Proteomic and metabolomic approaches to biomarker discovery

CERN Document Server

Issaq, Haleem J

2013-01-01

Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

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

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Łukasz Pietrzyk

2016-01-01

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

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

Science.gov (United States)

Pietrzyk, Łukasz

2016-01-01

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

Recent mass spectrometry-based proteomics for biomarker discovery in lung cancer, COPD, and asthma.

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Fujii, Kiyonaga; Nakamura, Haruhiko; Nishimura, Toshihide

2017-04-01

Lung cancer and related diseases have been one of the most common causes of deaths worldwide. Genomic-based biomarkers may hardly reflect the underlying dynamic molecular mechanism of functional protein interactions, which is the center of a disease. Recent developments in mass spectrometry (MS) have made it possible to analyze disease-relevant proteins expressed in clinical specimens by proteomic challenges. Areas covered: To understand the molecular mechanisms of lung cancer and its subtypes, chronic obstructive pulmonary disease (COPD), asthma and others, great efforts have been taken to identify numerous relevant proteins by MS-based clinical proteomic approaches. Since lung cancer is a multifactorial disease that is biologically associated with asthma and COPD among various lung diseases, this study focused on proteomic studies on biomarker discovery using various clinical specimens for lung cancer, COPD, and asthma. Expert commentary: MS-based exploratory proteomics utilizing clinical specimens, which can incorporate both experimental and bioinformatic analysis of protein-protein interaction and also can adopt proteogenomic approaches, makes it possible to reveal molecular networks that are relevant to a disease subgroup and that could differentiate between drug responders and non-responders, good and poor prognoses, drug resistance, and so on.

Cancer biomarker discovery: the entropic hallmark.

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Berretta, Regina; Moscato, Pablo

2010-08-18

It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles

Convergence of biomarkers, bioinformatics and nanotechnology for individualized cancer treatment

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

2013-01-01

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

Systems biology and biomarker discovery

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Rodland, Karin D.

2010-12-01

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

Other biomarkers for detecting prostate cancer.

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Nogueira, Lucas; Corradi, Renato; Eastham, James A

2010-01-01

Prostate-specific antigen (PSA) has been used for detecting prostate cancer since 1994. Although it is the best cancer biomarker available, PSA is not perfect. It lacks both the sensitivity and specificity to accurately detect the presence of prostate cancer. None of the PSA thresholds currently in use consistently identify patients with prostate cancer and exclude patients without cancer. Novel approaches to improve our ability to detect prostate cancer and predict the course of the disease are needed. Additional methods for detecting prostate cancer have been evaluated. Despite the discovery of many new biomarkers, only a few have shown some clinical value. These markers include human kallikrein 2, urokinase-type plasminogen activator receptor, prostate-specific membrane antigen, early prostate cancer antigen, PCA3, alpha-methylacyl-CoA racemase and glutathione S-transferase pi hypermethylation. We review the reports on biomarkers for prostate cancer detection, and their possible role in the clinical practice.

Sample preparation and fractionation for proteome analysis and cancer biomarker discovery by mass spectrometry.

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Ahmed, Farid E

2009-03-01

Sample preparation and fractionation technologies are one of the most crucial processes in proteomic analysis and biomarker discovery in solubilized samples. Chromatographic or electrophoretic proteomic technologies are also available for separation of cellular protein components. There are, however, considerable limitations in currently available proteomic technologies as none of them allows for the analysis of the entire proteome in a simple step because of the large number of peptides, and because of the wide concentration dynamic range of the proteome in clinical blood samples. The results of any undertaken experiment depend on the condition of the starting material. Therefore, proper experimental design and pertinent sample preparation is essential to obtain meaningful results, particularly in comparative clinical proteomics in which one is looking for minor differences between experimental (diseased) and control (nondiseased) samples. This review discusses problems associated with general and specialized strategies of sample preparation and fractionation, dealing with samples that are solution or suspension, in a frozen tissue state, or formalin-preserved tissue archival samples, and illustrates how sample processing might influence detection with mass spectrometric techniques. Strategies that dramatically improve the potential for cancer biomarker discovery in minimally invasive, blood-collected human samples are also presented.

Averaged differential expression for the discovery of biomarkers in the blood of patients with prostate cancer.

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V Uma Bai

Full Text Available The identification of a blood-based diagnostic marker is a goal in many areas of medicine, including the early diagnosis of prostate cancer. We describe the use of averaged differential display as an efficient mechanism for biomarker discovery in whole blood RNA. The process of averaging reduces the problem of clinical heterogeneity while simultaneously minimizing sample handling.RNA was isolated from the blood of prostate cancer patients and healthy controls. Samples were pooled and subjected to the averaged differential display process. Transcripts present at different levels between patients and controls were purified and sequenced for identification. Transcript levels in the blood of prostate cancer patients and controls were verified by quantitative RT-PCR. Means were compared using a t-test and a receiver-operating curve was generated. The Ring finger protein 19A (RNF19A transcript was identified as having higher levels in prostate cancer patients compared to healthy men through the averaged differential display process. Quantitative RT-PCR analysis confirmed a more than 2-fold higher level of RNF19A mRNA levels in the blood of patients with prostate cancer than in healthy controls (p = 0.0066. The accuracy of distinguishing cancer patients from healthy men using RNF19A mRNA levels in blood as determined by the area under the receiving operator curve was 0.727.Averaged differential display offers a simplified approach for the comprehensive screening of body fluids, such as blood, to identify biomarkers in patients with prostate cancer. Furthermore, this proof-of-concept study warrants further analysis of RNF19A as a clinically relevant biomarker for prostate cancer detection.

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

Biomarkers in cancer screening: a public health perspective.

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Srivastava, Sudhir; Gopal-Srivastava, Rashmi

2002-08-01

definitive technology, such as CT scan. The National Cancer Institute's Early Detection Research Network (EDRN) has begun an innovative, investigator-initiated project to improve methods for detecting the biomarkers of cancer cells. The EDRN is a consortium of more than 32 institutions to link discovery of biomarkers to the next steps in the process of developing early detection tests. These discoveries will lead to early clinical validation of tests with improved accuracy and reliability.

Biomarkers: in medicine, drug discovery, and environmental health

National Research Council Canada - National Science Library

Vaidya, Vishal S; Bonventre, Joseph V

2010-01-01

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

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

DEFF Research Database (Denmark)

Schmitt, Manfred; Harbeck, Nadia; Brünner, Nils

2011-01-01

Clinical research on cancer biomarkers is essential in understanding recent discoveries in cancer biology and heterogeneity of the cancer disease. However, there are only a few examples of clinically useful studies that have identified cancer biomarkers with clinical benefit. Urokinase-type plasm...

Quantitative proteomic analysis of microdissected oral epithelium for cancer biomarker discovery.

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Xiao, Hua; Langerman, Alexander; Zhang, Yan; Khalid, Omar; Hu, Shen; Cao, Cheng-Xi; Lingen, Mark W; Wong, David T W

2015-11-01

Specific biomarkers are urgently needed for the detection and progression of oral cancer. The objective of this study was to discover cancer biomarkers from oral epithelium through utilizing high throughput quantitative proteomics approaches. Morphologically malignant, epithelial dysplasia, and adjacent normal epithelial tissues were laser capture microdissected (LCM) from 19 patients and used for proteomics analysis. Total proteins from each group were extracted, digested and then labelled with corresponding isobaric tags for relative and absolute quantitation (iTRAQ). Labelled peptides from each sample were combined and analyzed by liquid chromatography-mass spectrometry (LC-MS/MS) for protein identification and quantification. In total, 500 proteins were identified and 425 of them were quantified. When compared with adjacent normal oral epithelium, 17 and 15 proteins were consistently up-regulated or down-regulated in malignant and epithelial dysplasia, respectively. Half of these candidate biomarkers were discovered for oral cancer for the first time. Cornulin was initially confirmed in tissue protein extracts and was further validated in tissue microarray. Its presence in the saliva of oral cancer patients was also explored. Myoglobin and S100A8 were pre-validated by tissue microarray. These data demonstrated that the proteomic biomarkers discovered through this strategy are potential targets for oral cancer detection and salivary diagnostics. Copyright © 2015 Elsevier Ltd. All rights reserved.

State of the Art in Tumor Antigen and Biomarker Discovery

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Even-Desrumeaux, Klervi; Baty, Daniel; Chames, Patrick

2011-01-01

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

Systems Biology Modeling of the Radiation Sensitivity Network: A Biomarker Discovery Platform

International Nuclear Information System (INIS)

Eschrich, Steven; Zhang Hongling; Zhao Haiyan; Boulware, David; Lee, Ji-Hyun; Bloom, Gregory; Torres-Roca, Javier F.

2009-01-01

Purpose: The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials: Radiosensitivity, as represented by the survival fraction at 2 Gy was modeled in 48 human cancer cell lines. We applied a linear regression algorithm that integrates gene expression with biological variables, including ras status (mut/wt), tissue of origin and p53 status (mut/wt). Results: The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression analysis. This network was reduced to a 10-hub network that includes c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1, and IRF1. Nine targets associated with radiosensitization drugs are linked to the network, demonstrating clinical relevance. Furthermore, the model identified four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis, as was the tissue of origin, and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included DNA repair, cell cycle, apoptosis, and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon, and breast cancers. Conclusion: We have developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We believe this platform will play a central role in the integration of biology into clinical radiation oncology practice.

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

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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

2009-01-01

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

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

DNA Methylation Biomarkers: Cancer and Beyond

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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.

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.

Mass Spectrometry-Based Biomarker Discovery.

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Zhou, Weidong; Petricoin, Emanuel F; Longo, Caterina

2017-01-01

The discovery of candidate biomarkers within the entire proteome is one of the most important and challenging goals in proteomic research. Mass spectrometry-based proteomics is a modern and promising technology for semiquantitative and qualitative assessment of proteins, enabling protein sequencing and identification with exquisite accuracy and sensitivity. For mass spectrometry analysis, protein extractions from tissues or body fluids and subsequent protein fractionation represent an important and unavoidable step in the workflow for biomarker discovery. Following extraction of proteins, the protein mixture must be digested, reduced, alkylated, and cleaned up prior to mass spectrometry. The aim of our chapter is to provide comprehensible and practical lab procedures for sample digestion, protein fractionation, and subsequent mass spectrometry analysis.

Mass spectrometry for protein quantification in biomarker discovery.

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Wang, Mu; You, Jinsam

2012-01-01

Major technological advances have made proteomics an extremely active field for biomarker discovery in recent years due primarily to the development of newer mass spectrometric technologies and the explosion in genomic and protein bioinformatics. This leads to an increased emphasis on larger scale, faster, and more efficient methods for detecting protein biomarkers in human tissues, cells, and biofluids. Most current proteomic methodologies for biomarker discovery, however, are not highly automated and are generally labor-intensive and expensive. More automation and improved software programs capable of handling a large amount of data are essential to reduce the cost of discovery and to increase throughput. In this chapter, we discuss and describe mass spectrometry-based proteomic methods for quantitative protein analysis.

Glycoscience aids in biomarker discovery

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

2012-06-01

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

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

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

2017-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-07-19

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

Biomarker discovery in mass spectrometry-based urinary proteomics.

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

2016-04-01

Urinary proteomics has become one of the most attractive topics in disease biomarker discovery. MS-based proteomic analysis has advanced continuously and emerged as a prominent tool in the field of clinical bioanalysis. However, only few protein biomarkers have made their way to validation and clinical practice. Biomarker discovery is challenged by many clinical and analytical factors including, but not limited to, the complexity of urine and the wide dynamic range of endogenous proteins in the sample. This article highlights promising technologies and strategies in the MS-based biomarker discovery process, including study design, sample preparation, protein quantification, instrumental platforms, and bioinformatics. Different proteomics approaches are discussed, and progresses in maximizing urinary proteome coverage and standardization are emphasized in this review. MS-based urinary proteomics has great potential in the development of noninvasive diagnostic assays in the future, which will require collaborative efforts between analytical scientists, systems biologists, and clinicians. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

The role of pancreatic cancer-derived exosomes in cancer progress and their potential application as biomarkers.

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Jin, H; Wu, Y; Tan, X

2017-08-01

Pancreatic cancer is one of the most deadly cancers, with dismal prognosis due to its poor early detection rate and high metastatic rate. Thus, elucidation of the molecular mechanisms accounting for its metastasis and discovery of competent biomarkers is required. Exosomes are multivesicular body-derived small extracellular vesicles released by various cell types that serve as important message carriers during intercellular communication. They are also known to play critical roles during cancer-genesis, cancer-related immune reactions, and metastasis. They also possess promising potential as novel biomarkers for cancer early detection. Therefore, extensive studies on pancreatic cancer-derived exosomes are currently being performed because they hold the promising potential of elevating the overall survival rate of patients with pancreatic cancer. In the present review, we focus on the role of exosomes in pancreatic cancer-related immune reactions, metastasis, and complications, and on their potential application as pancreatic cancer biomarkers.

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

International Nuclear Information System (INIS)

Yang, Xu; Lazar, Iulia M

2009-01-01

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

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

International Nuclear Information System (INIS)

Mannello, Ferdinando; Ligi, Daniela

2013-01-01

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

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

Directory of Open Access Journals (Sweden)

Jianwen She

2013-09-01

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

Integrative analysis to select cancer candidate biomarkers to targeted validation

Science.gov (United States)

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

2015-01-01

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

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,

Mass Spectrometry–Based Biomarker Discovery: Toward a Global Proteome Index of Individuality

Science.gov (United States)

Hawkridge, Adam M.; Muddiman, David C.

2011-01-01

Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry–based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed. PMID:20636062

Biomarker Gene Signature Discovery Integrating Network Knowledge

Directory of Open Access Journals (Sweden)

Holger Fröhlich

2012-02-01

Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

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

Science.gov (United States)

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

2014-07-01

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

The application of mass-spectrometry-based protein biomarker discovery to theragnostics

OpenAIRE

Street, Jonathan M; Dear, James W

2010-01-01

Over the last decade rapid developments in mass spectrometry have allowed the identification of multiple proteins in complex biological samples. This proteomic approach has been applied to biomarker discovery in the context of clinical pharmacology (the combination of biomarker and drug now being termed ‘theragnostics’). In this review we provide a roadmap for early protein biomarker discovery studies, focusing on some key questions that regularly confront researchers.

Key drivers of biomedical innovation in cancer drug discovery

OpenAIRE

Huber, Margit A; Kraut, Norbert

2014-01-01

Discovery and translational research has led to the identification of a series of ?cancer drivers??genes that, when mutated or otherwise misregulated, can drive malignancy. An increasing number of drugs that directly target such drivers have demonstrated activity in clinical trials and are shaping a new landscape for molecularly targeted cancer therapies. Such therapies rely on molecular and genetic diagnostic tests to detect the presence of a biomarker that predicts response. Here, we highli...

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

Prognostic Biomarkers Used for Localised Prostate Cancer Management: A Systematic Review.

Science.gov (United States)

Lamy, Pierre-Jean; Allory, Yves; Gauchez, Anne-Sophie; Asselain, Bernard; Beuzeboc, Philippe; de Cremoux, Patricia; Fontugne, Jacqueline; Georges, Agnès; Hennequin, Christophe; Lehmann-Che, Jacqueline; Massard, Christophe; Millet, Ingrid; Murez, Thibaut; Schlageter, Marie-Hélène; Rouvière, Olivier; Kassab-Chahmi, Diana; Rozet, François; Descotes, Jean-Luc; Rébillard, Xavier

2017-03-07

Prostate cancer stratification is based on tumour size, pretreatment PSA level, and Gleason score, but it remains imperfect. Current research focuses on the discovery and validation of novel prognostic biomarkers to improve the identification of patients at risk of aggressive cancer or of tumour relapse. This systematic review by the Intergroupe Coopérateur Francophone de Recherche en Onco-urologie (ICFuro) analysed new evidence on the analytical validity and clinical validity and utility of six prognostic biomarkers (PHI, 4Kscore, MiPS, GPS, Prolaris, Decipher). All available data for the six biomarkers published between January 2002 and April 2015 were systematically searched and reviewed. The main endpoints were aggressive prostate cancer prediction, additional value compared to classical prognostic parameters, and clinical benefit for patients with localised prostate cancer. The preanalytical and analytical validations were heterogeneous for all tests and often not adequate for the molecular signatures. Each biomarker was studied for specific indications (candidates for a first or second biopsy, and potential candidates for active surveillance, radical prostatectomy, or adjuvant treatment) for which the level of evidence (LOE) was variable. PHI and 4Kscore were the biomarkers with the highest LOE for discriminating aggressive and indolent tumours in different indications. Blood biomarkers (PHI and 4Kscore) have the highest LOE for the prediction of more aggressive prostate cancer and could help clinicians to manage patients with localised prostate cancer. The other biomarkers show a potential prognostic value; however, they should be evaluated in additional studies to confirm their clinical validity. We reviewed studies assessing the value of six prognostic biomarkers for prostate cancer. On the basis of the available evidence, some biomarkers could help in discriminating between aggressive and non-aggressive tumours with an additional value compared to the

Searching for new biomarkers in ovarian cancer patients

DEFF Research Database (Denmark)

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

2017-01-01

, will be examined. Relevant microRNAs and DNA methylation patterns will be investigated using array technology. Patient exomes will be fully sequenced, and identified genetic variations will be validated with Next Generation Sequencing. In all cases, data will be correlated with clinical information on the patient...... of cancer and the discovery of new drugs. Moreover, biomarkers are a prerequisite for the development of precision medicine. This study will attack the ovarian cancer problem from several angles, thereby increasing the chance of successfully contributing to saving lives....

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.

SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

Science.gov (United States)

Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

2018-03-20

The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

Mass spectrometry based biomarker discovery, verification, and validation--quality assurance and control of protein biomarker assays.

Science.gov (United States)

Parker, Carol E; Borchers, Christoph H

2014-06-01

In its early years, mass spectrometry (MS)-based proteomics focused on the cataloging of proteins found in different species or different tissues. By 2005, proteomics was being used for protein quantitation, typically based on "proteotypic" peptides which act as surrogates for the parent proteins. Biomarker discovery is usually done by non-targeted "shotgun" proteomics, using relative quantitation methods to determine protein expression changes that correlate with disease (output given as "up-or-down regulation" or "fold-increases"). MS-based techniques can also perform "absolute" quantitation which is required for clinical applications (output given as protein concentrations). Here we describe the differences between these methods, factors that affect the precision and accuracy of the results, and some examples of recent studies using MS-based proteomics to verify cancer-related biomarkers. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Metabolomics for Biomarker Discovery: Moving to the Clinic

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

NARCIS (Netherlands)

N.Q. Liu (Ning Qing); R.B.H. Braakman (René); C. Stingl (Christoph); T.M. Luider (Theo); J.W.M. Martens (John); J.A. Foekens (John); A. Umar (Arzu)

2012-01-01

textabstractMass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while

Current Stem Cell Biomarkers and Their Functional Mechanisms in Prostate Cancer

Directory of Open Access Journals (Sweden)

Kaile Zhang

2016-07-01

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

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics.

Science.gov (United States)

Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

2016-09-01

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

Directory of Open Access Journals (Sweden)

Larry Gold

2010-12-01

Full Text Available The interrogation of proteomes ("proteomics" in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine.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.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 generation of evidence-based medicine.

Aptamer-based multiplexed proteomic technology for biomarker discovery.

Science.gov (United States)

Gold, Larry; Ayers, Deborah; Bertino, Jennifer; Bock, Christopher; Bock, Ashley; Brody, Edward N; Carter, Jeff; Dalby, Andrew B; Eaton, Bruce E; Fitzwater, Tim; Flather, Dylan; Forbes, Ashley; Foreman, Trudi; Fowler, Cate; Gawande, Bharat; Goss, Meredith; Gunn, Magda; Gupta, Shashi; Halladay, Dennis; Heil, Jim; Heilig, Joe; Hicke, Brian; Husar, Gregory; Janjic, Nebojsa; Jarvis, Thale; Jennings, Susan; Katilius, Evaldas; Keeney, Tracy R; Kim, Nancy; Koch, Tad H; Kraemer, Stephan; Kroiss, Luke; Le, Ngan; Levine, Daniel; Lindsey, Wes; Lollo, Bridget; Mayfield, Wes; Mehan, Mike; Mehler, Robert; Nelson, Sally K; Nelson, Michele; Nieuwlandt, Dan; Nikrad, Malti; Ochsner, Urs; Ostroff, Rachel M; Otis, Matt; Parker, Thomas; Pietrasiewicz, Steve; Resnicow, Daniel I; Rohloff, John; Sanders, Glenn; Sattin, Sarah; Schneider, Daniel; Singer, Britta; Stanton, Martin; Sterkel, Alana; Stewart, Alex; Stratford, Suzanne; Vaught, Jonathan D; Vrkljan, Mike; Walker, Jeffrey J; Watrobka, Mike; Waugh, Sheela; Weiss, Allison; Wilcox, Sheri K; Wolfson, Alexey; Wolk, Steven K; Zhang, Chi; Zichi, Dom

2010-12-07

The interrogation of proteomes ("proteomics") in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology and medicine. 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. 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 generation of evidence-based medicine.

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

The path from biomarker discovery to regulatory qualification

CERN Document Server

Goodsaid, Federico

2013-01-01

The Path from Biomarker Discovery to Regulatory Qualification is a unique guide that focuses on biomarker qualification, its history and current regulatory settings in both the US and abroad. This multi-contributed book provides a detailed look at the next step to developing biomarkers for clinical use and covers overall concepts, challenges, strategies and solutions based on the experiences of regulatory authorities and scientists. Members of the regulatory, pharmaceutical and biomarker development communities will benefit the most from using this book-it is a complete and practical guide to biomarker qualification, providing valuable insight to an ever-evolving and important area of regulatory science. For complimentary access to chapter 13, 'Classic' Biomarkers of Liver Injury, by John R. Senior, Associate Director for Science, Food and Drug Administration, Silver Spring, Maryland, USA, please visit the following site:  http://tinyurl.com/ClassicBiomarkers Contains a collection of experiences of different...

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...

Proteome analysis of body fluids for amyotrophic lateral sclerosis biomarker discovery.

