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Sample records for biomarker discovery platform

  1. Network-Based Protein Biomarker Discovery Platforms

    PubMed Central

    Kim, Minhyung

    2016-01-01

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

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

    SciTech Connect

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

    2009-10-01

    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.

  3. Solid-state nanopores: A new platform for DNA biomarker discovery

    NASA Astrophysics Data System (ADS)

    Marshall, Michael M.

    Solid-state (SS) nanopores emerged as a molecular detection platform in 2001, offering many advantages over their biological counterparts, α-hemolysin nanopores (α-HL). These advantages include better chemical, electrical, mechanical, and thermal stability, as well as size tunability and device integration. In addition, the size of α-HL restricts its application to translocations of single-stranded polynucleotides (ssDNA and ssRNA). This research project focused on developing a SS-nanopore platform for biomarker detection, based on differentiating ssDNA and double-stranded DNA (dsDNA) at the single-molecule scale. Reported dsDNA translocation measurements result in an average residence time of ~ 30 ns/bp, so the temporal resolution required for detection of small DNA duplexes can exceed available bandwidth limitations. To address this issue, several system parameters were explored in order to slow down translocation speed, thereby increasing temporal resolution and signal-to-noise ratio. These parameters included: applied voltage, pH, pore geometry, DNA binding agents, salt composition and concentration, and temperature. Experimental findings showed that SS-nanopores can be precisely fabricated using a controlled helium ion milling technique, acidic conditions cause DNA depurination that results in slower translocation durations, and single-stranded binding proteins (SSBs) bind preferentially to ssDNA, forming complexes with distinct translocation characteristics that permit large (> 7 kb) ds- and ssDNA to be effectively distinguished. Together, these data show that SS-nanopores can serve as a tool to electronically detect the presence and relative concentration of target DNA molecules with ultrahigh sensitivity, thus demonstrating their potential utility as a biomarker discovery platform in both biomedical and environmental applications.

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

    PubMed Central

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

    2015-01-01

    The diagnostic and prognostic potential of the vast quantity of publicly-available microarray data has driven the development of methods for integrating the data from different microarray platforms. Cross-platform integration, when appropriately implemented, has been shown to improve reproducibility and robustness of gene signature biomarkers. Microarray platform integration can be conceptually divided into approaches that perform early stage integration (cross-platform normalization) versus late stage data integration (meta-analysis). A growing number of statistical methods and associated software for platform integration are available to the user, however an understanding of their comparative performance and potential pitfalls is critical for best implementation. In this review we provide evidence-based, practical guidance to researchers performing cross-platform integration, particularly with an objective to discover biomarkers. PMID:27600230

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

    PubMed Central

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

    2015-01-01

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

  6. Mass spectrometry in biomarker applications: from untargeted discovery to targeted verification, and implications for platform convergence and clinical application

    SciTech Connect

    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 cytokines.

  7. Cancer biomarker discovery and validation

    PubMed Central

    Goossens, Nicolas; Nakagawa, Shigeki; Sun, Xiaochen; Hoshida, Yujin

    2015-01-01

    With the emergence of genomic profiling technologies and selective molecular targeted therapies, biomarkers play an increasingly important role in the clinical management of cancer patients. Single gene/protein or multi-gene “signature”-based assays have been introduced to measure specific molecular pathway deregulations that guide therapeutic decision-making as predictive biomarkers. Genome-based prognostic biomarkers are also available for several cancer types for potential incorporation into clinical prognostic staging systems or practice guidelines. However, there is still a large gap between initial biomarker discovery studies and their clinical translation due to the challenges in the process of cancer biomarker development. In this review we summarize the steps of biomarker development, highlight key issues in successful validation and implementation, and overview representative examples in the oncology field. We also discuss regulatory issues and future perspectives in the era of big data analysis and precision medicine. PMID:26213686

  8. Proteomics Discovery of Disease Biomarkers.

    PubMed

    Ahram, Mamoun; Petricoin, Emanuel F

    2008-01-01

    Recent technological developments in proteomics have shown promising initiatives in identifying novel biomarkers of various diseases. Such technologies are capable of investigating multiple samples and generating large amount of data end-points. Examples of two promising proteomics technologies are mass spectrometry, including an instrument based on surface enhanced laser desorption/ionization, and protein microarrays. Proteomics data must, however, undergo analytical processing using bioinformatics. Due to limitations in proteomics tools including shortcomings in bioinformatics analysis, predictive bioinformatics can be utilized as an alternative strategy prior to performing elaborate, high-throughput proteomics procedures. This review describes mass spectrometry, protein microarrays, and bioinformatics and their roles in biomarker discovery, and highlights the significance of integration between proteomics and bioinformatics.

  9. Metagenomic biomarker discovery and explanation

    PubMed Central

    2011-01-01

    This study describes and validates a new method for metagenomic biomarker discovery by way of class comparison, tests of biological consistency and effect size estimation. This addresses the challenge of finding organisms, genes, or pathways that consistently explain the differences between two or more microbial communities, which is a central problem to the study of metagenomics. We extensively validate our method on several microbiomes and a convenient online interface for the method is provided at http://huttenhower.sph.harvard.edu/lefse/. PMID:21702898

  10. Systems biology and biomarker discovery

    SciTech Connect

    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.

  11. Serum proteomics for biomarker discovery in nonalcoholic fatty liver disease.

    PubMed

    Yilmaz, Yusuf

    2012-08-16

    Proteomic platforms have gained increasing attention in the clinical spectrum of nonalcoholic fatty liver disease (NAFLD). This approach allows for the unbiased discovery of circulating biochemical markers, i.e., it is not limited to known molecules of presumed importance. This manuscript provides an overview of proteomic serum biomarker discovery in NAFLD. Hemoglobin is currently the most widely replicated proteomic circulating biomarker of NAFLD; it was identified as a biomarker of fatty liver in two distinct proteomic studies and subsequently validated using distinct analytical methods by independent research groups in large replication cohorts. Given the increasing availability of numerous serum samples and the refinement of the technological platforms available to scrutinize the blood proteome, large collaborative studies between academia and industry are warmly encouraged to identify novel, unbiased circulating biomarkers of NAFLD.

  12. Biomarker discovery of nasopharyngeal carcinoma by proteomics.

    PubMed

    Xiao, Liang; Xiao, Ta; Wang, Zhi-Ming; Cho, William C S; Xiao, Zhi-Qiang

    2014-04-01

    Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors in southern China and southern Asia, and poses one of the most serious public health problems in these areas. Early diagnosis, predicting metastasis, recurrence, prognosis and therapeutic response of NPC remain a challenge. Discovery of diagnostic and predictive biomarkers is an ideal way to achieve these objectives. Proteomics has great potential in identifying cancer biomarkers. Comparative proteomics has identified a large number of potential biomarkers associated with NPC, although the clinical performance of such biomarkers needs to be further validated. In this article, we review the latest discovery and progress of biomarkers for early diagnosis, predicting metastasis, recurrence, prognosis and therapeutic response of NPC, inform the readers of the current status of proteomics-based NPC biomarker findings and suggest avenues for future work.

  13. Analysis of Glycoproteins for Biomarker Discovery

    PubMed Central

    He, Jintang; Liu, Yashu; Wu, Jing; Lubman, David M.

    2012-01-01

    Summary Glycoproteins play an important role in cell signaling and cell-cell interaction. The alterations of glycoproteins are often relevant to progression of diseases and these changed glycoproteins can be important biomarkers. The lectin-based glycoproteomic technology has extensively been used for high-throughput screening of potential glycoprotein biomarkers. Here we describe a multi-lectin affinity chromatography and label-free quantitative glycoproteomic approach for discovery of glycoprotein biomarkers relevant to differentiation of glioblastoma stem cells. PMID:23625399

  14. Biological Networks for Cancer Candidate Biomarkers Discovery.

    PubMed

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

    2016-01-01

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

  15. Biological Networks for Cancer Candidate Biomarkers Discovery

    PubMed Central

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

    2016-01-01

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

  16. Biological Networks for Cancer Candidate Biomarkers Discovery

    PubMed Central

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

    2016-01-01

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

  17. Computational biomarker pipeline from discovery to clinical implementation: plasma proteomic biomarkers for cardiac transplantation.

