of selected variables by plotting selection frequencies and correlation loading plots of the variables. In addition, predictive ability was studied by comparing errors of cross validation and CMV. According to the results, Sparse PLSR outperformed Jack-knife PLSR under the conditions tested. Jack...

  16. Blood-Based Biomarkers of Early-Onset Breast Cancer

    Science.gov (United States)

    2015-10-01

    AWARD NUMBER: W81XWH-13-1-0214 TITLE: Blood -based biomarkers of early-onset breast cancer PRINCIPAL INVESTIGATOR: Nasim Ahmadiyeh...DATES COVERED 30 Sep 2014 - 29 Sep 2015 4. TITLE AND SUBTITLE Blood -based biomarkers of early-onset breast cancer 5a. CONTRACT NUMBER W81XWH-13-1...While the normal breast is the ideal tissue in which to study this phenomenon, gene expression profiling of blood lymphocytes has been successfully

  17. Statistical spectroscopic tools for biomarker discovery and systems medicine.

    Science.gov (United States)

    Robinette, Steven L; Lindon, John C; Nicholson, Jeremy K

    2013-06-04

    Metabolic profiling based on comparative, statistical analysis of NMR spectroscopic and mass spectrometric data from complex biological samples has contributed to increased understanding of the role of small molecules in affecting and indicating biological processes. To enable this research, the development of statistical spectroscopy has been marked by early beginnings in applying pattern recognition to nuclear magnetic resonance data and the introduction of statistical total correlation spectroscopy (STOCSY) as a tool for biomarker identification in the past decade. Extensions of statistical spectroscopy now compose a family of related tools used for compound identification, data preprocessing, and metabolic pathway analysis. In this Perspective, we review the theory and current state of research in statistical spectroscopy and discuss the growing applications of these tools to medicine and systems biology. We also provide perspectives on how recent institutional initiatives are providing new platforms for the development and application of statistical spectroscopy tools and driving the development of integrated "systems medicine" approaches in which clinical decision making is supported by statistical and computational analysis of metabolic, phenotypic, and physiological data.

  18. 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

    2016-11-01

    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 (prelevance of SHMT2 was validated on IHC data. The mitochondrial localization of SHMT2 protein was visualized on IHC staining. Independent and pooled analysis confirmed that SHMT2 expression was associated with breast cancer tumor aggressiveness (TNM staging and Elson grade) in a dose-dependent manner (pvalue 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.

  19. 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.

  20. Intact-protein analysis system for discovery of serum-based disease biomarkers.

    Science.gov (United States)

    Wang, Hong; Hanash, Samir

    2011-01-01

    Profiling of serum and plasma proteins has substantial relevance to the discovery of circulating disease biomarkers. However, the extreme complexity and vast dynamic range of protein abundance in serum and plasma present a formidable challenge for protein analysis. Thus, integration of multiple technologies is required to achieve high-resolution and high-sensitivity proteomic analysis of serum or plasma. In this chapter, we describe an orthogonal multidimensional intact-protein analysis system (IPAS) (Wang et al., Mol Cell Proteomics 4:618-625, 2005) coupled with protein tagging (Faca et al., J Proteome Res 5:2009-2018, 2006) to profile the serum and plasma proteomes quantitatively, which we have applied in our biomarker discovery studies (Katayama et al., Genome Med 1:47, 2009; Faca et al., PLoS Med 5:e123, 2008; Zhang et al. Genome Biol 9:R93, 2008).

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

    Science.gov (United States)

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

    2014-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Kirstin Mittelstrass

    2011-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Diederick Duijvesz

    Full Text Available BACKGROUND: 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, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery. 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. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS mode. Accurate Mass and Time (AMT tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry. RESULTS: Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant 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. CONCLUSIONS: Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.

  4. Clinical Advances in Molecular Biomarkers for Cancer Diagnosis and Therapy

    OpenAIRE

    Sarkar, Fazlul H.; Philip, Philip A.; Seema Sethi; Shadan Ali

    2013-01-01

    Cancer diagnosis is currently undergoing a paradigm shift with the incorporation of molecular biomarkers as part of routine diagnostic panel. The molecular alteration ranges from those involving the DNA, RNA, microRNAs (miRNAs) and proteins. The miRNAs are recently discovered small non-coding endogenous single-stranded RNAs that critically regulates the development, invasion and metastasis of cancers. They are altered in cancers and have the potential to serve as diagnostic markers for cancer...

  5. 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

  6. 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

  7. 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.

  8. 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.

  9. Biomarker discovery by sparse canonical correlation analysis of complex clinical phenotypes of tuberculosis and malaria.

    Directory of Open Access Journals (Sweden)

    Juho Rousu

    2013-04-01

    Full Text Available Biomarker discovery aims to find small subsets of relevant variables in 'omics data that correlate with the clinical syndromes of interest. Despite the fact that clinical phenotypes are usually characterized by a complex set of clinical parameters, current computational approaches assume univariate targets, e.g. diagnostic classes, against which associations are sought for. We propose an approach based on asymmetrical sparse canonical correlation analysis (SCCA that finds multivariate correlations between the 'omics measurements and the complex clinical phenotypes. We correlated plasma proteomics data to multivariate overlapping complex clinical phenotypes from tuberculosis and malaria datasets. We discovered relevant 'omic biomarkers that have a high correlation to profiles of clinical measurements and are remarkably sparse, containing 1.5-3% of all 'omic variables. We show that using clinical view projections we obtain remarkable improvements in diagnostic class prediction, up to 11% in tuberculosis and up to 5% in malaria. Our approach finds proteomic-biomarkers that correlate with complex combinations of clinical-biomarkers. Using the clinical-biomarkers improves the accuracy of diagnostic class prediction while not requiring the measurement plasma proteomic profiles of each subject. Our approach makes it feasible to use omics' data to build accurate diagnostic algorithms that can be deployed to community health centres lacking the expensive 'omics measurement capabilities.

  10. Aberrant Glycosylation as Biomarker for Cancer: Focus on CD43

    Directory of Open Access Journals (Sweden)

    Franca Maria Tuccillo

    2014-01-01

    Full Text Available Glycosylation is a posttranslational modification of proteins playing a major role in cell signalling, immune recognition, and cell-cell interaction because of their glycan branches conferring structure variability and binding specificity to lectin ligands. Aberrant expression of glycan structures as well as occurrence of truncated structures, precursors, or novel structures of glycan may affect ligand-receptor interactions and thus interfere with regulation of cell adhesion, migration, and proliferation. Indeed, aberrant glycosylation represents a hallmark of cancer, reflecting cancer-specific changes in glycan biosynthesis pathways such as the altered expression of glycosyltransferases and glycosidases. Most studies have been carried out to identify changes in serum glycan structures. In most cancers, fucosylation and sialylation are significantly modified. Thus, aberrations in glycan structures can be used as targets to improve existing serum cancer biomarkers. The ability to distinguish differences in the glycosylation of proteins between cancer and control patients emphasizes glycobiology as a promising field for potential biomarker identification. In this review, we discuss the aberrant protein glycosylation associated with human cancer and the identification of protein glycoforms as cancer biomarkers. In particular, we will focus on the aberrant CD43 glycosylation as cancer biomarker and the potential to exploit the UN1 monoclonal antibody (UN1 mAb to identify aberrant CD43 glycoforms.

  11. Circulating Nucleosomes and Nucleosome Modifications as Biomarkers in Cancer

    Science.gov (United States)

    McAnena, Peter; Brown, James A. L.; Kerin, Michael J.

    2017-01-01

    Traditionally the stratification of many cancers involves combining tumour and clinicopathological features (e.g., patient age; tumour size, grade, receptor status and location) to inform treatment options and predict recurrence risk and survival. However, current biomarkers often require invasive excision of the tumour for profiling, do not allow monitoring of the response to treatment and stratify patients into broad heterogeneous groups leading to inconsistent treatment responses. Here we explore and describe the benefits of using circulating biomarkers (nucleosomes and/or modifications to nucleosomes) as a non-invasive method for detecting cancer and monitoring response to treatment. Nucleosomes (DNA wound around eight core histone proteins) are responsible for compacting our genome and their composition and post-translational modifications are responsible for regulating gene expression. Here, we focus on breast and colorectal cancer as examples where utilizing circulating nucleosomes as biomarkers hold real potential as liquid biopsies. Utilizing circulating nucleosomes as biomarkers is an exciting new area of research that promises to allow both the early detection of cancer and monitoring of treatment response. Nucleosome-based biomarkers combine with current biomarkers, increasing both specificity and sensitivity of current tests and have the potential to provide individualised precision-medicine based treatments for patients. PMID:28075351

  12. 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.

  13. Mechanisms of CTC Biomarkers in Breast Cancer Brain Metastasis

    Science.gov (United States)

    2015-10-01

    represents the most devastating and feared consequence of breast cancer . BCBM is usually fatal and is increasing in frequency with occult brain...metastatic breast cancer (stage IV) patients with or without clinically diagnosed BCBM employing multiparametric flow cytometry (FACS; ARIA IIID system)(10...AWARD NUMBER: W81XWH-14-1-0214 TITLE: Mechanisms of CTC Biomarkers in Breast Cancer Brain Metastasis PRINCIPAL INVESTIGATOR: Dario

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

    Science.gov (United States)

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

    2016-06-01

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

  15. 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.

  16. 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

  17. 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...... into subgroups based on DNA biomarkers may improve prognosis. Serial monitoring of DNA-methylation markers in blood during treatment may be useful, particularly when the cancer burden is below the detection level for standard imaging techniques. Overall, aberrant DNA methylation has a great potential...

  18. 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.

  19. 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.

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

    Science.gov (United States)

    Orsini, M; Travaglione, A; Capobianco, E

    2013-07-01

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

  1. 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.

  2. Discovery of Hyperpolarized Molecular Imaging Biomarkers in a Novel Prostate Tissue Slice Culture Model

    Science.gov (United States)

    2013-06-01

    compatible bioreactor optimized in year 1 to identify hyperpolarized metabolic biomarkers of prostate cancer presence and aggressiveness. To...accomplish this goal my group finished the engineering of a 5 mm bioreactor and acquired hyperpolarized [1-13C]pyruvate data indicating that similar signal...to noise and quality data can be achieved with 4 to 5 prostate tissue slices in the 5 mm bioreactor as was acquired from 30-40 tissue slices in the

  3. Hypermethylated DNA, a Biomarker for colorectal cancer

    DEFF Research Database (Denmark)

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

    2016-01-01

    and specific for CRC have been proposed. Articles describing the use of hypermethylated promoter regions in blood or stool as biomarkers for CRC were systematically reviewed. METHOD: The Medline, Web of Science, and Embase databases were used in a systematic literature search. Studies were included...

  4. Indications of success: Strategies for utilizing neuroimaging biomarkers in CNS drug discovery and development: CINP/JSNP working group report.

    Science.gov (United States)

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

    2016-12-28

    Despite large unmet medical needs in the field for several decades, central nervous system (CNS) drug discovery and development has been largely unsuccessful. Biomarkers, particularly those utilizing neuroimaging, have played important roles in aiding CNS drug development, including dosing determination of investigational new drugs (INDs). The utility of biomarkers as tools to overcome issues of CNS drug development is the subject for this review.In this review aimed at employing biomarkers as tools to overcome issues surrounding CNS drug development, we first analyzed problems in utilizing biomarkers in processes of drug discovery and development for CNS disorders. Based on this analysis, we propose a new paradigm containing five distinct tiers to further clarify the use of biomarkers and establish new strategies for decision-making in the context of clinical drug development. Specifically, we discuss more rational ways to determine optimal dose for INDs with novel mechanisms and targets, and propose additional categorization criteria to further the use of biomarkers in patient stratification and efficacy prediction. Finally, we propose validation and development of new neuroimaging biomarkers through Public-Private-Partnerships to realize rational and successful drug discovery and development for CNS disorders.

  5. 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.

  6. 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.

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

    NARCIS (Netherlands)

    Reimers, Marlies Suzanne

    2015-01-01

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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Biomarker discovery for ovine paratuberculosis (Johne's disease) by proteomic serum profiling.

    Science.gov (United States)

    Zhong, L; Taylor, D; Begg, D J; Whittington, R J

    2011-07-01

    Paratuberculosis (Johne's disease) is a chronic granulomatous enteritis affecting ruminants and other species. It is caused by Mycobacterium avium subsp. paratuberculosis (MAP). In this study, surface enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI TOF-MS) was used as a platform to identify candidate biomarkers from sheep serum. Multivariate biomarker models which aimed to differentiate sheep with paratuberculosis and vaccinated-exposed sheep from unexposed animals were proposed based on classification and regression tree (CART) and linear discriminant analysis (LDA) algorithms from two array types. The accuracy of classification of sheep into unexposed or exposed groups ranged from 75 to 100% among models. SELDI was used to monitor protein profile changes over time during an experimental infection trial by examining sera collected at 4-, 8- and 13-months post infection. Although three different SELDI instruments were used, nine consistent proteomic features were observed associated with exposure to MAP. Two of the putative serum biomarkers were purified from serum using chromatographic methods and were identified as transthyretin and alpha haemoglobin by tandem mass spectrometry. They belong to highly abundant, acute phase reactants in the serum proteome and have also been discovered as serum biomarkers in human inflammatory conditions and cancer. Their relationship to the pathogenesis of Johne's disease remains to be elucidated.

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

    Directory of Open Access Journals (Sweden)

    Craig A Gedye

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

  14. 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

  15. 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).

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Proteoglycans as potential microenvironmental biomarkers for colon cancer.

    Science.gov (United States)

    Suhovskih, Anastasia V; Aidagulova, Svetlana V; Kashuba, Vladimir I; Grigorieva, Elvira V

    2015-09-01

    Glycosylation changes occur widely in colon tumours, suggesting glycosylated molecules as potential biomarkers for colon cancer diagnostics. In this study, proteoglycans (PGs) expression levels and their transcriptional patterns are investigated in human colon tumours in vivo and carcinoma cells in vitro. According to RT-PCR analysis, normal and cancer colon tissues expressed a specific set of PGs (syndecan-1, perlecan, decorin, biglycan, versican, NG2/CSPG4, serglycin, lumican, CD44), while the expression of glypican-1, brevican and aggrecan was almost undetectable. Overall transcriptional activity of the PGs in normal and cancer tissues was similar, although expression patterns were different. Expression of decorin and perlecan was down-regulated 2-fold in colon tumours, while biglycan and versican expression was significantly up-regulated (6-fold and 3-fold, respectively). Expression of collagen1A1 was also increased 6-fold in colon tumours. However, conventional HCT-116 colon carcinoma and AG2 colon cancer-initiating cells did not express biglycan and decorin and were versican-positive and -negative, respectively, demonstrating an extracellular origin of the PGs in cancer tissue. Selective expression of heparan sulfate (HS) proteoglycans syndecan-1 and perlecan in the AG2 colon cancer-initiating cell line suggests these PGs as potential biomarkers for cancer stem cells. Overall transcriptional activity of the HS biosynthetic system was similar in normal and cancer tissues, although significant up-regulation of extracellular sulfatases SULF1/2 argues for a possible distortion of HS sulfation patterns in colon tumours. Taken together, the obtained results suggest versican, biglycan, collagen1A1 and SULF1/2 expression as potential microenvironmental biomarkers and/or targets for colon cancer diagnostics and treatment.

  1. 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.

  2. Non-invasive actionable biomarkers for metastatic prostate cancer

    Directory of Open Access Journals (Sweden)

    Jun Luo

    2016-10-01

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

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

    Science.gov (United States)

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

    2009-05-01

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

  4. 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.

  5. Tobacco carcinogens, their biomarkers and tobacco-induced cancer.

    Science.gov (United States)

    Hecht, Stephen S

    2003-10-01

    The devastating link between tobacco products and human cancers results from a powerful alliance of two factors - nicotine and carcinogens. Without either one of these, tobacco would be just another commodity, instead of being the single greatest cause of death due to preventable cancer. Nicotine is addictive and toxic, but it is not carcinogenic. This addiction, however, causes people to use tobacco products continually, and these products contain many carcinogens. What are the mechanisms by which this deadly combination leads to 30% of cancer-related deaths in developed countries, and how can carcinogen biomarkers help to reveal these mechanisms?

  6. Validation of Biomarkers for Prostate Cancer Prognosis

    Science.gov (United States)

    2013-10-01

    incontinence and urinary urgency as well as sexual dysfunction. Furthermore, evidence from many sources suggests that most prostate cancers are...mainly surgery and radiation therapy, result in well documented significant morbidities, including significant lower urinary tract symptoms such as

  7. 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.