Science.gov (United States)

Krüger, Thomas; Lautenschläger, Janin; Grosskreutz, Julian; Rhode, Heidrun

2013-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder of motor neurons leading to death of the patients, mostly within 2-5 years after disease onset. The pathomechanism of motor neuron degeneration is only partially understood and therapeutic strategies based on mechanistic insights are largely ineffective. The discovery of reliable biomarkers of disease diagnosis and progression is the sine qua non of both the revelation of insights into the ALS pathomechanism and the assessment of treatment efficacies. Proteomic approaches are an important pillar in ALS biomarker discovery. Cerebrospinal fluid is the most promising body fluid for differential proteome analyses, followed by blood (serum, plasma), and even urine and saliva. The present study provides an overview about reported peptide/protein biomarker candidates that showed significantly altered levels in certain body fluids of ALS patients. These findings have to be discussed according to proposed pathomechanisms to identify modifiers of disease progression and to pave the way for the development of potential therapeutic strategies. Furthermore, limitations and advantages of proteomic approaches for ALS biomarker discovery in different body fluids and reliable validation of biomarker candidates have been addressed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Inflammatory biomarkers and cancer

DEFF Research Database (Denmark)

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

2017-01-01

and previous cancer diagnoses compared to patients who were not diagnosed with cancer. Previous cancer, C-reactive protein (CRP) and suPAR were significantly associated with newly diagnosed cancer during follow-up in multiple logistic regression analyses adjusted for age, sex and CRP. Neither any of the PRRs......In Denmark, patients with serious nonspecific symptoms and signs of cancer (NSSC) are referred to the diagnostic outpatient clinics (DOCs) where an accelerated cancer diagnostic program is initiated. Various immunological and inflammatory biomarkers have been associated with cancer, including...... soluble urokinase plasminogen activator receptor (suPAR) and the pattern recognition receptors (PRRs) pentraxin-3, mannose-binding lectin, ficolin-1, ficolin-2 and ficolin-3. We aimed to evaluate these biomarkers and compare their diagnostic ability to classical biomarkers for diagnosing cancer...

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

Science.gov (United States)

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

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.

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.

Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

Directory of Open Access Journals (Sweden)

Oguzhan Begik

2017-07-01

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

Three-Dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation.

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Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W Andy

2016-11-30

Glycoproteins have vast structural diversity that plays an important role in many biological processes and have great potential as disease biomarkers. Here, we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase glycoprotein array (polyGPA), to capture and profile glycoproteomes specifically, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture preoxidized glycans on glycoproteins from complex protein samples such as biofluids. The captured glycoproteins were subsequently detected using the same validated antibodies as in RPPA. We demonstrated the outstanding specificity, sensitivity, and quantitative capabilities of polyGPA by capturing and detecting purified as well as endogenous α-1-acid glycoprotein (AGP) in human plasma. We further applied quantitative N-glycoproteomics and the strategy to validate a panel of glycoproteins identified as potential biomarkers for bladder cancer by analyzing urine glycoproteins from bladder cancer patients or matched healthy individuals.

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

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

DEFF Research Database (Denmark)

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

2017-01-01

Tumor recurrence remains the main reason for breast cancer-associated mortality, and there are unmet clinical demands for the discovery of new biomarkers and development of treatment solutions to benefit patients with breast cancer at high risk of recurrence. Here we report the identification of ...

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

Science.gov (United States)

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

2004-01-01

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

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.

Circulating exosomes and exosomal microRNAs as biomarkers in gastrointestinal cancer.

Science.gov (United States)

Nedaeinia, R; Manian, M; Jazayeri, M H; Ranjbar, M; Salehi, R; Sharifi, M; Mohaghegh, F; Goli, M; Jahednia, S H; Avan, A; Ghayour-Mobarhan, M

2017-02-01

The most important biological function of exosomes is their possible use as biomarkers in clinical diagnosis. Compared with biomarkers identified in conventional specimens such as serum or urine, exosomal biomarkers provide the highest amount of sensitivity and specificity, which can be attributed to their excellent stability. Exosomes, which harbor different types of proteins, nucleic acids and lipids, are present in almost all bodily fluids. The molecular constituents of exosomes, especially exosomal proteins and microRNAs (miRNAs), are promising as biomarkers in clinical diagnosis. This discovery that exosomes also contain messenger RNAs and miRNAs shows that they could be carriers of genetic information. Although the majority of RNAs found in exosomes are degraded RNA fragments with a length of exosomal miRNAs have been found to be associated with certain diseases. Several studies have pointed out miRNA contents of circulating exosomes that are similar to those of originating cancer cells. In this review, the recent advances in circulating exosomal miRNAs as biomarkers in gastrointestinal cancers are discussed. These studies indicated that miRNAs can be detected in exosomes isolated from body fluids such as saliva, which suggests potential advantages of using exosomal miRNAs as noninvasive novel biomarkers.

Biomarkers of HIV-associated Cancer

OpenAIRE

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

2014-01-01

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

Biomarkers of cancer cachexia.

Science.gov (United States)

Loumaye, Audrey; Thissen, Jean-Paul

2017-12-01

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

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

KAUST Repository

Kaur, Mandeep; MacPherson, Cameron R; Schmeier, Sebastian; Narasimhan, Kothandaraman; Choolani, Mahesh; Bajic, Vladimir B.

2011-01-01

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.

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.

Mass spectrometry imaging enriches biomarker discovery approaches with candidate mapping.

Science.gov (United States)

Scott, Alison J; Jones, Jace W; Orschell, Christie M; MacVittie, Thomas J; Kane, Maureen A; Ernst, Robert K

2014-01-01

Integral to the characterization of radiation-induced tissue damage is the identification of unique biomarkers. Biomarker discovery is a challenging and complex endeavor requiring both sophisticated experimental design and accessible technology. The resources within the National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Consortium, Medical Countermeasures Against Radiological Threats (MCART), allow for leveraging robust animal models with novel molecular imaging techniques. One such imaging technique, MALDI (matrix-assisted laser desorption ionization) mass spectrometry imaging (MSI), allows for the direct spatial visualization of lipids, proteins, small molecules, and drugs/drug metabolites-or biomarkers-in an unbiased manner. MALDI-MSI acquires mass spectra directly from an intact tissue slice in discrete locations across an x, y grid that are then rendered into a spatial distribution map composed of ion mass and intensity. The unique mass signals can be plotted to generate a spatial map of biomarkers that reflects pathology and molecular events. The crucial unanswered questions that can be addressed with MALDI-MSI include identification of biomarkers for radiation damage that reflect the response to radiation dose over time and the efficacy of therapeutic interventions. Techniques in MALDI-MSI also enable integration of biomarker identification among diverse animal models. Analysis of early, sublethally irradiated tissue injury samples from diverse mouse tissues (lung and ileum) shows membrane phospholipid signatures correlated with histological features of these unique tissues. This paper will discuss the application of MALDI-MSI for use in a larger biomarker discovery pipeline.

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

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Venugopal Abhilash

2009-01-01

Full Text Available Mass spectrometry-based quantitative proteomics has emerged as a powerful approach that has the potential to accelerate biomarker discovery, both for diagnostic as well as therapeutic purposes. Proteomics has traditionally been synonymous with 2D gels but is increasingly shifting to the use of gel-free systems and liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS. Quantitative proteomic approaches have already been applied to investigate various neurological disorders, especially in the context of identifying biomarkers from cerebrospinal fluid and serum. This review highlights the scope of different applications of quantitative proteomics in understanding neurological disorders with special emphasis on biomarker discovery.

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

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Julie L. Hentze

2017-12-01

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

Profiling of circulating microRNAs for prostate cancer biomarker discovery

DEFF Research Database (Denmark)

Haldrup, Christa; Kosaka, Nobuyoshi; Ochiya, Takahiro

2014-01-01

Prostate cancer (PC) is the most frequent cancer in men in the Western world. Currently, serum prostate-specific antigen levels and digital rectal examinations are used to indicate the need for diagnostic prostate biopsy, but lack in specificity and sensitivity. Thus, many men undergo unnecessary...... performed genome-wide miRNA profiling of serum samples from 13 benign prostatic hyperplasia (BPH) control patients and 31 PC patients. Furthermore, we carefully reviewed the literature on circulating miRNA biomarkers for PC. Our results confirmed the de-regulation of miR-141 and miR-375, two of the most...... well-documented candidate miRNA markers for PC. Moreover, we identified several new potential serum miRNA markers for PC and developed three novel and highly specific (100 %) miRNA candidate marker panels able to identify 84 % of all PC patients (miR-562/miR-210/miR-501-3p/miR-375/miR-551b), 80...

Biomarkers: Delivering on the expectation of molecularly driven, quantitative health.

Science.gov (United States)

Wilson, Jennifer L; Altman, Russ B

2018-02-01

Biomarkers are the pillars of precision medicine and are delivering on expectations of molecular, quantitative health. These features have made clinical decisions more precise and personalized, but require a high bar for validation. Biomarkers have improved health outcomes in a few areas such as cancer, pharmacogenetics, and safety. Burgeoning big data research infrastructure, the internet of things, and increased patient participation will accelerate discovery in the many areas that have not yet realized the full potential of biomarkers for precision health. Here we review themes of biomarker discovery, current implementations of biomarkers for precision health, and future opportunities and challenges for biomarker discovery. Impact statement Precision medicine evolved because of the understanding that human disease is molecularly driven and is highly variable across patients. This understanding has made biomarkers, a diverse class of biological measurements, more relevant for disease diagnosis, monitoring, and selection of treatment strategy. Biomarkers' impact on precision medicine can be seen in cancer, pharmacogenomics, and safety. The successes in these cases suggest many more applications for biomarkers and a greater impact for precision medicine across the spectrum of human disease. The authors assess the status of biomarker-guided medical practice by analyzing themes for biomarker discovery, reviewing the impact of these markers in the clinic, and highlight future and ongoing challenges for biomarker discovery. This work is timely and relevant, as the molecular, quantitative approach of precision medicine is spreading to many disease indications.

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

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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.

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

Science.gov (United States)

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

2017-02-01

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

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

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Rachel M Ostroff

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

Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel

Science.gov (United States)

2016-12-01

Award Number: W81XWH-12-1-0382 TITLE: Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel PRINCIPAL...SUBTITLE Biomarker Discovery in Gulf War Veterans: Development of a War Illness Diagnostic Panel 5a. CONTRACT NUMBER W81XWH-12-1-0382 5b. GRANT...of the 1990-1991 Gulf War are affected by Gulf War illness (GWI), the chronic condition currently defined only by veterans’ self-reported symptoms

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.

Secreted proteins as a fundamental source for biomarker discovery

Czech Academy of Sciences Publication Activity Database

Šťastná, Miroslava; Van Eyk, J.E.

2012-01-01

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

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.

A Standardized and Reproducible Urine Preparation Protocol for Cancer Biomarkers Discovery

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Julia Beretov

2014-01-01

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

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

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

2012-01-01

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

Tumor interstitial fluid - a treasure trove of cancer biomarkers.

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

2013-11-01

Tumor interstitial fluid (TIF) is a proximal fluid that, in addition to the set of blood soluble phase-borne proteins, holds a subset of aberrantly externalized components, mainly proteins, released by tumor cells and tumor microenvironment through various mechanisms, which include classical secretion, non-classical secretion, secretion via exosomes and membrane protein shedding. Consequently, the interstitial aqueous phase of solid tumors is a highly promising resource for the discovery of molecules associated with pathological changes in tissues. Firstly, it allows one to delve deeper into the regulatory mechanisms and functions of secretion-related processes in tumor development. Secondly, the anomalous secretion of molecules that is innate to tumors and the tumor microenvironment, being associated with cancer progression, offers a valuable source for biomarker discovery and possible targets for therapeutic intervention. Here we provide an overview of the features of tumor-associated interstitial fluids, based on recent and updated information obtained mainly from our studies of breast cancer. Data from the study of interstitial fluids recovered from several other types of cancer are also discussed. This article is a part of a Special Issue entitled: The Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

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

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Heewon Park

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

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

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

2018-05-01

Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements

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

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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.

Novel ageing-biomarker discovery using data-intensive technologies.

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Griffiths, H R; Augustyniak, E M; Bennett, S J; Debacq-Chainiaux, F; Dunston, C R; Kristensen, P; Melchjorsen, C J; Navarrete, Santos A; Simm, A; Toussaint, O

2015-11-01

Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for biomarker discovery; (1) microarray analyses and/or proteomics in cell systems e.g. endothelial progenitor cells or T cell ageing including a stress model; and (2) investigation of cellular material and plasma directly from tightly-defined proband subsets of different ages using proteomic, transcriptomic and miR array. The first approach provided longitudinal insight into endothelial progenitor and T cell ageing. This review describes the strategy and use of hypothesis-free, data-intensive approaches to explore cellular proteins, miR, mRNA and plasma proteins as healthy ageing biomarkers, using ageing models and directly within samples from adults of different ages. It considers the challenges associated with integrating multiple models and pilot studies as rational biomarkers for a large cohort study. From this approach, a number of high-throughput methods were developed to evaluate novel, putative biomarkers of ageing in the MARK-AGE cohort. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Biomarker discovery in high grade sarcomas by mass spectrometry imaging

OpenAIRE

Lou, S.

2017-01-01

This thesis demonstrates a detailed biomarker discovery Mass Spectrometry Imaging workflow for histologically heterogeneous high grade sarcomas. Panels of protein and metabolite signatures were discovered either distinguishing different histological subtypes or stratifying high risk patients with poor survival.

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

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

2014-09-09

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

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

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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.

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

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

2017-09-01

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

Imaging biomarker roadmap for cancer studies

NARCIS (Netherlands)

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

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

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

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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.

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

Science.gov (United States)

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

2013-01-01

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

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

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Kirwan, Alan; Utratna, Marta; O'Dwyer, Michael E; Joshi, Lokesh; Kilcoyne, Michelle

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques.

Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood.

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Zhang, Fan; Kaufman, Howard L; Deng, Youping; Drabier, Renee

2013-01-01

Curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the biomarkers are associated with Signaling, Hemostasis, Hormones, and Immune System, which are consistent with previous findings. Our prediction model can serve as a general model for biomarker discovery in early detection of other cancers. In the future, Polymerase Chain Reaction (PCR) is planned for validation of the ability of these potential biomarkers for early detection of breast cancer.

Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.

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Moon, Myungjin; Nakai, Kenta

2018-04-01

Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.

Comparative Tissue Proteomics of Microdissected Specimens Reveals Novel Candidate Biomarkers of Bladder Cancer*

Science.gov (United States)

Chen, Chien-Lun; Chung, Ting; Wu, Chih-Ching; Ng, Kwai-Fong; Yu, Jau-Song; Tsai, Cheng-Han; Chang, Yu-Sun; Liang, Ying; Tsui, Ke-Hung; Chen, Yi-Ting

2015-01-01

More than 380,000 new cases of bladder cancer are diagnosed worldwide, accounting for ∼150,200 deaths each year. To discover potential biomarkers of bladder cancer, we employed a strategy combining laser microdissection, isobaric tags for relative and absolute quantitation labeling, and liquid chromatography-tandem MS (LC-MS/MS) analysis to profile proteomic changes in fresh-frozen bladder tumor specimens. Cellular proteins from four pairs of surgically resected primary bladder cancer tumor and adjacent nontumorous tissue were extracted for use in two batches of isobaric tags for relative and absolute quantitation experiments, which identified a total of 3220 proteins. A DAVID (database for annotation, visualization and integrated discovery) analysis of dysregulated proteins revealed that the three top-ranking biological processes were extracellular matrix organization, extracellular structure organization, and oxidation-reduction. Biological processes including response to organic substances, response to metal ions, and response to inorganic substances were highlighted by up-expressed proteins in bladder cancer. Seven differentially expressed proteins were selected as potential bladder cancer biomarkers for further verification. Immunohistochemical analyses showed significantly elevated levels of three proteins—SLC3A2, STMN1, and TAGLN2—in tumor cells compared with noncancerous bladder epithelial cells, and suggested that TAGLN2 could be a useful tumor tissue marker for diagnosis (AUC = 0.999) and evaluating lymph node metastasis in bladder cancer patients. ELISA results revealed significantly increased urinary levels of both STMN1 and TAGLN2 in bladder cancer subgroups compared with control groups. In comparisons with age-matched hernia urine specimens, urinary TAGLN2 in bladder cancer samples showed the largest fold change (7.13-fold), with an area-under-the-curve value of 0.70 (p < 0.001, n = 205). Overall, TAGLN2 showed the most significant

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

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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

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

LENUS (Irish Health Repository)

Tonry, Claire L

2016-07-18

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

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.

Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.

Science.gov (United States)

Bouchal, Pavel; Roumeliotis, Theodoros; Hrstka, Roman; Nenutil, Rudolf; Vojtesek, Borivoj; Garbis, Spiros D

2009-01-01

The present pilot study constitutes a proof-of-principle in the use of a quantitative LC-MS/MS based proteomic method for the comparative analysis of representative low-grade breast primary tumor tissues with and without metastases and metastasis in lymph node relative to the nonmetastatic tumor type. The study method incorporated iTRAQ stable isotope labeling, two-dimensional liquid chromatography, nanoelectrospray ionization and high resolution tandem mass spectrometry using the hybrid QqTOF platform (iTRAQ-2DLC-MS/MS). The principal aims of this study were (1) to define the protein spectrum obtainable using this approach, and (2) to highlight potential candidates for verification and validation studies focused on biomarkers involved in metastatic processes in breast cancer. The study resulted in the reproducible identification of 605 nonredundant proteins (p biomarker discovery program.

Prognostic and predictive potential molecular biomarkers in colon cancer.

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

2011-01-01

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

A New Serum Biomarker for Lung Cancer - Transthyretin

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Liyun LIU

2009-04-01

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

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.

Proteomic biomarker discovery in 1000 human plasma samples with mass spectrometry

DEFF Research Database (Denmark)

Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John

2016-01-01

automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked...

Biomarkers for personalized oncology: recent advances and future challenges.

Science.gov (United States)

Kalia, Madhu

2015-03-01

Cancer is a group of diseases characterized by the uncontrolled growth and spread of abnormal cells and oncology is a branch of medicine that deals with tumors. The last decade has seen significant advances in the development of biomarkers in oncology that play a critical role in understanding molecular and cellular mechanisms which drive tumor initiation, maintenance and progression. Clinical molecular diagnostics and biomarker discoveries in oncology are advancing rapidly as we begin to understand the complex mechanisms that transform a normal cell into an abnormal one. These discoveries have fueled the development of novel drug targets and new treatment strategies. The standard of care for patients with advanced-stage cancers has shifted away from an empirical treatment strategy based on the clinical-pathological profile to one where a biomarker driven treatment algorithm based on the molecular profile of the tumor is used. Recent advances in multiplex genotyping technologies and high-throughput genomic profiling by next-generation sequencing make possible the rapid and comprehensive analysis of the cancer genome of individual patients even from very little tumor biopsy material. Predictive (diagnostic) biomarkers are helpful in matching targeted therapies with patients and in preventing toxicity of standard (systemic) therapies. Prognostic biomarkers identify somatic germ line mutations, changes in DNA methylation, elevated levels of microRNA (miRNA) and circulating tumor cells (CTC) in blood. Predictive biomarkers using molecular diagnostics are currently in use in clinical practice of personalized oncotherapy for the treatment of five diseases: chronic myeloid leukemia, colon, breast, lung cancer and melanoma and these biomarkers are being used successfully to evaluate benefits that can be achieved through targeted therapy. Examples of these molecularly targeted biomarker therapies are: tyrosine kinase inhibitors in chronic myeloid leukemia and

Common Subcluster Mining in Microarray Data for Molecular Biomarker Discovery.

Science.gov (United States)

Sadhu, Arnab; Bhattacharyya, Balaram

2017-10-11

Molecular biomarkers can be potential facilitators for detection of cancer at early stage which is otherwise difficult through conventional biomarkers. Gene expression data from microarray experiments on both normal and diseased cell samples provide enormous scope to explore genetic relations of disease using computational techniques. Varied patterns of expressions of thousands of genes at different cell conditions along with inherent experimental error make the task of isolating disease related genes challenging. In this paper, we present a data mining method, common subcluster mining (CSM), to discover highly perturbed genes under diseased condition from differential expression patterns. The method builds heap through superposing near centroid clusters from gene expression data of normal samples and extracts its core part. It, thus, isolates genes exhibiting the most stable state across normal samples and constitute a reference set for each centroid. It performs the same operation on datasets from corresponding diseased samples and isolates the genes showing drastic changes in their expression patterns. The method thus finds the disease-sensitive genesets when applied to datasets of lung cancer, prostrate cancer, pancreatic cancer, breast cancer, leukemia and pulmonary arterial hypertension. In majority of the cases, few new genes are found over and above some previously reported ones. Genes with distinct deviations in diseased samples are prospective candidates for molecular biomarkers of the respective disease.

Advances in molecular biomarkers for gastric cancer: miRNAs as emerging novel cancer markers.

Science.gov (United States)

Wu, Hua-Hsi; Lin, Wen-chang; Tsai, Kuo-Wang

2014-01-23

Carcinoma of the stomach is one of the most prevalent cancer types in the world. Although the incidence of gastric cancer is declining, the outcomes of gastric cancer patients remain dismal because of the lack of effective biomarkers to detect early gastric cancer. Modern biomedical research has explored many potential gastric cancer biomarker genes by utilising serum protein antigens, oncogenic genes or gene families through improving molecular biological technologies, such as microarray, RNA-Seq and the like. Recently, the small noncoding microRNAs (miRNAs) have been suggested to be critical regulators in the oncogenesis pathways and to serve as useful clinical biomarkers. This new class of biomarkers is emerging as a novel molecule for cancer diagnosis and prognosis, including gastric cancer. By translational suppression of target genes, miRNAs play a significant role in the gastric cancer cell physiology and tumour progression. There are potential implications of previously discovered gastric cancer molecular biomarkers and their expression modulations by respective miRNAs. Therefore, many miRNAs are found to play oncogenic roles or tumour-suppressing functions in human cancers. With the surprising stability of miRNAs in tissues, serum or other body fluids, miRNAs have emerged as a new type of cancer biomarker with immeasurable clinical potential.

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.

Biomarkers as drug development tools: discovery, validation, qualification and use.

Science.gov (United States)

Kraus, Virginia B

2018-06-01

The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

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Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

2014-07-01

Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

Proteomic profiling of mammary carcinomas identifies C7orf24, a gamma-glutamyl cyclotransferase, as a potential cancer biomarker

DEFF Research Database (Denmark)

Gromov, Pavel; Gromova, Irina; Friis, Esbern

2010-01-01

Breast cancer is the leading cause of cancer deaths in women today and is the most common cancer (excluding skin cancers) among women in the Western world. Although cancers detected by screening mammography are significantly smaller than nonscreening ones, noninvasive biomarkers for detection......, and a novel protein, C7orf24, was identified as being upregulated in cancer cells. Protein expression levels of C7orf24 were evaluated by immunohistochemical assays to qualify deregulation of this protein. Analysis of C7orf24 expression showed up-regulation in 36.4 and 23.4% of cases present in the discovery...

Connective tissue-activating peptide III: a novel blood biomarker for early lung cancer detection.