    PubMed

    Cohen Freue, Gabriela V; Meredith, Anna; Smith, Derek; Bergman, Axel; Sasaki, Mayu; Lam, Karen K Y; Hollander, Zsuzsanna; Opushneva, Nina; Takhar, Mandeep; Lin, David; Wilson-McManus, Janet; Balshaw, Robert; Keown, Paul A; Borchers, Christoph H; McManus, Bruce; Ng, Raymond T; McMaster, W Robert

    2013-04-01

    Recent technical advances in the field of quantitative proteomics have stimulated a large number of biomarker discovery studies of various diseases, providing avenues for new treatments and diagnostics. However, inherent challenges have limited the successful translation of candidate biomarkers into clinical use, thus highlighting the need for a robust analytical methodology to transition from biomarker discovery to clinical implementation. We have developed an end-to-end computational proteomic pipeline for biomarkers studies. At the discovery stage, the pipeline emphasizes different aspects of experimental design, appropriate statistical methodologies, and quality assessment of results. At the validation stage, the pipeline focuses on the migration of the results to a platform appropriate for external validation, and the development of a classifier score based on corroborated protein biomarkers. At the last stage towards clinical implementation, the main aims are to develop and validate an assay suitable for clinical deployment, and to calibrate the biomarker classifier using the developed assay. The proposed pipeline was applied to a biomarker study in cardiac transplantation aimed at developing a minimally invasive clinical test to monitor acute rejection. Starting with an untargeted screening of the human plasma proteome, five candidate biomarker proteins were identified. Rejection-regulated proteins reflect cellular and humoral immune responses, acute phase inflammatory pathways, and lipid metabolism biological processes. A multiplex multiple reaction monitoring mass-spectrometry (MRM-MS) assay was developed for the five candidate biomarkers and validated by enzyme-linked immune-sorbent (ELISA) and immunonephelometric assays (INA). A classifier score based on corroborated proteins demonstrated that the developed MRM-MS assay provides an appropriate methodology for an external validation, which is still in progress. Plasma proteomic biomarkers of acute cardiac

  18. Computational biology for cardiovascular biomarker discovery.

    PubMed

    Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

    2009-07-01

    Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

  19. Antibody microarrays as tools for biomarker discovery.

    PubMed

    Sanchez-Carbayo, Marta

    2011-01-01

    The cancer biomarkers field is being enriched by molecular profiling obtained by high-throughput approaches. Targeted antibody arrays are strongly contributing to the identification of protein cancer -biomarker candidates and functional proteomic analyses. Due to their versatility, novel technological and experimental design implementations are broadening the applications of antibody arrays. However, the cancer biomarker candidates delivered to date using this technology are still in their early developmental phase, requiring validation with high number of specimens focusing on specific clinical endpoints. Innovative strategies multiplexing protein measurements of protein extracts of cultured cells, tissue and body fluids using antibody arrays combined with appropriate validation approaches are enabling the -discovery of cancer-associated biomarkers. This review describes these strategies and cancer biomarker candidates reported to date that may assist in the diagnosis, surveillance, prognosis, and potentially for predictive and therapeutic purposes for patients affected with solid and hematological neoplasias.

  20. Biomarkers in pharmacology and drug discovery.

    PubMed

    Anderson, D C; Kodukula, Krishna

    2014-01-01

    Biomarkers, quantitatively measurable indicators of biological or pathogenic processes, once validated play a critical role in disease diagnostics, the prediction of disease progression, and/or monitoring of the response to treatment. They may also represent drug targets. A number of different methods can be used for biomarker discovery and validation, including proteomics methods, metabolomics, imaging, and genome wide association studies (GWASs) and can be analysed using receiver operating characteristic (ROC) plots. The relative utility of single biomarkers compared to biomarker panels is discussed, along with paradigms for biomarker development, the latter in the context of three large-scale biomarker consortia, the Critical Path Predictive Safety Testing Consortium (PSTC), the NCI Early Detection Research Network (EDRN) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The importance of systematic optimization of many parameters in biomarker analysis, including validation, reproducibility, study design, statistical analysis and avoidance of bias are critical features used by these consortia. Problems including introduction of bias into study designs, data reporting or data analysis are also reviewed.

  1. Statistical Aspects in Proteomic Biomarker Discovery.

    PubMed

    Jung, Klaus

    2016-01-01

    In the pursuit of a personalized medicine, i.e., the individual treatment of a patient, many medical decision problems are desired to be supported by biomarkers that can help to make a diagnosis, prediction, or prognosis. Proteomic biomarkers are of special interest since they can not only be detected in tissue samples but can also often be easily detected in diverse body fluids. Statistical methods play an important role in the discovery and validation of proteomic biomarkers. They are necessary in the planning of experiments, in the processing of raw signals, and in the final data analysis. This review provides an overview on the most frequent experimental settings including sample size considerations, and focuses on exploratory data analysis and classifier development.

  2. Using Aptamers for Cancer Biomarker Discovery

    PubMed Central

    Chang, Yun Min; Donovan, Michael J.; Tan, Weihong

    2013-01-01

    Aptamers are single-stranded synthetic DNA- or RNA-based oligonucleotides that fold into various shapes to bind to a specific target, which includes proteins, metals, and molecules. Aptamers have high affinity and high specificity that are comparable to that of antibodies. They are obtained using iterative method, called (Systematic Evolution of Ligands by Exponential Enrichment) SELEX and cell-based SELEX (cell-SELEX). Aptamers can be paired with recent advances in nanotechnology, microarray, microfluidics, and other technologies for applications in clinical medicine. One particular area that aptamers can shed a light on is biomarker discovery. Biomarkers are important in diagnosis and treatment of cancer. In this paper, we will describe ways in which aptamers can be used to discover biomarkers for cancer diagnosis and therapeutics. PMID:23401749

  3. Random Glycopeptide Bead Libraries for Seromic Biomarker Discovery

    PubMed Central

    Kračun, Stjepan K.; Cló, Emilano; Clausen, Henrik; Levery, Steven B.; Jensen, Knud J.; Blixt, Ola

    2010-01-01

    Identification of disease specific biomarkers is important to address early diagnosis and management of disease. Aberrant post-translational modifications (PTM) of proteins such as O-glycosylations (O-PTMs) are emerging as triggers of autoantibodies that can serve as sensitive biomarkers. Here we have developed a random glycopeptide bead library screening platform for detection of autoantibodies and other binding proteins. Libraries were build on biocompatible PEGA beads including a safety-catch C-terminal amide linker (SCAL) that allowed mild cleavage conditions (I2/NaBH4 and TFA) for release of glycopeptides and sequence determination by ESI-MSn. As proof-of principle, tumor specific glycopeptide reporter epitopes were built-in into the libraries and were detected by tumor specific monoclonal antibodies and autoantibodies from cancer patients. Sequenced and identified glycopeptides were re-synthesized at preparative scale by automated parallel peptide synthesis and printed on microarrays for validation and broader analysis with larger sets of sera. We further showed that chemical synthesis of the monosaccharide O-glycopeptide library (Tn-glycoform) could be diversified to other tumor glycoforms by on-bead enzymatic glycosylation reactions with recombinant glycosyltransferases. Hence, we have developed a high-throughput flexible platform for rapid biomarker discovery O-glycopeptides and the method has applicability in other types of assays like lectin/antibody/enzyme specificity studies as well as investigation of other PTMs. PMID:20886906

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

    PubMed

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

    2014-05-01

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

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

    PubMed Central

    Clark, David; Mao, Li

    2012-01-01

    Biomarker discovery can identify molecular markers in various cancers that can be used for detection, screening, diagnosis, and monitoring of disease progression. Lectin-affinity is a technique that can be used for the enrichment of glycoproteins from a complex sample, facilitating the discovery of novel cancer biomarkers associated with a disease state. PMID:22710864

  6. Biomarker Gene Signature Discovery Integrating Network Knowledge

    PubMed Central

    Cun, Yupeng; Fröhlich, Holger

    2012-01-01

    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. PMID:24832044

  7. Biomarker Discovery by Novel Sensors Based on Nanoproteomics Approaches

    PubMed Central

    Dasilva, Noelia; Díez, Paula; Matarraz, Sergio; González-González, María; Paradinas, Sara; Orfao, Alberto; Fuentes, Manuel

    2012-01-01

    During the last years, proteomics has facilitated biomarker discovery by coupling high-throughput techniques with novel nanosensors. In the present review, we focus on the study of label-based and label-free detection systems, as well as nanotechnology approaches, indicating their advantages and applications in biomarker discovery. In addition, several disease biomarkers are shown in order to display the clinical importance of the improvement of sensitivity and selectivity by using nanoproteomics approaches as novel sensors. PMID:22438764