  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. Discovery Radiomics via StochasticNet Sequencers for Cancer Detection

    OpenAIRE

    Shafiee, Mohammad Javad; Chung, Audrey G.; Kumar, Devinder; Khalvati, Farzad; Haider, Masoom; Wong, Alexander

    2015-01-01

    Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits. In this study, we introduce a novel discovery radiomics framework where we directly discover custom radiomic features from the wealth of available...

  10. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer

    Directory of Open Access Journals (Sweden)

    Raquel Conde-Muíño

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  12. Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery.

    Science.gov (United States)

    Elschenbroich, Sarah; Kislinger, Thomas

    2011-02-01

    Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.

  13. 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.

  14. 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.

  15. 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...

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

    Science.gov (United States)

    Wachter, Astrid; Bernhardt, Stephan; Beissbarth, Tim; Korf, Ulrike

    2015-01-01

    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. PMID:27600238

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Donavon Hiss

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jasmina Saric

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

  20. 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.

  1. 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...

  2. 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.

  3. 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...... the relationships between ambient air pollution and biological markers of dose and early response. The evidence for each marker was evaluated using assessment criteria which rate a group of studies from A (strong) to C (weak) on amount of evidence, replication of findings, and protection from bias. Biomarkers...

  4. 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

  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.

  6. Validation of Biomarkers for Prostate Cancer Prognosis

    Science.gov (United States)

    2015-11-01

    example the OncotypeDx assay has been calibrated and already validated precisely for this purpose. In addition, multiparametric MRI shows good ...testing. Cancer 119: 3906-3909, 2013. Zuxiong Chen, Zulfiqar G. Gulzar, Catherine A. St. Hill, Bruce Walcheck, James D. Brooks: Increased expression...Jamaspishvili T, Wei W, Feng Z, Good J, Hawley S, Fazli L, McKenney J, Simko J, Hurtado-Coll A, Carroll P, Gleave M, Lance R, Lin D, Nelson P, Thompson I

  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. 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.

  9. 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

  10. MicroRNAs: Potential biomarkers in cancer

    OpenAIRE

    George, G. P.; Mittal, Rama Devi

    2010-01-01

    microRNAs (miRNAs) are evolutionarily conserved small noncoding RNAs, also known as micromanagers of gene expression. Polymorphisms in the miRNA pathway (miR-polymorphisms) are emerging as powerful tools to study the biology of a disease and have the potential to be used in disease prognosis and diagnosis. Advancements in the miRNA field also indicate a clear involvement of deregulated miRNA gene signatures in cancers, and several polymorphisms in pre-miRNA, miRNA binding sites or targets hav...

  11. Functional Proteomics-Based Ovarian Cancer Biomarkers

    Science.gov (United States)

    2010-11-01

    levels and regulation of stathmin in paclitaxel-resistant ovarian cancer cells." Oncogene 22.55 (2003): 8924-8930. 11  Bankaitis-Davis, Danute, et...activator of transcription 6, phosphorylated Not Valid 56 149 * STATHMIN Stathmin 1 Validated 83 75 10 Survivin (BIRC5)baculoviral IAP repeat...Y182 34 FOXO3A 75 STATHMIN 117 BAD.PS112 35 P27 76 4EBP1 118 ER.ALPHA. 36 JNK 77 MCL1 118 ER.ALPHA.PS167 37 TAU 78 MIFT 119 ER.ALPHA 38 GATA3 79

  12. 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

  13. 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....

  14. Biomarker discovery by CE-MS enables sequence analysis via MS/MS with platform-independent separation.

    Science.gov (United States)

    Zürbig, Petra; Renfrow, Matthew B; Schiffer, Eric; Novak, Jan; Walden, Michael; Wittke, Stefan; Just, Ingo; Pelzing, Matthias; Neusüss, Christian; Theodorescu, Dan; Root, Karen E; Ross, Mark M; Mischak, Harald

    2006-06-01

    CE-MS is a successful proteomic platform for the definition of biomarkers in different body fluids. Besides the biomarker defining experimental parameters, CE migration time and molecular weight, especially biomarker's sequence identity is an indispensable cornerstone for deeper insights into the pathophysiological pathways of diseases or for made-to-measure therapeutic drug design. Therefore, this report presents a detailed discussion of different peptide sequencing platforms consisting of high performance separation method either coupled on-line or off-line to different MS/MS devices, such as MALDI-TOF-TOF, ESI-IT, ESI-QTOF and Fourier transform ion cyclotron resonance, for sequencing indicative peptides. This comparison demonstrates the unique feature of CE-MS technology to serve as a reliable basis for the assignment of peptide sequence data obtained using different separation MS/MS methods to the biomarker defining parameters, CE migration time and molecular weight. Discovery of potential biomarkers by CE-MS enables sequence analysis via MS/MS with platform-independent sample separation. This is due to the fact that the number of basic and neutral polar amino acids of biomarkers sequences distinctly correlates with their CE-MS migration time/molecular weight coordinates. This uniqueness facilitates the independent entry of different sequencing platforms for peptide sequencing of CE-MS-defined biomarkers from highly complex mixtures.

  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. 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.

  17. 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.

  18. Biomarkers for the clinical management of breast cancer: international perspective.

    Science.gov (United States)

    Patani, Neill; Martin, Lesley-Ann; Dowsett, Mitch

    2013-07-01

    The higher incidence of breast cancer in developed countries has been tempered by reductions in mortality, largely attributable to mammographic screening programmes and advances in adjuvant therapy. Optimal systemic management requires consideration of clinical, pathological and biological parameters. Oestrogen receptor alpha (ERα), progesterone receptor (PgR) and human epidermal growth factor receptor 2 (HER2) are established biomarkers evaluated at diagnosis, which identify cardinal subtypes of breast cancer. Their prognostic and predictive utility effectively guides systemic treatment with endocrine, anti-HER2 and chemotherapy. Hence, accurate and reliable determination remains of paramount importance. However, the goals of personalized medicine and targeted therapies demand further information regarding residual risk and potential benefit of additional treatments in specific circumstances. The need for biomarkers which are fit for purpose, and the demands placed upon them, is therefore expected to increase. Technological advances, in particular high-throughput global gene expression profiling, have generated multi-gene signatures providing further prognostic and predictive information. The rational integration of routinely evaluated clinico-pathological parameters with key indicators of biological activity, such as proliferation markers, also provides a ready opportunity to improve the information available to guide systemic therapy decisions. The additional value of such information and its proper place in patient management is currently under evaluation in prospective clinical trials. Expanding the utility of biomarkers to lower resource settings requires an emphasis on cost effectiveness, quality assurance and possible international variations in tumor biology; the potential for improved clinical outcomes should be justified against logistical and economic considerations.

  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. 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.

  1. Photonic crystal enhanced fluorescence for early breast cancer biomarker detection.

    Science.gov (United States)

    Cunningham, Brian T; Zangar, Richard C

    2012-08-01

    Photonic crystal surfaces offer a compelling platform for improving the sensitivity of surface-based fluorescent assays used in disease diagnostics. Through the complementary processes of photonic crystal enhanced excitation and enhanced extraction, a periodic dielectric-based nanostructured surface can simultaneously increase the electric field intensity experienced by surface-bound fluorophores and increase the collection efficiency of emitted fluorescent photons. Through the ability to inexpensively fabricate photonic crystal surfaces over substantial surface areas, they are amenable to single-use applications in biological sensing, such as disease biomarker detection in serum. In this review, we will describe the motivation for implementing high-sensitivity, multiplexed biomarker detection in the context of breast cancer diagnosis. We will summarize recent efforts to improve the detection limits of such assays though the use of photonic crystal surfaces. Reduction of detection limits is driven by low autofluorescent substrates for photonic crystal fabrication, and detection instruments that take advantage of their unique features.

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

    Directory of Open Access Journals (Sweden)

    Garner Harold R

    2009-05-01

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

  3. A 2015 survey of established or potential epigenetic biomarkers for the accurate detection of human cancers.

    Science.gov (United States)

    Amacher, David E

    2016-07-01

    Context The silencing or activation of cancer-associated genes by epigenetic mechanisms can ultimately lead to the clonal expansion of cancer cells. Objective The aim of this review is to summarize all relevant epigenetic biomarkers that have been proposed to date for the diagnosis of some prevalent human cancers. Methods A Medline search for the terms epigenetic biomarkers, human cancers, DNA methylation, histone modifications and microRNAs was performed. Results One hundred fifty-seven relevant publications were found and reviewed. Conclusion To date, a significant number of potential epigenetic cancer biomarkers of human cancer have been investigated, and some have advanced to clinical implementation.

  4. 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.

  5. 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.

  6. 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......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...

  7. 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

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

    Directory of Open Access Journals (Sweden)

    Sudhanshu Shukla

    2016-08-01

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

  9. 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

  10. 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 ...

  11. Bioinformatics for cancer immunotherapy target discovery

    DEFF Research Database (Denmark)

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

    2014-01-01

    The mechanisms of immune response to cancer have been studied extensively and great effort has been invested into harnessing the therapeutic potential of the immune system. Immunotherapies have seen significant advances in the past 20 years, but the full potential of protective and therapeutic...... 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...

  12. Circulating exosomal microRNAs as biomarkers of colon cancer.

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    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

  13. 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.

  14. Blood-based biomarkers of aggressive prostate cancer.

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    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

  15. 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.

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

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    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.

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

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    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.

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

    Science.gov (United States)

    Masuda, Shinobu

    2016-07-01

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

  19. 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.

  20. Quantitative network measures as biomarkers for classifying prostate cancer disease states: a systems approach to diagnostic biomarkers.

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    Matthias Dehmer

    Full Text Available Identifying diagnostic biomarkers based on genomic features for an accurate disease classification is a problem of great importance for both, basic medical research and clinical practice. In this paper, we introduce quantitative network measures as structural biomarkers and investigate their ability for classifying disease states inferred from gene expression data from prostate cancer. We demonstrate the utility of our approach by using eigenvalue and entropy-based graph invariants and compare the results with a conventional biomarker analysis of the underlying gene expression data.

  1. Identification of a biomarker panel for colorectal cancer diagnosis

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    García-Bilbao Amaia

    2012-01-01

    Full Text Available Abstract Background Malignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries. Methods A genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables. Results After an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples. Conclusions We have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955.

  2. 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.

  3. 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.

  4. Exosomal miRNAs as cancer biomarkers and therapeutic targets

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    Arron Thind

    2016-07-01

    Full Text Available 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.

  5. The Janus serum bank and biomarkers of cancer

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    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.

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

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    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

  7. Gradually implemented new biomarkers for prognostication of breast cancer : complete case analysis may introduce bias

    NARCIS (Netherlands)

    Pathy, Nirmala Bhoo; Uiterwaal, Cuno S. P. M.; Taib, Nur Aishah; Verkooijen, Helena M.; Yip, Cheng Har

    2012-01-01

    Objective: Many recent studies investigated the prognostic value of new biomarkers in breast cancer using data from cancer registries. Some of these studies were conducted using only patients for whom biomarker status was available (or tested). Using human epidermal growth factor receptor 2 (HER2) a

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

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    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.

  9. 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.

  10. Discovery and validation of breast cancer subtypes

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    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.

  11. Mouse models for the discovery of colorectal cancer driver genes.

    Science.gov (United States)

    Clark, Christopher R; Starr, Timothy K

    2016-01-14

    Colorectal cancer (CRC) constitutes a major public health problem as the third most commonly diagnosed and third most lethal malignancy worldwide. The prevalence and the physical accessibility to colorectal tumors have made CRC an ideal model for the study of tumor genetics. Early research efforts using patient derived CRC samples led to the discovery of several highly penetrant mutations (e.g., APC, KRAS, MMR genes) in both hereditary and sporadic CRC tumors. This knowledge has enabled researchers to develop genetically engineered and chemically induced tumor models of CRC, both of which have had a substantial impact on our understanding of the molecular basis of CRC. Despite these advances, the morbidity and mortality of CRC remains a cause for concern and highlight the need to uncover novel genetic drivers of CRC. This review focuses on mouse models of CRC with particular emphasis on a newly developed cancer gene discovery tool, the Sleeping Beauty transposon-based mutagenesis model of CRC.

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

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    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.

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

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    Yinhai Wang

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

  14. The journey from discoveries in fundamental immunology to cancer immunotherapy.

    Science.gov (United States)

    Miller, Jacques F A P; Sadelain, Michel

    2015-04-13

    Recent advances in cancer immunotherapy have directly built on 50 years of fundamental and technological advances that made checkpoint blockade and T cell engineering possible. In this review, we intend to show that research, not specifically designed to bring relief or cure to any particular disease, can, when creatively exploited, lead to spectacular results in the management of cancer. The discovery of thymus immune function, T cells, and immune surveillance bore the seeds for today's targeted immune interventions and chimeric antigen receptors.

  15. 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.

  16. NMR metabolic fingerprints of murine melanocyte and melanoma cell lines: application to biomarker discovery

    Science.gov (United States)

    Santana-Filho, Arquimedes Paixão de; Jacomasso, Thiago; Riter, Daniel Suss; Barison, Andersson; Iacomini, Marcello; Winnischofer, Sheila Maria Brochado; Sassaki, Guilherme Lanzi

    2017-01-01

    Melanoma is the most aggressive type of skin cancer and efforts to improve the diagnosis of this neoplasia are largely based on the use of cell lines. Metabolomics is currently undergoing great advancements towards its use to screening for disease biomarkers. Although NMR metabolomics includes both 1D and 2D methodologies, there is a lack of data in the literature regarding heteronuclear 2D NMR assignments of the metabolome from eukaryotic cell lines. The present study applied NMR-based metabolomics strategies to characterize aqueous and lipid extracts from murine melanocytes and melanoma cell lines with distinct tumorigenic potential, successfully obtaining fingerprints of the metabolites from the extracts of the cell lines by means of 2D NMR HSQC correlation maps. Relative amounts of the identified metabolites were compared between the 4 cell lines. Multivariate analysis of 1H NMR data was able not only to differentiate the melanocyte cell line from the tumorigenic ones but also distinguish among the 3 tumorigenic cell lines. We also investigated the effects of mitogenic agents, and found that they can markedly influence the metabolome of the melanocyte cell line, resembling the pattern of most proliferative cell lines. PMID:28198377

  17. In vivo biomarker expression patterns are preserved in 3D cultures of Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Windus, Louisa C.E.; Kiss, Debra L.; Glover, Tristan [Eskitis Institute for Cell and Molecular Therapies, Discovery Biology, Griffith University, Nathan 4111, Brisbane, Queensland (Australia); Avery, Vicky M., E-mail: v.avery@griffith.edu.au [Eskitis Institute for Cell and Molecular Therapies, Discovery Biology, Griffith University, Nathan 4111, Brisbane, Queensland (Australia)

    2012-11-15

    Here we report that Prostate Cancer (PCa) cell-lines DU145, PC3, LNCaP and RWPE-1 grown in 3D matrices in contrast to conventional 2D monolayers, display distinct differences in cell morphology, proliferation and expression of important biomarker proteins associated with cancer progression. Consistent with in vivo growth rates, in 3D cultures, all PCa cell-lines were found to proliferate at significantly lower rates in comparison to their 2D counterparts. Moreover, when grown in a 3D matrix, metastatic PC3 cell-lines were found to mimic more precisely protein expression patterns of metastatic tumour formation as found in vivo. In comparison to the prostate epithelial cell-line RWPE-1, metastatic PC3 cell-lines exhibited a down-regulation of E-cadherin and {alpha}6 integrin expression and an up-regulation of N-cadherin, Vimentin and {beta}1 integrin expression and re-expressed non-transcriptionally active AR. In comparison to the non-invasive LNCaP cell-lines, PC3 cells were found to have an up-regulation of chemokine receptor CXCR4, consistent with a metastatic phenotype. In 2D cultures, there was little distinction in protein expression between metastatic, non-invasive and epithelial cells. These results suggest that 3D cultures are more representative of in vivo morphology and may serve as a more biologically relevant model in the drug discovery pipeline. -- Highlights: Black-Right-Pointing-Pointer We developed and optimised 3D culturing techniques for Prostate Cancer cell-lines. Black-Right-Pointing-Pointer We investigated biomarker expression in 2D versus 3D culture techniques. Black-Right-Pointing-Pointer Metastatic PC3 cells re-expressed non-transcriptionally active androgen receptor. Black-Right-Pointing-Pointer Metastatic PCa cell lines retain in vivo-like antigenic profiles in 3D cultures.

  18. 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).