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Yee, John; Sadar, Marianne D; Sin, Don D; Kuzyk, Michael; Xing, Li; Kondra, Jennifer; McWilliams, Annette; Man, S F Paul; Lam, Stephen

2009-06-10

There are no reliable blood biomarkers to detect early lung cancer. We used a novel strategy that allows discovery of differentially present proteins against a complex and variable background. Mass spectrometry analyses of paired pulmonary venous-radial arterial blood from 16 lung cancer patients were applied to identify plasma proteins potentially derived from the tumor microenvironment. Two differentially expressed proteins were confirmed in 64 paired venous-arterial blood samples using an immunoassay. Twenty-eight pre- and postsurgical resection peripheral blood samples and two independent, blinded sets of plasma from 149 participants in a lung cancer screening study (49 lung cancers and 100 controls) and 266 participants from the National Heart Lung and Blood Institute Lung Health Study (45 lung cancer and 221 matched controls) determined the accuracy of the two protein markers to detect subclinical lung cancer. Connective tissue-activating peptide III (CTAP III)/ neutrophil activating protein-2 (NAP-2) and haptoglobin were identified to be significantly higher in venous than in arterial blood. CTAP III/NAP-2 levels decreased after tumor resection (P = .01). In two independent population cohorts, CTAP III/NAP-2 was significantly associated with lung cancer and improved the accuracy of a lung cancer risk prediction model that included age, smoking, lung function (FEV(1)), and an interaction term between FEV(1) and CTAP III/NAP-2 (area under the curve, 0.84; 95% CI, 0.77 to 0.91) compared to CAPIII/NAP-2 alone. We identified CTAP III/NAP-2 as a novel biomarker to detect preclinical lung cancer. The study underscores the importance of applying blood biomarkers as part of a multimodal lung cancer risk prediction model instead of as stand-alone tests.

Random glycopeptide bead libraries for seromic biomarker discovery

DEFF Research Database (Denmark)

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

2010-01-01

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...... to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid discovery of O-glycopeptide biomarkers and the method has applicability in other types of assays such as lectin...

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

International Nuclear Information System (INIS)

Kang, Un-Beom; Ahn, Younghee; Lee, Jong Won; Kim, Yong-Hak; Kim, Joon; Yu, Myeong-Hee; Noh, Dong-Young; Lee, Cheolju

2010-01-01

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

Proteomic Biomarker Discovery in 1000 Human Plasma Samples with Mass Spectrometry.

Science.gov (United States)

Cominetti, Ornella; Núñez Galindo, Antonio; Corthésy, John; Oller Moreno, Sergio; Irincheeva, Irina; Valsesia, Armand; Astrup, Arne; Saris, Wim H M; Hager, Jörg; Kussmann, Martin; Dayon, Loïc

2016-02-05

The overall impact of proteomics on clinical research and its translation has lagged behind expectations. One recognized caveat is the limited size (subject numbers) of (pre)clinical studies performed at the discovery stage, the findings of which fail to be replicated in larger verification/validation trials. Compromised study designs and insufficient statistical power are consequences of the to-date still limited capacity of mass spectrometry (MS)-based workflows to handle large numbers of samples in a realistic time frame, while delivering comprehensive proteome coverages. We developed a highly automated proteomic biomarker discovery workflow. Herein, we have applied this approach to analyze 1000 plasma samples from the multicentered human dietary intervention study "DiOGenes". Study design, sample randomization, tracking, and logistics were the foundations of our large-scale study. We checked the quality of the MS data and provided descriptive statistics. The data set was interrogated for proteins with most stable expression levels in that set of plasma samples. We evaluated standard clinical variables that typically impact forthcoming results and assessed body mass index-associated and gender-specific proteins at two time points. We demonstrate that analyzing a large number of human plasma samples for biomarker discovery with MS using isobaric tagging is feasible, providing robust and consistent biological results.

Nanomaterials based biosensors for cancer biomarker detection

International Nuclear Information System (INIS)

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

2016-01-01

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

Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances

Science.gov (United States)

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

2016-01-01

Colorectal cancer (CRC) is the second most commonly diagnosed cancer among females and third among males worldwide. It also contributes significantly to cancer-related deaths, despite the continuous progress in diagnostic and therapeutic methods. Biomarkers currently play an important role in the detection and treatment of patients with colorectal cancer. Risk stratification for screening might be augmented by finding new biomarkers which alone or as a complement of existing tests might recognize either the predisposition or early stage of the disease. Biomarkers have also the potential to change diagnostic and treatment algorithms by selecting the proper chemotherapeutic drugs across a broad spectrum of patients. There are attempts to personalise chemotherapy based on presence or absence of specific biomarkers. In this review, we update review published last year and describe our understanding of tumour markers and biomarkers role in CRC screening, diagnosis, treatment and follow-up. Goal of future research is to identify those biomarkers that could allow a non-invasive and cost-effective diagnosis, as well as to recognise the best prognostic panel and define the predictive biomarkers for available treatments. PMID:26855534

Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances.

Science.gov (United States)

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

2016-02-07

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

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

International Nuclear Information System (INIS)

Amacher, David E.

2010-01-01

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

Exosomal miRNAs as biomarkers for prostate cancer

Directory of Open Access Journals (Sweden)

Nina Pettersen Hessvik

2013-03-01

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

Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

Science.gov (United States)

Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

2016-03-10

Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

Latest discoveries and trends in translational cancer research: highlights of the 2008 Annual Meeting of the American Association for Cancer Research.

Science.gov (United States)

Cho, William C S

2008-08-01

The Annual Meeting of the American Association for Cancer Research (AACR) is the world's largest and most comprehensive gathering of cancer researchers. At the 2008 AACR Annual Meeting, innovative research approaches, novel technologies, potentially life-saving therapies in the pipeline, late-breaking clinical trial findings, and new approaches to cancer prevention were presented by top scientists. Reflecting the global state of cancer research with an eye toward future trends, several areas of great science and discovery in the cancer field were shared in this report, which include cancer biomarkers, the role of microRNAs in cancer research, cancer stem cells, tumor microenvironment, targeted therapy, and cancer prevention. This article presents an overview of hot topics discussed at the 2008 AACR Annual Meeting and recapitulates some scientific sessions geared toward new technologies, recent progress, and current challenges reported by cancer researchers. For those who did not attend the meeting, this report may serve as a highlight of this important international cancer research meeting.

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

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

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...... occur early during tumorigenesis. This may open up for effective screening, and analysis of blood or nipple aspirate may later help in diagnosing breast cancer. As a more detailed molecular characterization of different types of breast cancer becomes available, the ability to divide patients...... as a versatile biomarker tool for screening, diagnosis, prognosis and monitoring of breast cancer. Standardization of methods and biomarker panels will be required to fully exploit this clinical potential....

Lessons for tumor biomarker trials: vicious cycles, scientific method & developing guidelines.

Science.gov (United States)

Hayes, Daniel; Raison, Claire

2015-02-01

Interview with Daniel Hayes, by Claire Raison (Commissioning Editor) Daniel F Hayes, M.D. is the Stuart A Padnos Professor of Breast Cancer Research and co-Director of the Breast Oncology Program at the University of Michigan Comprehensive Cancer Center (Ann Arbor, MI, USA). Dr Hayes has extensive experience in clinical and translational breast cancer biomarker research, and in drug development and clinical trials. Around 30 years ago, he led the discovery of the circulating breast tumor biomarker, CA15-3, which started his career into further tumor biomarker work. The main thrust of his work since then has been in clinical trials, tumor biomarkers and trying to integrate the two. Dr Hayes is Chair of the Correlative Sciences Committee of the North American Breast Cancer Group (now called the Breast Cancer Steering Committee), and co-chairs the Expert Panel for Tumor Biomarker Practice Guidelines for the American Society of Clinical Oncology.

Role of proteomics in the discovery of autism biomarkers

Energy Technology Data Exchange (ETDEWEB)

Ayadhi, L. A.; Halepoto, D. M. [King Saud Univ., Riyadh (Saudi Arabia). Dept. of Physiology

2013-02-15

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

Role of proteomics in the discovery of autism biomarkers

International Nuclear Information System (INIS)

Ayadhi, L.A.; Halepoto, D.M.

2013-01-01

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

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....

Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

Directory of Open Access Journals (Sweden)

Yingrong Chen

2015-01-01

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

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

Science.gov (United States)

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

Evaluation of a Serum Lung Cancer Biomarker Panel.

Science.gov (United States)

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results.

Phase II cancer clinical trials for biomarker-guided treatments.

Science.gov (United States)

Jung, Sin-Ho

2018-01-01

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

Aberrantly methylated DNA as a biomarker in breast cancer.

Science.gov (United States)

Kristiansen, Søren; Jørgensen, Lars M; Guldberg, Per; Sölétormos, György

2013-01-01

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

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.

Serum and Plasma Metabolomic Biomarkers for Lung Cancer.

Science.gov (United States)

Kumar, Nishith; Shahjaman, Md; Mollah, Md Nurul Haque; Islam, S M Shahinul; Hoque, Md Aminul

2017-01-01

In drug invention and early disease prediction of lung cancer, metabolomic biomarker detection is very important. Mortality rate can be decreased, if cancer is predicted at the earlier stage. Recent diagnostic techniques for lung cancer are not prognosis diagnostic techniques. However, if we know the name of the metabolites, whose intensity levels are considerably changing between cancer subject and control subject, then it will be easy to early diagnosis the disease as well as to discover the drug. Therefore, in this paper we have identified the influential plasma and serum blood sample metabolites for lung cancer and also identified the biomarkers that will be helpful for early disease prediction as well as for drug invention. To identify the influential metabolites, we considered a parametric and a nonparametric test namely student׳s t-test as parametric and Kruskal-Wallis test as non-parametric test. We also categorized the up-regulated and down-regulated metabolites by the heatmap plot and identified the biomarkers by support vector machine (SVM) classifier and pathway analysis. From our analysis, we got 27 influential (p-value<0.05) metabolites from plasma sample and 13 influential (p-value<0.05) metabolites from serum sample. According to the importance plot through SVM classifier, pathway analysis and correlation network analysis, we declared 4 metabolites (taurine, aspertic acid, glutamine and pyruvic acid) as plasma biomarker and 3 metabolites (aspartic acid, taurine and inosine) as serum biomarker.

Shotgun Proteomics and Biomarker Discovery

Directory of Open Access Journals (Sweden)

W. Hayes McDonald

2002-01-01

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

Biomarker assessment and molecular testing for prognostication in breast cancer.

Science.gov (United States)

Kos, Zuzana; Dabbs, David J

2016-01-01

Current treatment of breast cancer incorporates clinical, pathological and molecular data. Oestrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2) define prognosis and identify tumours for targeted therapy, and remain the sole established single-molecule biomarkers defining the minimum breast cancer pathology data set. Ki67 remains one of the most promising yet controversial biomarkers in breast cancer, implemented routinely in some, but not all, pathology departments. Beyond the single-molecule biomarkers, a host of multigene expression tests have been developed to interrogate the driver pathways and biology of individual breast cancers to predict clinical outcome more accurately. A minority of these assays have entered into clinical practice. This review focuses on the established biomarkers of ER, PR and HER2, the controversial but clinically implemented biomarker Ki67 and the currently marketed gene expression signatures. © 2015 John Wiley & Sons Ltd.

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

Science.gov (United States)

Shukla, Hem D

2017-10-25

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

Differential membrane proteomics using 18O-labeling to identify biomarkers for cholangiocarcinoma

DEFF Research Database (Denmark)

Kristiansen, Troels Zakarias; Harsha, H C; Grønborg, Mads

2008-01-01

Quantitative proteomic methodologies allow profiling of hundreds to thousands of proteins in a high-throughput fashion. This approach is increasingly applied to cancer biomarker discovery to identify proteins that are differentially regulated in cancers. Fractionation of protein samples based...

Comprehensive Analysis of MILE Gene Expression Data Set Advances Discovery of Leukaemia Type and Subtype Biomarkers.

Science.gov (United States)

Labaj, Wojciech; Papiez, Anna; Polanski, Andrzej; Polanska, Joanna

2017-03-01

Large collections of data in studies on cancer such as leukaemia provoke the necessity of applying tailored analysis algorithms to ensure supreme information extraction. In this work, a custom-fit pipeline is demonstrated for thorough investigation of the voluminous MILE gene expression data set. Three analyses are accomplished, each for gaining a deeper understanding of the processes underlying leukaemia types and subtypes. First, the main disease groups are tested for differential expression against the healthy control as in a standard case-control study. Here, the basic knowledge on molecular mechanisms is confirmed quantitatively and by literature references. Second, pairwise comparison testing is performed for juxtaposing the main leukaemia types among each other. In this case by means of the Dice coefficient similarity measure the general relations are pointed out. Moreover, lists of candidate main leukaemia group biomarkers are proposed. Finally, with this approach being successful, the third analysis provides insight into all of the studied subtypes, followed by the emergence of four leukaemia subtype biomarkers. In addition, the class enhanced DEG signature obtained on the basis of novel pipeline processing leads to significantly better classification power of multi-class data classifiers. The developed methodology consisting of batch effect adjustment, adaptive noise and feature filtration coupled with adequate statistical testing and biomarker definition proves to be an effective approach towards knowledge discovery in high-throughput molecular biology experiments.

Mathematical modeling for novel cancer drug discovery and development.

Science.gov (United States)

Zhang, Ping; Brusic, Vladimir

2014-10-01

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

Biomarkers and Targeted Therapy in Pancreatic Cancer

Directory of Open Access Journals (Sweden)

Fataneh Karandish

2016-01-01

Full Text Available Pancreatic ductal adenocarcinoma (PDAC constitutes 90% of pancreatic cancers. PDAC is a complex and devastating disease with only 1%–3% survival rate in five years after the second stage. Treatment of PDAC is complicated due to the tumor microenvironment, changing cell behaviors to the mesenchymal type, altered drug delivery, and drug resistance. Considering that pancreatic cancer shows early invasion and metastasis, critical research is needed to explore different aspects of the disease, such as elaboration of biomarkers, specific signaling pathways, and gene aberration. In this review, we highlight the biomarkers, the fundamental signaling pathways, and their importance in targeted drug delivery for pancreatic cancers.

Biomarkers and Targeted Therapy in Pancreatic Cancer.

Science.gov (United States)

Karandish, Fataneh; Mallik, Sanku

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) constitutes 90% of pancreatic cancers. PDAC is a complex and devastating disease with only 1%-3% survival rate in five years after the second stage. Treatment of PDAC is complicated due to the tumor microenvironment, changing cell behaviors to the mesenchymal type, altered drug delivery, and drug resistance. Considering that pancreatic cancer shows early invasion and metastasis, critical research is needed to explore different aspects of the disease, such as elaboration of biomarkers, specific signaling pathways, and gene aberration. In this review, we highlight the biomarkers, the fundamental signaling pathways, and their importance in targeted drug delivery for pancreatic cancers.

Tumor antigens as proteogenomic biomarkers in invasive ductal carcinomas

DEFF Research Database (Denmark)

Olsen, Lars Rønn; Campos, Benito; Winther, Ole

2014-01-01

directly linked to the hallmarks of cancer. The results found by proteogenomic analysis of the 32 tumor antigens studied here, capture largely the same pathway irregularities as those elucidated from large-scale screening of genomics analyses, where several thousands of genes are often found......Background: The majority of genetic biomarkers for human cancers are defined by statistical screening of high-throughput genomics data. While a large number of genetic biomarkers have been proposed for diagnostic and prognostic applications, only a small number have been applied in the clinic....... Similarly, the use of proteomics methods for the discovery of cancer biomarkers is increasing. The emerging field of proteogenomics seeks to enrich the value of genomics and proteomics approaches by studying the intersection of genomics and proteomics data. This task is challenging due to the complex nature...

Database-augmented Mass Spectrometry Analysis of Exosomes Identifies Claudin 3 as a Putative Prostate Cancer Biomarker.

Science.gov (United States)

Worst, Thomas Stefan; von Hardenberg, Jost; Gross, Julia Christina; Erben, Philipp; Schnölzer, Martina; Hausser, Ingrid; Bugert, Peter; Michel, Maurice Stephan; Boutros, Michael

2017-06-01

In prostate cancer and other malignancies sensitive and robust biomarkers are lacking or have relevant limitations. Prostate specific antigen (PSA), the only biomarker widely used in prostate cancer, is suffering from low specificity. Exosomes offer new perspectives in the discovery of blood-based biomarkers. Here we present a proof-of principle study for a proteomics-based identification pipeline, implementing existing data sources, to exemplarily identify exosome-based biomarker candidates in prostate cancer.Exosomes from malignant PC3 and benign PNT1A cells and from FBS-containing medium were isolated using sequential ultracentrifugation. Exosome and control samples were analyzed on an LTQ-Orbitrap XL mass spectrometer. Proteomic data is available via ProteomeXchange with identifier PXD003651. We developed a scoring scheme to rank 64 proteins exclusively found in PC3 exosomes, integrating data from four public databases and published mass spectrometry data sets. Among the top candidates, we focused on the tight junction protein claudin 3. Retests under serum-free conditions using immunoblotting and immunogold labeling confirmed the presence of claudin 3 on PC3 exosomes. Claudin 3 levels were determined in the blood plasma of patients with localized ( n = 58; 42 with Gleason score 6-7, 16 with Gleason score ≥8) and metastatic prostate cancer ( n = 11) compared with patients with benign prostatic hyperplasia ( n = 15) and healthy individuals ( n = 15) using ELISA, without prior laborious exosome isolation. ANOVA showed different CLDN3 plasma levels in these groups ( p = 0.004). CLDN3 levels were higher in patients with Gleason ≥8 tumors compared with patients with benign prostatic hyperplasia ( p = 0.012) and Gleason 6-7 tumors ( p = 0.029). In patients with localized tumors CLDN3 levels predicted a Gleason score ≥ 8 (AUC = 0.705; p = 0.016) and did not correlate with serum PSA.By using the described workflow claudin 3 was identified and validated as a

Biomarkers for predicting complete debulking in ovarian cancer

DEFF Research Database (Denmark)

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

2014-01-01

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

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

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

Science.gov (United States)

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

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. 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. 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://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa).

Science.gov (United States)

Stephan, Carsten; Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-04-01

PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of (~)50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective.

Combined serum and EPS-urine proteomic analysis using iTRAQ technology for discovery of potential prostate cancer biomarkers.

Science.gov (United States)

Zhang, Mo; Chen, Lizhu; Yuan, Zhengwei; Yang, Zeyu; Li, Yue; Shan, Liping; Yin, Bo; Fei, Xiang; Miao, Jianing; Song, Yongsheng

2016-11-01

Prostate cancer (PCa) is one of the most common malignant tumors and a major cause of cancer-related death for men worldwide. The aim of our study was to identify potential non-invasive serum and expressed prostatic secretion (EPS)-urine biomarkers for accurate diagnosis of PCa. Here, we performed a combined isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis to compare protein profiles using pooled serum and EPS-urine samples from 4 groups of patients: benign prostate hyperplasia (BPH), high grade prostatic intraepithelial neoplasia (HGPIN), localized PCa and metastatic PCa. The differentially expressed proteins were rigorously selected and further validated in a large and independent cohort using classical ELISA and Western blot assays. Finally, we established a multiplex biomarker panel consisting of 3 proteins (serum PF4V1, PSA, and urinary CRISP3) with an excellent diagnostic capacity to differentiate PCa from BPH [area under the receiver operating characteristic curve (AUC) of 0.941], which showed an evidently greater discriminatory ability than PSA alone (AUC, 0.757) (P<0.001). Importantly, even when PSA level was in the gray zone (4-10 ng/mL), a combination of PF4V1 and CRISP3 could achieve a relatively high diagnostic efficacy (AUC, 0.895). Furthermore, their combination also had the potential to distinguish PCa from HGPIN (AUC, 0.934). Our results demonstrated that the combined application of serum and EPS-urine biomarkers can improve the diagnosis of PCa and provide a new prospect for non-invasive PCa detection.

Biomarkers for bladder cancer management: present and future

Science.gov (United States)

Ye, Fei; Wang, Li; Castillo-Martin, Mireia; McBride, Russell; Galsky, Matthew D; Zhu, Jun; Boffetta, Paolo; Zhang, David Y; Cordon-Cardo, Carlos

2014-01-01

Accurate and sensitive detection of bladder cancer is critical to diagnose this deadly disease at an early stage, estimate prognosis, predict response to treatment, and monitor recurrence. In past years, laboratory diagnosis and surveillance of urinary bladder cancer have improved significantly. Although urine cytology remains the gold standard test, many new urinary biomarkers have been identified. Furthermore, recent advances in genomic studies of bladder cancer have helped to refine our understanding of the pathogenesis of the disease, the biological basis for outcome disparities, and to inform more efficient treatment and surveillance strategies. In this article, the established diagnostic tests, newly identified biomarkers and genomic landscape of bladder cancer will be reviewed. PMID:25374904

Metabolome analysis for discovering biomarkers of gastroenterological cancer.

Science.gov (United States)

Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

2014-09-01

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2014-10-01

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

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

Directory of Open Access Journals (Sweden)

Hem D. Shukla

2017-10-01

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

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.

Molecular biomarkers to guide precision medicine in localized prostate cancer.

Science.gov (United States)

Smits, Minke; Mehra, Niven; Sedelaar, Michiel; Gerritsen, Winald; Schalken, Jack A

2017-08-01

Major advances through tumor profiling technologies, that include next-generation sequencing, epigenetic, proteomic and transcriptomic methods, have been made in primary prostate cancer, providing novel biomarkers that may guide precision medicine in the near future. Areas covered: The authors provided an overview of novel molecular biomarkers in tissue, blood and urine that may be used as clinical tools to assess prognosis, improve selection criteria for active surveillance programs, and detect disease relapse early in localized prostate cancer. Expert commentary: Active surveillance (AS) in localized prostate cancer is an accepted strategy in patients with very low-risk prostate cancer. Many more patients may benefit from watchful waiting, and include patients of higher clinical stage and grade, however selection criteria have to be optimized and early recognition of transformation from localized to lethal disease has to be improved by addition of molecular biomarkers. The role of non-invasive biomarkers is challenging the need for repeat biopsies, commonly performed at 1 and 4 years in men under AS programs.

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

Science.gov (United States)

Kretschmer, Alexander; Tilki, Derya

2017-12-01

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

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

DEFF Research Database (Denmark)

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

2010-01-01

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

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

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Jochen Neuhaus

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

A Timely shift from shotgun to targeted proteomics and how it can be groundbreaking for cancer research

DEFF Research Database (Denmark)

Faria, Sara S.; Morris, Carlos F.M.; Silva, Adriano R.

2017-01-01

shifting potential of modern targeted proteomics applied to cancer research can be demonstrated by the large number of advancements and increasing examples of new and more useful biomarkers found during the course of this review in different aspects of cancer research. Out of the many studies dedicated...... to cancer biomarker discovery, we were able to devise some clear trends, such as the fact that breast cancer is the most common type of tumor studied and that most of the research for any given type of cancer is focused on the discovery diagnostic biomarkers, with the exception of those that rely on samples...... applicable results have called for the implementation of more direct, hypothesis-based studies such as those made available through targeted approaches, that might be able to streamline biomarker discovery and validation as a means to increase survivability of affected patients. In fact, the paradigm...