  8. Discovery of nutritional biomarkers: future directions based on omics technologies.

    PubMed

    Odriozola, Leticia; Corrales, Fernado J

    2015-07-01

    Understanding the interactions between food and human biology is of utmost importance to facilitate the development of more efficient nutritional interventions that might improve our wellness status and future health outcomes by reducing risk factors for non-transmittable chronic diseases, such as cardiovascular diseases, cancer, obesity and metabolic syndrome. Dissection of the molecular mechanisms that mediate the physiological effects of diets and bioactive compounds is one of the main goals of current nutritional investigation and the food industry as might lead to the discovery of novel biomarkers. It is widely recognized that the availability of robust nutritional biomarkers represents a bottleneck that delays the innovation process of the food industry. In this regard, omics sciences have opened up new avenues of research and opportunities in nutrition. Advances in mass spectrometry, nuclear magnetic resonance, next generation sequencing and microarray technologies allow massive genome, gene expression, proteomic and metabolomic profiling, obtaining a global and in-depth analysis of physiological/pathological scenarios. For this reason, omics platforms are most suitable for the discovery and characterization of novel nutritional markers that will define the nutritional status of both individuals and populations in the near future, and to identify the nutritional bioactive compounds responsible for the health outcomes.

  9. A steroidomic approach for biomarkers discovery in doping control.

    PubMed

    Boccard, Julien; Badoud, Flavia; Grata, Elia; Ouertani, Samia; Hanafi, Mohamed; Mazerolles, Gérard; Lantéri, Pierre; Veuthey, Jean-Luc; Saugy, Martial; Rudaz, Serge

    2011-12-10

    Anti-doping authorities have high expectations of the athlete steroidal passport (ASP) for anabolic-androgenic steroids misuse detection. However, it is still limited to the monitoring of known well-established compounds and might greatly benefit from the discovery of new relevant biomarkers candidates. In this context, steroidomics opens the way to the untargeted simultaneous evaluation of a high number of compounds. Analytical platforms associating the performance of ultra-high pressure liquid chromatography (UHPLC) and the high mass-resolving power of quadrupole time-of-flight (QTOF) mass spectrometers are particularly adapted for such purpose. An untargeted steroidomic approach was proposed to analyse urine samples from a clinical trial for the discovery of relevant biomarkers of testosterone undecanoate oral intake. Automatic peak detection was performed and a filter of reference steroid metabolites mass-to-charge ratio (m/z) values was applied to the raw data to ensure the selection of a subset of steroid-related features. Chemometric tools were applied for the filtering and the analysis of UHPLC-QTOF-MS(E) data. Time kinetics could be assessed with N-way projections to latent structures discriminant analysis (N-PLS-DA) and a detection window was confirmed. Orthogonal projections to latent structures discriminant analysis (O-PLS-DA) classification models were evaluated in a second step to assess the predictive power of both known metabolites and unknown compounds. A shared and unique structure plot (SUS-plot) analysis was performed to select the most promising unknown candidates and receiver operating characteristic (ROC) curves were computed to assess specificity criteria applied in routine doping control. This approach underlined the pertinence to monitor both glucuronide and sulphate steroid conjugates and include them in the athletes passport, while promising biomarkers were also highlighted. PMID:21831550

  10. Capillary separations enabling tissue proteomics-based biomarker discovery.

    PubMed

    Guo, Tong; Lee, Cheng S; Wang, Weijie; DeVoe, Don L; Balgley, Brian M

    2006-09-01

    Development of the capability to enable large-scale proteome studies, analogous to comprehensive gene expression analysis, will clearly have far-reaching impacts on protein biomarker investigations of human diseases such as cancer through interrogation of the archived fresh frozen and formalin-fixed and paraffin-embedded tissue collections. This review therefore focuses on the most recent advances in microdissection techniques and proteome platforms for procuring homogeneous subpopulations of tumor cells or structures and performing comprehensive analysis of protein profiles within tissue specimens, respectively. Developments in capillary separations capable of providing extremely high resolving power and selective analyte enrichment are particularly highlighted for their roles within the broader context of a state-of-the-art integrated tissue proteome effort. The capabilities of CIEF-based multidimensional separations for performing proteome analysis from minute samples create new opportunities in the pursuit of biomarker discovery using enriched and selected cell populations procured from tissue specimens. These proteome technological advances combined with recently developed tissue microdissection techniques provide powerful tools for those seeking to gain a greater understanding at the global level of the cellular machinery associated with human diseases such as cancer.

  11. Biomarker Discovery in Neurodegenerative Diseases: A Proteomic Approach

    PubMed Central

    Shi, Min; Caudle, W. Michael; Zhang, Jing

    2010-01-01

    Biomarkers for neurodegenerative disorders are essential to facilitate disease diagnosis, ideally at early stages, monitor disease progression, and assess response to existing and future treatments. Application of proteomics to the human brain, cerebrospinal fluid and plasma has greatly hastened the unbiased and high-throughput searches for novel biomarkers. There are many steps critical to biomarker discovery, whether for neurodegenerative or other diseases, including sample preparation, protein/peptide separation and identification, as well as independent confirmation and validation. In this review we have summarized current proteomics technologies involved in discovery of biomarkers for neurodegenerative diseases, practical considerations and limitations of several major aspects, as well as the current status of candidate biomarkers revealed by proteomics for Alzheimer and Parkinson diseases. PMID:18938247

  12. Biomarker discovery: success as a function of risk mitigation.

    PubMed

    Weiser, Stefan

    2016-01-01

    Protein biomarker discovery is a fascinating enterprise; however, success in terms of products for in vitro diagnostic use is sparse. New developments in mass spectrometry-based quantitative proteomics as discovery technology have opened up new avenues for this endeavor. In addition to choice of technology, sample properties, study design and validation strategy are potent pillars required for project success. The challenge for successful biomarker discovery can be described by a series of risks that need to be mitigated. This article intends to describe the major risks along with possible solutions. PMID:27426622

  13. An in vivo platform for tumor biomarker assessment.

    PubMed

    Servais, Elliot L; Suzuki, Kei; Colovos, Christos; Rodriguez, Luis; Sima, Camelia; Fleisher, Martin; Rusch, Valerie W; Sadelain, Michel; Adusumilli, Prasad S

    2011-01-01

    Tumor biomarkers provide a quantitative tool for following tumor progression and response to therapy. However, investigations of clinically useful tumor biomarkers are time-consuming, costly, and limited by patient and tumor heterogeneity. In addition, assessment of biomarkers as indicators of therapy response is confounded by the concomitant use of multiple therapeutic interventions. Herein we report our use of a clinically relevant orthotopic animal model of malignant pleural mesothelioma for investigating tumor biomarkers. Utilizing multi-modality imaging with correlative histopathology, we demonstrate the utility and accuracy of the mouse model in investigating tumor biomarkers--serum soluble mesothelin-related peptide (SMRP) and osteopontin (OPN). This model revealed percentage change in SMRP level to be an accurate biomarker of tumor progression and therapeutic response--a finding consistent with recent clinical studies. This in vivo platform demonstrates the advantages of a validated mouse model for the timely and cost-effective acceleration of human biomarker translational research. PMID:22046338

  14. Mass spectrometry-based quantitative analysis and biomarker discovery.

    PubMed

    Suzuki, Naoto

    2011-01-01

      Mass spectrometry-based quantitative analysis and biomarker discovery using metabolomics approach represent one of the major platforms in clinical fields including for the prognosis or diagnosis, assessment of severity and response to therapy in a number of clinical disease states as well as therapeutic drug monitoring (TDM). This review first summarizes our mass spectrometry-based research strategy and some results on relationship between cysteinyl leukotriene (cysLT), thromboxane (TX), 12-hydroxyeicosatetraenoic acid (12-HETE) and other metabolites of arachidonic acid and diseases such as atopic dermatitis, rheumatoid arthritis and diabetes mellitus. For the purpose of evaluating the role of these metabolites of arachidonic acid in disease status, we have developed sensitive determination methods with simple solid-phase extraction and applied in clinical settings. In addition to these endogenous compounds, using mass spectrometry, we have developed actually applicable quantitative methods for TDM. Representative example was a method of TDM for sirolimus, one of the immunosuppressant agents for a recipient of organ transplant, which requires rigorous monitoring of blood level. As we recognized great potential in mass spectrometry during these researches, we have become interested in metabolomics as the non-targeted analysis of metabolites. Now, established strategy for the metabolomics investigation applies to samples from cells, animals and humans to separate groups based on altered patterns of metabolites in biological fluids and to identify metabolites as potential biomarkers discriminating groups. We would be honored if our research using mass spectrometry would contribute to provide useful information in the field of medical pharmacy. PMID:21881303