  19. Long Non-Coding RNA as Potential Biomarker for Prostate Cancer: Is It Making a Difference?

    Science.gov (United States)

    Deng, Junli; Tang, Jie; Wang, Guo; Zhu, Yuan-Shan

    2017-01-01

    Whole genome transcriptomic analyses have identified numerous long non-coding RNA (lncRNA) transcripts that are increasingly implicated in cancer biology. LncRNAs are found to promote essential cancer cell functions such as proliferation, invasion, and metastasis, with the potential to serve as novel biomarkers of various cancers and to further reveal uncharacterized aspects of tumor biology. However, the biological and molecular mechanisms as well as the clinical applications of lncRNAs in diverse diseases are not completely understood, and remain to be fully explored. LncRNAs may be critical players and regulators in prostate cancer carcinogenesis and progression, and could serve as potential biomarkers for prostate cancer. This review focuses on lncRNA biomarkers that are already available for clinical use and provides an overview of lncRNA biomarkers that are under investigation for clinical development in prostate cancer. PMID:28272371

  20. 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.

  1. Excerpts from the 1st international NTNU symposium on current and future clinical biomarkers of cancer

    DEFF Research Database (Denmark)

    Robles, Ana I; Olsen, Karina Standahl; Tsui, Dana W T;

    2016-01-01

    The goal of biomarker research is to identify clinically valid markers. Despite decades of research there has been disappointingly few molecules or techniques that are in use today. The "1st International NTNU Symposium on Current and Future Clinical Biomarkers of Cancer: Innovation and Implement......The goal of biomarker research is to identify clinically valid markers. Despite decades of research there has been disappointingly few molecules or techniques that are in use today. The "1st International NTNU Symposium on Current and Future Clinical Biomarkers of Cancer: Innovation...

  2. (Very) Early technology assessment and translation of predictive biomarkers in breast cancer.

    Science.gov (United States)

    Miquel-Cases, Anna; Schouten, Philip C; Steuten, Lotte M G; Retèl, Valesca P; Linn, Sabine C; van Harten, Wim H

    2017-01-01

    Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation.

  3. Identification of urine protein biomarkers with the potential for early detection of lung cancer

    OpenAIRE

    Hongjuan Zhang; Jing Cao; Lin Li; Yanbin Liu; Hong Zhao; Nan Li; Bo Li; Aiqun Zhang; Huanwei Huang; She Chen; Mengqiu Dong; Lei Yu; Jian Zhang; Liang Chen

    2015-01-01

    Lung cancer is the leading cause of cancer-related deaths and has an overall 5-year survival rate lower than 15%. Large-scale clinical trials have demonstrated a significant relative reduction in mortality in high-risk individuals with low-dose computed tomography screening. However, biomarkers capable of identifying the most at-risk population and detecting lung cancer before it becomes clinically apparent are urgently needed in the clinic. Here, we report the identification of urine biomark...

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

    OpenAIRE

    Yingrong Chen; Zhihong Ma; Lishan Min; Hongwei Li; Bin Wang; Jing Zhong; Licheng Dai

    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...

  5. 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.

  6. Single Gene Prognostic Biomarkers in Ovarian Cancer: A Meta-Analysis

    Science.gov (United States)

    Willis, Scooter; Villalobos, Victor M.; Gevaert, Olivier; Abramovitz, Mark; Williams, Casey; Sikic, Branimir I.; Leyland-Jones, Brian

    2016-01-01

    Purpose To discover novel prognostic biomarkers in ovarian serous carcinomas. Methods A meta-analysis of all single genes probes in the TCGA and HAS ovarian cohorts was performed to identify possible biomarkers using Cox regression as a continuous variable for overall survival. Genes were ranked by p-value using Stouffer’s method and selected for statistical significance with a false discovery rate (FDR) <.05 using the Benjamini-Hochberg method. Results Twelve genes with high mRNA expression were prognostic of poor outcome with an FDR <.05 (AXL, APC, RAB11FIP5, C19orf2, CYBRD1, PINK1, LRRN3, AQP1, DES, XRCC4, BCHE, and ASAP3). Twenty genes with low mRNA expression were prognostic of poor outcome with an FDR <.05 (LRIG1, SLC33A1, NUCB2, POLD3, ESR2, GOLPH3, XBP1, PAXIP1, CYB561, POLA2, CDH1, GMNN, SLC37A4, FAM174B, AGR2, SDR39U1, MAGT1, GJB1, SDF2L1, and C9orf82). Conclusion A meta-analysis of all single genes identified thirty-two candidate biomarkers for their possible role in ovarian serous carcinoma. These genes can provide insight into the drivers or regulators of ovarian cancer and should be evaluated in future studies. Genes with high expression indicating poor outcome are possible therapeutic targets with known antagonists or inhibitors. Additionally, the genes could be combined into a prognostic multi-gene signature and tested in future ovarian cohorts. PMID:26886260

  7. Application of proteomics in the discovery of candidate protein biomarkers in a diabetes autoantibody standardization program sample subset.

    Science.gov (United States)

    Metz, Thomas O; Qian, Wei-Jun; Jacobs, Jon M; Gritsenko, Marina A; Moore, Ronald J; Polpitiya, Ashoka D; Monroe, Matthew E; Camp, David G; Mueller, Patricia W; Smith, Richard D

    2008-02-01

    Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted "-omics" approaches are underutilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program, with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. alpha-2-Glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples.

  8. RNA Editing and Drug Discovery for Cancer Therapy

    Directory of Open Access Journals (Sweden)

    Wei-Hsuan Huang

    2013-01-01

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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  15. 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.

  16. 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.

  17. Building the Evidence Base of Blood-Based Biomarkers for Early Detection of Cancer: A Rapid Systematic Mapping Review

    Directory of Open Access Journals (Sweden)

    Lesley Uttley

    2016-08-01

    Interpretation: This study is the first to systematically and comprehensively map blood biomarkers for early detection of cancer. Use of this rapid systematic mapping approach found a broad range of relevant biomarkers allowing an evidence-based approach to identification of promising biomarkers for development of a blood-based cancer screening test in the general population.

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

    DEFF Research Database (Denmark)

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-02-19

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

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Geramizadeh

    2015-10-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  3. [Circulating biomarkers association in the follow-up of patients with oral cancer].

    Science.gov (United States)

    Colella, G; Cozzolino, A; Santagata, M; Vicidomini, A; Itro, A

    2001-05-01

    The goal of this study is to analyze the importance of circulating biomarkers association in the management of patients affected by oral cancer. In this study a survey is made of the international experience from 1980 to 1990 based on the presence of CEA, LASA, SCC Ag, TPA, ferritina, CA-50 and others in patients affected by oral cancer and the sensitivity and specificity of these circulating biomarkers association are assessed. In patients with active disease, the results obtained at the time of diagnosis of oral cancer are not satisfactory due to poor specificity of these circulating biomarkers association. The conclusions is drawn that the circulating biomarkers association (especially CEA, SCC Ag, LASA, ferritin, TPA and CA-50) appears to be useful in the prognosis and staging of oral cancer, while their presence is not significative for the diagnosis.

  4. Potential utility of cancer-specific biomarkers for assessing response to hormonal treatments in metastatic prostate cancer

    NARCIS (Netherlands)

    Schalken, J.; Dijkstra, S.; Baskin-Bey, E.; Oort, I. van

    2014-01-01

    Prostate cancer is the second leading cause of cancer death in men and there is an urgent clinical need to improve its detection and treatment. The introduction of prostate-specific antigen (PSA) as a biomarker for prostate cancer several decades ago represented an important step forward in our abil

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

    Directory of Open Access Journals (Sweden)

    Kendall K

    2013-05-01

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

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

    Directory of Open Access Journals (Sweden)

    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

  7. Circulating MicroRNAs as Biomarkers and Mediators of Cell–Cell Communication in Cancer

    OpenAIRE

    Taylor, Molly A.

    2015-01-01

    The realization of personalized medicine for cancer will rely not only on the development of new therapies, but on biomarkers that direct these therapies to the right patient. MicroRNA expression profiles in the primary tumor have been shown to differ between cancer patients and healthy individuals, suggesting they might make useful biomarkers. However, examination of microRNA expression in the primary tumor requires an invasive biopsy procedure. More recently, microRNAs have been shown to be...

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

    Science.gov (United States)

    2004-10-01

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

  9. Applying tobacco carcinogen and toxicant biomarkers in product regulation and cancer prevention.

    Science.gov (United States)

    Hecht, Stephen S; Yuan, Jian-Min; Hatsukami, Dorothy

    2010-06-21

    Tobacco carcinogen and toxicant biomarkers are metabolites or protein or DNA adducts of specific compounds in tobacco products. Highly reliable analytical methods, based mainly on mass spectrometry, have been developed and applied in large studies of many of these biomarkers. A panel of tobacco carcinogen and toxicant biomarkers is suggested here, and typical values for smokers and nonsmokers are summarized. This panel of biomarkers has potential applications in the new and challenging area of tobacco product regulation and in the development of rational approaches to cancer prevention by establishing carcinogen and toxicant uptake and excretion in people exposed to tobacco products.

  10. 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.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Richard J Perrin

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

  13. 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

  14. 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.

  15. Identification of serum biomarkers for lung cancer using magnetic bead-based SELDI-TOF-MS

    OpenAIRE

    SONG, QI-BIN; Hu, Wei-Guo; Wang, Peng; Yao, Yi; Zeng, Hua-zong

    2011-01-01

    Aim: To identify novel serum biomarkers for lung cancer diagnosis using magnetic bead-based surface-enhanced laser desorption/ionization time-of-flight mass spectrum (SELDI-TOF-MS). Methods: The protein fractions of 121 serum specimens from 30 lung cancer patients, 30 pulmonary tuberculosis patients and 33 healthy controls were enriched using WCX magnetic beads and subjected to SELDI-TOF-MS. The spectra were analyzed using Bio-marker Wizard version 3.1.0 and Biomarker Patterns Software versio...

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Maryam Ebadi

    2015-01-01

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

  18. 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.

  19. Multiplexed cancer biomarker detection using chip-integrated silicon photonic sensor arrays.

    Science.gov (United States)

    Washburn, Adam L; Shia, Winnie W; Lenkeit, Kimberly A; Lee, So-Hyun; Bailey, Ryan C

    2016-09-21

    The analysis of disease-specific biomarker panels holds promise for the early detection of a range of diseases, including cancer. Blood-based biomarkers, in particular, are attractive targets for minimally-invasive disease diagnosis. Specifically, a panel of organ-specific biomarkers could find utility as a general disease surveillance tool enabling earlier detection or prognostic monitoring. Using arrays of chip-integrated silicon photonic sensors, we describe the simultaneous detection of eight cancer biomarkers in serum in a relatively rapid (1 hour) and fully automated antibody-based sandwich assay. Biomarkers were chosen for their applicability to a range of organ-specific cancers, including disease of the pancreas, liver, ovary, breast, lung, colorectum, and prostate. Importantly, we demonstrate that selected patient samples reveal biomarker "fingerprints" that may be useful for a personalized cancer diagnosis. More generally, we show that the silicon photonic technology is capable of measuring multiplexed panels of protein biomarkers that may have broad utility in clinical diagnostics.

  20. 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.

  1. Anti-cancer drug discovery: update and comparisons in yeast, Drosophila, and zebrafish.

    Science.gov (United States)

    Gao, Guangxun; Chen, Liang; Huang, Chuanshu

    2014-01-01

    Discovery of novel cancer chemotherapeutics focuses on screening and identifying compounds that can target 'cancer-specific' biological processes while causing minimal toxicity to non-tumor cells. Alternatively, model organisms with highly conserved cancer-related cellular processes relative to human cells may offer new opportunities for anticancer drug discovery when combined with chemical screening. Some organisms used for chemotherapeutic discovery include yeast, Drosophila, and zebrafish which are similar in important ways relevant to cancer study but offer distinct advantages as well. Here, we describe these model attributes and the rationale for using them in cancer drug screening research.

  2. 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......Autoantibodies to cancer antigens hold promise as biomarkers for early detection of cancer. Proteins that are aberrantly processed in cancer cells are likely to present autoantibody targets. The extracellular mucin MUC1 is overexpressed and aberrantly glycosylated in many cancers; thus, we...... evaluated whether autoantibodies generated to aberrant O-glycoforms of MUC1 might serve as sensitive diagnostic biomarkers for cancer. Using an antibody-based glycoprofiling ELISA assay, we documented that aberrant truncated glycoforms were not detected in sera of cancer patients. An O...

  3. Blood and tissue biomarkers in prostate cancer: state of the art.

    Science.gov (United States)

    Fiorentino, Michelangelo; Capizzi, Elisa; Loda, Massimo

    2010-02-01

    The prevalence of prostate cancer (PCa) is high and increases with age. PCa is the most common cutaneous cancer in American men. Prostate-specific antigen (PSA) screening has impacted the detection of PCa and is directly responsible for a dramatic decrease in stage at diagnosis. Gleason score and stage at the time of diagnosis remain the mainstay to predict prognosis, in the absence of more accurate and reliable tissue or blood biomarkers. Despite extensive research efforts, very few biomarkers of PCa have been introduced to date in clinical practice. Even screening with PSA has recently been questioned. A thorough analysis of all tissue and serum biomarkers in prostate cancer research cannot be easily synthesized, and goes beyond the scope of the present article. Therefore the authors focus here on the most recently reported tissue and circulating biomarkers for PCa whose application in clinical practice is either current or expected in the near future.

  4. 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.

  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. Serum Helicobacter pylori NapA antibody as a potential biomarker for gastric cancer

    OpenAIRE

    Jingjing Liu; Huimin Liu; Tingting Zhang; Xiyun Ren; Christina Nadolny; Xiaoqun Dong; Lina Huang; Kexin Yuan; Wenjing Tian; Yunhe Jia

    2014-01-01

    Helicobacter pylori (H. pylori) infection is strongly associated with gastric cancer. However, only a minority of infected individuals ever develop gastric cancer. This risk stratification may be in part due to differences among strains. The relationship between neutrophil-activating protein (NapA) and gastric cancer is unclear. The purpose of this study is to evaluate the significance of NapA as a biomarker in gastric cancer. We used enzyme linked immunosorbent assay (ELISA) to determine the...

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

    OpenAIRE

    Jay Morris; Michael J. Wargovich; Brown, Vondina R.

    2010-01-01

    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...

  8. 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

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

    Science.gov (United States)

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

    2014-12-01

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

  10. Receiver Operating Characteristic (ROC to Determine Cut-Off Points of Biomarkers in Lung Cancer Patients

    Directory of Open Access Journals (Sweden)

    Heidi L. Weiss

    2004-01-01

    Full Text Available The role of biomarkers in disease prognosis continues to be an important investigation in many cancer studies. In order for these biomarkers to have practical application in clinical decision making regarding patient treatment and follow-up, it is common to dichotomize patients into those with low vs. high expression levels. In this study, receiver operating characteristic (ROC curves, area under the curve (AUC of the ROC, sensitivity, specificity, as well as likelihood ratios were calculated to determine levels of growth factor biomarkers that best differentiate lung cancer cases versus control subjects. Selected cut-off points for p185erbB-2 and EGFR membrane appear to have good discriminating power to differentiate control tissues versus uninvolved tissues from patients with lung cancer (AUC = 89% and 90%, respectively; while AUC increased to at least 90% for selected cut-off points for p185erbB-2 membrane, EGFR membrane, and FASE when comparing between control versus carcinoma tissues from lung cancer cases. Using data from control subjects compared to patients with lung cancer, we presented a simple and intuitive approach to determine dichotomized levels of biomarkers and validated the value of these biomarkers as surrogate endpoints for cancer outcome.

  11. Development of a sequential workflow based on LC-PRM for the verification of endometrial cancer protein biomarkers in uterine aspirate samples.

    Science.gov (United States)

    Martinez-Garcia, Elena; Lesur, Antoine; Devis, Laura; Campos, Alexandre; Cabrera, Silvia; van Oostrum, Jan; Matias-Guiu, Xavier; Gil-Moreno, Antonio; Reventos, Jaume; Colas, Eva; Domon, Bruno

    2016-08-16

    About 30% of endometrial cancer (EC) patients are diagnosed at an advanced stage of the disease, which is associated with a drastic decrease in the 5-year survival rate. The identification of biomarkers in uterine aspirate samples, which are collected by a minimally invasive procedure, would improve early diagnosis of EC. We present a sequential workflow to select from a list of potential EC biomarkers, those which are the most promising to enter a validation study. After the elimination of confounding contributions by residual blood proteins, 52 potential biomarkers were analyzed in uterine aspirates from 20 EC patients and 18 non-EC controls by a high-resolution accurate mass spectrometer operated in parallel reaction monitoring mode. The differential abundance of 26 biomarkers was observed, and among them ten proteins showed a high sensitivity and specificity (AUC > 0.9). The study demonstrates that uterine aspirates are valuable samples for EC protein biomarkers screening. It also illustrates the importance of a biomarker verification phase to fill the gap between discovery and validation studies and highlights the benefits of high resolution mass spectrometry for this purpose. The proteins verified in this study have an increased likelihood to become a clinical assay after a subsequent validation phase.