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

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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. ©2014 American Association for Cancer Research.

A network-based biomarker approach for molecular investigation and diagnosis of lung cancer

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Chen Bor-Sen

2011-01-01

Full Text Available Abstract Background Lung cancer is the leading cause of cancer deaths worldwide. Many studies have investigated the carcinogenic process and identified the biomarkers for signature classification. However, based on the research dedicated to this field, there is no highly sensitive network-based method for carcinogenesis characterization and diagnosis from the systems perspective. Methods In this study, a systems biology approach integrating microarray gene expression profiles and protein-protein interaction information was proposed to develop a network-based biomarker for molecular investigation into the network mechanism of lung carcinogenesis and diagnosis of lung cancer. The network-based biomarker consists of two protein association networks constructed for cancer samples and non-cancer samples. Results Based on the network-based biomarker, a total of 40 significant proteins in lung carcinogenesis were identified with carcinogenesis relevance values (CRVs. In addition, the network-based biomarker, acting as the screening test, proved to be effective in diagnosing smokers with signs of lung cancer. Conclusions A network-based biomarker using constructed protein association networks is a useful tool to highlight the pathways and mechanisms of the lung carcinogenic process and, more importantly, provides potential therapeutic targets to combat cancer.

Mass Spectrometry-Based N-Glycomics of Colorectal Cancer

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Manveen K. Sethi

2015-12-01

Full Text Available Colorectal cancer (CRC is one of the most prevalent cancers worldwide. An increased molecular understanding of the CRC pathology is warranted to gain insights into the underlying molecular and cellular mechanisms of the disease. Altered protein glycosylation patterns are associated with most diseases including malignant transformation. Recent advances in mass spectrometry and bioinformatics have accelerated glycomics research and present a new paradigm for cancer biomarker discovery. Mass spectrometry (MS-based glycoproteomics and glycomics, therefore, hold considerable promise to improve the discovery of novel biomarkers with utility in disease diagnosis and therapy. This review focuses on the emerging field of glycomics to present a comprehensive review of advances in technologies and their application in studies aimed at discovering novel glycan-based biomarkers. We will also discuss some of the challenges associated with using glycans as biomarkers.

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

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Kramer Alon

2009-01-01

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

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

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Kendall K

2013-05-01

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

Prostate-Specific Antigen (PSA) Screening and New Biomarkers for Prostate Cancer (PCa)

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Rittenhouse, Harry; Hu, Xinhai; Cammann, Henning; Jung, Klaus

2014-01-01

Abstract PSA screening reduces PCa-mortality but the disadvantages overdiagnosis and overtreatment require multivariable risk-prediction tools to select appropriate treatment or active surveillance. This review explains the differences between the two largest screening trials and discusses the drawbacks of screening and its meta-analysisxs. The current American and European screening strategies are described. Nonetheless, PSA is one of the most widely used tumor markers and strongly correlates with the risk of harboring PCa. However, while PSA has limitations for PCa detection with its low specificity there are several potential biomarkers presented in this review with utility for PCa currently being studied. There is an urgent need for new biomarkers especially to detect clinically significant and aggressive PCa. From all PSA-based markers, the FDA-approved prostate health index (phi) shows improved specificity over percent free and total PSA. Another kallikrein panel, 4K, which includes KLK2 has recently shown promise in clinical research studies but has not yet undergone formal validation studies. In urine, prostate cancer gene 3 (PCA3) has also been validated and approved by the FDA for its utility to detect PCa. The potential correlation of PCA3 with cancer aggressiveness requires more clinical studies. The detection of the fusion of androgen-regulated genes with genes of the regulatory transcription factors in tissue of ~50% of all PCa-patients is a milestone in PCa research. A combination of the urinary assays for TMPRSS2:ERG gene fusion and PCA3 shows an improved accuracy for PCa detection. Overall, the field of PCa biomarker discovery is very exciting and prospective. PMID:27683457

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

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Nelson S. Yee

2012-01-01

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

microRNA Biomarkers to Generate Sensitivity to Abiraterone-Resistant Prostate Cancer

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2017-09-01

CYP17A1 inhibition with abiraterone in castration- resistant prostate cancer : induction of steroidogenesis and androgen receptor splice variants...AWARD NUMBER: W81XWH-15-1-0353 TITLE: microRNA Biomarkers to Generate Sensitivity to Abiraterone-Resistant Prostate Cancer PRINCIPAL...TITLE AND SUBTITLE microRNA Biomarkers to Generate Sensitivity to Abiraterone- Resistant Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER

Molecular alterations and biomarkers in colorectal cancer

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Grady, William M.; Pritchard, Colin C.

2013-01-01

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

Untargeted mass spectrometry-based metabolomic profiling of pleural effusions: fatty acids as novel cancer biomarkers for malignant pleural effusions.

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Lam, Ching-Wan; Law, Chun-Yiu

2014-09-05

Untargeted mass spectrometry-based metabolomic profiling is a powerful analytical method used for broad-spectrum identification and quantification of metabolites in biofluids in human health and disease states. In this study, we exploit metabolomic profiling for cancer biomarker discovery for diagnosis of malignant pleural effusions. We envisage the result will be clinically useful since currently there are no cancer biomarkers that are accurate enough for the diagnosis of malignant pleural effusions. Metabolomes of 32 malignant pleural effusions from lung cancer patients and 18 benign effusions from patients with pulmonary tuberculosis were analyzed using reversed-phase liquid chromatography tandem mass spectrometry (LC-MS/MS) using AB SCIEX TripleTOF 5600. MS spectra were analyzed using XCMS, PeakView, and LipidView. Metabolome-Wide Association Study (MWAS) was performed by Receiver Operating Characteristic Curve Explorer and Tester (ROCCET). Insignificant markers were filtered out using a metabolome-wide significance level (MWSL) with p-value pleural effusions. Using a ratio of FFA 18:1-to-ceramide (d18:1/16:0), the area-under-ROC was further increased to 0.99 (95% CI = 0.91-1.00) with sensitivity 93.8% and specificity 100.0%. Using untargeted metabolomic profiling, the diagnostic cancer biomarker with the largest area-under-ROC can be determined objectively. This lipogenic phenotype could be explained by overexpression of fatty acid synthase (FASN) in cancer cells. The diagnostic performance of FFA 18:1-to-ceramide (d18:1/16:0) ratio supports its use for diagnosis of malignant pleural effusions.

Discovery – Methotrexate: Chemotherapy Treatment for Cancer

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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.

Renal Cancer Biomarkers | NCI Technology Transfer Center | TTC

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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.

microRNA Biomarker Discovery and High-Throughput DNA Sequencing Are Possible Using Long-term Archived Serum Samples.

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Rounge, Trine B; Lauritzen, Marianne; Langseth, Hilde; Enerly, Espen; Lyle, Robert; Gislefoss, Randi E

2015-09-01

The impacts of long-term storage and varying preanalytical factors on the quality and quantity of DNA and miRNA from archived serum have not been fully assessed. Preanalytical and analytical variations and degradation may introduce bias in representation of DNA and miRNA and may result in loss or corruption of quantitative data. We have evaluated DNA and miRNA quantity, quality, and variability in samples stored up to 40 years using one of the oldest prospective serum collections in the world, the Janus Serumbank, a biorepository dedicated to cancer research. miRNAs are present and stable in archived serum samples frozen at -25°C for at least 40 years. Long-time storage did not reduce miRNA yields; however, varying preanalytical conditions had a significant effect and should be taken into consideration during project design. Of note, 500 μL serum yielded sufficient miRNA for qPCR and small RNA sequencing and on average 650 unique miRNAs were detected in samples from presumably healthy donors. Of note, 500 μL serum yielded sufficient DNA for whole-genome sequencing and subsequent SNP calling, giving a uniform representation of the genomes. DNA and miRNA are stable during long-term storage, making large prospectively collected serum repositories an invaluable source for miRNA and DNA biomarker discovery. Large-scale biomarker studies with long follow-up time are possible utilizing biorepositories with archived serum and state-of-the-art technology. ©2015 American Association for Cancer Research.

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

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Serkova, Natalie J.; Standiford, Theodore J.

2011-01-01

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

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

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Cesaroni, Matteo; Powell, Jasmine; Sapienza, Carmen

2014-01-01

We have validated differences in DNA methylation levels of candidate genes previously reported to discriminate between normal colon mucosa of colon cancer patients 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 cancer patients 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 10 of the validated candidate genes plus eight additional candidates. This model exhibited 96% sensitivity and 100% specificity in a 40-sample training set and classified all eight samples in the test set correctly. Moreover, we found a moderate-strong correlation (Pearson coefficients r=0.253-0.722) between methylation levels in colon mucosa and methylation levels in peripheral blood for seven of the 18 genes in the support vector model. These seven genes, alone, classified 44 of the 48 patients in the validation set correctly and five CpGs selected from only two of the seven genes classified 41 of the 48 patients in the discovery set correctly. These results suggest that methylation biomarkers may be developed that will, at minimum, serve as useful objective and quantitative diagnostic complements to colonoscopy as a cancer-screening tool. These data also suggest that it may be possible to monitor biomarker methylation levels in tissues collected much less invasively than by colonoscopy. PMID:24806665

Oral Microbiome: A New Biomarker Reservoir for Oral and Oropharyngeal Cancers

OpenAIRE

Lim, Yenkai; Totsika, Makrina; Morrison, Mark; Punyadeera, Chamindie

2017-01-01

Current biomarkers (DNA, RNA and protein) for oral cavity and oropharyngeal cancers demonstrate biological variations between individuals, rendering them impractical for clinical translation. Whilst these biomarkers originate from the host, there is not much information in the literature about the influence of oral microbiota on cancer pathogenesis, especially in oral cancers. Oral microbiotas are known to participate in disease initiation and progression not only limited to the oral cavity, ...

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

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Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

Physical Activity, Biomarkers, and Disease Outcomes in Cancer Survivors: A Systematic Review

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Friedenreich, Christine M.; Courneya, Kerry S.; Siddiqi, Sameer M.; McTiernan, Anne; Alfano, Catherine M.

2012-01-01

Background Cancer survivors often seek information about how lifestyle factors, such as physical activity, may influence their prognosis. We systematically reviewed studies that examined relationships between physical activity and mortality (cancer-specific and all-cause) and/or cancer biomarkers. Methods We identified 45 articles published from January 1950 to August 2011 through MEDLINE database searches that were related to physical activity, cancer survival, and biomarkers potentially relevant to cancer survival. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement to guide this review. Study characteristics, mortality outcomes, and biomarker-relevant and subgroup results were abstracted for each article that met the inclusion criteria (ie, research articles that included participants with a cancer diagnosis, mortality outcomes, and an assessment of physical activity). Results There was consistent evidence from 27 observational studies that physical activity is associated with reduced all-cause, breast cancer–specific, and colon cancer–specific mortality. There is currently insufficient evidence regarding the association between physical activity and mortality for survivors of other cancers. Randomized controlled trials of exercise that included biomarker endpoints suggest that exercise may result in beneficial changes in the circulating level of insulin, insulin-related pathways, inflammation, and, possibly, immunity; however, the evidence is still preliminary. Conclusions Future research directions identified include the need for more observational studies on additional types of cancer with larger sample sizes; the need to examine whether the association between physical activity and mortality varies by tumor, clinical, or risk factor characteristics; and the need for research on the biological mechanisms involved in the association between physical activity and survival after a cancer diagnosis. Future randomized

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

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Giulia Selvolini

2017-03-01

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

Exosome: emerging biomarker in breast cancer

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Jia, Yunlu; Chen, Yongxia; Wang, Qinchuan; Jayasinghe, Ushani; Luo, Xiao; Wei, Qun; Wang, Ji; Xiong, Hanchu; Chen, Cong; Xu, Bin; Hu, Wenxian; Wang, Linbo; Zhao, Wenhe; Zhou, Jichun

2017-01-01

Exosomes are nano-sized membrane vesicles released by a variety of cell types, and are thought to play important roles in intercellular communications. In breast cancer, through horizontal transfer of various bioactive molecules, such as proteins and mRNAs, exosomes are emerging as local and systemic cell-to-cell mediators of oncogenic information and play an important role on cancer progression. This review outlines the current knowledge and concepts concerning the exosomes involvement in breast cancer pathogenesis (including tumor initiation, invasion and metastasis, angiogenesis, immune system modulation and tumor microenvironment) and cancer therapy resistance. Moreover, the potential use of exosomes as promising diagnostic and therapeutic biomarkers in breast cancer are also discussed. PMID:28402944

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

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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

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

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

2017-10-01

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

Emerging biomarkers in the diagnosis of prostate cancer

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Filella X

2018-05-01

Full Text Available Xavier Filella, Esther Fernández-Galan, Rosa Fernández Bonifacio, Laura Foj Department of Biochemistry and Molecular Genetics (CDB, Hospital Clínic, IDIBAPS, Barcelona, Catalonia, Spain Abstract: Prostate cancer (PCa is the second most common cancer in men worldwide. A large proportion of PCa are latent, never destined to progress or affect the patients’ life. It is of utmost importance to identify which PCa are destined to progress and which would benefit from an early radical treatment. Prostate-specific antigen (PSA remains the most used test to detect PCa. Its limited specificity and an elevated rate of overdiagnosis are the main problems associated with PSA testing. New PCa biomarkers have been proposed to improve the accuracy of PSA in the management of early PCa. Commercially available biomarkers such as PCA3 score, Prostate Health Index (PHI, and the four-kallikrein panel are used with the purpose of reducing the number of unnecessary biopsies and providing information related to the aggressiveness of the tumor. The relationship with PCa aggressiveness seems to be confirmed by PHI and the four-kallikrein panel, but not by the PCA3 score. In this review, we also summarize new promising biomarkers, such as PSA glycoforms, TMPRSS2:ERG fusion gene, microRNAs, circulating tumor cells, androgen receptor variants, and PTEN gene. All these emerging biomarkers could change the management of early PCa, offering more accurate results than PSA. Nonetheless, large prospective studies comparing these new biomarkers among them are required to know their real value in PCa detection and prognosis. Keywords: prostate cancer, PSA, PHI, four-kallikrein panel, PCA3, miRNAs

Predictive Biomarkers of Radiation Sensitivity in Rectal Cancer

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Tut, Thein Ga

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

Molecular pathology of prostate cancer.

Science.gov (United States)

Cazares, L H; Drake, R R; Esquela-Kirscher, A; Lance, R S; Semmes, O J; Troyer, D A

2010-01-01

This chapter includes discussion of the molecular pathology of tissue, blood, urine, and expressed prostatic secretions. Because we are unable to reliably image the disease in vivo, a 12 core method that oversamples the peripheral zone is widely used. This generates large numbers of cores that need to be carefully processed and sampled. In spite of the large number of tissue cores, the amount of tumor available for study is often quite limited. This is a particular challenge for research, as new biomarker assays will need to preserve tissue architecture intact for histopathology. Methods of processing and reporting pathology are discussed. With the exception of ductal variants, recognized subtypes of prostate cancer are largely confined to research applications, and most prostate cancers are acinar. Biomarker discovery in urine and expressed prostatic secretions would be useful since these are readily obtained and are proximate fluids. The well-known challenges of biomarker discovery in blood and urine are referenced and discussed. Mediators of carcinogenesis can serve as biomarkers as exemplified by mutations in PTEN and TMPRSS2:ERG fusion. The use of proteomics in biomarker discovery with an emphasis on imaging mass spectroscopy of tissues is discussed. Small RNAs are of great interest, however, their usefulness as biomarkers in clinical decision making remains the subject of ongoing research. The chapter concludes with an overview of blood biomarkers such as circulating nucleic acids and tumor cells and bound/free isoforms of prostate specific antigen (PSA).

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

DWI as an Imaging Biomarker for Bladder Cancer

NARCIS (Netherlands)

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

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

Molecular correlates of trait anxiety: expanding biomarker discovery from protein expression to turnover

OpenAIRE

Zhang, Yaoyang

2010-01-01

Depression and anxiety disorders affect a great number of people in the world. Although remarkable efforts have been devoted to understanding the clinical and biological basis of these disorders, progress has been relatively slow. Furthermore, no laboratory test currently is available for diagnosis of anxiety and depression. These disorders are mainly diagnosed empirically on the basis of a doctor’s personal observations and experiences. Hence, discovery of biomarkers for these psychiatric di...

Biomarker-guided repurposing of chemotherapeutic drugs for cancer therapy

DEFF Research Database (Denmark)

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

2013-01-01

-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 (Top1...

Fusion peptides from oncogenic chimeric proteins as putative specific biomarkers of cancer.

Science.gov (United States)

Conlon, Kevin P; Basrur, Venkatesha; Rolland, Delphine; Wolfe, Thomas; Nesvizhskii, Alexey I; MacCoss, Michael J; Lim, Megan S; Elenitoba-Johnson, Kojo S J

2013-10-01

Chromosomal translocations encoding chimeric fusion proteins constitute one of the most common mechanisms underlying oncogenic transformation in human cancer. Fusion peptides resulting from such oncogenic chimeric fusions, though unique to specific cancer subtypes, are unexplored as cancer biomarkers. Here we show, using an approach termed fusion peptide multiple reaction monitoring mass spectrometry, the direct identification of different cancer-specific fusion peptides arising from protein chimeras that are generated from the juxtaposition of heterologous genes fused by recurrent chromosomal translocations. Using fusion peptide multiple reaction monitoring mass spectrometry in a clinically relevant scenario, we demonstrate the specific, sensitive, and unambiguous detection of a specific diagnostic fusion peptide in clinical samples of anaplastic large cell lymphoma, but not in a diverse array of benign lymph nodes or other forms of primary malignant lymphomas and cancer-derived cell lines. Our studies highlight the utility of fusion peptides as cancer biomarkers and carry broad implications for the use of protein biomarkers in cancer detection and monitoring.

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

Science.gov (United States)

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

2012-12-01

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

Bone remodeling and regulating biomarkers in women at the time of breast cancer diagnosis.

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Yao, Song; Zhang, Yali; Tang, Li; Roh, Janise M; Laurent, Cecile A; Hong, Chi-Chen; Hahn, Theresa; Lo, Joan C; Ambrosone, Christine B; Kushi, Lawrence H; Kwan, Marilyn L

2017-02-01

The majority of breast cancer patients receive endocrine therapy, including aromatase inhibitors known to cause increased bone resorption. Bone-related biomarkers at the time of breast cancer diagnosis may predict future risk of osteoporosis and fracture after endocrine therapy. In a large population of 2,401 female breast cancer patients who later underwent endocrine therapy, we measured two bone remodeling biomarkers, TRAP5b and BAP, and two bone regulating biomarkers, RANKL and OPG, in serum samples collected at the time of breast cancer diagnosis. We analyzed these biomarkers and their ratios with patients' demographic, lifestyle, clinical tumor characteristics, as well as bone health history. The presence of bone metastases, prior bisphosphonate (BP) treatment, and blood collection after chemotherapy had a significant impact on biomarker levels. After excluding these cases and controlling for blood collection time, several factors, including age, race/ethnicity, body mass index, physical activity, alcohol consumption, smoking, and hormonal replacement therapy, were significantly associated with bone biomarkers, while vitamin D or calcium supplements and tumor characteristics were not. When prior BP users were included in, recent history of osteoporosis and fracture was also associated. Our findings support further investigation of these biomarkers with bone health outcomes after endocrine therapy initiation in women with breast cancer.

PET Metabolic Biomarkers for Cancer

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Etienne Croteau

2016-01-01

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

Evaluation of Multimodal Imaging Biomarkers of Prostate Cancer

Science.gov (United States)

2016-11-01

relationship prostate cancer growth, androgen receptor (AR) levels, hypoxia, and translocator protein (TSPO) levels. As described in the statement of work... bladder uptake) that enable robust detection of small prostate cancers . In contrast, high background and variable uptake of FDHT and FMISO confounded the...Award Number: W81XWH-12-1-0245 TITLE: Evaluation of Multimodal Imaging Biomarkers of Prostate Cancer PRINCIPAL INVESTIGATOR: Christopher Chad

RNA Biomarkers: Frontier of Precision Medicine for Cancer

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Xiaochen Xi

2017-02-01

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

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

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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.

Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers.

Science.gov (United States)

Rantalainen, Mattias; Klevebring, Daniel; Lindberg, Johan; Ivansson, Emma; Rosin, Gustaf; Kis, Lorand; Celebioglu, Fuat; Fredriksson, Irma; Czene, Kamila; Frisell, Jan; Hartman, Johan; Bergh, Jonas; Grönberg, Henrik

2016-11-30

Sequencing-based breast cancer diagnostics have the potential to replace routine biomarkers and provide molecular characterization that enable personalized precision medicine. Here we investigate the concordance between sequencing-based and routine diagnostic biomarkers and to what extent tumor sequencing contributes clinically actionable information. We applied DNA- and RNA-sequencing to characterize tumors from 307 breast cancer patients with replication in up to 739 patients. We developed models to predict status of routine biomarkers (ER, HER2,Ki-67, histological grade) from sequencing data. Non-routine biomarkers, including mutations in BRCA1, BRCA2 and ERBB2(HER2), and additional clinically actionable somatic alterations were also investigated. Concordance with routine diagnostic biomarkers was high for ER status (AUC = 0.95;AUC(replication) = 0.97) and HER2 status (AUC = 0.97;AUC(replication) = 0.92). The transcriptomic grade model enabled classification of histological grade 1 and histological grade 3 tumors with high accuracy (AUC = 0.98;AUC(replication) = 0.94). Clinically actionable mutations in BRCA1, BRCA2 and ERBB2(HER2) were detected in 5.5% of patients, while 53% had genomic alterations matching ongoing or concluded breast cancer studies. Sequencing-based molecular profiling can be applied as an alternative to histopathology to determine ER and HER2 status, in addition to providing improved tumor grading and clinically actionable mutations and molecular subtypes. Our results suggest that sequencing-based breast cancer diagnostics in a near future can replace routine biomarkers.

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

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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.

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

Molecular Biomarkers in the Clinical Management of Prostate Cancer.

Science.gov (United States)

Udager, Aaron M; Tomlins, Scott A

2018-01-08

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

The future workforce in cancer prevention: advancing discovery, research, and technology.

Science.gov (United States)

Newhauser, Wayne D; Scheurer, Michael E; Faupel-Badger, Jessica M; Clague, Jessica; Weitzel, Jeffrey; Woods, Kendra V

2012-05-01

As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Urinary metalloproteinases: noninvasive biomarkers for breast cancer risk assessment

DEFF Research Database (Denmark)

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

2008-01-01

Matrix metalloproteinases (MMP) and a disintegrin and metalloprotease 12 (ADAM 12) can be detected in the urine of breast cancer patients and provide independent prediction of disease status. To evaluate the potential of urinary metalloproteinases as biomarkers to predict breast cancer risk statu...