  15. Biomarkers for Bone Tumors: Discovery from Genomics and Proteomics Studies and Their Challenges

    PubMed Central

    Wan-Ibrahim, Wan I; Singh, Vivek A; Hashim, Onn H; Abdul-Rahman, Puteri S

    2015-01-01

    Diagnosis of bone tumor currently relies on imaging and biopsy, and hence, the need to find less invasive ways for its accurate detection. More recently, numerous promising deoxyribonucleic acid (DNA) and protein biomarkers with significant prognostic, diagnostic and/or predictive abilities for various types of bone tumors have been identified from genomics and proteomics studies. This article reviewed the putative biomarkers for the more common types of bone tumors (that is, osteosarcoma, Ewing sarcoma, chondrosarcoma [malignant] and giant cell tumor [benign]) that were unveiled from the studies. The benefits and drawbacks of these biomarkers, as well as the technology platforms involved in the research, were also discussed. Challenges faced in the biomarker discovery studies and the problems in their translation from the bench to the clinical settings were also addressed. PMID:26581086

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

    PubMed Central

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

    2015-01-01

    Abstract Context: Specific soluble biomarkers could be a precious tool for diagnosis, prognosis and personalized management of osteoarthritic (OA) patients. Objective: To describe the path of soluble biomarker development from discovery to clinical qualification and regulatory adoption toward OA-related biomarker qualification. Methods and results: This review summarizes current guidance on the use of biomarkers in OA in clinical trials and their utility at five stages, including preclinical development and phase 1 to phase 4 trials. It also presents all the available regulatory requirements. Conclusions: The path through the adoption of a specific soluble biomarker for OA is steep but is worth the challenge due to the benefit that it can provide. PMID:26954785

  17. Ovarian Cancer Biomarker Discovery Based on Genomic Approaches

    PubMed Central

    Lee, Jung-Yun; Kim, Hee Seung; Suh, Dong Hoon; Kim, Mi-Kyung; Chung, Hyun Hoon; Song, Yong-Sang

    2013-01-01

    Ovarian cancer presents at an advanced stage in more than 75% of patients. Early detection has great promise to improve clinical outcomes. Although the advancing proteomic technologies led to the discovery of numerous ovarian cancer biomarkers, no screening method has been recommended for early detection of ovarian cancer. Complexity and heterogeneity of ovarian carcinogenesis is a major obstacle to discover biomarkers. As cancer arises due to accumulation of genetic change, understanding the close connection between genetic changes and ovarian carcinogenesis would provide the opportunity to find novel gene-level ovarian cancer biomarkers. In this review, we summarize the various gene-based biomarkers by genomic technologies, including inherited gene mutations, epigenetic changes, and differential gene expression. In addition, we suggest the strategy to discover novel gene-based biomarkers with recently introduced next generation sequencing. PMID:25337559

  18. Proteomics of gliomas: initial biomarker discovery and evolution of technology.

    PubMed

    Kalinina, Juliya; Peng, Junmin; Ritchie, James C; Van Meir, Erwin G

    2011-09-01

    Gliomas are a group of aggressive brain tumors that diffusely infiltrate adjacent brain tissues, rendering them largely incurable, even with multiple treatment modalities and agents. Mostly asymptomatic at early stages, they present in several subtypes with astrocytic or oligodendrocytic features and invariably progress to malignant forms. Gliomas are difficult to classify precisely because of interobserver variability during histopathologic grading. Identifying biological signatures of each glioma subtype through protein biomarker profiling of tumor or tumor-proximal fluids is therefore of high priority. Such profiling not only may provide clues regarding tumor classification but may identify clinical biomarkers and pathologic targets for the development of personalized treatments. In the past decade, differential proteomic profiling techniques have utilized tumor, cerebrospinal fluid, and plasma from glioma patients to identify the first candidate diagnostic, prognostic, predictive, and therapeutic response markers, highlighting the potential for glioma biomarker discovery. The number of markers identified, however, has been limited, their reproducibility between studies is unclear, and none have been validated for clinical use. Recent technological advancements in methodologies for high-throughput profiling, which provide easy access, rapid screening, low sample consumption, and accurate protein identification, are anticipated to accelerate brain tumor biomarker discovery. Reliable tools for biomarker verification forecast translation of the biomarkers into clinical diagnostics in the foreseeable future. Herein we update the reader on the recent trends and directions in glioma proteomics, including key findings and established and emerging technologies for analysis, together with challenges we are still facing in identifying and verifying potential glioma biomarkers.

  19. Proteomic Approaches in Biomarker Discovery: New Perspectives in Cancer Diagnostics

    PubMed Central

    Kocevar, Nina; Komel, Radovan

    2014-01-01

    Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies. PMID:24550697

  20. Proteomic discovery of diabetic nephropathy biomarkers.

    PubMed

    Merchant, Michael L; Klein, Jon B

    2010-11-01

    Diabetes mellitus (DM) is a complex systemic disease with complications that result from both genetic predisposition and dysregulated metabolic pathways. It is highly prevalent, with current estimates stating that there are 17.5 million diagnosed and 6.6 million undiagnosed patients with diabetes in the United States. DM and its complications impose a significant societal and economic burden. The medical costs of common microvascular complications of uncontrolled DM, diabetic nephropathy (DN) and diabetic retinopathy account for 29% and 15%, respectively, of the $116 billion worth expenditures associated with diabetes. A substantial gap exists in our knowledge related to the understanding of these complications. To advance therapy and decrease the societal burden of DM, there is a clear need for biomarkers that can diagnose DN at an early stage and predict its course. Proteomics has evolved into a high-throughput, analytical discipline used to analyze complex biological data sets. These open-ended, hypothesis-generating approaches, when appropriately designed and interpreted, are well suited to the study of the pathogenic mechanisms of diabetic microvascular disease and the identification of biomarkers of DN. In this study, we review the evolving role played by proteomics in expanding our understanding of the diagnosis and pathogenesis of DN. PMID:21044770

  1. System-wide peripheral biomarker discovery using information theory.

    PubMed

    Alterovitz, Gil; Xiang, Michael; Liu, Jonathan; Chang, Amelia; Ramoni, Marco F

    2008-01-01

    The identification of reliable peripheral biomarkers for clinical diagnosis, patient prognosis, and biological functional studies would allow for access to biological information currently available only through invasive methods. Traditional approaches have so far considered aspects of tissues and biofluid markers independently. Here we introduce an information theoretic framework for biomarker discovery, integrating biofluid and tissue information. This allows us to identify tissue information in peripheral biofluids. We treat tissue-biofluid interactions as an information channel through functional space using 26 proteomes from 45 different sources to determine quantitatively the correspondence of each biofluid for specific tissues via relative entropy calculation of proteomes mapped onto phenotype, function, and drug space. Next, we identify candidate biofluids and biomarkers responsible for functional information transfer (p < 0.01). A total of 851 unique candidate biomarkers proxies were identified. The biomarkers were found to be significant functional tissue proxies compared to random proteins (p < 0.001). This proxy link is found to be further enhanced by filtering the biofluid proteins to include only significant tissue-biofluid information channels and is further validated by gene expression. Furthermore, many of the candidate biomarkers are novel and have yet to be explored. In addition to characterizing proteins and their interactions with a systemic perspective, our work can be used as a roadmap to guide biomedical investigation, from suggesting biofluids for study to constraining the search for biomarkers. This work has applications in disease screening, diagnosis, and protein function studies. PMID:18229689

  2. Extracellular vesicle microRNAs: biomarker discovery in various diseases based on RT-qPCR.

    PubMed

    Liu, Ying; Lu, Qianjin

    2015-01-01

    In recent years, biomarker discovery based on extracellular microRNAs (miRNAs), especially exosome miRNAs, has drawn wide attention. While exosome isolation and identification technologies are increasingly sophisticated, the preanalytical process of exosome miRNAs seems to be no longer a crucial problem. Though next-generation sequencing, microarray and digital PCR have been recommended as good downstream analytical platforms for exosome miRNA quantification, they are still more constrained in clinical utility compared with RT-qPCR method at present. In this review, we will trace back to the origin and summarize current studies of biomarker discovery based on extracellular vesicle miRNAs, and provide an overview and latest developments of RT-qPCR-based data normalization, in order to further assist the development of translational medicine. PMID:26287938

  3. Application of “omics” to Prion Biomarker Discovery

    PubMed Central

    Huzarewich, Rhiannon L. C. H.; Siemens, Christine G.; Booth, Stephanie A.