  12. 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

  13. Cancer screening: a mathematical model relating secreted blood biomarker levels to tumor sizes.

    Directory of Open Access Journals (Sweden)

    Amelie M Lutz

    2008-08-01

    Full Text Available BACKGROUND: Increasing efforts and financial resources are being invested in early cancer detection research. Blood assays detecting tumor biomarkers promise noninvasive and financially reasonable screening for early cancer with high potential of positive impact on patients' survival and quality of life. For novel tumor biomarkers, the actual tumor detection limits are usually unknown and there have been no studies exploring the tumor burden detection limits of blood tumor biomarkers using mathematical models. Therefore, the purpose of this study was to develop a mathematical model relating blood biomarker levels to tumor burden. METHODS AND FINDINGS: Using a linear one-compartment model, the steady state between tumor biomarker secretion into and removal out of the intravascular space was calculated. Two conditions were assumed: (1 the compartment (plasma is well-mixed and kinetically homogenous; (2 the tumor biomarker consists of a protein that is secreted by tumor cells into the extracellular fluid compartment, and a certain percentage of the secreted protein enters the intravascular space at a continuous rate. The model was applied to two pathophysiologic conditions: tumor biomarker is secreted (1 exclusively by the tumor cells or (2 by both tumor cells and healthy normal cells. To test the model, a sensitivity analysis was performed assuming variable conditions of the model parameters. The model parameters were primed on the basis of literature data for two established and well-studied tumor biomarkers (CA125 and prostate-specific antigen [PSA]. Assuming biomarker secretion by tumor cells only and 10% of the secreted tumor biomarker reaching the plasma, the calculated minimally detectable tumor sizes ranged between 0.11 mm(3 and 3,610.14 mm(3 for CA125 and between 0.21 mm(3 and 131.51 mm(3 for PSA. When biomarker secretion by healthy cells and tumor cells was assumed, the calculated tumor sizes leading to positive test results ranged

  14. Validated biomarkers: The key to precision treatment in patients with breast cancer.

    Science.gov (United States)

    Duffy, Michael J; O'Donovan, Norma; McDermott, Enda; Crown, John

    2016-10-01

    Recent DNA sequencing and gene expression studies have shown that at a molecular level, almost every case of breast cancer is unique and different from other breast cancers. For optimum management therefore, every patient should receive treatment that is guided by the molecular composition of their tumor, i.e., precision treatment. While such a scenario is still some distance into the future, biomarkers are beginning to play an important role in preparing the way for precision treatment. In particular, biomarkers are increasingly being used for predicting patient outcome and informing as to the most appropriate type of systemic therapy to be administered. Mandatory biomarkers for every newly diagnosed case of breast cancer are estrogen receptors and progesterone receptors in selecting patients for endocrine treatment and HER2 for identifying patients likely to benefit from anti-HER2 therapy. Amongst the best validated prognostic biomarker tests are uPA/PAI-1, MammaPrint and Oncotype DX. Although currently, there are no biomarkers available for predicting response to specific forms of chemotherapy, uPA/PAI-1 and Oncotype DX can aid the identification of lymph node-negative patients that are most likely to benefit from adjuvant chemotherapy, in general. In order to accelerate progress towards precision treatment for women with breast cancer, we need additional predictive biomarkers, especially for enhancing the positive predictive value for endocrine and anti-HER2 therapies, as well as biomarkers for predicting response to specific forms of chemotherapy. The ultimate biomarker test for achieving the goal of precision treatment for patients with breast cancer will likely require a combination of gene sequencing and transcriptomic analysis of every patient's tumor.

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

    Science.gov (United States)

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

    2015-02-01

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

  16. AGR3 in breast cancer: prognostic impact and suitable serum-based biomarker for early cancer detection.

    Science.gov (United States)

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

    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 (Pbreast tumours (multivariate hazard ratio: 2.186, 95% CI: 1.008-4.740, Pbreast 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.

  17. 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

  18. 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.

  19. Custom database development and biomarker discovery methods for MALDI-TOF mass spectrometry-based identification of high-consequence bacterial pathogens.

    Science.gov (United States)

    Tracz, Dobryan M; Tyler, Andrea D; Cunningham, Ian; Antonation, Kym S; Corbett, Cindi R

    2017-03-01

    A high-quality custom database of MALDI-TOF mass spectral profiles was developed with the goal of improving clinical diagnostic identification of high-consequence bacterial pathogens. A biomarker discovery method is presented for identifying and evaluating MALDI-TOF MS spectra to potentially differentiate biothreat bacteria from less-pathogenic near-neighbour species.

  20. 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.

  1. An Integrated Analysis of Heterogeneous Drug Responses in Acute Myeloid Leukemia That Enables the Discovery of Predictive Biomarkers.

    Science.gov (United States)

    Chen, Weihsu C; Yuan, Julie S; Xing, Yan; Mitchell, Amanda; Mbong, Nathan; Popescu, Andreea C; McLeod, Jessica; Gerhard, Gitte; Kennedy, James A; Bogdanoski, Goce; Lauriault, Stevan; Perdu, Sofie; Merkulova, Yulia; Minden, Mark D; Hogge, Donna E; Guidos, Cynthia; Dick, John E; Wang, Jean C Y

    2016-03-01

    Many promising new cancer drugs proceed through preclinical testing and early-phase trials only to fail in late-stage clinical testing. Thus, improved models that better predict survival outcomes and enable the development of biomarkers are needed to identify patients most likely to respond to and benefit from therapy. Here, we describe a comprehensive approach in which we incorporated biobanking, xenografting, and multiplexed phospho-flow (PF) cytometric profiling to study drug response and identify predictive biomarkers in acute myeloid leukemia (AML) patients. To test the efficacy of our approach, we evaluated the investigational JAK2 inhibitor fedratinib (FED) in 64 patient samples. FED robustly reduced leukemia in mouse xenograft models in 59% of cases and was also effective in limiting the protumorigenic activity of leukemia stem cells as shown by serial transplantation assays. In parallel, PF profiling identified FED-mediated reduction in phospho-STAT5 (pSTAT5) levels as a predictive biomarker of in vivo drug response with high specificity (92%) and strong positive predictive value (93%). Unexpectedly, another JAK inhibitor, ruxolitinib (RUX), was ineffective in 8 of 10 FED-responsive samples. Notably, this outcome could be predicted by the status of pSTAT5 signaling, which was unaffected by RUX treatment. Consistent with this observed discrepancy, PF analysis revealed that FED exerted its effects through multiple JAK2-independent mechanisms. Collectively, this work establishes an integrated approach for testing novel anticancer agents that captures the inherent variability of response caused by disease heterogeneity and in parallel, facilitates the identification of predictive biomarkers that can help stratify patients into appropriate clinical trials.

  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.

  3. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    Science.gov (United States)

    2015-10-01

    Award Number: W81XWH-10-1-0582 TITLE: ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer PRINCIPAL...ETS gene fusion status associated with clinical outcomes following radiation therapy , by analyzing both the collected biomarker and clinical data...denotes absence of an ERG fusion). ETS gene fusions status did not predict outcomes following radiation therapy , as demonstrated by Kaplan Meier

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

    OpenAIRE

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

    2014-01-01

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

  5. 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

  6. High-resolution taxonomic profiling of the subgingival microbiome for biomarker discovery and periodontitis diagnosis.

    Science.gov (United States)

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

    2015-02-01

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

  7. 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.

  8. 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.

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

    Institute of Scientific and Technical Information of China (English)

    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/Ionization Time of Flight Mass Spectrome- try (SELDI-TOF-MS). The data analyzed by both Biomarker Wizard? and Biomarker Patterns? 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 sul- fate-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 indi- viduals with sensitivity of 84.1% and specificity of 80%. These findings demonstrated that SAA could be characterized as a biomarker related to pathological stages of lung cancer.

  10. 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.

  11. 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...... were recorded at each visit to the outpatient clinic. Results. Among the 165 patients, 49 developed recurrence (R+), 107 did not (R-) and 11 developed a new primary cancer, including 2 in the R+ group. Within the 3 years of observation, 78 (47.3%) of the 165 patients underwent 117 (range 1...

  12. The Transcription Factor ZNF217 Is a Prognostic Biomarker and Therapeutic Target during Breast Cancer Progression

    Science.gov (United States)

    Littlepage, Laurie E.; Adler, Adam S.; Kouros-Mehr, Hosein; Huang, Guiqing; Chou, Jonathan; Krig, Sheryl R.; Griffith, Obi L.; Korkola, James E.; Qu, Kun; Lawson, Devon A.; Xue, Qing; Sternlicht, Mark D.; Dijkgraaf, Gerrit J. P.; Yaswen, Paul; Rugo, Hope S.; Sweeney, Colleen A.; Collins, Colin C.; Gray, Joe W.; Chang, Howard Y.; Werb, Zena

    2013-01-01

    The transcription factor ZNF217 is a candidate oncogene in the amplicon on chromosome 20q13 that occurs in 20% to 30% of primary human breast cancers and that correlates with poor prognosis. We show that Znf217 overexpression drives aberrant differentiation and signaling events, promotes increased self-renewal capacity, mesenchymal marker expression, motility, and metastasis, and represses an adult tissue stem cell gene signature downregulated in cancers. By in silico screening, we identified candidate therapeutics that at low concentrations inhibit growth of cancer cells expressing high ZNF217. We show that the nucleoside analogue triciribine inhibits ZNF217-induced tumor growth and chemotherapy resistance and inhibits signaling events [e.g., phospho-AKT, phospho-mitogen-activated protein kinase (MAPK)] in vivo. Our data suggest that ZNF217 is a biomarker of poor prognosis and a therapeutic target in patients with breast cancer and that triciribine may be part of a personalized treatment strategy in patients overexpressing ZNF217. Because ZNF217 is amplified in numerous cancers, these results have implications for other cancers. SIGNIFICANCE This study finds that ZNF217 is a poor prognostic indicator and therapeutic target in patients with breast cancer and may be a strong biomarker of triciribine treatment efficacy in patients. Because previous clinical trials for triciribine did not include biomarkers of treatment efficacy, this study provides a rationale for revisiting triciribine in the clinical setting as a therapy for patients with breast cancer who overexpress ZNF217. PMID:22728437

  13. 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.

  14. 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

  15. 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.

  16. Hierarchy of Gene Expression as a Biomarker for Breast Cancer Prognosis

    Science.gov (United States)

    Chen, Man

    2013-03-01

    Cancer is a dedifferentiation of healthy cellular and genetic processes. At the same time, specific oncological pathways are activated in the cancer state. Cancer metastasis exposes cancer cells to a variety of microenvironments, in which physics of evolution suggests modularity is a relevant order parameter. We were thus motivated to examine the structure in gene and tissue networks of breast cancer patients. We studied the relation between metastasis and breast cancer network structure. We found that hierarchy of cancer networks distinguishes non-metastatic from metastatic patient populations. We also found that for cancer-associated genes, likelihood of metastasis is correlated with increased network hierarchy. Conversely for tissue networks using all gene data, reduced network structure is correlated with likelihood of metastasis. We suggest hierarchy of gene expression may be useful as a biomarker for breast cancer breast cancer metastasis and recurrence. For those patients with reduced structure, which is at least 5% of the patient population, this biomarker provides a strong signal for likelihood of cancer metastasis.

  17. [The level of evidence for the use of biomarkers in the early detection of prostate cancer].

    Science.gov (United States)

    Lamy, Pierre-Jean; Gauchez, Anne-Sophie; Salomon, Laurent; Haugh, Margaret; Ceraline, Jocelyn; Fulla, Yvonne; Georges, Agnès; Larré, Stéphane; Loric, Sylvain; Luporsi, Elisabeth; Martin, Pierre-Marie; Mazerolles, Catherine; Molinié, Vincent; Mongiat-Artus, Pierre; Piffret, Jacques; Thuillier, François; Perrin, Paul; Rebillard, Xavier

    2016-01-01

    To systematically review the evidence for the use of PSA and other biomarkers in the early detection of prostate cancer, we searched PubMed for clinical trials and studies assessing PSA and other biomarkers in the early detection of prostate cancer, published between 2000 and May 2013 that included >200 subjects. The level of evidence (LOE) for clinical utility was evaluated using the tumor marker utility grading system. A total of 84 publications, corresponding to 70 trials and studies were selected for inclusion in this review. We attributed a level of evidence (LoE) of IA to PSA for early PCa detection, but we do not recommend its use in mass screening. Emerging biomarkers were assessed in prospective case-control and cohort studies: PCA3 (n=3); kallikreins (n=3); [-2]proPSA (n=5); fusion oncogenes (n=2). These studies used biopsy results for prostate cancer to determine specificity and sensitivity, but they did not assess the effect on PCa mortality. The LoE attributed was III-C. PSA can be used for early prostate cancer detection but mass screening is not recommended. Studies on other biomarkers suggest that they could be used, individually or in combination, to improve the selection of patients with elevated PSA levels for biopsy, but RCTs assessing their impact on prostate cancer management and mortality are needed. A better use of available tests is possible for men at risk in order to maximize the risk-benefit ratio.

  18. 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

  19. LiverCancerMarkerRIF: a liver cancer biomarker interactive curation system combining text mining and expert annotations

    Science.gov (United States)

    Dai, Hong-Jie; Wu, Johnny Chi-Yang; Lin, Wei-San; Reyes, Aaron James F.; dela Rosa, Mira Anne C.; Syed-Abdul, Shabbir; Tsai, Richard Tzong-Han; Hsu, Wen-Lian

    2014-01-01

    Biomarkers are biomolecules in the human body that can indicate disease states and abnormal biological processes. Biomarkers are often used during clinical trials to identify patients with cancers. Although biomedical research related to biomarkers has increased over the years and substantial effort has been expended to obtain results in these studies, the specific results obtained often contain ambiguities, and the results might contradict each other. Therefore, the information gathered from these studies must be appropriately integrated and organized to facilitate experimentation on biomarkers. In this study, we used liver cancer as the target and developed a text-mining–based curation system named LiverCancerMarkerRIF, which allows users to retrieve biomarker-related narrations and curators to curate supporting evidence on liver cancer biomarkers directly while browsing PubMed. In contrast to most of the other curation tools that require curators to navigate away from PubMed and accommodate distinct user interfaces or Web sites to complete the curation process, our system provides a user-friendly method for accessing text-mining–aided information and a concise interface to assist curators while they remain at the PubMed Web site. Biomedical text-mining techniques are applied to automatically recognize biomedical concepts such as genes, microRNA, diseases and investigative technologies, which can be used to evaluate the potential of a certain gene as a biomarker. Through the participation in the BioCreative IV user-interactive task, we examined the feasibility of using this novel type of augmented browsing-based curation method, and collaborated with curators to curate biomarker evidential sentences related to liver cancer. The positive feedback received from curators indicates that the proposed method can be effectively used for curation. A publicly available online database containing all the aforementioned information has been constructed at http

  20. Lung Cancer Signature Biomarkers: tissue specific semantic similarity based clustering of Digital Differential Display (DDD data

    Directory of Open Access Journals (Sweden)

    Srivastava Mousami

    2012-11-01

    Full Text Available Abstract Background The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used ‘Gene Ontology semantic similarity score’ to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal and disease (cancer sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Results Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95 identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1–4. Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1, chemotherapy/drug resistance biomarkers (panel 2, hypoxia regulated biomarkers (panel 3 and lung extra cellular matrix biomarkers (panel 4. Conclusions Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3, HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1

  1. 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.

  2. 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.

  3. 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.

  4. Cancer epigenetics drug discovery and development: the challenge of hitting the mark.

    Science.gov (United States)

    Campbell, Robert M; Tummino, Peter J

    2014-01-01

    Over the past several years, there has been rapidly expanding evidence of epigenetic dysregulation in cancer, in which histone and DNA modification play a critical role in tumor growth and survival. These findings have gained the attention of the drug discovery and development community, and offer the potential for a second generation of cancer epigenetic agents for patients following the approved "first generation" of DNA methylation (e.g., Dacogen, Vidaza) and broad-spectrum HDAC inhibitors (e.g., Vorinostat, Romidepsin). This Review provides an analysis of prospects for discovery and development of novel cancer agents that target epigenetic proteins. We will examine key examples of epigenetic dysregulation in tumors as well as challenges to epigenetic drug discovery with emerging biology and novel classes of drug targets. We will also highlight recent successes in cancer epigenetics drug discovery and consider important factors for clinical success in this burgeoning area.