Nanotechnology for Early Cancer Detection

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Joon Won Park

2010-01-01

Full Text Available Vast numbers of studies and developments in the nanotechnology area have been conducted and many nanomaterials have been utilized to detect cancers at early stages. Nanomaterials have unique physical, optical and electrical properties that have proven to be very useful in sensing. Quantum dots, gold nanoparticles, magnetic nanoparticles, carbon nanotubes, gold nanowires and many other materials have been developed over the years, alongside the discovery of a wide range of biomarkers to lower the detection limit of cancer biomarkers. Proteins, antibody fragments, DNA fragments, and RNA fragments are the base of cancer biomarkers and have been used as targets in cancer detection and monitoring. It is highly anticipated that in the near future, we might be able to detect cancer at a very early stage, providing a much higher chance of treatment.

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

Science.gov (United States)

Teotia, Pradeep Kumar; Kaler, R. S.

2018-01-01

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

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

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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...

Identification and Validation of PCAT14 as Prognostic Biomarker in Prostate Cancer

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Sudhanshu Shukla

2016-08-01

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

Molecular Elucidation of Disease Biomarkers at the Interface of Chemistry and Biology.

Science.gov (United States)

Zhang, Liqin; Wan, Shuo; Jiang, Ying; Wang, Yanyue; Fu, Ting; Liu, Qiaoling; Cao, Zhijuan; Qiu, Liping; Tan, Weihong

2017-02-22

Disease-related biomarkers are objectively measurable molecular signatures of physiological status that can serve as disease indicators or drug targets in clinical diagnosis and therapy, thus acting as a tool in support of personalized medicine. For example, the prostate-specific antigen (PSA) biomarker is now widely used to screen patients for prostate cancer. However, few such biomarkers are currently available, and the process of biomarker identification and validation is prolonged and complicated by inefficient methods of discovery and few reliable analytical platforms. Therefore, in this Perspective, we look at the advanced chemistry of aptamer molecules and their significant role as molecular probes in biomarker studies. As a special class of functional nucleic acids evolved from an iterative technology termed Systematic Evolution of Ligands by Exponential Enrichment (SELEX), these single-stranded oligonucleotides can recognize their respective targets with selectivity and affinity comparable to those of protein antibodies. Because of their fast turnaround time and exceptional chemical properties, aptamer probes can serve as novel molecular tools for biomarker investigations, particularly in assisting identification of new disease-related biomarkers. More importantly, aptamers are able to recognize biomarkers from complex biological environments such as blood serum and cell surfaces, which can provide direct evidence for further clinical applications. This Perspective highlights several major advancements of aptamer-based biomarker discovery strategies and their potential contribution to the practice of precision medicine.

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

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 evalua...

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

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

Science.gov (United States)

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

2015-01-01

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

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

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Laura Lehtinen

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

Molecular lipid species in urinary exosomes as potential prostate cancer biomarkers.

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Skotland, Tore; Ekroos, Kim; Kauhanen, Dimple; Simolin, Helena; Seierstad, Therese; Berge, Viktor; Sandvig, Kirsten; Llorente, Alicia

2017-01-01

Exosomes have recently appeared as a novel source of noninvasive cancer biomarkers, since these nanovesicles contain molecules from cancer cells and can be detected in biofluids. We have here investigated the potential use of lipids in urinary exosomes as prostate cancer biomarkers. A high-throughput mass spectrometry quantitative lipidomic analysis was performed to reveal the lipid composition of urinary exosomes in prostate cancer patients and healthy controls. Control samples were first analysed to characterise the lipidome of urinary exosomes and test the reproducibility of the method. In total, 107 lipid species were quantified in urinary exosomes. Several differences, for example, in cholesterol and phosphatidylcholine, were found between urinary exosomes and exosomes derived from cell lines, thus showing the importance of in vivo studies for biomarker analysis. The 36 most abundant lipid species in urinary exosomes were then quantified in 15 prostate cancer patients and 13 healthy controls. Interestingly, the levels of nine lipids species were found to be significantly different when the two groups were compared. The highest significance was shown for phosphatidylserine (PS) 18:1/18:1 and lactosylceramide (d18:1/16:0), the latter also showed the highest patient-to-control ratio. Furthermore, combinations of these lipid species and PS 18:0-18:2 distinguished the two groups with 93% sensitivity and 100% specificity. Finally, in agreement with the reported dysregulation of sphingolipid metabolism in cancer cells, alteration in specific sphingolipid lipid classes were observed. This study shows for the first time the potential use of exosomal lipid species in urine as prostate cancer biomarkers. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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Michael Phillips

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

Engineered gold nanoparticles for identification of novel ovarian biomarkers

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Giri, Karuna

Ovarian cancer is a leading cause of cancer related death among women in the US and worldwide. The disease has a high mortality rate due to limited tools available that can diagnose ovarian cancer at an early stage and the lack of effective treatments for disease free survival at late stages. Identification of proteins specifically expressed/overexpressed in ovarian cancer could lead to identification of novel diagnostic biomarkers and therapeutic targets that improve patient outcomes. In this regard, mass spectrometry is a powerful tool to probe the proteome of a cancer cell. It can aid discovery of proteins important for the pathophysiology of ovarian cancer. These proteins in turn could serve as diagnostic and treatment biomarkers of the disease. However, a limitation of mass spectrometry based proteomic analyses is that the technique lacks sensitivity and is biased against detection of low abundance proteins. With current approaches to biomarker discovery, we may therefore be overlooking candidate proteins that are important for ovarian cancer. This study presents a new approach to enrich low abundance proteins and subsequently detect them with mass spectrometry. Gold nanoparticles (AuNPs) and functionalization of their surfaces provide an excellent opportunity to capture and enrich low abundance proteins. First, the study focused on conducting an extensive investigation of the time evolution of nanoparticle-protein interaction and understanding drivers of protein attachment on nanoparticle surface. The adsorption of proteins to AuNPs was found to be highly dynamic with multiple attachment and detachment events which decreased over time. Initially, electrostatic forces played an important role in protein binding and structurally flexible proteins such as those involved in RNA processing were more likely to bind to AuNPs. More importantly, the feasibility and success of protein enrichment by AuNPs was evaluated. The AuNPs based approach was able to detect

Further Development of an Exhaled microRNA Biomarker of Lung Cancer Risk

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2017-08-01

AWARD NUMBER: W81XWH-16-1-0328 TITLE: Further Development of an Exhaled microRNA Biomarker of Lung Cancer Risk PRINCIPAL INVESTIGATOR: Dr...4. TITLE AND SUBTITLE Further Development of an Exhaled microRNA Biomarker of Lung Cancer Risk 5b. GRANT NUMBER W81XWH 16-1-0328 5c. PROGRAM...devise a non-invasive airway based exhaled microRNA metric for lung cancer risk, initial work to be tested in a case control study. We expanded the

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

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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.

Circulating microRNAs as specific biomarkers for breast cancer detection.

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Enders K O Ng

Full Text Available 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.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%.These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening.

Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

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Chauhan, Ranjit; Lahiri, Nivedita

2016-01-01

Hepatocellular carcinoma (HCC), one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future. PMID:27398029

Tissue- and Serum-Associated Biomarkers of Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Ranjit Chauhan

2016-01-01

Full Text Available Hepatocellular carcinoma (HCC, one of the leading causes of cancer deaths in the world, is offering a challenge to human beings, with the current modes of treatment being a palliative approach. Lack of proper curative or preventive treatment methods encouraged extensive research around the world with an aim to detect a vaccine or therapeutic target biomolecule that could lead to development of a drug or vaccine against HCC. Biomarkers or biological disease markers have emerged as a potential tool as drug/vaccine targets, as they can accurately diagnose, predict, and even prevent the diseases. Biomarker expression in tissue, serum, plasma, or urine can detect tumor in very early stages of its development and monitor the cancer progression and also the effect of therapeutic interventions. Biomarker discoveries are driven by advanced techniques, such as proteomics, transcriptomics, whole genome sequencing, micro- and micro-RNA arrays, and translational clinics. In this review, an overview of the potential of tissue- and serum-associated HCC biomarkers as diagnostic, prognostic, and therapeutic targets for drug development is presented. In addition, we highlight recently developed micro-RNA, long noncoding RNA biomarkers, and single-nucleotide changes, which may be used independently or as complementary biomarkers. These active investigations going on around the world aimed at conquering HCC might show a bright light in the near future.

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

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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).

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

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2017-07-01

AWARD NUMBER: W81XWH-16-1-0274 TITLE: Molecular Characterization of H.pylori Strains and Biomarkers in Gastric Cancer PRINCIPAL INVESTIGATOR...SUBTITLE Molecular Characterization of H.pylori Strains and Biomarkers in Gastric Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-16-1-0274 5c...organoid technology via collaboration with Dr. Mary Estes (Baylor College of Medicine ) and her lab, via one-on-one visits, has guided Dr. Alex Peniche with

CBD: a biomarker database for colorectal cancer.

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Zhang, Xueli; Sun, Xiao-Feng; Cao, Yang; Ye, Benchen; Peng, Qiliang; Liu, Xingyun; Shen, Bairong; Zhang, Hong

2018-01-01

Colorectal cancer (CRC) biomarker database (CBD) was established based on 870 identified CRC biomarkers and their relevant information from 1115 original articles in PubMed published from 1986 to 2017. In this version of the CBD, CRC biomarker data were collected, sorted, displayed and analysed. The CBD with the credible contents as a powerful and time-saving tool provide more comprehensive and accurate information for further CRC biomarker research. The CBD was constructed under MySQL server. HTML, PHP and JavaScript languages have been used to implement the web interface. The Apache was selected as HTTP server. All of these web operations were implemented under the Windows system. The CBD could provide to users the multiple individual biomarker information and categorized into the biological category, source and application of biomarkers; the experiment methods, results, authors and publication resources; the research region, the average age of cohort, gender, race, the number of tumours, tumour location and stage. We only collect data from the articles with clear and credible results to prove the biomarkers are useful in the diagnosis, treatment or prognosis of CRC. The CBD can also provide a professional platform to researchers who are interested in CRC research to communicate, exchange their research ideas and further design high-quality research in CRC. They can submit their new findings to our database via the submission page and communicate with us in the CBD.Database URL: http://sysbio.suda.edu.cn/CBD/.

Peptidomics of urine and other biofluids for cancer diagnostics.

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Bauça, Josep Miquel; Martínez-Morillo, Eduardo; Diamandis, Eleftherios P

2014-08-01

Cancer is a leading cause of death worldwide. The low diagnostic sensitivity and specificity of most current cancer biomarkers make early cancer diagnosis a challenging task. The comprehensive study of peptides and small proteins in a living system, known as "peptidomics," represents an alternative technological approach to the discovery of potential biomarkers for the assessment of a wide variety of pathologies. This review examines the current status of peptidomics for several body fluids, with a focus on urine, for cancer diagnostics applications. Several studies have used high-throughput technologies to characterize the peptide content of different body fluids. Because of its noninvasive collection and high stability, urine is a valuable source of candidate cancer biomarkers. A wide variety of preanalytical issues concerning patient selection and sample handling need to be considered, because not doing so can affect the quality of the results by introducing bias and artifacts. Optimization of both the analytical strategies and the processing of bioinformatics data is also essential to minimize the false-discovery rate. Peptidomics-based studies of urine and other body fluids have yielded a number of biomolecules and peptide panels with potential for diagnosing different types of cancer, especially of the ovary, prostate, and bladder. Large-scale studies are needed to validate these molecules as cancer biomarkers. © 2013 American Association for Clinical Chemistry.

MicroRNA: a new and promising potential biomarker for diagnosis and prognosis of ovarian cancer

International Nuclear Information System (INIS)

Pal, Manish K.; Jaiswar, Shyam P.; Dwivedi, Vinaya N.; Tripathi, Amit K.; Dwivedi, Ashish; Sankhwar, Pushplata

2015-01-01

Epithelial ovarian cancer (EOC) is the leading cause of death among all gynecological malignancies. Despite the technological and medical advances over the past four decades, such as the development of several biological markers (mRNA and proteins biomarkers), the mortality rate of ovarian cancer remains a challenge because of its late diagnosis, which is specifically attributed to low specificities and sensitivities. Under this compulsive scenario, recent advances in expression biology have shifted in identifying and developing specific and sensitive biomarkers, such as microRNAs (miRNAs) for cancer diagnosis and prognosis. MiRNAs are a novel class of small non-coding RNAs that deregulate gene expression at the posttranscriptional level, either by translational repression or by mRNA degradation. These mechanisms may be involved in a complex cascade of cellular events associated with the pathophysiology of many types of cancer. MiRNAs are easily detectable in tissue and blood samples of cancer patients. Therefore, miRNAs hold good promise as potential biomarkers in ovarian cancer. In this review, we attempted to provide a comprehensive profile of key miRNAs involved in ovarian carcinoma to establish miRNAs as more reliable non-invasive clinical biomarkers for early detection of ovarian cancer compared with protein and DNA biomarkers

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

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Terry, Mary Beth; McDonald, Jasmine A; Wu, Hui Chen; Eng, Sybil; Santella, Regina M

2016-01-01

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

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

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2017-10-01

for prostate cancer , the work may impact development of diagnostic /prognostic products based on pThoc1. The presence of the THO ribonucleoprotin...AWARD NUMBER: W81XWH-14-1-0475 TITLE: The Thoc1 Ribonucleoprotein as a Novel Biomarker for Prostate Cancer Treatment Assignment PRINCIPAL...15Sept 2016 - 14Sep2017 4. TITLE AND SUBTITLE The Thoc1 Ribonucleoprotein as a Novel Biomarker for Prostate 5a. CONTRACT NUMBER Cancer Treatment

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

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

2017-07-01

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

Gene set-based module discovery in the breast cancer transcriptome

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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.

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids

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2014-01-01

Background Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we develop and apply a semi-automated literature mining method to mine abstracts obtained from PubMed to discover putative biomarkers of breast and lung cancers in specific biofluids. Methodology A positive set of abstracts was defined by the terms ‘breast cancer’ and ‘lung cancer’ in conjunction with 14 separate ‘biofluids’ (bile, blood, breastmilk, cerebrospinal fluid, mucus, plasma, saliva, semen, serum, synovial fluid, stool, sweat, tears, and urine), while a negative set of abstracts was defined by the terms ‘(biofluid) NOT breast cancer’ or ‘(biofluid) NOT lung cancer.’ More than 5.3 million total abstracts were obtained from PubMed and examined for biomarker-disease-biofluid associations (34,296 positive and 2,653,396 negative for breast cancer; 28,355 positive and 2,595,034 negative for lung cancer). Biological entities such as genes and proteins were tagged using ABNER, and processed using Python scripts to produce a list of putative biomarkers. Z-scores were calculated, ranked, and used to determine significance of putative biomarkers found. Manual verification of relevant abstracts was performed to assess our method’s performance. Results Biofluid-specific markers were identified from the literature, assigned relevance scores based on frequency of occurrence, and validated using known biomarker lists and/or databases for lung and breast cancer [NCBI’s On-line Mendelian Inheritance in Man (OMIM), Cancer Gene annotation server for cancer genomics (CAGE), NCBI’s Genes & Disease, NCI’s Early Detection Research Network (EDRN), and others]. The specificity of each marker for a given biofluid was calculated, and the performance of our semi-automated literature mining method assessed for breast and lung cancer

Disease Classification and Biomarker Discovery Using ECG Data

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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.

More Accurate Oral Cancer Screening with Fewer Salivary Biomarkers

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James Michael Menke

2017-10-01

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

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

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Craig A Gedye

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

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

Science.gov (United States)

Gedye, Craig A; Hussain, Ali; Paterson, Joshua; Smrke, Alannah; Saini, Harleen; Sirskyj, Danylo; Pereira, Keira; Lobo, Nazleen; Stewart, Jocelyn; Go, Christopher; Ho, Jenny; Medrano, Mauricio; Hyatt, Elzbieta; Yuan, Julie; Lauriault, Stevan; Meyer, Mona; Kondratyev, Maria; van den Beucken, Twan; Jewett, Michael; Dirks, Peter; Guidos, Cynthia J; Danska, Jayne; Wang, Jean; Wouters, Bradly; Neel, Benjamin; Rottapel, Robert; Ailles, Laurie E

2014-01-01

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 markers.

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

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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.

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

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 ...

Search for Breast Cancer Biomarkers in Fractionated Serum Samples by Protein Profiling With SELDI-TOF MS

NARCIS (Netherlands)

Opstal - van Winden, A.W.J.; Beijnen, J.H.; de Loof, A.; van Heerde, W.L.; Vermeulen, R.; Peeters, P.H.M.; van Gils, C.H.

2012-01-01

BackgroundMany high-abundant acute phase reactants have been previously detected as potential breast cancer biomar-kers. However, they are unlikely to be specific for breast cancer. Cancer-specific biomarkers are thought to be among the lower abundant proteins.MethodsWe aimed to detect lower

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

Science.gov (United States)

Lin, Ja-An; He, Pei

2015-06-01

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

A new device for liver cancer biomarker detection with high accuracy

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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.

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

Nanobody medicated immunoassay for ultrasensitive detection of cancer biomarker alpha-fetoprotein.

Science.gov (United States)

Chen, Jing; He, Qing-hua; Xu, Yang; Fu, Jin-heng; Li, Yan-ping; Tu, Zhui; Wang, Dan; Shu, Mei; Qiu, Yu-lou; Yang, Hong-wei; Liu, Yuan-yuan

2016-01-15

Immunoassay for cancer biomarkers plays an important role in cancer prevention and early diagnosis. To the development of immunoassay, the quality and stability of applied antibody is one of the key points to obtain reliability and high sensitivity for immunoassay. The main purpose of this study was to develop a novel immunoassay for ultrasensitive detection of cancer biomarker alpha-fetoprotein (AFP) based on nanobody against AFP. Two nanobodies which bind to AFP were selected from a phage display nanobody library by biopanning strategy. The prepared nanobodies are clonable, thermally stable and applied in both sandwich enzyme linked immunoassay (ELISA) and immuno-PCR assay for ultrasensitive detection of AFP. The limit detection of sandwich ELISA setup with optimized nanobodies was 0.48ng mL(-1), and the half of saturation concentration (SC50) value was 6.68±0.56ng mL(-1). These nanobodies were also used to develop an immuno-PCR assay for ultrasensitive detection of AFP, its limit detection values was 0.005ng mL(-1), and the linear range was 0.01-10,000ng mL(-1). These established immunoassays based on nanobodies were highly specific to AFP and with negligible cross reactivity with other tested caner biomarkers. Furthermore, this novel concept of nanobodies mediated immunoassay may provide potential applications in a general method for the ultrasensitive detection of various cancer biomarkers. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Dey Dipak K

2008-01-01

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

Identification of prostate cancer biomarkers in urinary exosomes.

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

2015-10-06

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.

Systems-based biological concordance and predictive reproducibility of gene set discovery methods in cardiovascular disease.

Science.gov (United States)

Azuaje, Francisco; Zheng, Huiru; Camargo, Anyela; Wang, Haiying

2011-08-01

The discovery of novel disease biomarkers is a crucial challenge for translational bioinformatics. Demonstration of both their classification power and reproducibility across independent datasets are essential requirements to assess their potential clinical relevance. Small datasets and multiplicity of putative biomarker sets may explain lack of predictive reproducibility. Studies based on pathway-driven discovery approaches have suggested that, despite such discrepancies, the resulting putative biomarkers tend to be implicated in common biological processes. Investigations of this problem have been mainly focused on datasets derived from cancer research. We investigated the predictive and functional concordance of five methods for discovering putative biomarkers in four independently-generated datasets from the cardiovascular disease domain. A diversity of biosignatures was identified by the different methods. However, we found strong biological process concordance between them, especially in the case of methods based on gene set analysis. With a few exceptions, we observed lack of classification reproducibility using independent datasets. Partial overlaps between our putative sets of biomarkers and the primary studies exist. Despite the observed limitations, pathway-driven or gene set analysis can predict potentially novel biomarkers and can jointly point to biomedically-relevant underlying molecular mechanisms. Copyright © 2011 Elsevier Inc. All rights reserved.

Predicting risk of cancer during HIV infection: the role of inflammatory and coagulation biomarkers.

Science.gov (United States)

Borges, Álvaro H; Silverberg, Michael J; Wentworth, Deborah; Grulich, Andrew E; Fätkenheuer, Gerd; Mitsuyasu, Ronald; Tambussi, Giuseppe; Sabin, Caroline A; Neaton, James D; Lundgren, Jens D

2013-06-01

To investigate the relationship between inflammatory [interleukin-6 (IL-6) and C-reactive protein (CRP)] and coagulation (D-dimer) biomarkers and cancer risk during HIV infection. A prospective cohort. HIV-infected patients on continuous antiretroviral therapy (ART) in the control arms of three randomized trials (N=5023) were included in an analysis of predictors of cancer (any type, infection-related or infection-unrelated). Hazard ratios for IL-6, CRP and D-dimer levels (log2-transformed) were calculated using Cox models stratified by trial and adjusted for demographics and CD4+ cell counts and adjusted also for all biomarkers simultaneously. To assess the possibility that biomarker levels were elevated at entry due to undiagnosed cancer, analyses were repeated excluding early cancer events (i.e. diagnosed during first 2 years of follow-up). During approximately 24,000 person-years of follow-up (PYFU), 172 patients developed cancer (70 infection-related; 102 infection-unrelated). The risk of developing cancer was associated with higher levels (per doubling) of IL-6 (hazard ratio 1.38, Passociated with cancer risk when all biomarkers were considered simultaneously. Results for infection-related and infection-unrelated cancers were similar to results for any cancer. Hazard ratios excluding 69 early cancer events were 1.31 (P=0.007), 1.14 (P=0.02) and 1.07 (P=0.49) for IL-6, CRP and D-dimer, respectively. Activated inflammation and coagulation pathways are associated with increased cancer risk during HIV infection. This association was stronger for IL-6 and persisted after excluding early cancer. Trials of interventions may be warranted to assess whether cancer risk can be reduced by lowering IL-6 levels in HIV-positive individuals.

Podoplanin - an emerging cancer biomarker and therapeutic target.