    2010-01-01

    The advent of genomics and proteomics has been a catalyst for the discovery of biomarkers able to discriminate biological processes such as the pathogenesis of complex diseases. Prompt detection of prion diseases is particularly desirable given their transmissibility, which is responsible for a number of human health risks stemming from exogenous sources of prion protein. Diagnosis relies on the ability to detect the biomarker PrPSc, a pathological isoform of the host protein PrPC, which is an essential component of the infectious prion. Immunochemical detection of PrPSc is specific and sensitive enough for antemortem testing of brain tissue, however, this is not the case in accessible biological fluids or for the detection of recently identified novel prions with unique biochemical properties. A complementary approach to the detection of PrPSc itself is to identify alternative, “surrogate” gene or protein biomarkers indicative of disease. Biomarkers are also useful to track the progress of disease, especially important in the assessment of therapies, or to identify individuals “at risk”. In this review we provide perspective on current progress and pitfalls in the use of “omics” technologies to screen body fluids and tissues for biomarker discovery in prion diseases. PMID:20224650

  4. Cancer Biomarker Discovery: The Entropic Hallmark

    PubMed Central

    Berretta, Regina; Moscato, Pablo

    2010-01-01

    Background 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. Methodology/Principal Findings 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. Conclusions/Significance 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-througput 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

  5. Multiplatform Biomarker Discovery for Bladder Cancer Recurrence Diagnosis

    PubMed Central

    De Paoli, Marine; Gogalic, Selma; Sauer, Ursula; Preininger, Claudia; Pandha, Hardev; Simpson, Guy; Horvath, Andras

    2016-01-01

    Purpose. Nonmuscle invasive bladder cancer (BCa) has a high recurrence rate requiring lifelong surveillance. Urinary biomarkers are promising as simple alternatives to cystoscopy for the diagnosis of recurrent bladder cancer. However, no single marker can achieve the required accuracy. The purpose of this study was to select a multiparameter panel, comprising urinary biomarkers and clinical parameters, for BCa recurrence diagnosis. Experimental Design. Candidate biomarkers were measured in urine samples of BCa patients with recurrence and BCa patients without recurrence. A multiplatform strategy was used for marker quantification comprising a multiplexed microarray and an automated platform for ELISA analysis. A multivariate statistical analysis combined the results from both platforms with the collected clinical data. Results. The best performing combination of biomarkers and clinical parameters achieved an AUC value of 0.91, showing better performance than individual parameters. This panel comprises six biomarkers (cadherin-1, IL-8, ErbB2, IL-6, EN2, and VEGF-A) and three clinical parameters (number of past recurrences, number of BCG therapies, and stage at time of diagnosis). Conclusions. The multiparameter panel could be a useful noninvasive tool for BCa surveillance and potentially impact the clinical management of this disease. Validation of results in an independent cohort is warranted. PMID:27660385

  6. Multiplatform Biomarker Discovery for Bladder Cancer Recurrence Diagnosis

    PubMed Central

    De Paoli, Marine; Gogalic, Selma; Sauer, Ursula; Preininger, Claudia; Pandha, Hardev; Simpson, Guy; Horvath, Andras

    2016-01-01

    Purpose. Nonmuscle invasive bladder cancer (BCa) has a high recurrence rate requiring lifelong surveillance. Urinary biomarkers are promising as simple alternatives to cystoscopy for the diagnosis of recurrent bladder cancer. However, no single marker can achieve the required accuracy. The purpose of this study was to select a multiparameter panel, comprising urinary biomarkers and clinical parameters, for BCa recurrence diagnosis. Experimental Design. Candidate biomarkers were measured in urine samples of BCa patients with recurrence and BCa patients without recurrence. A multiplatform strategy was used for marker quantification comprising a multiplexed microarray and an automated platform for ELISA analysis. A multivariate statistical analysis combined the results from both platforms with the collected clinical data. Results. The best performing combination of biomarkers and clinical parameters achieved an AUC value of 0.91, showing better performance than individual parameters. This panel comprises six biomarkers (cadherin-1, IL-8, ErbB2, IL-6, EN2, and VEGF-A) and three clinical parameters (number of past recurrences, number of BCG therapies, and stage at time of diagnosis). Conclusions. The multiparameter panel could be a useful noninvasive tool for BCa surveillance and potentially impact the clinical management of this disease. Validation of results in an independent cohort is warranted.

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

    PubMed Central

    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. PMID:24212823

  8. Analytical considerations for mass spectrometry profiling in serum biomarker discovery.

    PubMed

    Whiteley, Gordon R; Colantonio, Simona; Sacconi, Andrea; Saul, Richard G

    2009-03-01

    The potential of using mass spectrometry profiling as a diagnostic tool has been demonstrated for a wide variety of diseases. Various cancers and cancer-related diseases have been the focus of much of this work because of both the paucity of good diagnostic markers and the knowledge that early diagnosis is the most powerful weapon in treating cancer. The implementation of mass spectrometry as a routine diagnostic tool has proved to be difficult, however, primarily because of the stringent controls that are required for the method to be reproducible. The method is evolving as a powerful guide to the discovery of biomarkers that could, in turn, be used either individually or in an array or panel of tests for early disease detection. Using proteomic patterns to guide biomarker discovery and the possibility of deployment in the clinical laboratory environment on current instrumentation or in a hybrid technology has the possibility of being the early diagnosis tool that is needed. PMID:19389551

  9. Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery

    PubMed Central

    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

    2010-01-01

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

  10. Discovery of novel biomarkers and phenotypes by semantic technologies

    PubMed Central

    2013-01-01

    Background Biomarkers and target-specific phenotypes are important to targeted drug design and individualized medicine, thus constituting an important aspect of modern pharmaceutical research and development. More and more, the discovery of relevant biomarkers is aided by in silico techniques based on applying data mining and computational chemistry on large molecular databases. However, there is an even larger source of valuable information available that can potentially be tapped for such discoveries: repositories constituted by research documents. Results This paper reports on a pilot experiment to discover potential novel biomarkers and phenotypes for diabetes and obesity by self-organized text mining of about 120,000 PubMed abstracts, public clinical trial summaries, and internal Merck research documents. These documents were directly analyzed by the InfoCodex semantic engine, without prior human manipulations such as parsing. Recall and precision against established, but different benchmarks lie in ranges up to 30% and 50% respectively. Retrieval of known entities missed by other traditional approaches could be demonstrated. Finally, the InfoCodex semantic engine was shown to discover new diabetes and obesity biomarkers and phenotypes. Amongst these were many interesting candidates with a high potential, although noticeable noise (uninteresting or obvious terms) was generated. Conclusions The reported approach of employing autonomous self-organising semantic engines to aid biomarker discovery, supplemented by appropriate manual curation processes, shows promise and has potential to impact, conservatively, a faster alternative to vocabulary processes dependent on humans having to read and analyze all the texts. More optimistically, it could impact pharmaceutical research, for example to shorten time-to-market of novel drugs, or speed up early recognition of dead ends and adverse reactions. PMID:23402646

  11. Metabolite differentiation and discovery lab (MeDDL): a new tool for biomarker discovery and mass spectral visualization.