  5. 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.

  6. Applying bioinformatics to proteomics: is machine learning the answer to biomarker discovery for PD and MSA?

    Science.gov (United States)

    Mattison, Hayley A; Stewart, Tessandra; Zhang, Jing

    2012-11-01

    Bioinformatics tools are increasingly being applied to proteomic data to facilitate the identification of biomarkers and classification of patients. In the June, 2012 issue, Ishigami et al. used principal component analysis (PCA) to extract features and support vector machine (SVM) to differentiate and classify cerebrospinal fluid (CSF) samples from two small cohorts of patients diagnosed with either Parkinson's disease (PD) or multiple system atrophy (MSA) based on differences in the patterns of peaks generated with matrix-assisted desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). PCA accurately segregated patients with PD and MSA from controls when the cohorts were combined, but did not perform well when segregating PD from MSA. On the other hand, SVM, a machine learning classification model, correctly classified the samples from patients with early PD or MSA, and the peak at m/z 6250 was identified as a strong contributor to the ability of SVM to distinguish the proteomic profiles of either cohort when trained on one cohort. This study, while preliminary, provides promising results for the application of bioinformatics tools to proteomic data, an approach that may eventually facilitate the ability of clinicians to differentiate and diagnose closely related parkinsonian disorders.

  7. Identification of protein biomarkers for cervical cancer using human cervicovaginal fluid.

    Directory of Open Access Journals (Sweden)

    Geert A A Van Raemdonck

    Full Text Available OBJECTIVES: Cervicovaginal fluid (CVF can be considered as a potential source of biomarkers for diseases of the lower female reproductive tract. The fluid can easily be collected, thereby offering new opportunities such as the development of self tests. Our objective was to identify a CVF protein biomarker for cervical cancer or its precancerous state. METHODS: A differential proteomics study was set up using CVF samples from healthy and precancerous women. Label-free spectral counting was applied to quantify protein abundances. RESULTS: The proteome analysis revealed 16 candidate biomarkers of which alpha-actinin-4 (p = 0.001 and pyruvate kinase isozyme M1/M2 (p = 0.014 were most promising. Verification of alpha-actinin-4 by ELISA (n = 28 showed that this candidate biomarker discriminated between samples from healthy and both low-risk and high-risk HPV-infected women (p = 0.009. Additional analysis of longitudinal samples (n = 29 showed that alpha-actinin-4 levels correlated with virus persistence and clearing, with a discrimination of approximately 18 pg/ml. CONCLUSIONS: Our results show that CVF is an excellent source of protein biomarkers for detection of lower female genital tract pathologies and that alpha-actinin-4 derived from CVF is a promising candidate biomarker for the precancerous state of cervical cancer. Further studies regarding sensitivity and specificity of this biomarker will demonstrate its utility for improving current screening programs and/or its use for a cervical cancer self-diagnosis test.

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

    Science.gov (United States)

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

  9. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy

    Science.gov (United States)

    Topalian, Suzanne L.; Taube, Janis M.; Anders, Robert A.; Pardoll, Drew M.

    2017-01-01

    With recent approvals for multiple therapeutic antibodies that block cytotoxic T lymphocyte associated antigen 4 (CTLA4) and programmed cell death protein 1 (PD1) in melanoma, non-small-cell lung cancer and kidney cancer, and additional immune checkpoints being targeted clinically, many questions still remain regarding the optimal use of drugs that block these checkpoint pathways. Defining biomarkers that predict therapeutic effects and adverse events is a crucial mandate, highlighted by recent approvals for two PDL1 diagnostic tests. Here, we discuss biomarkers for anti-PD1 therapy based on immunological, genetic and virological criteria. The unique biology of the CTLA4 immune checkpoint, compared with PD1, requires a different approach to biomarker development. Mechanism-based insights from such studies may guide the design of synergistic treatment combinations based on immune checkpoint blockade. PMID:27079802

  10. 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.

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

    NARCIS (Netherlands)

    Gemert, W.A.M. van

    2015-01-01

    Background: Postmenopausal breast cancer is the most prevalent cancer in Western women. There are several known risk factors for postmenopausal breast cancer of which few are lifestyle-related and, thereby, modifiable. These risk factors provide an opportunity for primary prevention. In this thesis,

  12. 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.

  13. Prostate Cancer in African-American Men: Serum Biomarkers for Early Detection Using Nanoparticles

    Science.gov (United States)

    2009-11-01

    sali S. Ultrasensitive Voltammetric Detection of IL-10, a Lung Cancer Biomarker, in Serum using SiO2 Nanowires Template. Sensors Lett 2007; 5:1-4. 15...chromatography cortisol and cortisone analyses before and at the end of a race in elite cyclists. Chromatography B 2005: 824, 51–6. 26. Jerkunica I...quantity of these molecules. The attempts were made to employ this effect for diagnosis of various dis- eases, including ovarian, lung , and prostate cancers

  14. 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.

  15. 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...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    BACKGROUND: Few studies have investigated the association between whole-grain intake and colorectal cancer. Because whole-grain intake estimation might be prone to measurement errors, more objective measures (eg, biomarkers) could assist in investigating such associations. METHODS: The associatio...

  17. Biomarkers in tissue from patients with upper gastrointestinal cancers treated with erlotinib and bevacizumab

    DEFF Research Database (Denmark)

    Rohrberg, Kristoffer Staal; Pappot, Helle; Lassen, Ulrik

    2011-01-01

    not be recommended in an unselected population of patients with chemo-refractory UGI cancer. However, a subpopulation of patients did benefit from the therapy. In this prospectively planned biomarker study we investigated vascular endothelial growth factor A (VEGF-A), VEGF receptor 2 (VEGFR-2) and epidermal growth...

  18. 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.

  19. 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.

  20. Serum Helicobacter pylori NapA antibody as a potential biomarker for gastric cancer.

    Science.gov (United States)

    Liu, Jingjing; Liu, Huimin; Zhang, Tingting; Ren, Xiyun; Nadolny, Christina; Dong, Xiaoqun; Huang, Lina; Yuan, Kexin; Tian, Wenjing; Jia, Yunhe

    2014-02-20

    Helicobacter pylori (H. pylori) infection is strongly associated with gastric cancer. However, only a minority of infected individuals ever develop gastric cancer. This risk stratification may be in part due to differences among strains. The relationship between neutrophil-activating protein (NapA) and gastric cancer is unclear. The purpose of this study is to evaluate the significance of NapA as a biomarker in gastric cancer. We used enzyme linked immunosorbent assay (ELISA) to determine the status of H. pylori infection. Indirect ELISA method was used for detection of NapA antibody titer in the serum of H. pylori infected individuals. Unconditional logistic regressions were adopted to analyze the variables and determine the association of NapA and gastric cancer. The results of study indicated serum H. pylori NapA antibody level were associated with a reduced risk for development of gastric cancer. It may be used in conjugation with other indicators for gastric cancer detection.

  1. Mechanisms of CTC Biomarkers in Breast Cancer Brain Metastasis

    Science.gov (United States)

    2015-10-01

    obtained at the middle of vein puncture after the first 5 ml of blood was discarded to avoid contamination by normal epithelial cells . All samples (25...Supplementary Fig. 1) in which the endomembrane furrow separates the daughter and mother cell during cell -division events18. Biomarker profiling of...gating parameters to select for DAPI− (4′ , 6-diamidino-2-phenylindole)/ EpCAM−/CD45−/CD44+/CD24− cells . Cells were then subsequently sorted to obtain

  2. Chromosomal aberrations and SCEs as biomarkers of cancer risk

    DEFF Research Database (Denmark)

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

    2006-01-01

    between CA analysis and cancer detection, i.e., is obviously not explained by undetected cancer. The present evidence indicates that both chromatid-type and chromosome-type CAs predict cancer, even though some data suggest that chromosome-type CAs may have a more pronounced predictive value than chromatid...... species. Although the association between CA level and cancer is seen at the group level, an association probably also exists for the individual, although it is not known if an individual approach could be feasible. However, group level evidence should be enough to support the use of CA analysis as a tool...

  3. Tests detecting biomarkers for screening of colorectal cancer: What is on the horizon?

    Directory of Open Access Journals (Sweden)

    Phalguni, Angaja

    2015-06-01

    Full Text Available Aim: To identify new and emerging screening tests for colorectal cancer (CRC that involves detection of various biomarkers like blood, DNA and RNA in samples of faeces, tissue or blood. Current practice: Screening for CRC can be done by bowel visualisation techniques and tests that measure biomarkers. The Bowel Cancer Screening Programme (BCSP in England uses a guaiac faecal occult blood test. Methods: The strategy was to search available literature, identify developers and contact them for relevant information. Advice from experts was sought on potential utility and likely impact of identified technologies on the BCSP.Results: Ninety-three companies and five research groups were contacted. Sixty-nine relevant tests were identified. Detailed information was available for 48 tests, of these 73% were CE marked and the remainder were considered as emerging. Forty-nine tests use immunochemical methods to detect occult blood in faeces. Eight, four and two tests detect biomarkers in a sample of blood, or exfoliated cells either shed in faeces or collected from rectal mucosa respectively. Six tests were grouped as ‘other tests’. Most of the identified tests are performed manually and give qualitative detection of biomarkers. Conclusion: Variation in test performance and characteristics was observed amongst the 69 identified tests. Automated, quantitative FIT with a variable cut off are the preferred approach in the BSCP. However the units used to report FITs results do not enable comparison across products. Tests detecting biomarkers other than occult blood are more specific to neoplasms but have limited sensitivity due to the heterogeneity of cancer. Research is ongoing to identify an optimal panel of biomarkers, simplifying and automating the test, and reducing the cost.

  4. Alterations in inflammatory biomarkers and energy intake in cancer cachexia: a prospective study in patients with inoperable pancreatic cancer.

    Science.gov (United States)

    Bye, Asta; Wesseltoft-Rao, Nima; Iversen, Per Ole; Skjegstad, Grete; Holven, Kirsten B; Ulven, Stine; Hjermstad, Marianne J

    2016-06-01

    Chronic systemic inflammatory response is proposed as an underlying mechanism for development of cancer cachexia. We conducted a prospective study to examine changes in inflammatory biomarkers during the disease course and the relationship between inflammatory biomarkers and cachexia in patients with inoperable pancreatic cancer. Twenty patients, median (range) age 67.5 (35-79) years, 5 females, were followed for median 5.5 (1-12) months. Cachexia was diagnosed according to the 2011 consensus-based classification system (weight loss >5 % past six months, BMI 2 %, or sarcopenia) and the modified Glasgow Prognostic score (mGPS) that combines CRP and albumin levels. Inflammatory biomarkers were measured by enzyme immunoassays. The patients had increased levels of most inflammatory biomarkers, albeit not all statistically significant, both at study entry and close to death, indicating ongoing inflammation. According to the consensus-based classification system, eleven (55 %) patients were classified as cachectic upon inclusion. They did not differ from non-cachectic patients with regard to inflammatory biomarkers or energy intake. According to the mGPS, seven (35 %) were defined as cachectic and had a higher IL-6 (p cachexia.

  5. Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2011-02-01

    Full Text Available Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms. Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

  6. Tissue microarrays for testing basal biomarkers in familial breast cancer cases

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    Rozany Mucha Dufloth

    Full Text Available CONTEXT AND OBJECTIVE: The proteins p63, p-cadherin and CK5 are consistently expressed by the basal and myoepithelial cells of the breast, although their expression in sporadic and familial breast cancer cases has yet to be fully defined. The aim here was to study the basal immunopro-file of a breast cancer case series using tissue microarray technology. DESIGN AND SETTING: This was a cross-sectional study at Universidade Estadual de Campinas, Brazil, and the Institute of Pathology and Mo-lecular Immunology, Porto, Portugal. METHODS: Immunohistochemistry using the antibodies p63, CK5 and p-cadherin, and also estrogen receptor (ER and Human Epidermal Receptor Growth Factor 2 (HER2, was per-formed on 168 samples from a breast cancer case series. The criteria for identifying women at high risk were based on those of the Breast Cancer Linkage Consortium. RESULTS: Familial tumors were more frequently positive for the p-cadherin (p = 0.0004, p63 (p < 0.0001 and CK5 (p < 0.0001 than was sporadic cancer. Moreover, familial tumors had coexpression of the basal biomarkers CK5+/ p63+, grouped two by two (OR = 34.34, while absence of coexpression (OR = 0.13 was associ-ated with the sporadic cancer phenotype. CONCLUSION: Familial breast cancer was found to be associated with basal biomarkers, using tissue microarray technology. Therefore, characterization of the familial breast cancer phenotype will improve the understanding of breast carcinogenesis.

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

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    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.

  8. A meta analysis of pancreatic microarray datasets yields new targets as cancer genes and biomarkers.

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    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.

  9. Serological proteome analysis of dogs with breast cancer unveils common serum biomarkers with human counterparts.

    Science.gov (United States)

    Zamani-Ahmadmahmudi, Mohamad; Nassiri, Seyed Mahdi; Rahbarghazi, Reza

    2014-03-01

    Canine mammary tumor is being touted as a model for investigating the human breast cancer. Breast cancer of the both species has similar biological behavior, histopathologic characteristics, and metastatic pattern. In this study, we used the serological proteome analysis to detect autoantigens that elicit a humoral response in dogs with mammary tumor in order to identify serum biomarkers with potential usefulness as diagnostic markers and to better understand molecular mechanisms underlying canine breast cancer development. Protein extract from a cell line was subject to 2DE followed by Western blotting using sera from 15 dogs with mammary tumor and sera from 15 healthy control dogs. Immunoreactive autoantigens were subsequently identified by the MALDI-TOF MS. Four autoantigens, including manganese-superoxide dismutase, triose phosphate isomerase, alpha-enolase, and phosphoglycerate mutase1, with significantly higher immunoreactivity in the tumor samples than in the normal samples were identified as biomarker candidates. Immunohistochemistry and Western blotting revealed higher expression of these biomarkers in the malignant tumors than in the normal or benign tumors. The autoantigens found in this study have been reported to elicit autoantibody response in the human breast cancer, indicating the similarity of breast cancer proteome profile in dogs with that in human beings.

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

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    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.

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

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    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.

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

    Science.gov (United States)

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

    2015-01-01

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

  13. 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.

  14. 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.

  15. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.

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    Elena Pereira

    Full Text Available High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential

  16. 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...

  17. A survey of immunohistochemical biomarkers for basal-like breast cancer against a gene expression profile gold standard.

    Science.gov (United States)

    Won, Jennifer R; Gao, Dongxia; Chow, Christine; Cheng, Jinjin; Lau, Sherman Y H; Ellis, Matthew J; Perou, Charles M; Bernard, Philip S; Nielsen, Torsten O

    2013-11-01

    Gene expression profiling of breast cancer delineates a particularly aggressive subtype referred to as 'basal-like', which comprises ∼15% of all breast cancers, afflicts younger women and is refractory to endocrine and anti-HER2 therapies. Immunohistochemical surrogate definitions for basal-like breast cancer, such as the clinical ER/PR/HER2 triple-negative phenotype and models incorporating positive expression for CK5 (CK5/6) and/or EGFR are heavily cited. However, many additional biomarkers for basal-like breast cancer have been described in the literature. A parallel comparison of 46 proposed immunohistochemical biomarkers of basal-like breast cancer was performed against a gene expression profile gold standard on a tissue microarray containing 42 basal-like and 80 non-basal-like breast cancer cases. Ki67 and PPH3 were the most sensitive biomarkers (both 92%) positively expressed in the basal-like subtype, whereas CK14, IMP3 and NGFR were the most specific (100%). Among biomarkers surveyed, loss of INPP4B (a negative regulator of phosphatidylinositol signaling) was 61% sensitive and 99% specific with the highest odds ratio (OR) at 108, indicating the strongest association with basal-like breast cancer. Expression of nestin, a common marker of neural progenitor cells that is also associated with the triple-negative/basal-like phenotype and poor breast cancer prognosis, possessed the second highest OR at 29 among the 46 biomarkers surveyed, as well as 54% sensitivity and 96% specificity. As a positively expressed biomarker, nestin possesses technical advantages over INPP4B that make it a more ideal biomarker for identification of basal-like breast cancer. The comprehensive immunohistochemical biomarker survey presented in this study is a necessary step for determining an optimized surrogate immunopanel that best defines basal-like breast cancer in a practical and clinically accessible way.

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

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    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

  19. 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.

  20. 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.