Science.gov (United States)

Krishnan, Harini; Rayes, Julie; Miyashita, Tomoyuki; Ishii, Genichiro; Retzbach, Edward P; Sheehan, Stephanie A; Takemoto, Ai; Chang, Yao-Wen; Yoneda, Kazue; Asai, Jun; Jensen, Lasse; Chalise, Lushun; Natsume, Atsushi; Goldberg, Gary S

2018-03-25

Podoplanin (PDPN) is a transmembrane receptor glycoprotein that is upregulated on transformed cells, cancer associated fibroblasts (CAFs), and inflammatory macrophages that contribute to cancer progression. In particular, PDPN increases tumor cell clonal capacity, epithelial mesenchymal transition (EMT), migration, invasion, metastasis, and inflammation. Antibodies, CAR-T cells, biologics, and synthetic compounds that target PDPN can inhibit cancer progression and septic inflammation in preclinical models. This review describes recent advances in how PDPN may be used as a biomarker and therapeutic target for many types of cancer including glioma, squamous cell carcinoma, mesothelioma, and melanoma. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

The extracellular domain of Her2 in serum as a biomarker of breast cancer.

Science.gov (United States)

Perrier, Alexandre; Gligorov, Joseph; Lefèvre, Guillaume; Boissan, Mathieu

2018-02-28

Breast cancer is a major health problem worldwide. In ~15% of breast cancers, the epidermal growth factor receptor HER2, a transmembrane protein, is overexpressed. This HER2 overexpression is associated with an aggressive form of the disease and a poor clinical prognosis. The extracellular domain (ECD) of HER2 is released into the blood by a proteolytic mechanism known as "ECD shedding". This proteolytic shedding leaves a constitutively active truncated receptor in the membrane that is 10-100-fold more oncogenic than the full-length receptor and promotes the growth and survival of cancer cells. Shedding of the HER2 ECD is increased during metastasis: whereas 15% of primary breast cancer patients have elevated levels of serum HER2 ECD (sHER2 ECD), the levels reach 45% in patients with metastatic disease. Thus, sHER2 ECD has been proposed as a promising biomarker for cancer recurrence and for monitoring the disease status of patients overexpressing HER2. Nevertheless, in 2016, the American Society of Clinical Oncology advises clinicians not to use soluble HER2 levels to guide their choice of adjuvant therapy for patients with HER2-positive breast cancer, because the evidence was considered not strong enough. Currently, biomarkers such as carcinoembryonic antigen and cancer antigen 15-3 are widely used to monitor metastatic breast cancer disease even if the level of evidence of clinical impact of this monitoring is poor. In this article, we review the evidence that sHER2 ECD might be used in some situations as a biomarker for breast cancer. Although this serum biomarker will not replace the direct measurement of tumor HER2 status for diagnosis of early-stage tumors; it might be especially useful in metastatic disease for prognosis, as an indicator of cancer progression and of therapy response, particularly to anti-HER2 therapies. Owing to these data, sHER2 ECD should be considered as a promising biomarker to detect cancer recurrence and metastasis.

The Janus serum bank and biomarkers of cancer

Directory of Open Access Journals (Sweden)

Randi Gislefoss

2009-10-01

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

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

International Nuclear Information System (INIS)

Windus, Louisa C.E.; Kiss, Debra L.; Glover, Tristan; Avery, Vicky M.

2012-01-01

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 α6 integrin expression and an up-regulation of N-cadherin, Vimentin and β1 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: ► We developed and optimised 3D culturing techniques for Prostate Cancer cell-lines. ► We investigated biomarker expression in 2D versus 3D culture techniques. ► Metastatic PC3 cells re-expressed non-transcriptionally active androgen receptor. ► Metastatic PCa cell lines retain in vivo-like antigenic profiles in 3D cultures

Defining glycoprotein cancer biomarkers by MS in conjunction with glycoprotein enrichment.

Science.gov (United States)

Song, Ehwang; Mechref, Yehia

2015-01-01

Protein glycosylation is an important and common post-translational modification. More than 50% of human proteins are believed to be glycosylated to modulate the functionality of proteins. Aberrant glycosylation has been correlated to several diseases, such as inflammatory skin diseases, diabetes mellitus, cardiovascular disorders, rheumatoid arthritis, Alzheimer's and prion diseases, and cancer. Many approved cancer biomarkers are glycoproteins which are not highly abundant proteins. Therefore, effective qualitative and quantitative assessment of glycoproteins entails enrichment methods. This chapter summarizes glycoprotein enrichment methods, including lectin affinity, immunoaffinity, hydrazide chemistry, hydrophilic interaction liquid chromatography, and click chemistry. The use of these enrichment approaches in assessing the qualitative and quantitative changes of glycoproteins in different types of cancers are presented and discussed. This chapter highlights the importance of glycoprotein enrichment techniques for the identification and characterization of new reliable cancer biomarkers.

Circulating exosomal microRNAs as biomarkers of colon cancer.

Directory of Open Access Journals (Sweden)

Hiroko Ogata-Kawata

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

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...

Epigenome-Wide Tumor DNA Methylation Profiling Identifies Novel Prognostic Biomarkers of Metastatic-Lethal Progression in Men Diagnosed with Clinically Localized Prostate Cancer.

Science.gov (United States)

Zhao, Shanshan; Geybels, Milan S; Leonardson, Amy; Rubicz, Rohina; Kolb, Suzanne; Yan, Qingxiang; Klotzle, Brandy; Bibikova, Marina; Hurtado-Coll, Antonio; Troyer, Dean; Lance, Raymond; Lin, Daniel W; Wright, Jonathan L; Ostrander, Elaine A; Fan, Jian-Bing; Feng, Ziding; Stanford, Janet L

2017-01-01

Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential. Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum. Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR. ©2016 American Association for Cancer Research.

Direct detection of cancer biomarkers in blood using a "place n play" modular polydimethylsiloxane pump.

Science.gov (United States)

Zhang, Honglian; Li, Gang; Liao, Lingying; Mao, Hongju; Jin, Qinghui; Zhao, Jianlong

2013-01-01

Cancer biomarkers have significant potential as reliable tools for the early detection of the disease and for monitoring its recurrence. However, most current methods for biomarker detection have technical difficulties (such as sample preparation and specific detector requirements) which limit their application in point of care diagnostics. We developed an extremely simple, power-free microfluidic system for direct detection of cancer biomarkers in microliter volumes of whole blood. CEA and CYFRA21-1 were chosen as model cancer biomarkers. The system automatically extracted blood plasma from less than 3 μl of whole blood and performed a multiplex sample-to-answer assay (nano-ELISA (enzyme-linked immunosorbent assay) technique) without the use of external power or extra components. By taking advantage of the nano-ELISA technique, this microfluidic system detected CEA at a concentration of 50 pg/ml and CYFRA21-1 at a concentration of 60 pg/ml within 60 min. The combination of PnP polydimethylsiloxane (PDMS) pump and nano-ELISA technique in a single microchip system shows great promise for the detection of cancer biomarkers in a drop of blood.

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

Science.gov (United States)

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

2014-10-01

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

A review of molecular biomarkers for bladder cancer

African Journals Online (AJOL)

McRoy

Volume 2 Issue 3 September – December 2013 ... methodology were identified but only half of them have shown consistence ... Conclusion: It is envisaged that a combination ... biomarkers for bladder cancer are adopted in the UK standard practice. ... words used for the literature review were ..... Multi centre validation.

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

Directory of Open Access Journals (Sweden)

Isaac D

2017-07-01

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

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

DEFF Research Database (Denmark)

Sandfeld-Paulsen, B; 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...... Bonferroni correction. Results were adjusted for clinico-pathological characteristics, stage, histology, age, sex and performance status. CONCLUSION: We illustrate the promising aspects associated with the use of exosomal membrane-bound proteins as a biomarker and demonstrate that they are a strong...

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

Science.gov (United States)

Mino-Kenudson, Mari

2017-10-01

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

Biomarker in Cisplatin-Based Chemotherapy for Urinary Bladder Cancer.

Science.gov (United States)

Ecke, Thorsten H

2015-01-01

The treatment of metastasized bladder cancer has been evolving during recent years. Cisplatin based chemotherapy combinations are still gold standard in the treatment of advanced and metastasized bladder cancer. But new therapies are approaching. Based to this fact biological markers will become more important for decisions in bladder cancer treatment. A systematic MEDLINE search of the key words "cisplatin", "bladder cancer", "DNA marker", "protein marker", "methylation biomarker", "predictive marker", "prognostic marker" has been made. This review aims to highlight the most relevant clinical and experimental studies investigating markers for metastasized transitional carcinoma of the urothelium treated by cisplatin based regimens.

Diagnostic and Prognostic MicroRNA Biomarkers for Prostate Cancer in Cell-free Urine

DEFF Research Database (Denmark)

Fredsøe, Jacob Christian; Rasmussen, Anne Karin; Thomsen, Anni Rønfeldt

2017-01-01

Background: Widespread use of prostate-specific antigen (PSA) testing for prostate cancer (PC) detection has led to extensive overdiagnosis and overtreatment. Urine-based microRNA (miRNA) biomarkers could be useful in PC diagnosis and prognosis. Objective: To train and validate urine-based micro......RNA (miRNA) biomarkers that may assist in PC diagnosis and prognosis. Design, setting, and participants: We profiled the expression levels of 92 miRNAs via reverse transcriptase–poymerase chain reaction in cell-free urine samples from 29 patients with benign prostatic hyperplasia (BPH) and 215 patients...... could help in primary diagnosis of PC and guide treatment decisions. Further validation studies are warranted. Patient summary: Using two large patient cohorts, we searched for novel prostate cancer biomarkers in urine. We found two new sets of microRNA biomarkers in urine that could accurately predict...

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.

Crowdsourcing Disease Biomarker Discovery Research: The IP4IC Study.

Science.gov (United States)

Chancellor, Michael B; Bartolone, Sarah N; Veerecke, Andrew; Lamb, Laura E

2018-05-01

Biomarker discovery is limited by readily assessable, cost efficient human samples available in large numbers that represent the entire heterogeneity of the disease. We developed a novel, active participation crowdsourcing method to determine BP-RS (Bladder Permeability Defect Risk Score). It is based on noninvasive urinary cytokines to discriminate patients with interstitial cystitis/bladder pain syndrome who had Hunner lesions from controls and patients with interstitial cystitis/bladder pain syndrome but without Hunner lesions. We performed a national crowdsourcing study in cooperation with the Interstitial Cystitis Association. Patients answered demographic, symptom severity and urinary frequency questionnaires on a HIPAA (Health Insurance Portability and Accountability Act) compliant website. Urine samples were collected at home, stabilized with a preservative and sent to Beaumont Hospital for analysis. The expression of 3 urinary cytokines was used in a machine learning algorithm to develop BP-RS. The IP4IC study collected a total of 448 urine samples, representing 153 patients (147 females and 6 males) with interstitial cystitis/bladder pain syndrome, of whom 54 (50 females and 4 males) had Hunner lesions. A total of 159 female and 136 male controls also participated, who were age matched. A defined BP-RS was calculated to predict interstitial cystitis/bladder pain syndrome with Hunner lesions or a bladder permeability defect etiology with 89% validity. In this novel participation crowdsourcing study we obtained a large number of urine samples from 46 states, which were collected at home, shipped and stored at room temperature. Using a machine learning algorithm we developed BP-RS to quantify the risk of interstitial cystitis/bladder pain syndrome with Hunner lesions, which is indicative of a bladder permeability defect etiology. To our knowledge BP-RS is the first validated urine biomarker assay for interstitial cystitis/bladder pain syndrome and one of the

A Comprehensive Peptidome Profiling Technology for the Identification of Early Detection Biomarkers for Lung Adenocarcinoma

Science.gov (United States)

Ueda, Koji; Saichi, Naomi; Takami, Sachiko; Kang, Daechun; Toyama, Atsuhiko; Daigo, Yataro; Ishikawa, Nobuhisa; Kohno, Nobuoki; Tamura, Kenji; Shuin, Taro; Nakayama, Masato; Sato, Taka-Aki; Nakamura, Yusuke; Nakagawa, Hidewaki

2011-01-01

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000–5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273–283, FIBA 5–16, and LBN 306–313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens. PMID:21533267

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

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

Directory of Open Access Journals (Sweden)

Paul R West

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

Metabolomics as a Tool for Discovery of Biomarkers of Autism Spectrum Disorder in the Blood Plasma of Children

Science.gov (United States)

West, Paul R.; Amaral, David G.; Bais, Preeti; Smith, Alan M.; Egnash, Laura A.; Ross, Mark E.; Palmer, Jessica A.; Fontaine, Burr R.; Conard, Kevin R.; Corbett, Blythe A.; Cezar, Gabriela G.; Donley, Elizabeth L. R.; Burrier, Robert E.

2014-01-01

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

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

Exosomes in Cancer Liquid Biopsy: A Focus on Breast Cancer

OpenAIRE

Sina Halvaei; Shiva Daryani; Zahra Eslami-S; Tannaz Samadi; Narges Jafarbeik-Iravani; Tayebeh Oghabi Bakhshayesh; Keivan Majidzadeh-A; Rezvan Esmaeili

2018-01-01

The important challenge about cancer is diagnosis in primary stages and proper treatment. Although classical clinico-pathological features of the tumor have major prognostic value, the advances in diagnosis and treatment are indebted to discovery of molecular biomarkers and control of cancer in the pre-invasive state. Moreover, the efficiency of available therapeutic options is highly diminished, and chemotherapy is still the main treatment due to lack of enough specific targets. Accordingly,...

Prostate cancer biomarker profiles in urinary sediments and exosomes

NARCIS (Netherlands)

Dijkstra, Siebren; Birker, Ingrid L.; Smit, Frank P.; Leyten, Gisele H. J. M.; de Reijke, Theo M.; van Oort, Inge M.; Mulders, Peter F. A.; Jannink, Sander A.; Schalken, Jack A.

2014-01-01

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

Prostate cancer biomarker profiles in urinary sediments and exosomes

NARCIS (Netherlands)

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

2014-01-01

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

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

Directory of Open Access Journals (Sweden)

Pierre-Olivier Gaudreau

2016-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

Breast Cancer Biomarkers Based on Nipple and Fine Needle Aspirates

National Research Council Canada - National Science Library

Russo, Irma H

2005-01-01

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

Integrating text mining, data mining, and network analysis for identifying genetic breast cancer trends.

Science.gov (United States)

Jurca, Gabriela; Addam, Omar; Aksac, Alper; Gao, Shang; Özyer, Tansel; Demetrick, Douglas; Alhajj, Reda

2016-04-26

Breast cancer is a serious disease which affects many women and may lead to death. It has received considerable attention from the research community. Thus, biomedical researchers aim to find genetic biomarkers indicative of the disease. Novel biomarkers can be elucidated from the existing literature. However, the vast amount of scientific publications on breast cancer make this a daunting task. This paper presents a framework which investigates existing literature data for informative discoveries. It integrates text mining and social network analysis in order to identify new potential biomarkers for breast cancer. We utilized PubMed for the testing. We investigated gene-gene interactions, as well as novel interactions such as gene-year, gene-country, and abstract-country to find out how the discoveries varied over time and how overlapping/diverse are the discoveries and the interest of various research groups in different countries. Interesting trends have been identified and discussed, e.g., different genes are highlighted in relationship to different countries though the various genes were found to share functionality. Some text analysis based results have been validated against results from other tools that predict gene-gene relations and gene functions.

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

NARCIS (Netherlands)

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

2004-01-01

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

The endothelial lipase protein is promising urinary biomarker for diagnosis of gastric cancer.

Science.gov (United States)

Dong, Xueyan; Wang, Guoqing; Zhang, Guoqing; Ni, Zhaohui; Suo, Jian; Cui, Juan; Cui, Ai; Yang, Qing; Xu, Ying; Li, Fan

2013-03-19

Gastric cancer is one of the most common malignant tumors in the world. Finding effective diagnostic biomarkers in urine or serum would represent the most ideal solution to detecting gastric cancer during annual physical examination. This study was to evaluate the potential of endothelial lipase (EL) as a urinary biomarker for diagnosis of gastric cancer. The expression levels of EL was measured using Western blotting and immunohistochemical staining experiments on (tissue, serum, and urine) samples of gastric cancer patients versus healthy people. We also checked the EL levels in the urine samples of other cancer types (lung, colon and rectum cancers) and benign lesions (gastritis and gastric leiomyoma) to check if EL was specific to gastric cancer. We observed a clear separation between the EL expression levels in the urine samples of 90 gastric cancer patients and of 57 healthy volunteers. It was approximately 9.9 fold average decrease of the EL expression levels in the urine samples of gastric cancer compared to the healthy controls (P cancer. Interestingly, the expression levels of EL in tissue and serum samples were not nearly as discriminative as in urine samples (P = 0.90 and P = 0.79). In immunohistochemical experiments, positive expression of the EL protein was found in 67% (8/12) of gastric adjacent noncancerous and in 58% (7/12) of gastric cancer samples. There was no significant statistical in the expression levels of this protein between the gastric cancer and the matching noncancerous tissues (P =0.67). The urinary EL as a highly accurate gastric cancer biomarker that is potentially applicable to the general screening with high sensitivity and specificity. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/4527331618757552.

Exosomal Proteins as a Diagnostic Biomarkers in Lung Cancer

DEFF Research Database (Denmark)

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

2016-01-01

INTRODUCTION: Exosomes have been suggested as promising biomarkers in NSCLC because they contain proteins from their originating cells and are readily available in plasma. In this study, we explored the potential of exosome protein profiling in diagnosing lung cancers of all stages and various...

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.

Novel robust biomarkers for human bladder cancer based on activation of intracellular signaling pathways

OpenAIRE

Lezhnina, Ksenia; Kovalchuk, Olga; Zhavoronkov, Alexander A.; Korzinkin, Mikhail B.; Zabolotneva, Anastasia A.; Shegay, Peter V.; Sokov, Dmitry G.; Gaifullin, Nurshat M.; Rusakov, Igor G.; Aliper, Alexander M.; Roumiantsev, Sergey A.; Alekseev, Boris Y.; Borisov, Nikolay M.; Buzdin, Anton A.

2014-01-01

We recently proposed a new bioinformatic algorithm called OncoFinder for quantifying the activation of intracellular signaling pathways. It was proved advantageous for minimizing errors of high-throughput gene expression analyses and showed strong potential for identifying new biomarkers. Here, for the first time, we applied OncoFinder for normal and cancerous tissues of the human bladder to identify biomarkers of bladder cancer. Using Illumina HT12v4 microarrays, we profiled gene expression ...

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

International Nuclear Information System (INIS)

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

2011-01-01

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 [ 18F ]fluorocyclo butane 1 carboxylic acid ([ 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, [ 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. [ 18F ]FACBC that correlates with LAT1 function is a potential PET tracer for malignant breast tumor imaging

[Interlaboratory trials for quality assurance of breast cancer biomarkers in Germany].

Science.gov (United States)

Krusche, C A; von Wasielewski, R; Rüschoff, J; Fisseler-Eckhoff, A; Kreipe, H H

2008-07-01

In the age of personalized medicine, and in addition to typing and grading, breast cancer pathologists are now also involved in determining biomarkers such as steroid hormone receptors and Her-2, which are of the utmost importance in adjuvant therapy. In order to assure quality of these biomarker assays, external proficiency testing has been implemented in Germany. Since 2002 trials have been conducted annually, with up to 180 participating laboratories. More than 85% of all participants achieved good results in clearly negative and positive cases seen in daily practice. If at all, discordant results were observed in the rarer low steroid-hormone receptor expressing tumors and Her-2 borderline cases (2+). Regular participation in interlaboratory testing leads to significantly improved immunohistochemical results, particularly in these problematic cases. Tissue microarrays (TMA) with 20-24 different breast cancer samples including cell lines meant that a huge number of pathologists were challenged with identical samples, providing the prerequisite for comparability. Participation is recommended for pathology departments involved in the service for breast units. The organizational frame work of the trials is described here. The confidence of cooperating disciplines in breast cancer biomarkers assessed by pathologists will be fostered by external proficiency testing as presented here.

Toward Precision Medicine: A Cancer Molecular Subtyping Nano-Strategy for RNA Biomarkers in Tumor and Urine.

Science.gov (United States)

Koo, Kevin M; Wee, Eugene J H; Mainwaring, Paul N; Wang, Yuling; Trau, Matt

2016-12-01

Cancer is a heterogeneous disease which manifests as different molecular subtypes due to the complex nature of tumor initiation, progression, and metastasis. The concept of precision medicine aims to exploit this cancer heterogeneity by incorporating diagnostic technology to characterize each cancer patient's molecular subtype for tailored treatments. To characterize cancer molecular subtypes accurately, a suite of multiplexed bioassays have currently been developed to detect multiple oncogenic biomarkers. Despite the reliability of current multiplexed detection techniques, novel strategies are still needed to resolve limitations such as long assay time, complex protocols, and difficulty in interpreting broad overlapping spectral peaks of conventional fluorescence readouts. Herein a rapid (80 min) multiplexed platform strategy for subtyping prostate cancer tumor and urine samples based on their RNA biomarker profiles is presented. This is achieved by combining rapid multiplexed isothermal reverse transcription-recombinase polymerase amplification (RT-RPA) of target RNA biomarkers with surface-enhanced Raman spectroscopy (SERS) nanotags for "one-pot" readout. This is the first translational application of a RT-RPA/SERS-based platform for multiplexed cancer biomarker detection to address a clinical need. With excellent sensitivity of 200 zmol (100 copies) and specificity, we believed that this platform methodology could be a useful tool for rapid multiplexed subtyping of cancers. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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

2017-01-01

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

Microfluidic extraction and microarray detection of biomarkers from cancer tissue slides

Science.gov (United States)

Nguyen, H. T.; Dupont, L. N.; Jean, A. M.; Géhin, T.; Chevolot, Y.; Laurenceau, E.; Gijs, M. A. M.

2018-03-01

We report here a new microfluidic method allowing for the quantification of human epidermal growth factor receptor 2 (HER2) expression levels from formalin-fixed breast cancer tissues. After partial extraction of proteins from the tissue slide, the extract is routed to an antibody (Ab) microarray for HER2 titration by fluorescence. Then the HER2-expressing cell area is evaluated by immunofluorescence (IF) staining of the tissue slide and used to normalize the fluorescent HER2 signal measured from the Ab microarray. The number of HER2 gene copies measured by fluorescence in situ hybridization (FISH) on an adjacent tissue slide is concordant with the normalized HER2 expression signal. This work is the first study implementing biomarker extraction and detection from cancer tissue slides using microfluidics in combination with a microarray system, paving the way for further developments towards multiplex and precise quantification of cancer biomarkers.