    PubMed

    Grigsby, Claude C; Rizki, Mateen M; Tamburino, Louis A; Pitsch, Rhonda L; Shiyanov, Pavel A; Cool, David R

    2010-06-01

    The goal of this work was to design and implement a prototype software tool for the visualization and analysis of small molecule metabolite GC-MS and LC-MS data for biomarker discovery. The key features of the Metabolite Differentiation and Discovery Lab (MeDDL) software platform include support for the manipulation of large data sets, tools to provide a multifaceted view of the individual experimental results, and a software architecture amenable to modification and addition of new algorithms and software components. The MeDDL tool, through its emphasis on visualization, provides unique opportunities by combining the following: easy use of both GC-MS and LC-MS data; use of both manufacturer specific data files as well as netCDF (network Common Data Form); preprocessing (peak registration and alignment in both time and mass); powerful visualization tools; and built in data analysis functionality. PMID:20443621

  12. Detection of biomarkers using recombinant antibodies coupled to nanostructured platforms.

    PubMed

    Kierny, Michael R; Cunningham, Thomas D; Kay, Brian K

    2012-01-01

    The utility of biomarker detection in tomorrow's personalized health care field will mean early and accurate diagnosis of many types of human physiological conditions and diseases. In the search for biomarkers, recombinant affinity reagents can be generated to candidate proteins or post-translational modifications that differ qualitatively or quantitatively between normal and diseased tissues. The use of display technologies, such as phage-display, allows for manageable selection and optimization of affinity reagents for use in biomarker detection. Here we review the use of recombinant antibody fragments, such as scFvs and Fabs, which can be affinity-selected from phage-display libraries, to bind with both high specificity and affinity to biomarkers of cancer, such as Human Epidermal growth factor Receptor 2 (HER2) and Carcinoembryonic antigen (CEA). We discuss how these recombinant antibodies can be fabricated into nanostructures, such as carbon nanotubes, nanowires, and quantum dots, for the purpose of enhancing detection of biomarkers at low concentrations (pg/mL) within complex mixtures such as serum or tissue extracts. Other sensing technologies, which take advantage of 'Surface Enhanced Raman Scattering' (gold nanoshells), frequency changes in piezoelectric crystals (quartz crystal microbalance), or electrical current generation and sensing during electrochemical reactions (electrochemical detection), can effectively provide multiplexed platforms for detection of cancer and injury biomarkers. Such devices may soon replace the traditional time consuming ELISAs and Western blots, and deliver rapid, point-of-care diagnostics to market.

  13. Detection of biomarkers using recombinant antibodies coupled to nanostructured platforms

    PubMed Central

    Kierny, Michael R.; Cunningham, Thomas D.; Kay, Brian K.

    2012-01-01

    The utility of biomarker detection in tomorrow's personalized health care field will mean early and accurate diagnosis of many types of human physiological conditions and diseases. In the search for biomarkers, recombinant affinity reagents can be generated to candidate proteins or post-translational modifications that differ qualitatively or quantitatively between normal and diseased tissues. The use of display technologies, such as phage-display, allows for manageable selection and optimization of affinity reagents for use in biomarker detection. Here we review the use of recombinant antibody fragments, such as scFvs and Fabs, which can be affinity-selected from phage-display libraries, to bind with both high specificity and affinity to biomarkers of cancer, such as Human Epidermal growth factor Receptor 2 (HER2) and Carcinoembryonic antigen (CEA). We discuss how these recombinant antibodies can be fabricated into nanostructures, such as carbon nanotubes, nanowires, and quantum dots, for the purpose of enhancing detection of biomarkers at low concentrations (pg/mL) within complex mixtures such as serum or tissue extracts. Other sensing technologies, which take advantage of ‘Surface Enhanced Raman Scattering’ (gold nanoshells), frequency changes in piezoelectric crystals (quartz crystal microbalance), or electrical current generation and sensing during electrochemical reactions (electrochemical detection), can effectively provide multiplexed platforms for detection of cancer and injury biomarkers. Such devices may soon replace the traditional time consuming ELISAs and Western blots, and deliver rapid, point-of-care diagnostics to market. PMID:22833780

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

    PubMed

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

    2010-01-01

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

  15. Proteomics for discovery of candidate colorectal cancer biomarkers

    PubMed Central

    Álvarez-Chaver, Paula; Otero-Estévez, Olalla; Páez de la Cadena, María; Rodríguez-Berrocal, Francisco J; Martínez-Zorzano, Vicenta S

    2014-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in Europe and other Western countries, mainly due to the lack of well-validated clinically useful biomarkers with enough sensitivity and specificity to detect this disease at early stages. Although it is well known that the pathogenesis of CRC is a progressive accumulation of mutations in multiple genes, much less is known at the proteome level. Therefore, in the last years many proteomic studies have been conducted to find new candidate protein biomarkers for diagnosis, prognosis and as therapeutic targets for this malignancy, as well as to elucidate the molecular mechanisms of colorectal carcinogenesis. An important advantage of the proteomic approaches is the capacity to look for multiple differentially expressed proteins in a single study. This review provides an overview of the recent reports describing the different proteomic tools used for the discovery of new protein markers for CRC such as two-dimensional electrophoresis methods, quantitative mass spectrometry-based techniques or protein microarrays. Additionally, we will also focus on the diverse biological samples used for CRC biomarker discovery such as tissue, serum and faeces, besides cell lines and murine models, discussing their advantages and disadvantages, and summarize the most frequently identified candidate CRC markers. PMID:24744574

  16. Metabolomics analysis for biomarker discovery: advances and challenges.

    PubMed

    Monteiro, M S; Carvalho, M; Bastos, M L; Guedes de Pinho, P

    2013-01-01

    Over the last decades there has been a change in biomedical research with the search for single genes, transcripts, proteins, or metabolites being substituted by the coverage of the entire genome, transcriptome, proteome, and metabolome with the "omics" approaches. The emergence of metabolomics, defined as the comprehensive analysis of all metabolites in a system, is still recent compared to other "omics" fields, but its particular features and the improvement of both analytical techniques and pattern recognition methods has contributed greatly to its increasingly use. The feasibility of metabolomics for biomarker discovery is supported by the assumption that metabolites are important players in biological systems and that diseases cause disruption of biochemical pathways, which are not new concepts. In fact, metabolomics, meaning the parallel assessment of multiple metabolites, has been shown to have benefits in various clinical areas. Compared to classical diagnostic approaches and conventional clinical biomarkers, metabolomics offers potential advantages in sensitivity and specificity. Despite its potential, metabolomics still retains several intrinsic limitations which have a great impact on its widespread implementation - these limitations in biological and experimental measurements. This review will provide an insight to the characteristics, strengths, limitations, and recent advances in metabolomics, always keeping in mind its potential application in clinical/ health areas as a biomarker discovery tool. PMID:23210853

  17. Analytical Validation Considerations of Multiplex Mass-Spectrometry-Based Proteomic Platforms for Measuring Protein Biomarkers

    PubMed Central

    2015-01-01

    Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein–protein interaction networks and signaling pathways underlying the disease), “staggers” to make a significant impact with only an average ∼1.5 protein biomarkers per year approved by the FDA over the past 15–20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years. PMID:25171765

  18. Analytical validation considerations of multiplex mass-spectrometry-based proteomic platforms for measuring protein biomarkers.

    PubMed

    Boja, Emily S; Fehniger, Thomas E; Baker, Mark S; Marko-Varga, György; Rodriguez, Henry

    2014-12-01

    Protein biomarker discovery and validation in current omics era are vital for healthcare professionals to improve diagnosis, detect cancers at an early stage, identify the likelihood of cancer recurrence, stratify stages with differential survival outcomes, and monitor therapeutic responses. The success of such biomarkers would have a huge impact on how we improve the diagnosis and treatment of patients and alleviate the financial burden of healthcare systems. In the past, the genomics community (mostly through large-scale, deep genomic sequencing technologies) has been steadily improving our understanding of the molecular basis of disease, with a number of biomarker panels already authorized by the U.S. Food and Drug Administration (FDA) for clinical use (e.g., MammaPrint, two recently cleared devices using next-generation sequencing platforms to detect DNA changes in the cystic fibrosis transmembrane conductance regulator (CFTR) gene). Clinical proteomics, on the other hand, albeit its ability to delineate the functional units of a cell, more likely driving the phenotypic differences of a disease (i.e., proteins and protein-protein interaction networks and signaling pathways underlying the disease), "staggers" to make a significant impact with only an average ∼ 1.5 protein biomarkers per year approved by the FDA over the past 15-20 years. This statistic itself raises the concern that major roadblocks have been impeding an efficient transition of protein marker candidates in biomarker development despite major technological advances in proteomics in recent years.