  1. Comparison of Predicted Probabilities of Proportional Hazards Regression and Linear Discriminant Analysis Methods Using a Colorectal Cancer Molecular Biomarker Database

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    Upender Manne

    2007-01-01

    Full Text Available Background: Although a majority of studies in cancer biomarker discovery claim to use proportional hazards regression (PHREG to the study the ability of a biomarker to predict survival, few studies use the predicted probabilities obtained from the model to test the quality of the model. In this paper, we compared the quality of predictions by a PHREG model to that of a linear discriminant analysis (LDA in both training and test set settings. Methods: The PHREG and LDA models were built on a 491 colorectal cancer (CRC patient dataset comprised of demographic and clinicopathologic variables, and phenotypic expression of p53 and Bcl-2. Two variable selection methods, stepwise discriminant analysis and the backward selection, were used to identify the final models. The endpoint of prediction in these models was five-year post-surgery survival. We also used linear regression model to examine the effect of bin size in the training set on the accuracy of prediction in the test set.Results: The two variable selection techniques resulted in different models when stage was included in the list of variables available for selection. However, the proportion of survivors and non-survivors correctly identified was identical in both of these models. When stage was excluded from the variable list, the error rate for the LDA model was 42% as compared to an error rate of 34% for the PHREG model.Conclusions: This study suggests that a PHREG model can perform as well or better than a traditional classifier such as LDA to classify patients into prognostic classes. Also, this study suggests that in the absence of the tumor stage as a variable, Bcl-2 expression is a strong prognostic molecular marker of CRC.

  2. Nestin servers as a promising prognostic biomarker in non-small cell lung cancer.

    Science.gov (United States)

    Liu, Fang; Zhang, Yuan; Lu, Ming; Wang, Cong; Li, Qingbao; Gao, Yongsheng; Mu, Dianbin; Cao, Yan; Li, Miaomiao; Meng, Xiangjiao

    2017-01-01

    Lung cancer is currently the leading cause of cancer-related death worldwide and it is important to identify the predictive and/or prognostic markers for the cancer. Nestin, a proliferative and multipotent biomarker has been reported to be associated with prognosis in non-small cell lung cancer (NSCLC) in a few studies. In the present study, we retrospectively recruited 153 patients with NSCLC. Nestin protein expression in tumor samples was determined by immunohistochemistry staining. Nestin expression was related with tumor differentiation (P=0.036), lymphatic metastasis (N stage, P=0.011), and p-TNM stage (P=0.013), while there was no significant association between Nestin expression level and age, smoking habits, gender, histologic type, and T stage. Nestin was an independent prognostic factor for overall survival in NSCLC with an adjusted hazard ratio of 2.701 (95% CI, 1.616-4.513, PCRISPR/Cas9 mediated genome editing. It was observed that knockout of Nestin caused enhancement of cancer cell apoptosis and inhibition of cell proliferation, colony formation, and invasion in A549 and H1299 cell lines. Furthermore, we examined the expression of epithelial-mesenchymal transition (EMT) related biomarkers such as E-cadherin and Vimentin in Nestin-depleted lung cancer cells and knockout of Nestin was found to inhibit EMT, suggesting the involvement of Nestin mediated EMT signaling in lung cancer. The finding above demonstrated that Nestin might serve as a prognostic factor and therapeutic target in NSCLCs.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. Blood-based protein biomarker panel for the detection of colorectal cancer.

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    Kim Y C Fung

    Full Text Available The majority of colorectal cancer (CRC cases are preventable by early detection and removal of precancerous polyps. Even though CRC is the second most common internal cancer in Australia, only 30 per cent of the population considered to have risk factors participate in stool-based test screening programs. Evidence indicates a robust, blood-based, diagnostic assay would increase screening compliance. A number of potential diagnostic blood-based protein biomarkers for CRC have been reported, but all lack sensitivity or specificity for use as a stand-alone diagnostic. The aim of this study was to identify and validate a panel of protein-based biomarkers in independent cohorts that could be translated to a reliable, non-invasive blood-based screening test.In two independent cohorts (n = 145 and n = 197, we evaluated seven single biomarkers in serum of CRC patients and age/gender matched controls that showed a significant difference between controls and CRC, but individually lack the sensitivity for diagnostic application. Using logistic regression strategies, we identified a panel of three biomarkers that discriminated between controls and CRC with 73% sensitivity at 95% specificity, when applied to either of the two cohorts. This panel comprised of Insulin like growth factor binding protein 2 (IGFBP2, Dickkopf-3 (DKK3, and Pyruvate kinase M2(PKM2.Due to the heterogeneous nature of CRC, a single biomarker is unlikely to have sufficient sensitivity or specificity for use as a stand-alone diagnostic screening test and a panel of markers may be more effective. We have identified a 3 biomarker panel that has higher sensitivity and specificity for early stage (Stage I and -II disease than the faecal occult blood test, raising the possibility for its use as a non-invasive blood diagnostic or screening test.

  8. Clinical investigation of TROP-2 as an independent biomarker and potential therapeutic target in colon cancer.

    Science.gov (United States)

    Zhao, Peng; Yu, Hai-Zheng; Cai, Jian-Hui

    2015-09-01

    Colon cancer is associated with a severe demographic and economic burden worldwide. The pathogenesis of colon cancer is highly complex and involves sequential genetic and epigenetic mechanisms. Despite extensive investigation, the pathogenesis of colon cancer remains to be elucidated. As the third most common type of cancer worldwide, the treatment options for colon cancer are currently limited. Human trophoblast cell‑surface marker (TROP‑2), is a cell‑surface transmembrane glycoprotein overexpressed by several types of epithelial carcinoma. In addition, TROP‑2 has been demonstrated to be associated with tumorigenesis and invasiveness in solid types of tumor. The aim of the present study was to investigate the protein expression of TROP‑2 in colon cancer tissues, and further explore the association between the expression of TROP‑2 and clinicopathological features of patients with colon cancer. The expression and localization of the TROP‑2 protein was examined using western blot analysis and immunofluorescence staining. Finally, the expression of TROP‑2 expression was correlated to conventional clinicopathological features of colon cancer using a χ2 test. The results revealed that TROP‑2 protein was expressed at high levels in the colon cancer tissues, which was associated with the development and pathological process of colon cancer. Therefore, TROP‑2 may be used as a biomarker to determine the clinical prognosis, and as a potential therapeutic target in colon cancer.

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

    Energy Technology Data Exchange (ETDEWEB)

    González, Maykel [Dept. of Molecular Engineering of Materials, Center of Applied Physics and Advanced Technology, National Autonomous University of Mexico (CFATA-UNAM), Boulevard Juriquilla 3001, Santiago de Querétaro, Querétaro 76230 (Mexico); Merino, Ulises [Dept. of Molecular Engineering of Materials, Center of Applied Physics and Advanced Technology, National Autonomous University of Mexico (CFATA-UNAM), Boulevard Juriquilla 3001, Santiago de Querétaro, Querétaro 76230 (Mexico); University of the Valley of Mexico (UVM), Boulevard Villas del Mesón 1000, Juriquilla, Santiago de Querétaro, Querétaro 76320 (Mexico); Vargas, Susana [Dept. of Molecular Engineering of Materials, Center of Applied Physics and Advanced Technology, National Autonomous University of Mexico (CFATA-UNAM), Boulevard Juriquilla 3001, Santiago de Querétaro, Querétaro 76230 (Mexico); Quintanilla, Francisco [University of the Valley of Mexico (UVM), Boulevard Villas del Mesón 1000, Juriquilla, Santiago de Querétaro, Querétaro 76320 (Mexico); Rodríguez, Rogelio, E-mail: rogelior@unam.mx [Dept. of Molecular Engineering of Materials, Center of Applied Physics and Advanced Technology, National Autonomous University of Mexico (CFATA-UNAM), Boulevard Juriquilla 3001, Santiago de Querétaro, Querétaro 76230 (Mexico)

    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) [Cl{sub 2}-Pt-(NH{sub 3}){sub 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. - Highlights: • A novel biocompatible hybrid porous polymer–ceramic material was synthesized. • The polymer–ceramic (HAp-based) material was used to prepare a biomarker. • The biomarker was impregnated with cis-diamine dichloride platinum (II). • The rate of cisplatin release was determined using inductively coupled plasma. • The kinetics of the cisplatin release was studied varying the biomarker porosity.

  10. 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.

  11. [The Functional Role of Exosomes in Cancer Biology and Their Potential as Biomarkers and Therapeutic Targets of Cancer].

    Science.gov (United States)

    Naito, Yutaka; Yoshioka, Yusuke; Ochiya, Takahiro

    2015-06-01

    Intercellular communication plays an important role in the regulation of various cellular events. In particular, cancer cells and the surrounding cells communicate with each other, and this intercellular communication triggers cancer initiation and progression through the secretion of molecules, including growth factors and cytokines. Recent advances in cancer biology have indicated that small membrane vesicles, termed exosomes, also serve as regulatory agents in intercellular communications. Exosomes contain functional cellular components, including proteins and microRNAs (miRNAs), and they transfer these components to recipient cells. This exosome-mediated intercellular communication leads to increased growth, invasion, and metastasis of cancer. Thus, researchers regard exosomes as important cues to understanding the molecular mechanisms of cancer biology. Indeed, several lines of evidence have demonstrated that exosomes can explain multiple aspects of cancer biology. In addition, increasing evidence suggests that exosomes and their specific molecules are also attractive for use as biomarkers and therapeutic targets in cancer. Recent reports showed the efficacy of a novel diagnosis by detecting component molecules of cancer-derived exosomes, including miRNAs and membrane proteins. Furthermore, clinical trials that test the application of exosomes for cancer therapy have already been reported. From these points of view, we will summarize experimental data that support the role of exosomes in cancer progression and the potential of exosomes for use in novel diagnostic and therapeutic approaches for cancer.

  12. 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.

  13. 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.

  14. 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.

  15. Metastin has potential as a suitable biomarker and novel effective therapy for cancer metastasis (Review).

    Science.gov (United States)

    Shoji, Sunao; Tang, Xian Yang; Sato, Haruhiro; Usui, Yukio; Uchida, Toyoaki; Terachi, Toshiro

    2010-09-01

    Cancer metastasis is a leading cause of death in cancer patients and is a multistep process involving complex interactions between tumor and host cells. To metastasize, tumor cells must invade or migrate from the primary tumor and be transported to close or distant secondary sites. A tumor cell should successfully accomplish each step of the pathway or metastasis may not develop. KiSS-1 is a human metastasis suppressor gene that inhibits metastasis of human melanomas and breast carcinomas without affecting tumorigenicity. KiSS-1 encodes a carboxy-terminally amidated peptide with 54 amino-acid residues. The peptide was isolated from human placenta as the endogenous ligand of an orphan G-protein-coupled receptor and termed 'metastin'. The literature reports metastin related to human carcinoma, such as melanoma, thyroid cancer, esophageal squamous cell carcinoma (ESCC), hepatocellular carcinoma, pancreatic carcinoma, as well as breast, ovarian, bladder and kidney cancer. These malignancies are difficult to treat and, even in early-stage cancer, a number of patients develop metastasis shortly after surgery. Studies have suggested that metastin inhibits tumor invasion or migration through focal adhesion kinase, paxillin, MAP kinase or Rho A. Additionally, metastin may be a biomarker in ESCC, pancreatic carcinoma and bladder cancer. Metastin has potential as a suitable biomarker in the identification of tumors with high metastatic potential and as a novel effective treatment modality for patients with metastasis.

  16. Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program sample subset

    Energy Technology Data Exchange (ETDEWEB)

    Metz, Thomas O.; Qian, Weijun; Jacobs, Jon M.; Gritsenko, Marina A.; Moore, Ronald J.; Polpitiya, Ashoka D.; Monroe, Matthew E.; Camp, David G.; mueller, Patricia W.; Smith, Richard D.

    2008-02-01

    Objective. Before biomarkers predictive of type 1 diabetes can be evaluated in proficiency evaluations, they must be identified and validated in initial, exploratory studies. Hypothesis-driven comparative studies may be performed to identify candidate biomarkers but are limited to the current knowledge of metabolic, signaling, and inflammatory pathways in the context of type 1 diabetes. Alternatively, untargeted “-omics” approaches may be employed in profiling studies to identify candidate biomarkers of type 1 diabetes.

  17. The Relevance of Epigenetic Biomarkers for Breast Cancer and Obesity for Personalised Treatment in Public Healthcare: A Systematic Review

    OpenAIRE

    Andrea Goettler; Haslberger, Alexander G.; Elena Ambrosino

    2016-01-01

    Background: Personalised medicine has gained attention as a result of the advances of genomic research in the last decade. This includes the rise in epigenetic research, which focuses on the environmental influences on the genome and examines biomarkers that might be useful for cancer therapy. This study investigates the epigenetic biomarkers for breast cancer and its risk factor, obesity, and evaluates their relevance for global public health. Methods: A systematic search of articles pub...

  18. What are the reasons for low use of graphene quantum dots in immunosensing of cancer biomarkers?

    Science.gov (United States)

    Hasanzadeh, Mohammad; Shadjou, Nasrin

    2017-02-01

    Graphene quantum dots-based immunosensors have recently gained importance for detecting antigens and biomarkers responsible for cancer diagnosis. This paper reports a literature survey of the applications of graphene quantum dots for sensing cancer biomarkers. The survey sought to explore three questions: (1) Do graphene quantum dots improve immunosensing technology? (2) If so, can graphene quantum dots have a critical, positive impact on construction of immuno-devices? And (3) What is the reason for some troubles in the application of this technology? The number of published papers in the field seems positively answer the first two questions. However additional efforts must be made to move from the bench to the real diagnosis. Some approaches to improve the analytical performance of graphene quantum dots-based immunosensors through their figures of merit have been also discussed.

  19. Circulating free DNA as biomarker and source for mutation detection in metastatic colorectal cancer

    DEFF Research Database (Denmark)

    Spindler, Karen Lise Garm; Pallisgaard, Niels; Andersen, Rikke Fredslund

    2015-01-01

    BACKGROUND: Circulating cell-free DNA (cfDNA) in plasma has shown potential as biomarker in various cancers and could become an importance source for tumour mutation detection. The objectives of our study were to establish a normal range of cfDNA in a cohort of healthy individuals and to compare...... this with four cohorts of metastatic colorectal cancer (mCRC) patients. We also investigated the prognostic value of cfDNA and analysed the tumour-specific KRAS mutations in the plasma. METHODS: The study was a prospective biomarker evaluation in four consecutive Phase II trials, including 229 patients...... the prognostic value of cfDNA measurement in plasma and utility for mutation detection with the method presented....

  20. Discovery of protein profiles for differentiated thyroid cancer using SELDI TOF MS

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Joon Kee; Lee, Myung Hoon; Joh, Chul Woo; Yoon, Seok Nam; Soh, Eui Young [College of Medicine, Univ. of Ajou, Suwon (Korea, Republic of)

    2003-07-01

    Low sensitivity of diagnostic whole body iodine scintigraphy and intermediate range of serum thyroglobulin (Tg) with or without anti-Tg antibody make it difficult to select the patients with differentiated thyroid cancer who need further treatment. Surfaced Enhanced Laser Desorption /Ionization - Time of Flight - Mass Spectrometry (SELDI TOF MS) is a useful method to evaluate cancer proteome, biomarkers and patterns of biomarkers. In this preliminary study, we evaluated and developed protein profiles for the discrimination between patients with differentiated thyroid cancer and non-cancer controls using SELDI technology. Serum samples from 10 healthy controls and from 14 patients with papillary thyroid cancer before thyroidectomy were analyzed by SELDI MS. Multiple protein peaks detected were analyzed by the computer software to develop a classifier for separating cancer patients form controls. The classifier was then challenged to 24 serum samples to determine the validity and accuracy of the classification system. All patients with papillary thyroid cancer had no other concomitant cancer or thyroiditis. Their serum Tg concentration was 55.8 (1.5 - 249.7) and 2 patients had extra-thyroidal extension. According to the SELDI analysis, protein peaks at 3696 Da, 4178 Da, and 8149 Da were more prominent in cancer patients than controls in various degrees. Among those, protein peak at 4178 Da was determined as classifier by computer software, and the sensitivity, specificity and accuracy for discrimination of cancer patients from controls was 92.9% (13/14), 90% (9/10) and 91.7% respectively. This preliminary study suggests that serum protein profiles of differentiated thyroid cancer can be used for differentiation between cancer patients and non-cancer controls. And further clinical studies in various test sets will offer useful information in selecting patients who require treatment.

  1. 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.