The Role of Biomarkers in Decreasing Risk of Cardiac Toxicity after Cancer Therapy

Directory of Open Access Journals (Sweden)

Christine Henri

2016-01-01

Full Text Available With the improvement of cancer therapy, survival related to malignancy has improved, but the prevalence of long-term cardiotoxicity has also increased. Cancer therapies with known cardiac toxicity include anthracyclines, biologic agents (trastuzumab, and multikinase inhibitors (sunitinib. The most frequent presentation of cardiac toxicity is dilated cardiomyopathy associated with poorest prognosis. Monitoring of cardiac toxicity is commonly performed by assessment of left ventricular (LV ejection fraction, which requires a significant amount of myocardial damage to allow detection of cardiac toxicity. Accordingly, this creates the impetus to search for more sensitive and reproducible biomarkers of cardiac toxicity after cancer therapy. Different biomarkers have been proposed to that end, the most studied ones included troponin release resulting from cardiomyocyte damage and natriuretic peptides reflecting elevation in LV filling pressure and wall stress. Increase in the levels of troponin and natriuretic peptides have been correlated with cumulative dose of anthracycline and the degree of LV dysfunction. Troponin is recognized as a highly efficient predictor of early and chronic cardiac toxicity, but there remains some debate regarding the clinical usefulness of the measurement of natriuretic peptides because of divergent results. Preliminary data are available for other biomarkers targeting inflammation, endothelial dysfunction, myocardial ischemia, and neuregulin-1. The purpose of this article is to review the available data to determine the role of biomarkers in decreasing the risk of cardiac toxicity after cancer therapy.

Prostate-specific antigen (PSA) as a possible biomarker in non-prostatic cancer: A review.

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Pérez-Ibave, Diana Cristina; Burciaga-Flores, Carlos Horacio; Elizondo-Riojas, Miguel-Ángel

2018-06-01

Prostate-specific antigen (PSA) is a serine protease produced by epithelial prostatic cells and its main function is to liquefy seminal coagulum. Currently, PSA is a biomarker for the diagnosis and screening of prostate cancer and it was the first cancer biomarker approved by the FDA. The quantity and serum isoforms of male PSA, allows distinguishing between carcinoma and benign inflammatory disease of the prostate. Initially, it was thought that PSA was produced only by the prostate, and thus, a protein that was expressed exclusively in men. However, several authors report that PSA is a protein that is expressed by multiple non-prostatic tissues not only in men but also in women. Some authors also report that in women, the expression of this protein is highly related to breast and colon cancer and therefore can act as a possible biomarker for early detection, diagnosis and prognosis of these cancers in women. In this review, we will focus on the characteristics of the PSA at a molecular level, its current clinical implications, the expression of this protein in non-prostatic tissues, and its relationship with cancer, especially in women. Copyright © 2018 Elsevier Ltd. All rights reserved.

Discovery – Cisplatin and The Treatment of Testicular and Other Cancers

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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.

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

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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. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Quantitative proteomic analysis by iTRAQ® for the identification of candidate biomarkers in ovarian cancer serum

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Higgins LeeAnn

2010-06-01

Full Text Available Abstract Background Ovarian cancer is the most lethal gynecologic malignancy, with the majority of cases diagnosed at an advanced stage when treatments are less successful. Novel serum protein markers are needed to detect ovarian cancer in its earliest stage; when detected early, survival rates are over 90%. The identification of new serum biomarkers is hindered by the presence of a small number of highly abundant proteins that comprise approximately 95% of serum total protein. In this study, we used pooled serum depleted of the most highly abundant proteins to reduce the dynamic range of proteins, and thereby enhance the identification of serum biomarkers using the quantitative proteomic method iTRAQ®. Results Medium and low abundance proteins from 6 serum pools of 10 patients each from women with serous ovarian carcinoma, and 6 non-cancer control pools were labeled with isobaric tags using iTRAQ® to determine the relative abundance of serum proteins identified by MS. A total of 220 unique proteins were identified and fourteen proteins were elevated in ovarian cancer compared to control serum pools, including several novel candidate ovarian cancer biomarkers: extracellular matrix protein-1, leucine-rich alpha-2 glycoprotein-1, lipopolysaccharide binding protein-1, and proteoglycan-4. Western immunoblotting validated the relative increases in serum protein levels for several of the proteins identified. Conclusions This study provides the first analysis of immunodepleted serum in combination with iTRAQ® to measure relative protein expression in ovarian cancer patients for the pursuit of serum biomarkers. Several candidate biomarkers were identified which warrant further development.

Translational Bioinformatics for Diagnostic and Prognostic Prediction of Prostate Cancer in the Next-Generation Sequencing Era

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Jiajia Chen

2013-01-01

Full Text Available The discovery of prostate cancer biomarkers has been boosted by the advent of next-generation sequencing (NGS technologies. Nevertheless, many challenges still exist in exploiting the flood of sequence data and translating them into routine diagnostics and prognosis of prostate cancer. Here we review the recent developments in prostate cancer biomarkers by high throughput sequencing technologies. We highlight some fundamental issues of translational bioinformatics and the potential use of cloud computing in NGS data processing for the improvement of prostate cancer treatment.

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

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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.

Mass spectrometry for biomarker development

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Wu, Chaochao; Liu, Tao; Baker, Erin Shammel; Rodland, Karin D.; Smith, Richard D.

2015-06-19

Biomarkers potentially play a crucial role in early disease diagnosis, prognosis and targeted therapy. In the past decade, mass spectrometry based proteomics has become increasingly important in biomarker development due to large advances in technology and associated methods. This chapter mainly focuses on the application of broad (e.g. shotgun) proteomics in biomarker discovery and the utility of targeted proteomics in biomarker verification and validation. A range of mass spectrometry methodologies are discussed emphasizing their efficacy in the different stages in biomarker development, with a particular emphasis on blood biomarker development.

Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

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Cui Ziyou

2009-03-01

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

Discovery and identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

Science.gov (United States)

Shi, Linan; Zhang, Jun; Wu, Peng; Feng, Kai; Li, Jing; Xie, Zhensheng; Xue, Peng; Cai, Tanxi; Cui, Ziyou; Chen, Xiulan; Hou, Junjie; Zhang, Jianzhong; Yang, Fuquan

2009-01-01

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

Early Detection of Cancer by Affinity Mass Spectrometry-Set Aside funds — EDRN Public Portal

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A.   RATIONALE The recent introduction of multiple reaction monitoring capabilities offers unprecedented capability to the research arsenal available to protein based biomarker discovery. Specific to the discovery process this technology offers an ability to monitor specific protein changes in concentration and/or post-translational modification. The ability to accurately confirm specific biomarkers in a sensitive and reproducible manner is critical to the confirmation and pre-validation process. We are proposing two collaborative studies that promise to develop Multiple Reaction Monitoring (MRM) work flows for the biomarker scientific community and specifically for EDRN. B.   GOALS The overall goal for this proposal is the identification of protein biomarkers that can be associated with prostate cancer detection. The underlying goal is the application of a novel technological approach aided by MRM toward biomarker discovery. An additional goal will be the dissemination of knowledge gained from these studies EDRN wide.

XMRV Discovery and Prostate Cancer-Related Research

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David E. Kang

2011-01-01

Full Text Available Xenotropic murine leukemia virus-related virus (XMRV was first reported in 2006 in a study of human prostate cancer patients with genetic variants of the antiviral enzyme, RNase L. Subsequent investigations in North America, Europe, Asia, and Africa have either observed or failed to detect XMRV in patients (prostate cancer, chronic fatigue syndrome-myalgic encephalomyelitis (CFS-ME, and immunosuppressed with respiratory tract infections or normal, healthy, control individuals. The principal confounding factors are the near ubiquitous presence of mouse-derived reagents, antibodies and cells, and often XMRV itself, in laboratories. XMRV infects and replicates well in many human cell lines, but especially in certain prostate cancer cell lines. XMRV also traffics to prostate in a nonhuman primate model of infection. Here, we will review the discovery of XMRV and then focus on prostate cancer-related research involving this intriguing virus.

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

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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.

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

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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.

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

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

2013-01-01

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

MicroRNAs in prostate cancer: Functional role as biomarkers.

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Kanwal, Rajnee; Plaga, Alexis R; Liu, Xiaoqi; Shukla, Girish C; Gupta, Sanjay

2017-10-28

MicroRNAs (miRNAs) are small endogenous non-coding molecules that alters gene expression through post-transcriptional regulation of messenger RNA. Compelling evidence suggest the role of miRNA in cancer biology having potential as diagnostic, prognostic and predictive biomarkers. This review summarizes the current knowledge on miRNA deregulated in prostate cancer and their role as oncogene, tumor suppressor and metastasis regulators. The emerging information elucidating the biological function of miRNA is promising and may lead to their potential usefulness as diagnostic/prognostic markers and development as effective therapeutic tools for management of prostate cancer. Copyright © 2017 Elsevier B.V. All rights reserved.

Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

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Zhu, Qiu-Li; Xu, Wang-Hong; Tao, Meng-Hua

2010-01-01

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

Biomarkers of the Metabolic Syndrome and Breast Cancer Prognosis

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Zhu, Qiu-Li; Xu, Wang-Hong [Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032 (China); Tao, Meng-Hua [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.

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.

Have biomarkers made their mark? A brief review of dental biomarkers

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Mohammed Kaleem Sultan

2014-01-01

Full Text Available Biomarkers are substances that are released into the human body by tumor cells or by other cells in response to tumor. A high level of a tumor marker is considered a sign of certain cancer, which makes biomarker the subject of many testing methods for the diagnosis of cancers. In recent times, these biomarkers have been successfully isolated to diagnose dental-related tumors, benign and malignant conditions. This article is a brief review of literature for various biomarkers used in the field of dentistry.

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

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

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

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

2017-12-01

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

Three-dimensionally Functionalized Reverse Phase Glycoprotein Array for Cancer Biomarker Discovery and Validation

OpenAIRE

Pan, Li; Aguilar, Hillary Andaluz; Wang, Linna; Iliuk, Anton; Tao, W. Andy

2016-01-01

Glycoproteins have vast structural diversity which plays an important role in many biological processes and have great potential as disease biomarkers. Here we report a novel functionalized reverse phase protein array (RPPA), termed polymer-based reverse phase GlycoProtein Array (polyGPA), to specifically capture and profile glycoproteomes, and validate glycoproteins. Nitrocellulose membrane functionalized with globular hydroxyaminodendrimers was used to covalently capture pre-oxidized glycan...

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...

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

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Borrebaeck, Carl A K

2017-03-01

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

Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics.

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Kucera, Radek; Smid, David; Topolcan, Ondrej; Karlikova, Marie; Fiala, Ondrej; Slouka, David; Skalicky, Tomas; Treska, Vladislav; Kulda, Vlastimil; Simanek, Vaclav; Safanda, Martin; Pesta, Martin

2016-04-01

The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Immunohistochemistry of colorectal cancer biomarker phosphorylation requires controlled tissue fixation.

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Abbey P Theiss

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

The utility of biomarkers in hepatocellular carcinoma: review of urine-based 1H-NMR studies – what the clinician needs to know

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Cartlidge CR

2017-11-01

Full Text Available Caroline R Cartlidge,1 M R Abellona U,2 Alzhraa M A Alkhatib,2 Simon D Taylor-Robinson1 1Department of Surgery and Cancer, Liver Unit, Division of Digestive Health, 2Department of Surgery and Cancer, Division of Computational and Systems Medicine, Faculty of Medicine, Imperial College London, London, UK Abstract: Hepatocellular carcinoma (HCC is the fifth most common malignancy, the third most common cause of cancer death, and the most common primary liver cancer. Overall, there is a need for more reliable biomarkers for HCC, as those currently available lack sensitivity and specificity. For example, the current gold-standard biomarker, serum alpha-fetoprotein, has a sensitivity of roughly only 70%. Cancer cells have different characteristic metabolic signatures in biofluids, compared to healthy cells; therefore, metabolite analysis in blood or urine should lead to the detection of suitable candidates for the detection of HCC. With the advent of metabonomics, this has increased the potential for new biomarker discovery. In this article, we look at approaches used to identify biomarkers of HCC using proton nuclear magnetic resonance (1H-NMR spectroscopy of urine samples. The various multivariate statistical analysis techniques used are explained, and the process of biomarker identification is discussed, with a view to simplifying the knowledge base for the average clinician. Keywords: hepatocellular carcinoma, biomarkers, metabonomics, urine, proton nuclear magnetic resonance spectroscopy, 1H-NMR 

Association of SNCA with Parkinson: replication in the Harvard NeuroDiscovery Center Biomarker Study

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Ding, Hongliu; Sarokhan, Alison K.; Roderick, Sarah S.; Bakshi, Rachit; Maher, Nancy E.; Ashourian, Paymon; Kan, Caroline G.; Chang, Sunny; Santarlasci, Andrea; Swords, Kyleen E.; Ravina, Bernard M.; Hayes, Michael T.; Sohur, U. Shivraj; Wills, Anne-Marie; Flaherty, Alice W.; Unni, Vivek K.; Hung, Albert Y.; Selkoe, Dennis J.; Schwarzschild, Michael A.; Schlossmacher, Michael G.; Sudarsky, Lewis R.; Growdon, John H.; Ivinson, Adrian J.; Hyman, Bradley T.; Scherzer, Clemens R.

2011-01-01

Background Mutations in the α-synuclein gene (SNCA) cause autosomal dominant forms of Parkinson’s disease, but the substantial risk conferred by this locus to the common sporadic disease has only recently emerged from genome-wide association studies. Methods Here we genotyped a prioritized non-coding variant in SNCA intron-4 in 344 patients with Parkinson’s and 275 controls from the longitudinal Harvard NeuroDiscovery Center Biomarker Study. Results The common minor allele of rs2736990 was associated with elevated disease susceptibility (odds ratio = 1.40, P value = 0.0032). Conclusions This result increases confidence in the notion that in many clinically well-characterized patients genetic variation in SNCA contributes to “sporadic” disease. PMID:21953863

MicroRNA-196a is a putative diagnostic biomarker and therapeutic target for laryngeal cancer.

Directory of Open Access Journals (Sweden)

Koichiro Saito

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

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

Science.gov (United States)

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

2015-08-01

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

Leveraging biospecimen resources for discovery or validation of markers for early cancer detection.

Science.gov (United States)

Schully, Sheri D; Carrick, Danielle M; Mechanic, Leah E; Srivastava, Sudhir; Anderson, Garnet L; Baron, John A; Berg, Christine D; Cullen, Jennifer; Diamandis, Eleftherios P; Doria-Rose, V Paul; Goddard, Katrina A B; Hankinson, Susan E; Kushi, Lawrence H; Larson, Eric B; McShane, Lisa M; Schilsky, Richard L; Shak, Steven; Skates, Steven J; Urban, Nicole; Kramer, Barnett S; Khoury, Muin J; Ransohoff, David F

2015-04-01

Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts. © Published by Oxford University Press 2015.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

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Khamis, Mona M; Adamko, Darryl J; El-Aneed, Anas

2017-03-01

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing

Biomarker-driven trial in metastatic pancreas cancer: feasibility in a multicenter study of saracatinib, an oral Src inhibitor, in previously treated pancreatic cancer

International Nuclear Information System (INIS)

Arcaroli, John; Quackenbush, Kevin; Dasari, Arvind; Powell, Rebecca; McManus, Martine; Tan, Aik-Choon; Foster, Nathan R; Picus, Joel; Wright, John; Nallapareddy, Sujatha; Erlichman, Charles; Hidalgo, Manuel; Messersmith, Wells A

2012-01-01

Src tyrosine kinases are overexpressed in pancreatic cancers, and the oral Src inhibitor saracatinib has shown antitumor activity in preclinical models of pancreas cancer. We performed a CTEP-sponsored Phase II clinical trial of saracatinib in previously treated pancreas cancer patients, with a primary endpoint of 6-month survival. A Simon MinMax two-stage phase II design was used. Saracatinib (175 mg/day) was administered orally continuously in 28-day cycles. In the unselected portion of the study, 18 patients were evaluable. Only two (11%) patients survived for at least 6 months, and three 6-month survivors were required to move to second stage of study as originally designed. The study was amended as a biomarker-driven trial (leucine rich repeat containing protein 19 [LRRC19] > insulin-like growth factor-binding protein 2 [IGFBP2] “top scoring pairs” polymerase chain reaction [PCR] assay, and PIK3CA mutant) based on preclinical data in a human pancreas tumor explant model. In the biomarker study, archival tumor tissue or fresh tumor biopsies were tested. Biomarker-positive patients were eligible for the study. Only one patient was PIK3CA mutant in a 3′ untranslated region (UTR) portion of the gene. This patient was enrolled in the study and failed to meet the 6-month survival endpoint. As the frequency of biomarker-positive patients was very low (<3%), the study was closed. Although we were unable to conclude whether enriching for a subset of second/third line pancreatic cancer patients treated with a Src inhibitor based on a biomarker would improve 6-month survival, we demonstrate that testing pancreatic tumor samples for a biomarker-driven, multicenter study in metastatic pancreas cancer is feasible

Novel Biomarker Discovery for Diagnostic and Therapeutic Strategies in Prostate Cancer

Science.gov (United States)

2015-06-01

Task 2: Prepare fluorinated RNA aptamer library for screening indolent and aggressive LNCaP cells. The pool of RNA aptamers is amplified from the...transcribed Fluorination of the nucleic acid backbone stabilizes the RNA aptamers against RNAse degradation. Status: completed. Task 3: Perform first...to metastasis-prone prostate cancer cell surface targets, and exert cell- specific toxicity . We propose that these aptamers may help to discriminate between progressive and indolent prostate cancer in clinical applications.

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.

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

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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.

Proteomic analysis of bronchoalveolar lavage fluid (BALF) from lung cancer patients using label-free mass spectrometry.

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Hmmier, Abduladim; O'Brien, Michael Emmet; Lynch, Vincent; Clynes, Martin; Morgan, Ross; Dowling, Paul

2017-06-01

Lung cancer is the leading cause of cancer-related mortality in both men and women throughout the world. The need to detect lung cancer at an early, potentially curable stage, is essential and may reduce mortality by 20%. The aim of this study was to identify distinct proteomic profiles in bronchoalveolar fluid (BALF) and plasma that are able to discriminate individuals with benign disease from those with non-small cell lung cancer (NSCLC). Using label-free mass spectrometry analysis of BALF during discovery-phase analysis, a significant number of proteins were found to have different abundance levels when comparing control to adenocarcinoma (AD) or squamous cell lung carcinoma (SqCC). Validation of candidate biomarkers identified in BALF was performed in a larger cohort of plasma samples by detection with enzyme-linked immunoassay. Four proteins (Cystatin-C, TIMP-1, Lipocalin-2 and HSP70/HSPA1A) were selected as a representative group from discovery phase mass spectrometry BALF analysis. Plasma levels of TIMP-1, Lipocalin-2 and Cystatin-C were found to be significantly elevated in AD and SqCC compared to control. The results presented in this study indicate that BALF is an important proximal biofluid for the discovery and identification of candidate lung cancer biomarkers. There is good correlation between the trend of protein abundance levels in BALF and that of plasma which validates this approach to develop a blood biomarker to aid lung cancer diagnosis, particularly in the era of lung cancer screening. The protein signatures identified also provide insight into the molecular mechanisms associated with lung malignancy.

Platelet RNA as a circulating biomarker trove for cancer diagnostics.

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Best, M G; Vancura, A; Wurdinger, T

2017-07-01

Platelets are multifunctional cell fragments, circulating in blood in high abundance. Platelets assist in thrombus formation, sensing of pathogens entering the blood stream, signaling to immune cells, releasing vascular remodeling factors, and, negatively, enhancing cancer metastasis. Platelets are 'educated' by their environment, including in patients with cancer. Cancer cells appear to initiate intraplatelet signaling, resulting in splicing of platelet pre-mRNAs, and enhance secretion of cytokines. Platelets can induce leukocyte and endothelial cell modeling factors, for example, through adenine nucleotides (ATP), thereby facilitating extravasation of cancer cells. Besides releasing factors, platelets can also sequester RNAs and proteins released by cancer cells. Thus, platelets actively respond to queues from local and systemic conditions, thereby altering their transcriptome and molecular content. Platelets contain a rich repertoire of RNA species, including mRNAs, small non-coding RNAs and circular RNAs; although studies regarding the functionality of the various platelet RNA species require more attention. Recent advances in high-throughput characterization of platelet mRNAs revealed 10 to > 1000 altered mRNAs in platelets in the presence of disease. Hence, platelet RNA appears to be dynamically affected by pathological conditions, thus possibly providing opportunities to use platelet RNA as diagnostic, prognostic, predictive, or monitoring biomarkers. In this review, we cover the literature regarding the platelet RNA families, processing of platelet RNAs, and the potential application of platelet RNA as disease biomarkers. © 2017 International Society on Thrombosis and Haemostasis.

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

National Research Council Canada - National Science Library

Du, Guangwei

2008-01-01

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

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

Implementation of External Quality Assurance Trials for Immunohistochemically Determined Breast Cancer Biomarkers in Germany

OpenAIRE

von Wasielewski, Reinhard; Krusche, Claudia A.; Rüschoff, Joseph; Fisseler-Eckhoff, Anette; Kreipe, Hans

2008-01-01

Besides typing and grading of breast cancer, Pathologists are involved in the determination of biomarkers, such as steroid hormone receptors and HER2, which are of utmost importance in adjuvant therapy. There have been concerns with regard to security and reproducibility of the biomarker assays done on tissue sections applying either immunohistochemistry or in-situ hybridisation. In order to assure the quality of these biomarker assays, a number of measures are required, among them external p...

Rapid label-free profiling of oral cancer biomarker proteins using nano-UPLC-Q-TOF ion mobility mass spectrometry.

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Nassar, Ala F; Williams, Brad J; Yaworksy, Dustin C; Patel, Vyomesh; Rusling, James F

2016-03-01

It has become quite clear that single cancer biomarkers cannot in general provide high sensitivity and specificity for reliable clinical cancer diagnostics. This paper explores the feasibility of rapid detection of multiple biomarker proteins in model oral cancer samples using label-free protein relative quantitation. MS-based label-free quantitative proteomics offer a rapid alternative that bypasses the need for stable isotope containing compounds to chemically bind and label proteins. Total protein content in oral cancer cell culture conditioned media was precipitated, subjected to proteolytic digestion, and then analyzed using a nano-UPLC (where UPLC is ultra-performance liquid chromatography) coupled to a hybrid Q-Tof ion-mobility mass spectrometry (MS). Rapid, simultaneous identification and quantification of multiple possible cancer biomarker proteins was achieved. In a comparative study between cancer and noncancer samples, approximately 952 proteins were identified using a high-throughput 1D ion mobility assisted data independent acquisition (IM-DIA) approach. As we previously demonstrated that interleukin-8 (IL-8) and vascular endothelial growth factor A (VEGF-A) were readily detected in oral cancer cell conditioned media(1), we targeted these biomarker proteins to validate our approach. Target biomarker protein IL-8 was found between 3.5 and 8.8 fmol, while VEGF-A was found at 1.45 fmol in the cancer cell media. Overall, our data suggest that the nano-UPLC-IM-DIA bioassay is a feasible approach to identify and quantify proteins in complex samples without the need for stable isotope labeling. These results have significant implications for rapid tumor diagnostics and prognostics by monitoring proteins such as IL-8 and VEGF-A implicated in cancer development and progression. The analysis in tissue or plasma is not possible at this time, but the subsequent work would be needed for validation. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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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.