  19. Quantitative proteomic approaches in biomarker discovery of inflammatory bowel disease.

    PubMed

    Han, Na-Young; Kim, Eun Hee; Choi, Joon; Lee, Hookeun; Hahm, Ki-Baik

    2012-10-01

    Proteomics offers considerable opportunities for either enhancing our biological understanding or discovering biomarkers, blood and biopsied specimen-based proteomic approaches, provide reproducible and quantitative tools that can complement clinical assessments and aid clinicians in the diagnosis and treatment of inflammatory bowel disease (IBD). Sometimes a differential diagnosis of Crohn's disease (CD) and ulcerative colitis (UC) and the prediction of treatment response can be deduced by finding meaningful biomarkers, for which the central platform for proteomics is tandem mass spectrometry (MS/MS). A range of workflows are available for protein (or peptide) separation prior to MS/MS as well as bioinformatics analysis to achieve protein identification, for which two-dimensional electrophoresis (2-DE) and subsequent mass spectrometry (MS), liquid chromatography-MS, difference gel electrophoresis following 2-DE, isobaric tags for relative and absolute quantification (iTRAQ), stable isotope labeling by amino acids and label-free quantification are under development. In this article, the current status and perspective of these advanced proteomic technologies are introduced, with examples of recent biomarkers focused on the diagnosis, treatment response, prognosis of IBD, and even colitis-associated carcinogenesis in both animal models and human patients. PMID:22988922

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

    PubMed

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

    2015-11-01

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

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

    PubMed Central

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

    2015-01-01

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

  2. Biomarker assay translation from discovery to clinical studies in cancer drug development: quantification of emerging protein biomarkers.

    PubMed

    Lee, Jean W; Figeys, Daniel; Vasilescu, Julian

    2007-01-01

    Many candidate biomarkers emerging from genomics and proteomics research have the potential to serve as predictive indexes for guiding the development of safer and more efficacious drugs. Research and development of biomarker discovery, selection, and clinical qualification, however, is still a relatively new field for the pharmaceutical industry. Advances in technology provide a plethora of analytical tools to discover and analyze mechanism-and-disease-specific biomarkers for drug development. In the discovery phase, differential proteomic analysis using mass spectrometry enables the identification of candidate biomarkers that are associated with a specific mechanism relevant to disease progression and affected by drug treatment. Reliable bioanalytical methods are then developed and implemented to select promising biomarkers for further studies in animals and humans. Quantitative analytical methods capable of generating reliable data constitute a solid basis for statistical assessment of the predictive utility of biomarkers. Biomarker method validation is diverse and for purposes that are very different from those of drug bioanalysis or diagnostic use. Besides being flexible, it should sufficiently demonstrate the method's ability to meet the study intent and the attendant regulatory requirements. Several papers have been published outlining specific requirements for successful biomarker method development and validation using a "Fit-for-Purpose" approach. Many of the challenges faced during biomarker discovery as well as during technology and process translation are discussed in this chapter, including preanalytical planning, assay development, and preclinical and clinical validation. Specific references to protein biomarkers for cancer drug development are also discussed.

  3. Oblique view of the Orbiter Discovery from an elevated platform ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    Oblique view of the Orbiter Discovery from an elevated platform in the Vehicle Assembly Building at NASA's Kennedy Space Center. Note the Forward Reaction Control System (RCS) Module from the forward section and the Orbiter Maneuvering System (OMS)/RCS pods from the aft section have been removed. Ground support equipment called Strongbacks are attached to the payload bay doors and the Flight Deck windows have been covered by ground support equipment. Also note the scale figure standing by the Orbiter. - Space Transportation System, Orbiter Discovery (OV-103), Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

  4. NOVEL AVENUES OF DRUG DISCOVERY AND BIOMARKERS FOR DIABETES MELLITUS

    PubMed Central

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

    2011-01-01

    Globally, developed nations spend a significant amount of their resources on healthcare initiatives that poorly translate into increased population life expectancy. As an example, the United States devotes sixteen percent of its gross domestic product to healthcare, the highest level in the world, but falls behind other nations that enjoy greater individual life expectancy. These observations point to the need for pioneering avenues of drug discovery to increase lifespan with controlled costs. In particular, innovative drug development for metabolic disorders such as diabetes mellitus (DM) becomes increasingly critical given that the number of diabetic individuals will increase exponentially over the next twenty years. Here we discuss the elucidation and targeting of novel cellular pathways that are intimately tied to oxidative stress in DM for new treatment strategies. Pathways that involve wingless, NAD+ precursors, and cytokines govern complex biological pathways that determine both cell survival and longevity during DM and its complications. Furthermore, the role of these entities as biomarkers for disease can further enhance their utility irrespective of their treatment potential. Greater understanding of the intricacies of these unique cellular mechanisms will shape future drug discovery for DM to provide focused clinical care with limited or absent long-term complications. PMID:20220043

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

    SciTech Connect

    Rodland, Karin D.

    2014-02-04

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

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

    SciTech Connect

    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.

  7. A platform for the discovery of new macrolide antibiotics

    NASA Astrophysics Data System (ADS)

    Seiple, Ian B.; Zhang, Ziyang; Jakubec, Pavol; Langlois-Mercier, Audrey; Wright, Peter M.; Hog, Daniel T.; Yabu, Kazuo; Allu, Senkara Rao; Fukuzaki, Takehiro; Carlsen, Peter N.; Kitamura, Yoshiaki; Zhou, Xiang; Condakes, Matthew L.; Szczypiński, Filip T.; Green, William D.; Myers, Andrew G.

    2016-05-01

    The chemical modification of structurally complex fermentation products, a process known as semisynthesis, has been an important tool in the discovery and manufacture of antibiotics for the treatment of various infectious diseases. However, many of the therapeutics obtained in this way are no longer effective, because bacterial resistance to these compounds has developed. Here we present a practical, fully synthetic route to macrolide antibiotics by the convergent assembly of simple chemical building blocks, enabling the synthesis of diverse structures not accessible by traditional semisynthetic approaches. More than 300 new macrolide antibiotic candidates, as well as the clinical candidate solithromycin, have been synthesized using our convergent approach. Evaluation of these compounds against a panel of pathogenic bacteria revealed that the majority of these structures had antibiotic activity, some efficacious against strains resistant to macrolides in current use. The chemistry we describe here provides a platform for the discovery of new macrolide antibiotics and may also serve as the basis for their manufacture.

  8. A platform for the discovery of new macrolide antibiotics.

    PubMed

    Seiple, Ian B; Zhang, Ziyang; Jakubec, Pavol; Langlois-Mercier, Audrey; Wright, Peter M; Hog, Daniel T; Yabu, Kazuo; Allu, Senkara Rao; Fukuzaki, Takehiro; Carlsen, Peter N; Kitamura, Yoshiaki; Zhou, Xiang; Condakes, Matthew L; Szczypiński, Filip T; Green, William D; Myers, Andrew G

    2016-05-18

    The chemical modification of structurally complex fermentation products, a process known as semisynthesis, has been an important tool in the discovery and manufacture of antibiotics for the treatment of various infectious diseases. However, many of the therapeutics obtained in this way are no longer effective, because bacterial resistance to these compounds has developed. Here we present a practical, fully synthetic route to macrolide antibiotics by the convergent assembly of simple chemical building blocks, enabling the synthesis of diverse structures not accessible by traditional semisynthetic approaches. More than 300 new macrolide antibiotic candidates, as well as the clinical candidate solithromycin, have been synthesized using our convergent approach. Evaluation of these compounds against a panel of pathogenic bacteria revealed that the majority of these structures had antibiotic activity, some efficacious against strains resistant to macrolides in current use. The chemistry we describe here provides a platform for the discovery of new macrolide antibiotics and may also serve as the basis for their manufacture.

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

    PubMed Central

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

    2015-01-01

    Mastering the systematic analysis of tumor tissues on a large scale has long been a technical challenge for proteomics. In 2001, reverse phase protein arrays (RPPA) were added to the repertoire of existing immunoassays, which, for the first time, allowed a profiling of minute amounts of tumor lysates even after microdissection. A characteristic feature of RPPA is its outstanding sample capacity permitting the analysis of thousands of samples in parallel as a routine task. Until today, the RPPA approach has matured to a robust and highly sensitive high-throughput platform, which is ideally suited for biomarker discovery. Concomitant with technical advancements, new bioinformatic tools were developed for data normalization and data analysis as outlined in detail in this review. Furthermore, biomarker signatures obtained by different RPPA screens were compared with another or with that obtained by other proteomic formats, if possible. Options for overcoming the downside of RPPA, which is the need to steadily validate new antibody batches, will be discussed. Finally, a debate on using RPPA to advance personalized medicine will conclude this article. PMID:27600238

  10. Biomarker Discovery in Subclinical Mycobacterial Infections of Cattle

    PubMed Central

    Janagama, Harish K.; Widdel, Andrea; Vulchanova, Lucy; Stabel, Judith R.; Waters, W. Ray; Palmer, Mitchell V.; Sreevatsan, Srinand