  2. Blood-Based Biomarkers for Lung Cancer Early Detection and Evaluation of CT-Based Lesions

    Science.gov (United States)

    2013-12-01

    normal bronchial epithelia from patients with NSCLC as well as in one high-risk patient with chronic obstructive pulmonary disease (Figure 3c...high-risk chronic obstructive pulmonary disease (COPD) patient is indicated (*), and positive (H1395) and negative (HCC-2935) controls are shown. EYA4...Cancer, Early Detection, MicroRNA , Gene expression, Genomics, Blood test, Biomarkers 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT

  3. A novel proteomic biomarker panel as a diagnostic tool for patients with ovarian cancer

    DEFF Research Database (Denmark)

    Høgdall, Claus; Fung, Eric T; Christensen, Ib J;

    2011-01-01

    Previous reports have shown that the proteomic markers apolipoprotein A1, hepcidin, transferrin, inter-alpha trypsin IV internal fragment, transthyretin, connective-tissue activating protein 3 and beta-2 microglobulin may discriminate between a benign pelvic mass and ovarian cancer (OC). The aim...... was to determine if these serum proteomic biomarkers alone as well as in combination with age and serum CA125, could be helpful in triage of women with a pelvic mass....

  4. 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 ...

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

    Directory of Open Access Journals (Sweden)

    Lucia Perez-Carbonell

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

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

    Science.gov (United States)

    2015-10-01

    biomarkers to determine the presence of or progression to aggressive disease. ( Lead site: FHCRC) Milestone 2. Execute collaboration agreement with...panel of four-kallikrein plasma-based markers to determine the presence of or progression to clinically relevant prostate cancer. ( Lead site: FHCRC... Lead site: FHCRC) Milestone 10. Urine specimens identified for analysis. Due 12/30/2014 COMPLETED Milestone 11. PCA3 and TMPRSS2:ERG validation

  7. Biomarkers in Veterinary Medicine.

    Science.gov (United States)

    Myers, Michael J; Smith, Emily R; Turfle, Phillip G

    2017-02-08

    This article summarizes the relevant definitions related to biomarkers; reviews the general processes related to biomarker discovery and ultimate acceptance and use; and finally summarizes and reviews, to the extent possible, examples of the types of biomarkers used in animal species within veterinary clinical practice and human and veterinary drug development. We highlight opportunities for collaboration and coordination of research within the veterinary community and leveraging of resources from human medicine to support biomarker discovery and validation efforts for veterinary medicine.

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

    Science.gov (United States)

    Hu, Zhi [El Cerrito, CA; Kuo, Wen-Lin [San Ramon, CA; Neve, Richard M [San Mateo, CA; Gray, Joe W [San Francisco, CA

    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.

  9. 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.

  10. Comparison of protein, microRNA, and mRNA yields using different methods of urinary exosome isolation for the discovery of kidney disease biomarkers.

    Science.gov (United States)

    Alvarez, M Lucrecia; Khosroheidari, Mahdieh; Kanchi Ravi, Rupesh; DiStefano, Johanna K

    2012-11-01

    Urinary exosomes are 40-100 nm vesicles containing protein, mRNA, and microRNA that may serve as biomarkers of renal dysfunction and structural injury. Currently, there is a need for more sensitive and specific biomarkers of renal injury and disease progression. Here we sought to identify the best exosome isolation methods for both proteomic analysis and RNA profiling as a first step for biomarker discovery. We used six different protocols; three were based on ultracentrifugation, one used a nanomembrane concentrator-based approach, and two utilized a commercial exosome precipitation reagent. The highest yield of exosomes was obtained using a modified exosome precipitation protocol, which also yielded the highest quantities of microRNA and mRNA and, therefore, is ideal for subsequent RNA profiling. This method is likewise suitable for downstream proteomic analyses if an ultracentrifuge is not available and/or a large number of samples are to be processed. Two of the ultracentrifugation methods, however, are better options for exosome isolation if an ultracentrifuge is available and few samples will be processed for proteomic analysis. Thus, our modified exosome precipitation method is a simple, fast, highly scalable, and effective alternative for the isolation of exosomes, and may facilitate the identification of exosomal biomarkers from urine.

  11. 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.

  12. Biomarkers in the Detection of Prostate Cancer in African Americans

    Science.gov (United States)

    2015-09-01

    hypermethylation with silencing of specific genes. 15. SUBJECT TERMS Prostate cancer, molecular markers, racial differences, active surveillance 16...SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a. REPORT U b. ABSTRACT U c...the biology of PrCa in AAs and this lack of knowledge can limit therapeutic options for AAs with PrCa, especially the choice of active surveillance

  13. Impact of biospecimens handling on biomarker research in breast cancer

    Directory of Open Access Journals (Sweden)

    Callari Maurizio

    2009-11-01

    Full Text Available Abstract Background Gene expression profiling is moving from the research setting to the practical clinical use. Gene signatures able to correctly identify high risk breast cancer patients as well as to predict response to treatment are currently under intense investigation. While technical issues dealing with RNA preparation, choice of array platforms, statistical analytical tools are taken into account, the tissue collection process is seldom considered. The time elapsed between surgical tissue removal and freezing of samples for biological characterizations is rarely well defined and/or recorded even for recently stored samples, despite the publications of standard operating procedures for biological sample collection for tissue banks. Methods Breast cancer samples from 11 patients were collected immediately after surgical removal and subdivided into aliquots. One was immediately frozen and the others were maintained at room temperature for respectively 2, 6 and 24 hrs. RNA was extracted and gene expression profile was determined using cDNA arrays. Phosphoprotein profiles were studied in parallel. Results Delayed freezing affected the RNA quality only in 3 samples, which were not subjected to gene profiling. In the 8 breast cancer cases with apparently intact RNA also in sample aliquots frozen at delayed times, 461 genes were modulated simply as a function of freezing timing. Some of these genes were included in gene signatures biologically and clinically relevant for breast cancer. Delayed freezing also affected detection of phosphoproteins, whose pattern may be crucial for clinical decision on target-directed drugs. Conclusion Time elapsed between surgery and freezing of samples appears to have a strong impact and should be considered as a mandatory variable to control for clinical implications of inadequate tissue handling.

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

    Science.gov (United States)

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

    2016-12-01

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

  15. Glypican-1 as a Biomarker for Prostate Cancer: Isolation and Characterization.

    Science.gov (United States)

    Truong, Quach; Justiniano, Irene O; Nocon, Aline L; Soon, Julie T; Wissmueller, Sandra; Campbell, Douglas H; Walsh, Bradley J

    2016-01-01

    Prostate cancer is the most frequently diagnosed male visceral cancer and the second leading cause of cancer death in the United States. Standard tests such as prostate-specific antigen (PSA) measurement have poor specificity (33%) resulting in a high number of false positive reports. Consequently there is a need for new biomarkers to address this problem. The MIL-38 antibody was first described nearly thirty years ago, however, until now, the identification of the target antigen remained elusive. By a series of molecular techniques and mass spectrometry, the MIL-38 antigen was identified to be the highly glycosylated proteoglycan Glypican-1 (GPC-1). This protein is present in two forms; a membrane bound core protein of 55-60 kDa and secreted soluble forms of 40 kDa and 52 kDa. GPC-1 identification was confirmed by immuno-precipitation, western blots and ELISA. An ELISA platform is currently being developed to assess the levels of GPC-1 in normal, benign prostatic hyperplasia (BPH) and prostate cancer patients to determine whether secreted GPC-1 may represent a clinically relevant biomarker for prostate cancer diagnosis.

  16. 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.

  17. Sensitive multiplex detection of serological liver cancer biomarkers using SERS-active photonic crystal fiber probe.

    Science.gov (United States)

    Dinish, U S; Balasundaram, Ghayathri; Chang, Young Tae; Olivo, Malini

    2014-11-01

    Surface-enhanced Raman scattering (SERS) spectroscopy possesses the most promising advantage of multiplex detection for biosensing applications, which is achieved due to the narrow 'fingerprint' Raman spectra from the analyte molecules. We developed an ultrasensitive platform for the multiplex detection of cancer biomarkers by combining the SERS technique with a hollow-core photonic crystal fiber (HCPCF). Axially aligned air channels inside the HCPCF provide an excellent platform for optical sensing using SERS. In addition to the flexibility of optical fibers, HCPCF provides better light confinement and a larger interaction length for the guided light and the analyte, resulting in an improvement in sensitivity to detect low concentrations of bioanalytes in extremely low sample volumes. Herein, for the first time, we demonstrate the sensitive multiplex detection of biomarkers immobilized inside the HCPCF using antibody-conjugated SERS-active nanoparticles (SERS nanotags). As a proof-of-concept for targeted multiplex detection, initially we carried out the sensing of epidermal growth factor receptor (EGFR) biomarker in oral squamous carcinoma cell lysate using three different SERS nanotags. Subsequently, we also achieved simultaneous detection of hepatocellular carcinoma (HCC) biomarkers-alpha fetoprotein (AFP) and alpha-1-antitrypsin (A1AT) secreted in the supernatant from Hep3b cancer cell line. Using a SERS-HCPCF sensing platform, we could successfully demonstrate the multiplex detection in an extremely low sample volume of ∼20 nL. In future, this study may lead to sensitive biosensing platform for the low concentration detection of biomarkers in an extremely low sample volume of body fluids to achieve early diagnosis of multiple diseases. (© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

  18. 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.

  19. 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

  20. PTRF/cavin-1 and MIF proteins are identified as non-small cell lung cancer biomarkers by label-free proteomics.

    Directory of Open Access Journals (Sweden)

    Angelo Gámez-Pozo

    Full Text Available 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.

  1. Metallothionein - immunohistochemical cancer biomarker: a meta-analysis.

    Directory of Open Access Journals (Sweden)

    Jaromir Gumulec

    Full Text Available Metallothionein (MT has been extensively investigated as a molecular marker of various types of cancer. In spite of the fact that numerous reviews have been published in this field, no meta-analytical approach has been performed. Therefore, results of to-date immunohistochemistry-based studies were summarized using meta-analysis in this review. Web of science, PubMed, Embase and CENTRAL databases were searched (up to April 30, 2013 and the eligibility of individual studies and heterogeneity among the studies was assessed. Random and fixed effects model meta-analysis was employed depending on the heterogeneity, and publication bias was evaluated using funnel plots and Egger's tests. A total of 77 studies were included with 8,015 tissue samples (4,631 cases and 3,384 controls. A significantly positive association between MT staining and tumors (vs. healthy tissues was observed in head and neck (odds ratio, OR 9.95; 95% CI 5.82-17.03 and ovarian tumors (OR 7.83; 1.09-56.29, and a negative association was ascertained in liver tumors (OR 0.10; 0.03-0.30. No significant associations were identified in breast, colorectal, prostate, thyroid, stomach, bladder, kidney, gallbladder, and uterine cancers and in melanoma. While no associations were identified between MT and tumor staging, a positive association was identified with the tumor grade (OR 1.58; 1.08-2.30. In particular, strong associations were observed in breast, ovarian, uterine and prostate cancers. Borderline significant association of metastatic status and MT staining were determined (OR 1.59; 1.03-2.46, particularly in esophageal cancer. Additionally, a significant association between the patient prognosis and MT staining was also demonstrated (hazard ratio 2.04; 1.47-2.81. However, a high degree of inconsistence was observed in several tumor types, including colorectal, kidney and prostate cancer. Despite the ambiguity in some tumor types, conclusive results are provided in the tumors of

  2. Quantitative optical biomarkers of lung cancer based intrinsic two-photon excited fluorescence signal

    Science.gov (United States)

    Li, Jingwen; Zhan, Zhenlin; Lin, Hongxin; Zuo, Ning; Zhu, Xiaoqin; Xie, Shusen; Chen, Jianxin; Zhuo, Shuangmu

    2016-10-01

    Alterations in the elastic fibers have been implicated in lung cancer. However, the label-free, microscopic imaging of elastic fibers in situ remains a major challenge. Here, we present the use of intrinsic two-photon excited fluorescence (TPEF) signal as a novel means for quantification of the elastic fibers in intact fresh human lung tissues. We obtained the TPEF images of elastic fibers from ex vivo the human lung tissues. We found that three features, including the elastic fibers area, the elastic fibers orientation, the elastic fibers structure, provide the quantitative identification of lung cancer and the direct visual cues for cancer versus non-cancer areas. These results suggest that the TPEF signal can be used as the label-free optical biomarkers for rapid clinical lung diagnosis and instant image-guided surgery.

  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. 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.

  6. IL-8 as a urinary biomarker for the detection of bladder cancer

    Directory of Open Access Journals (Sweden)

    Urquidi Virginia

    2012-05-01

    Full Text Available Abstract Background Current urine-based assays for bladder cancer (BCa diagnosis lack accuracy, so the search for improved biomarkers continues. Through genomic and proteomic profiling of urine, we have identified a panel of biomarkers associated with the presence of BCa. In this study, we evaluated the utility of three of these biomarkers, interleukin 8 (IL-8, Matrix metallopeptidase 9 (MMP-9 and Syndecan in the diagnosis of BCa through urinalysis. Methods Voided urines from 127 subjects, cancer subjects (n = 64, non-cancer subjects (n = 63 were analyzed. The protein concentrations of IL-8, MMP-9, and Syndecan were assessed by enzyme-linked immunosorbent assay (ELISA. Data were also compared to a commercial ELISA-based BCa detection assay (BTA-Trak© and urinary cytology. We used the area under the curve of a receiver operating characteristic (AUROC to compare the performance of each biomarker. Results Urinary protein concentrations of IL-8, MMP-9 and BTA were significantly elevated in BCa subjects. Of the experimental markers compared to BTA-Trak©, IL-8 was the most prominent marker (AUC; 0.79; 95% confidence interval [CI], 0.72-0.86. Multivariate regression analysis revealed that only IL-8 (OR; 1.51; 95% CI, 1.16-1.97, p = 0.002 was an independent factor for the detection of BCa. Conclusions These results suggest that the measurement of IL-8 in voided urinary samples may have utility for urine-based detection of BCa. These findings need to be confirmed in a larger, prospective cohort.

  7. Correlations between diffusion-weighted imaging and breast cancer biomarkers

    Energy Technology Data Exchange (ETDEWEB)

    Martincich, Laura; Deantoni, Veronica; Bertotto, Ilaria; Liotti, Michele; Regge, Daniele [Unit of Radiology, Institute for Cancer Research and Treatment (IRCC), Candiolo, Turin (Italy); Redana, Stefania; Rossi, Valentina; Aglietta, Massimo; Montemurro, Filippo [Institute for Cancer Research and Treatment (IRCC), Division of Medical Oncology, Candiolo, Turin (Italy); Kubatzki, Franziska; Ponzone, Riccardo [Institute for Cancer Research and Treatment (IRCC), Division of Gynecological Oncology, Candiolo, Turin (Italy); Sarotto, Ivana [Unit of Pathology, Institute for Cancer Research and Treatment (IRCC), Candiolo, Turin (Italy)

    2012-07-15

    We evaluated whether the apparent diffusion coefficient (ADC) provided by diffusion-weighted imaging (DWI) varies according to biological features in breast cancer. DWI was performed in 190 patients undergoing dynamic contrast-enhanced magnetic resonance imaging (MRI) for local staging. For each of the 192 index cancers we studied the correlation between ADC and classical histopathological and immunohistochemical breast tumour features (size, histological type, grade, oestrogen receptor [ER] and Ki-67 expression, HER2 status). ADC was compared with immunohistochemical surrogates of the intrinsic subtypes (Luminal A; Luminal B; HER2-enriched; triple-negative). Correlations were analysed using the Mann-Whitney U and Kruskal-Wallis H tests. A weak, statistically significant correlation was observed between ADC values and the percentage of ER-positive cells (-0.168, P = 0.020). Median ADC values were significantly higher in ER-negative than in ER-positive tumours (1.110 vs 1.050 x 10{sup -3} mm{sup 2}/s, P = 0.015). HER2-enriched tumours had the highest median ADC value (1.190 x 10{sup -3} mm{sup 2}/s, range 0.950-2.090). Multiple comparisons showed that this value was significantly higher than that of Luminal A (1.025 x 10{sup -3} mm{sup 2}/s [0.700-1.340], P = 0.004) and Luminal B/HER2-negative (1.060 x 10{sup -3} mm{sup 2}/s [0.470-2.420], P = 0.008) tumours. A trend towards statistical significance (P = 0.018) was seen with Luminal B/HER2-positive tumours. ADC values vary significantly according to biological tumour features, suggesting that cancer heterogeneity influences imaging parameters. (orig.)

  8. Biomolecular characterization of exosomes released from cancer stem cells: Possible implications for biomarker and treatment of cancer.