RNA Editing and Drug Discovery for Cancer Therapy

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Wei-Hsuan Huang

2013-01-01

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

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

International Nuclear Information System (INIS)

Willumsen, Nicholas; Bager, Cecilie L; Leeming, Diana J; Smith, Victoria; Christiansen, Claus; Karsdal, Morten A; Dornan, David; Bay-Jensen, Anne-Christine

2014-01-01

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

Oncofetal protein IMP3, a new cancer biomarker.

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Gong, Yuna; Woda, Bruce A; Jiang, Zhong

2014-05-01

IMP3 is a member of a family of RNA-binding proteins that consists of IMP1, IMP2 and IMP3. These proteins contain 2 RNA recognition motifs and 4 K-homology domains that allow them to bind RNAs strongly and specifically. IMP3 is an oncofetal protein involved in embryogenesis and its expression is associated with a number of malignant neoplasms. IMP3 is associated with aggressive and advanced cancers and is specifically expressed in malignant tumors but is not found in adjacent benign tissues. Moreover, in vitro studies have shown that IMP3 promotes tumor cell proliferation, adhesion, and invasion. This review focuses on the studies of IMP3 expression in different cancers and emphasizes the potential utility of IMP3 in routine surgical pathology practice. We also discuss IMP3 as a prognostic biomarker for cancer patients' outcomes.

Longitudinal Bank for Serum, Plasma, and DNA for Detection of Biomarkers

Energy Technology Data Exchange (ETDEWEB)

Vogelzang, Nicolas [Nevada Cancer Inst., Las Vegas, NV (United States); Fink, Louis [Nevada Cancer Inst., Las Vegas, NV (United States)

2007-11-12

The discovery of genetic or biochemical markers to discriminate malignant cancers from normal or benign disease states, markers to stage cancer or monitor disease progression and markers that provide an early indication of an individual’s response to chemotherapy have become a major research objectives of the oncology community over the past few years. The goal of the project is to create a patient specimen bank of serum, plasma, urine and tissues from approximately 1500 individuals. The collection of samples from individuals on a longitudinal basis provided proteomic and biochemical data to be correlated with clinical endpoints. This greatly enhanced our ability to identify biomarkers for staging different cancers and to detect patient responsiveness to therapy at an early state in the treatment process.

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

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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.

Utility of Glioblastoma Patient-Derived Orthotopic Xenografts in Drug Discovery and Personalized Therapy

Directory of Open Access Journals (Sweden)

Michele Patrizii

2018-02-01

Full Text Available Despite substantial effort and resources dedicated to drug discovery and development, new anticancer agents often fail in clinical trials. Among many reasons, the lack of reliable predictive preclinical cancer models is a fundamental one. For decades, immortalized cancer cell cultures have been used to lay the groundwork for cancer biology and the quest for therapeutic responses. However, cell lines do not usually recapitulate cancer heterogeneity or reveal therapeutic resistance cues. With the rapidly evolving exploration of cancer “omics,” the scientific community is increasingly investigating whether the employment of short-term patient-derived tumor cell cultures (two- and three-dimensional and/or patient-derived xenograft models might provide a more representative delineation of the cancer core and its therapeutic response. Patient-derived cancer models allow the integration of genomic with drug sensitivity data on a personalized basis and currently represent the ultimate approach for preclinical drug development and biomarker discovery. The proper use of these patient-derived cancer models might soon influence clinical outcomes and allow the implementation of tailored personalized therapy. When assessing drug efficacy for the treatment of glioblastoma multiforme (GBM, currently, the most reliable models are generated through direct injection of patient-derived cells or more frequently the isolation of glioblastoma cells endowed with stem-like features and orthotopically injecting these cells into the cerebrum of immunodeficient mice. Herein, we present the key strengths, weaknesses, and potential applications of cell- and animal-based models of GBM, highlighting our experience with the glioblastoma stem-like patient cell-derived xenograft model and its utility in drug discovery.

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

Prostatic specific antigen. From its early days until becoming a prostate cancer biomarker.

Science.gov (United States)

Dellavedova, T

2016-01-01

Prostate-specific antigen (PSA) has been since the mid 80's the most commonly used biomarker for measuring current and future risk of prostate cancer, for its early detection and to measure response to treatments and detecting recurrence in all stages of the disease. PSA's early development came along with progress in the field of immunology, which allowed detection and study of antigens from different tissues and fluids when injecting them into rabbits to promote immune response. Rubin Flocks in 1960 was the first to investigate and discover prostate-specific antigens in benign and malignant tissue. Some years later, Hara, a Japanese forensic investigator, found 'gamma seminoprotein', that he used to detect human semen in rape cases. However, his work published in Japanese did not reach the Englishspeaking scientific community. In 1970 Ablin discovered both in prostatic fluid and tissue what he called "prostate-specific antigen", but he didn't characterize or describe it. Investigators Li and Beling, and Sensabaugh, approached the current PSA, but they were limited by available technology at that time. Dr T Ming Chu led a research team on prostate cancer in New York, USA and published their results in 1979. He finally received the patent for the discovery of "human purified prostate antigen" in 1984. Due to this work, the Food and Drug Administration (FDA), in USA, approved the use of PSA for monitoring recurrence after treatment. It was later known that PSA was not prostate-specific since it was produced in other tissues and fluids, but it was recognized that it was human species-specific. Works by Papsidero and Stamey showed new indications and utilities for PSA, but it was Catalona who first used it as a marker for prostate cancer in 1991. Thanks to these advances FDA authorized in 1994 the clinical use of PSA for early detection of prostate cancer.

Identification of Gene Biomarkers for Distinguishing Small-Cell Lung Cancer from Non-Small-Cell Lung Cancer Using a Network-Based Approach

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Fei Long

2015-01-01

Full Text Available Lung cancer consists of two main subtypes: small-cell lung cancer (SCLC and non-small-cell lung cancer (NSCLC that are classified according to their physiological phenotypes. In this study, we have developed a network-based approach to identify molecular biomarkers that can distinguish SCLC from NSCLC. By identifying positive and negative coexpression gene pairs in normal lung tissues, SCLC, or NSCLC samples and using functional association information from the STRING network, we first construct a lung cancer-specific gene association network. From the network, we obtain gene modules in which genes are highly functionally associated with each other and are either positively or negatively coexpressed in the three conditions. Then, we identify gene modules that not only are differentially expressed between cancer and normal samples, but also show distinctive expression patterns between SCLC and NSCLC. Finally, we select genes inside those modules with discriminating coexpression patterns between the two lung cancer subtypes and predict them as candidate biomarkers that are of diagnostic use.

Isolation and enrichment of circulating biomarkers for cancer screening, detection, and diagnostics.

Science.gov (United States)

Hyun, Kyung-A; Kim, Junmoo; Gwak, Hogyeong; Jung, Hyo-Il

2016-01-21

Much research has been performed over the past several decades in an attempt to conquer cancer. Tissue biopsy is the conventional method for gathering biological materials to analyze cancer and has contributed greatly to the understanding of cancer. However, this method is limited because it is time-consuming (requires tissue sectioning, staining, and pathological analysis), costly, provides scarce starting materials for multiple tests, and is painful. A liquid biopsy, which analyzes cancer-derived materials from various body fluids using a minimally invasive procedure, is more practical for real-time monitoring of disease progression than tissue biopsy. Biomarkers analyzable through liquid biopsy include circulating tumor cells (CTCs), exosomes, circulating cell-free DNA (cfDNA), miRNA, and proteins. Research on CTCs has been actively conducted because CTCs provide information on the whole cell, unlike the other biomarkers mentioned above. However, owing to the rarity and heterogeneity of CTCs, CTC research faces many critical concerns. Although exosomes and cfDNA have some technical challenges, they are being highlighted as new target materials. That is because they also have genetic information on cancers. Even though the number of exosomes and cfDNA from early stage cancer patients are similar to healthy individuals, they are present in high concentrations after metastasis. In this article, we review several technologies for material analyses of cancer, discuss the critical concerns based on hands-on experience, and describe future directions for cancer screening, detection, and diagnostics.

Comparative proteomic analysis of human malignant ascitic fluids for the development of gastric cancer biomarkers.

Science.gov (United States)

Jin, Jonghwa; Son, Minsoo; Kim, Hyeyoon; Kim, Hyeyeon; Kong, Seong-Ho; Kim, Hark Kyun; Kim, Youngsoo; Han, Dohyun

2018-04-11

Malignant ascites is a sign of peritoneal seeding, which is one of the most frequent forms of incurable distant metastasis. Because the development of malignant ascites is associated with an extremely poor prognosis, determining whether it resulted from peritoneal seeding has critical clinical implications in diagnosis, choice of treatment, and active surveillance. At present, the molecular characterizations of malignant ascites are especially limited in case of gastric cancer. We aimed to identify malignant ascites-specific proteins that may contribute to the development of alternative methods for diagnosis and therapeutic monitoring and also increase our understanding of the pathophysiology of peritoneal seeding. First, comprehensive proteomic strategies were employed to construct an in-depth proteome of ascitic fluids. Label-free quantitative proteomic analysis was subsequently performed to identify candidates that can differentiate between malignant ascitic fluilds of gastric cancer patients from benign ascitic fluids. Finally, two candidate proteins were verified by ELISA in 84 samples with gastric cancer or liver cirrhosis. Comprehensive proteome profiling resulted in the identification of 5347 ascites proteins. Using label-free quantification, we identified 299 proteins that were differentially expressed in ascitic fluids between liver cirrhosis and stage IV gastric cancer patients. In addition, we identified 645 proteins that were significantly expressed in ascitic fluids between liver cirrhosis and gastric cancer patients with peritoneal seeding. Finally, Gastriscin and Periostin that can distinguish malignant ascites from benign ascites were verified by ELISA. This study identified and verified protein markers that can distinguish malignant ascites with or without peritoneal seeding from benign ascites. Consequently, our results could be a significant resource for gastric cancer research and biomarker discovery in the diagnosis of malignant ascites

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.

Creation of a Human Secretome: A Novel Composite Library of Human Secreted Proteins: Validation Using Ovarian Cancer Gene Expression Data and a Virtual Secretome Array.

Science.gov (United States)

Vathipadiekal, Vinod; Wang, Victoria; Wei, Wei; Waldron, Levi; Drapkin, Ronny; Gillette, Michael; Skates, Steven; Birrer, Michael

2015-11-01

To generate a comprehensive "Secretome" of proteins potentially found in the blood and derive a virtual Affymetrix array. To validate the utility of this database for the discovery of novel serum-based biomarkers using ovarian cancer transcriptomic data. The secretome was constructed by aggregating the data from databases of known secreted proteins, transmembrane or membrane proteins, signal peptides, G-protein coupled receptors, or proteins existing in the extracellular region, and the virtual array was generated by mapping them to Affymetrix probeset identifiers. Whole-genome microarray data from ovarian cancer, normal ovarian surface epithelium, and fallopian tube epithelium were used to identify transcripts upregulated in ovarian cancer. We established the secretome from eight public databases and a virtual array consisting of 16,521 Affymetrix U133 Plus 2.0 probesets. Using ovarian cancer transcriptomic data, we identified candidate blood-based biomarkers for ovarian cancer and performed bioinformatic validation by demonstrating rediscovery of known biomarkers including CA125 and HE4. Two novel top biomarkers (FGF18 and GPR172A) were validated in serum samples from an independent patient cohort. We present the secretome, comprising the most comprehensive resource available for protein products that are potentially found in the blood. The associated virtual array can be used to translate gene-expression data into cancer biomarker discovery. A list of blood-based biomarkers for ovarian cancer detection is reported and includes CA125 and HE4. FGF18 and GPR172A were identified and validated by ELISA as being differentially expressed in the serum of ovarian cancer patients compared with controls. ©2015 American Association for Cancer Research.

Implementation of proteomic biomarkers: making it work

Science.gov (United States)

Mischak, Harald; Ioannidis, John PA; Argiles, Angel; Attwood, Teresa K; Bongcam-Rudloff, Erik; Broenstrup, Mark; Charonis, Aristidis; Chrousos, George P; Delles, Christian; Dominiczak, Anna; Dylag, Tomasz; Ehrich, Jochen; Egido, Jesus; Findeisen, Peter; Jankowski, Joachim; Johnson, Robert W; Julien, Bruce A; Lankisch, Tim; Leung, Hing Y; Maahs, David; Magni, Fulvio; Manns, Michael P; Manolis, Efthymios; Mayer, Gert; Navis, Gerjan; Novak, Jan; Ortiz, Alberto; Persson, Frederik; Peter, Karlheinz; Riese, Hans H; Rossing, Peter; Sattar, Naveed; Spasovski, Goce; Thongboonkerd, Visith; Vanholder, Raymond; Schanstra, Joost P; Vlahou, Antonia

2012-01-01

While large numbers of proteomic biomarkers have been described, they are generally not implemented in medical practice. We have investigated the reasons for this shortcoming, focusing on hurdles downstream of biomarker verification, and describe major obstacles and possible solutions to ease valid biomarker implementation. Some of the problems lie in suboptimal biomarker discovery and validation, especially lack of validated platforms with well-described performance characteristics to support biomarker qualification. These issues have been acknowledged and are being addressed, raising the hope that valid biomarkers may start accumulating in the foreseeable future. However, successful biomarker discovery and qualification alone does not suffice for successful implementation. Additional challenges include, among others, limited access to appropriate specimens and insufficient funding, the need to validate new biomarker utility in interventional trials, and large communication gaps between the parties involved in implementation. To address this problem, we propose an implementation roadmap. The implementation effort needs to involve a wide variety of stakeholders (clinicians, statisticians, health economists, and representatives of patient groups, health insurance, pharmaceutical companies, biobanks, and regulatory agencies). Knowledgeable panels with adequate representation of all these stakeholders may facilitate biomarker evaluation and guide implementation for the specific context of use. This approach may avoid unwarranted delays or failure to implement potentially useful biomarkers, and may expedite meaningful contributions of the biomarker community to healthcare. PMID:22519700

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...

Prostate-Specific G-Protein Coupled Receptor, an Emerging Biomarker Regulating Inflammation and Prostate Cancer Invasion.

Science.gov (United States)

Rodriguez, M; Siwko, S; Liu, M

2016-01-01

Prostate cancer is highly prevalent among men in developed countries, but a significant proportion of detected cancers remain indolent, never progressing into aggressive carcinomas. This highlights the need to develop refined biomarkers that can distinguish between indolent and potentially dangerous cases. The prostate-specific G-protein coupled receptor (PSGR, or OR51E2) is an olfactory receptor family member with highly specific expression in human prostate epithelium that is highly overexpressed in PIN and prostate cancer. PSGR has been functionally implicated in prostate cancer cell invasiveness, suggesting a potential role in the transition to metastatic PCa. Recently, transgenic mice overexpressing PSGR in the prostate were reported to develop an acute inflammatory response followed by emergence of low grade PIN, whereas mice with compound PSGR overexpression and loss of PTEN exhibited accelerated formation of invasive prostate adenocarcinoma. This article will review recent PSGR findings with a focus on its role as a potential prostate cancer biomarker and regulator of prostate cancer invasion and inflammation.

Proteomic Analyses Reveal High Expression of Decorin and Endoplasmin (HSP90B1) Are Associated with Breast Cancer Metastasis and Decreased Survival

OpenAIRE

Cawthorn, Thomas R.; Moreno, Juan C.; Dharsee, Moyez; Tran-Thanh, Danh; Ackloo, Suzanne; Zhu, Pei Hong; Sardana, Girish; Chen, Jian; Kupchak, Peter; Jacks, Lindsay M.; Miller, Naomi A.; Youngson, Bruce J.; Iakovlev, Vladimir; Guidos, Cynthia J.; Vallis, Katherine A.

2012-01-01

BACKGROUND: Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample scree...

Urinary volatile compounds as biomarkers for lung cancer: a proof of principle study using odor signatures in mouse models of lung cancer.

Directory of Open Access Journals (Sweden)

Koichi Matsumura

2010-01-01

Full Text Available A potential strategy for diagnosing lung cancer, the leading cause of cancer-related death, is to identify metabolic signatures (biomarkers of the disease. Although data supports the hypothesis that volatile compounds can be detected in the breath of lung cancer patients by the sense of smell or through bioanalytical techniques, analysis of breath samples is cumbersome and technically challenging, thus limiting its applicability. The hypothesis explored here is that variations in small molecular weight volatile organic compounds ("odorants" in urine could be used as biomarkers for lung cancer. To demonstrate the presence and chemical structures of volatile biomarkers, we studied mouse olfactory-guided behavior and metabolomics of volatile constituents of urine. Sensor mice could be trained to discriminate between odors of mice with and without experimental tumors demonstrating that volatile odorants are sufficient to identify tumor-bearing mice. Consistent with this result, chemical analyses of urinary volatiles demonstrated that the amounts of several compounds were dramatically different between tumor and control mice. Using principal component analysis and supervised machine-learning, we accurately discriminated between tumor and control groups, a result that was cross validated with novel test groups. Although there were shared differences between experimental and control animals in the two tumor models, we also found chemical differences between these models, demonstrating tumor-based specificity. The success of these studies provides a novel proof-of-principle demonstration of lung tumor diagnosis through urinary volatile odorants. This work should provide an impetus for similar searches for volatile diagnostic biomarkers in the urine of human lung cancer patients.

Novel ageing-biomarker discovery using data-intensive technologies

OpenAIRE

Griffiths, H.R.; Augustyniak, E.M.; Bennett, S.J.; Debacq-Chainiaux, F.; Dunston, C.R.; Kristensen, P.; Melchjorsen, C.J.; Navarrete, Santos A.; Simm, A.; Toussaint, O.

2015-01-01

Ageing is accompanied by many visible characteristics. Other biological and physiological markers are also well-described e.g. loss of circulating sex hormones and increased inflammatory cytokines. Biomarkers for healthy ageing studies are presently predicated on existing knowledge of ageing traits. The increasing availability of data-intensive methods enables deep-analysis of biological samples for novel biomarkers. We have adopted two discrete approaches in MARK-AGE Work Package 7 for bioma...

TMPRSS2-ERG -specific transcriptional modulation is associated with prostate cancer biomarkers and TGF-β signaling

International Nuclear Information System (INIS)

Brase, Jan C; Sirma, Hüseyin; Sauter, Guido; Simon, Ronald; Schlomm, Thorsten; Beißbarth, Tim; Korf, Ulrike; Kuner, Ruprecht; Sültmann, Holger; Johannes, Marc; Mannsperger, Heiko; Fälth, Maria; Metzger, Jennifer; Kacprzyk, Lukasz A; Andrasiuk, Tatjana; Gade, Stephan; Meister, Michael

2011-01-01

TMPRSS2-ERG gene fusions occur in about 50% of all prostate cancer cases and represent promising markers for molecular subtyping. Although TMPRSS2-ERG fusion seems to be a critical event in prostate cancer, the precise functional role in cancer development and progression is still unclear. We studied large-scale gene expression profiles in 47 prostate tumor tissue samples and in 48 normal prostate tissue samples taken from the non-suspect area of clinical low-risk tumors using Affymetrix GeneChip Exon 1.0 ST microarrays. Comparison of gene expression levels among TMPRSS2-ERG fusion-positive and negative tumors as well as benign samples demonstrated a distinct transcriptional program induced by the gene fusion event. Well-known biomarkers for prostate cancer detection like CRISP3 were found to be associated with the gene fusion status. WNT and TGF-β/BMP signaling pathways were significantly associated with genes upregulated in TMPRSS2-ERG fusion-positive tumors. The TMPRSS2-ERG gene fusion results in the modulation of transcriptional patterns and cellular pathways with potential consequences for prostate cancer progression. Well-known biomarkers for prostate cancer detection were found to be associated with the gene fusion. Our results suggest that the fusion status should be considered in retrospective and future studies to assess biomarkers for prostate cancer detection, progression and targeted therapy

Novel single-chain antibody GD3A10 defines a chondroitin sulfate biomarker for ovarian cancer

NARCIS (Netherlands)

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

2014-01-01

AIMS: Ovarian cancer has the highest case-to-fatality-index of all gynecological cancers. In this study, tumor-related alterations in the extracellular matrix, especially regarding chondroitin sulfate glycosaminoglycans, are proposed as a novel biomarker in ovarian cancer. MATERIALS & METHODS: Phage

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

International Nuclear Information System (INIS)

Yoon, Joon Kee; Lee, Myung Hoon; Joh, Chul Woo; Yoon, Seok Nam; Soh, Eui Young

2003-01-01

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

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.

Mass spectrometry-based proteomic quest for diabetes biomarkers.

Science.gov (United States)

Shao, Shiying; Guo, Tiannan; Aebersold, Ruedi

2015-06-01

Diabetes mellitus (DM) is a metabolic disorder characterized by chronic hyperglycemia, which affects hundreds of millions of individuals worldwide. Early diagnosis and complication prevention of DM are helpful for disease treatment. However, currently available DM diagnostic markers fail to achieve the goals. Identification of new diabetic biomarkers assisted by mass spectrometry (MS)-based proteomics may offer solution for the clinical challenges. Here, we review the current status of biomarker discovery in DM, and describe the pressure cycling technology (PCT)-Sequential Window Acquisition of all Theoretical fragment-ion (SWATH) workflow for sample-processing, biomarker discovery and validation, which may accelerate the current quest for DM biomarkers. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Aberrant expression of PlncRNA-1 and TUG1: potential biomarkers for gastric cancer diagnosis and clinically monitoring cancer progression.

Science.gov (United States)

Baratieh, Zohreh; Khalaj, Zahra; Honardoost, Mohammad Amin; Emadi-Baygi, Modjtaba; Khanahmad, Hossein; Salehi, Mansoor; Nikpour, Parvaneh

2017-12-01

To evaluate PlncRNA-1, TUG1 and FAM83H-AS1 gene expression and their possible role as a biomarker in gastric cancer (GC) progression. Long noncoding RNA expressions and clinicopathological characteristics were assessed in 70 paired GC tissues. Furthermore, corresponding data from 318 GC patients were downloaded from The Cancer Genome Atlas database. Expression of PlncRNA-1 and TUG1 were significantly upregulated in GC tumoral tissues, and significantly correlated with clinicopathological characters. However, FAM83H-AS1 showed no consistently differential expression. The expression of these three long noncoding RNAs was significantly higher in The Cancer Genome Atlas tumoral tissues. In conclusion, PlncRNA-1 and TUG1 genes may play a critical role in GC progression and may serve as potential diagnostic biomarkers in GC patients.

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