    Science.gov (United States)

    Kumar, Dhruv; Gupta, Dwijendra; Shankar, Sharmila; Srivastava, Rakesh K

    2015-02-20

    Cancer recognized as one of the leading irrepressible health issues is contributing to increasing mortality-rate day-by-day. The tumor microenvironment is an important field of cancer to understand the detection, treatment and prevention of cancer. Recently, cancer stem cell (CSC) research has shown promising results aiming towards cancer diagnostics and treatment. Here, we found that prostate and breast cancer stem cells secreted vesicles of endosomal origin, called exosomes showed strong connection between autophagy and exosomes released from CSCs. Exosomes may serve as vesicles to communicate with neoplastic cells (autocrine and paracrine manner) and normal cells (paracrine and endocrine manner) and thereby suppress immune systems and regulate neoplastic growth, and metastasis. They can also be used as biomarkers for various cancers. We detected tetraspanin proteins (CD9, CD63, CD81), Alix and tumor susceptibility gene-101 (TSG101) of exosomal markers from rotenone treated CSCs. We have also detected the induction of autophagy genes, Atg7 and conversion of autophagy marker (LC3-I to LC3-II), and tetraspanin proteins (CD9, CD63, CD81) in rotenone treated CSCs by western blotting. The mRNA expression of CD9, CD63, CD81 and TSG101 analyzed by qRT-PCR showed that the rotenone induced the expression of CD9, CD63, CD81 and TSG101 in CSCs. Electron microscopy of rotenone treated CSCs showed the mitochondrial damage of CSCs as confirmed by the release of exosomes from CSCs. The constituents of exosomes may be useful to understand the mechanism of exosomes formation, release and function, and also serve as a useful biomarker and provide novel therapeutic strategies for the treatment and prevention of cancer.

  9. 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.

  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. Multiplexed cancer biomarker detection using quartz-based photonic crystal surfaces.

    Science.gov (United States)

    Huang, Cheng-Sheng; Chaudhery, Vikram; Pokhriyal, Anusha; George, Sherine; Polans, James; Lu, Meng; Tan, Ruimin; Zangar, Richard C; Cunningham, Brian T

    2012-01-17

    A photonic crystal (PC) surface is demonstrated as a high-sensitivity platform for detection of a panel of 21 cancer biomarker antigens using a sandwich enzyme-linked immunosorbent assay (ELISA) microarray format. A quartz-based PC structure fabricated by nanoimprint lithography, selected for its low autofluorescence, supports two independent optical resonances that simultaneously enable enhancement of fluorescence detection of biomarkers and label-free quantification of the density of antibody capture spots. A detection instrument is demonstrated that supports fluorescence and label-free imaging modalities, with the ability to optimize the fluorescence enhancement factor on a pixel-by-pixel basis throughout the microarray using an angle-scanning approach for the excitation laser that automatically compensates for variability in surface chemistry density and capture spot density. Measurements show that the angle-scanning illumination approach reduces the coefficient of variation of replicate assays by 20-99% compared to ordinary fluorescence microscopy, thus supporting reduction in limits of detectable biomarker concentration. Using the PC resonance, biomarkers in mixed samples were detectable at the lowest concentrations tested (2.1-41 pg/mL), resulting in a three-log range of quantitative detection.

  12. Angiopoietin-like protein 2 as a potential biomarker for colorectal cancer

    Science.gov (United States)

    YOSHINAGA, TAKUMA; SHIGEMITSU, TAKAMASA; NISHIMATA, HIROTO; KITAZONO, MASAKI; HORI, EMIKO; TOMIYOSHI, AYAKO; TAKEI, TAKAYUKI; YOSHIDA, MASAHIRO

    2015-01-01

    Colorectal cancer (CRC) is the third most common malignancy worldwide. Disease progression leads to its spread to other organs, such as the liver, and is associated with higher mortality rates. Early CRC detection is therefore crucial for maximizing the chances of complete cure. The measurement of serum-based tumor biomarkers has shown great potential for the detection of CRC. In this study, we investigated the feasibility of using angiopoietin-like protein 2 (ANGPTL2) as a candidate biomarker for CRC. We first investigated ANGPTL2 expression in 7 CRC cell lines, among which Colo320, NCC-CoCK-115P, Caco-2 and Colo205 exhibited comparatively high ANGPTL2 expression. The serum levels of ANGPTL2 in CRC patients (3.45±1.30 ng/ml) were higher compared with those in healthy controls (2.74±0.64 ng/ml) (P<0.05). A receiver operating characteristic analysis demonstrated that the diagnostic performance of ANGPTL2 was marginally lower compared with that of the established biomarker C-reactive protein, but higher compared with that of carbohydrate antigen 19-9. These results suggested that the simultaneous measurement of ANGPTL2, along with previously established serum biomarkers, may increase the likelihood of early detection of CRC. PMID:26623054

  13. 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.

  14. Discovery – Lung Cancer Screening Saves Lives: The NLST

    Science.gov (United States)

    NCI funded the National Lung Screening Trial, an eight-year study that used new technology to detect small, aggressive tumors early enough to surgically remove them. This approach reduced lung cancer deaths among participants by 20 percent.

  15. Discovery – BRCA Connection to Breast and Ovarian Cancer

    Science.gov (United States)

    NCI-funded research helped identify inherited BRCA1 and BRCA2 genetic mutations and their connection to breast and ovarian cancer. From this research, a screening test was also developed to help patients make informed decisions about their health.

  16. Network-based drugs and biomarkers

    DEFF Research Database (Denmark)

    Erler, Janine Terra; Linding, Rune

    2010-01-01

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

  17. 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

  18. 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.

  19. In vitro cultured lung cancer cells are not suitable for animal-based breath biomarker detection.

    Science.gov (United States)

    Schallschmidt, Kristin; Becker, Roland; Zwaka, Hanna; Menzel, Randolf; Johnen, Dorothea; Fischer-Tenhagen, Carola; Rolff, Jana; Nehls, Irene

    2015-02-10

    In vitro cultured lung cancer cell lines were investigated regarding the possible identification of volatile organic compounds as potential biomarkers. Gas samples from the headspace of pure culture medium and from the cultures of human lung adenocarcinoma cell lines A549 and Lu7466 were exposed to polypropylene fleece in order to absorb odour components. Sniffer dogs were trained with loaded fleeces of both cell lines, and honey bees were trained with fleeces exposed to A549. Afterwards, their ability to distinguish between cell-free culture medium odour and lung cancer cell odour was tested. Neither bees nor dogs were able to discriminate between odours from the cancer cell cultures and the pure culture medium. Solid phase micro extraction followed by gas chromatography with mass selective detection produced profiles of volatiles from the headspace offered to the animals. The profiles from the cell lines were largely similar; distinct differences were based on the decrease of volatile culture medium components due to the cells' metabolic activity. In summary, cultured lung cancer cell lines do not produce any biomarkers recognizable by animals or gas chromatographic analysis.

  20. 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.

  1. A pilot study to explore circulating tumour cells in pancreatic cancer as a novel biomarker

    Science.gov (United States)

    Khoja, L; Backen, A; Sloane, R; Menasce, L; Ryder, D; Krebs, M; Board, R; Clack, G; Hughes, A; Blackhall, F; Valle, J W; Dive, C

    2012-01-01

    Background: Obtaining tissue for pancreatic carcinoma diagnosis and biomarker assessment to aid drug development is challenging. Circulating tumour cells (CTCs) may represent a potential biomarker to address these unmet needs. We compared prospectively the utility of two platforms for CTC enumeration and characterisation in pancreatic cancer patients in a pilot exploratory study. Patients and methods: Blood samples were obtained prospectively from 54 consenting patients and analysed by CellSearch and isolation by size of epithelial tumour cells (ISET). CellSearch exploits immunomagnetic capture of CTCs-expressing epithelial markers, whereas ISET is a marker independent, blood filtration device. Circulating tumour cell expression of epithelial and mesenchymal markers was assessed to explore any discrepancy in CTC number between the two platforms. Results: ISET detected CTCs in more patients than CellSearch (93% vs 40%) and in higher numbers (median CTCs/7.5 ml, 9 (range 0–240) vs 0 (range 0–144)). Heterogeneity observed for epithelial cell adhesion molecule, pan-cytokeratin (CK), E-Cadherin, Vimentin and CK 7 expression in CTCs may account for discrepancy in CTC number between platforms. Conclusion: ISET detects more CTCs than CellSearch and offers flexible CTC characterisation with potential to investigate CTC biology and develop biomarkers for pancreatic cancer patient management. PMID:22187035

  2. Detection of label-free cancer biomarkers using nickel nanoislands and quartz crystal microbalance.

    Science.gov (United States)

    Martínez-Rivas, Adrián; Chinestra, Patrick; Favre, Gilles; Pinaud, Sébastien; Séverac, Childérick; Faye, Jean-Charles; Vieu, Christophe

    2010-09-07

    We present a technique for the label-free detection and recognition of cancer biomarkers using metal nanoislands intended to be integrated in a novel type of nanobiosensor. His-tagged (scFv)-F7N1N2 is the antibody fragment which is directly immobilized, by coordinative bonds, onto ~5 nm nickel islands, then deposited on the surface of a quartz crystal of a quartz crystal microbalance (QCM) to validate the technique. Biomarker GTPase RhoA was investigated because it has been found to be overexpressed in various tumors and because we have recently isolated and characterized a new conformational scFv which selectively recognizes the active form of RhoA. We implemented a surface chemistry involving an antibiofouling coating of polyethylene glycol silane (PEG-silane) (<2 nm thick) and Ni nanoislands to reach a label-free detection of the active antigen conformation of RhoA, at various concentrations. The methodology proposed here proves the viability of the concept by using Ni nanoislands as an anchoring surface layer enabling the detection of a specific conformation of a protein, identified as a potential cancer biomarker. Hence, this novel methodology can be transferred to a nanobiosensor to detect, at lower time consumption and with high sensitivity, specific biomolecules.

  3. 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

  4. Nestin servers as a promising prognostic biomarker in non-small cell lung cancer

    Science.gov (United States)

    Liu, Fang; Zhang, Yuan; Lu, Ming; Wang, Cong; Li, Qingbao; Gao, Yongsheng; Mu, Dianbin; Cao, Yan; Li, Miaomiao; Meng, Xiangjiao

    2017-01-01

    Lung cancer is currently the leading cause of cancer-related death worldwide and it is important to identify the predictive and/or prognostic markers for the cancer. Nestin, a proliferative and multipotent biomarker has been reported to be associated with prognosis in non-small cell lung cancer (NSCLC) in a few studies. In the present study, we retrospectively recruited 153 patients with NSCLC. Nestin protein expression in tumor samples was determined by immunohistochemistry staining. Nestin expression was related with tumor differentiation (P=0.036), lymphatic metastasis (N stage, P=0.011), and p-TNM stage (P=0.013), while there was no significant association between Nestin expression level and age, smoking habits, gender, histologic type, and T stage. Nestin was an independent prognostic factor for overall survival in NSCLC with an adjusted hazard ratio of 2.701 (95% CI, 1.616-4.513, Pcell proliferation, colony formation, invasion, and apoptosis by knockout of Nestin with a new developed method, CRISPR/Cas9 mediated genome editing. It was observed that knockout of Nestin caused enhancement of cancer cell apoptosis and inhibition of cell proliferation, colony formation, and invasion in A549 and H1299 cell lines. Furthermore, we examined the expression of epithelial-mesenchymal transition (EMT) related biomarkers such as E-cadherin and Vimentin in Nestin-depleted lung cancer cells and knockout of Nestin was found to inhibit EMT, suggesting the involvement of Nestin mediated EMT signaling in lung cancer. The finding above demonstrated that Nestin might serve as a prognostic factor and therapeutic target in NSCLCs.

  5. Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

    Science.gov (United States)

    Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

    2016-10-20

    The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

  6. 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

  7. 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.

  8. 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.

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

    DEFF Research Database (Denmark)

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

    2003-01-01

    The application of state-of-the-art proteomics and functional genomics technologies to the study of cancer is rapidly shifting toward the analysis of clinically relevant samples derived from patients, as the ultimate aim of translational research is to bring basic discoveries closer to the bedsid...

  10. 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

  11. SHOX2 DNA Methylation is a Biomarker for the diagnosis of lung cancer based on bronchial aspirates

    Directory of Open Access Journals (Sweden)

    Liloglou Triantafillos

    2010-11-01

    Full Text Available Abstract Background This study aimed to show that SHOX2 DNA methylation is a tumor marker in patients with suspected lung cancer by using bronchial fluid aspirated during bronchoscopy. Such a biomarker would be clinically valuable, especially when, following the first bronchoscopy, a final diagnosis cannot be established by histology or cytology. A test with a low false positive rate can reduce the need for further invasive and costly procedures and ensure early treatment. Methods Marker discovery was carried out by differential methylation hybridization (DMH and real-time PCR. The real-time PCR based HeavyMethyl technology was used for quantitative analysis of DNA methylation of SHOX2 using bronchial aspirates from two clinical centres in a case-control study. Fresh-frozen and Saccomanno-fixed samples were used to show the tumor marker performance in different sample types of clinical relevance. Results Valid measurements were obtained from a total of 523 patient samples (242 controls, 281 cases. DNA methylation of SHOX2 allowed to distinguish between malignant and benign lung disease, i.e. abscesses, infections, obstructive lung diseases, sarcoidosis, scleroderma, stenoses, at high specificity (68% sensitivity [95% CI 62-73%], 95% specificity [95% CI 91-97%]. Conclusions Hypermethylation of SHOX2 in bronchial aspirates appears to be a clinically useful tumor marker for identifying subjects with lung carcinoma, especially if histological and cytological findings after bronchoscopy are ambiguous.

  12. Absolute Quantification of Choline-Related Biomarkers in Breast Cancer Biopsies by Liquid Chromatography Electrospray Ionization Mass Spectrometry

    Directory of Open Access Journals (Sweden)

    Maria Chiara Mimmi

    2013-01-01

    Full Text Available It has been repeatedly demonstrated that choline metabolism is altered in a wide variety of cancers. In breast tumours, the choline metabolite profile is characterized by an elevation of phosphocholine and total choline-compounds. This pattern is increasingly being exploited as biomarker in cancer diagnosis.

  13. 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.

  14. Plasma and EBC microRNAs as early biomarkers of non-small-cell lung cancer.

    Science.gov (United States)

    Mozzoni, Paola; Banda, Iris; Goldoni, Matteo; Corradi, Massimo; Tiseo, Marcello; Acampa, Olga; Balestra, Valeria; Ampollini, Luca; Casalini, Angelo; Carbognani, Paolo; Mutti, Antonio

    2013-12-01

    Lung cancer is a major cause of death in Western countries. Current screening methods are invasive and still lead to a high percentage of false positives. There is, therefore, a need to find biomarkers that increase the probability of detecting lung cancer early. MicroRNAs (miRNAs) are stable molecules in blood plasma and exhaled breath condensate (EBC). We quantified miRNA-21 and miRNA-486 expression from plasma and EBC samples from patients with a diagnosis of non-small-cell lung cancer (NSCLC) and controls. miRNA-21 was significantly higher in plasma and in EBC of the NSCLC patients and miRNA-486 was significantly lower. This difference indicates a significantly improved diagnostic value, and suggests that these miRNAs could be clinically used as a first-line screening test in high-risk subjects.

  15. 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.

  16. Discovery of a selective irreversible BMX inhibitor for prostate cancer.

    Science.gov (United States)

    Liu, Feiyang; Zhang, Xin; Weisberg, Ellen; Chen, Sen; Hur, Wooyoung; Wu, Hong; Zhao, Zheng; Wang, Wenchao; Mao, Mao; Cai, Changmeng; Simon, Nicholas I; Sanda, Takaomi; Wang, Jinhua; Look, A Thomas; Griffin, James D; Balk, Steven P; Liu, Qingsong; Gray, Nathanael S

    2013-07-19

    BMX is a member of the TEC family of nonreceptor tyrosine kinases. We have used structure-based drug design in conjunction with kinome profiling to develop a potent, selective, and irreversible BMX kinase inhibitor, BMX-IN-1, which covalently modifies Cys496. BMX-IN-1 inhibits the proliferation of Tel-BMX-transformed Ba/F3 cells at two digit nanomolar concentrations but requires single digit micromolar concentrations to inhibit the proliferation of prostate cancer cell lines. Using a combinatorial kinase inhibitor screening strategy, we discovered that the allosteric Akt inhibitor, MK2206, is able to potentiate BMX inhibitor's antiproliferation efficacy against prostate cancer cells.

  17. Prediction of lung cancer based on serum biomarkers by gene expression programming methods.

    Science.gov (United States)

    Yu, Zhuang; Chen, Xiao-Zheng; Cui, Lian-Hua; Si, Hong-Zong; Lu, Hai-Jiao; Liu, Shi-Hai

    2014-01-01

    In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are frequently- used lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.

  18. 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 Qu