    2009-01-01

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

  11. Human platelets as a platform to monitor metabolic biomarkers using stable isotopes and LC–MS

    PubMed Central

    Basu, Sankha S; Deutsch, Eric C; Schmaier, Alec A; Lynch, David R; Blair, Ian A

    2014-01-01

    Background Intracellular metabolites such as CoA thioesters are modulated in a number of clinical settings. Their accurate measurement from surrogate tissues such as platelets may provide additional information to current serum and urinary biomarkers. Methods Freshly isolated platelets from healthy volunteers were treated with rotenone, propionate or isotopically labeled metabolic tracers. Using a recently developed LC–MS-based methodology, absolute changes in short-chain acyl-CoA thioesters were monitored, as well as relative metabolic labeling using isotopomer distribution analysis. Results Consistent with in vitro experiments, isolated platelets treated with rotenone showed decreased intracellular succinyl-CoA and increased β-hydroxybutyryl-CoA, while propionate treatment resulted in increased propionyl-CoA. In addition, isotopomers of the CoAs were readily detected in platelets treated with the [13C]- or [13C15N]-labeled metabolic precursors. Conclusion Here, we show that human platelets can provide a powerful ex vivo challenge platform with potential clinical diagnostic and biomarker discovery applications. PMID:24320127

  12. GWATCH: a web platform for automated gene association discovery analysis

    PubMed Central

    2014-01-01

    Background As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations. Findings Here we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis. Conclusions GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH. PMID:25374661

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

    PubMed

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

    2016-01-01

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

  14. From SOMAmer-Based Biomarker Discovery to Diagnostic and Clinical Applications: A SOMAmer-Based, Streamlined Multiplex Proteomic Assay

    PubMed Central

    Kraemer, Stephan; Vaught, Jonathan D.; Bock, Christopher; Gold, Larry; Katilius, Evaldas; Keeney, Tracy R.; Kim, Nancy; Saccomano, Nicholas A.; Wilcox, Sheri K.; Zichi, Dom; Sanders, Glenn M.

    2011-01-01

    Recently, we reported a SOMAmer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar), rapid, can be highly multiplexed (upwards of 60 analytes), and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community. PMID:22022604

  15. Redox Platforms in Cancer Drug Discovery and Development

    PubMed Central

    Tew, Kenneth D.; Townsend, Danyelle M.

    2010-01-01

    Redox homeostasis is frequently dysregulated in human disease, particularly cancer. Recent and ongoing efforts seek to validate and extend this platform for the discovery/development of anticancer drugs. As the primary source of cellular redox buffer, thiols (in particular glutathione) have been therapeutically targeted in cancer treatment, myeloproliferation, hematopoietic progenitor cell mobilization and immune response. A number of “redox modulating” drugs have been, or are, under development and the pipeline seems viable. Moreover, S-glutathionylation is a protein post-translational modification that influences a number of critical cell pathways and in the medium term, defining the “glutathionome” has the possibility to provide opportunities for target identification for therapeutic intervention perhaps with a relevance that parallels ongoing efforts with the kinome. PMID:21075043

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

    PubMed Central

    Lee, Bernett T.K.; Liew, Lailing; Lim, Jiahao; Tan, Jonathan K.L.; Lee, Tze Chuen; Veladandi, Pardha S.; Lim, Yun Ping; Han, Hao; Rajagopal, Gunaretnam; Anderson, N. Leigh

    2008-01-01

    CLUB (“Candidate List of yoUr Biomarkers”) is a freely available, web-based resource designed to support Cancer biomarker research. It is targeted to provide a comprehensive list of candidate biomarkers for various cancers that have been reported by the research community. CLUB provides tools for comparison of marker candidates from different experimental platforms, with the ability to filter, search, query and explore, molecular interaction networks associated with cancer biomarkers from the published literature and from data uploaded by the community. This complex and ambitious project is implemented in phases. As a first step, we have compiled from the literature an initial set of differentially expressed human candidate cancer biomarkers. Each candidate is annotated with information from publicly available databases such as Gene Ontology, Swiss-Prot database, National Center for Biotechnology Information’s reference sequences, Biomolecular Interaction Network Database and IntAct interaction. The user has the option to maintain private lists of biomarker candidates or share and export these for use by the community. Furthermore, users may customize and combine commonly used sets of selection procedures and apply them as a stored workflow using selected candidate lists. To enable an assessment by the user before taking a candidate biomarker to the experimental validation stage, the platform contains the functionality to identify pathways associated with cancer risk, staging, prognosis, outcome in cancer and other clinically associated phenotypes. The system is available at http://club.bii.a-star.edu.sg. PMID:19578495

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  19. Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

    SciTech Connect

    McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.; Webb-Robertson, Bobbie-Jo M.; Hafen, Ryan P.; Ramey, John A.; Rodland, Karin D.

    2013-01-01

    The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.

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

    PubMed Central

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

    2016-01-01

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

  1. Yeast display of antibody fragments: a discovery and characterization platform

    SciTech Connect

    Feldhaus, Michael; Siegel, Robert W.

    2004-07-01

    This review will focus on some of the novel attributes of the yeast surface display platform for the discovery and characterization of novel affinity reagents, optimization of those reagents, and novel uses of the platform. This is not intended to serve as an exhaustive review on the broader topic of general scFv technologies (see Winter et al., 1994; Smith and Petrenko, 1997; Bradbury et al., 2003) Furthermore, the scFv format of antibodies are easily manipulated through molecular cloning into a number of other formats such IgG, Fab, diabodies and such, for use in down steam applications and the reader is encouraged to read ?IgG?, ?Fab?, or your favorite format whenever scFv is seen in this review. This review is presented in 5 parts; (1) description of yeast display and its components, (2) library types and construction methods, (3) screening approaches for non-immune libraries and benefits, (4) screening approaches for directed evolution, kinetic on and off rates and (5) epitope complementation binning of clones.

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

    PubMed

    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.

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

    SciTech Connect

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

    2016-01-01

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

  4. Secreted proteins as a fundamental source for biomarker discovery

    PubMed Central

    Stastna, Miroslava; Van Eyk, Jennifer E.

    2012-01-01

    The proteins secreted by various cells (the secretomes) are a potential rich source of biomarkers since they reflect various states of the cells at real time and at given conditions. To have accessible, sufficient and reliable protein markers is desirable since they mark various stages of disease development and their presence/absence can be used for diagnosis, prognosis, risk stratification and therapeutic monitoring. As direct analysis of blood/plasma, a common and noninvasive patient screening method, can be difficult for candidate protein biomarker identification, the alternative/complementary approaches are required, one of them is the analysis of secretomes in cell conditioned media in vitro. Since the proteins secreted by cells as a response to various stimuli are most likely secreted into blood/plasma, the identification and preselection of candidate protein biomarkers from cell secretomes with subsequent validation of their presence at higher levels in serum/plasma is a promising approach. In this review, we discuss the proteins secreted by three progenitor cell types (smooth muscle, endothelial and cardiac progenitor cells) and two adult cell types (neonatal rat ventrical myocytes and smooth muscle cells) which can be relevant to cardiovascular research and which have been recently published in the literature. We found, at least for secretome studies included in this review, that secretomes of progenitor and adult cells overlap by 48% but the secretomes are very distinct among progenitor cell themselves as well as between adult cells. In addition, we compared secreted proteins to protein identifications listed in the Human Plasma PeptideAtlas and in two reports with cardiovascular-related proteins and we performed the extensive literature search to find if any of these secreted proteins were identified in a biomarker study. As expected, many proteins have been identified as biomarkers in cancer but 18 proteins (out of 62) have been tested as biomarkers in

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

    PubMed

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

    2014-02-01

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

  6. Cancer Biomarkers Discovery and Validation: State of the Art, Problems and Future Perspectives.

    PubMed

    Mordente, Alvaro; Meucci, Elisabetta; Martorana, Giuseppe Ettore; Silvestrini, Andrea

    2015-01-01

    Cancer is one of the major public health problems worldwide representing the leading cause of morbidity and mortality in industrialized countries. To reduce cancer morbidity and mortality as well as to facilitate the evolution from the traditional "one size fits all" strategy to a new "personalized" cancer therapy (i.e., the right drug to the right patient at the right time, using the right dose and schedule), there is an urgent need of reliable, robust, accurate and validated cancer biomarker tests.Unfortunately, despite the impressive advances in tumor biology research as well as in high-powerful "omics" technologies, the translation of candidate cancer biomarkers from bench to bedside is lengthy and challenging and only a few tumor marker tests have been adopted successfully into routine clinical care of oncologic patients.This chapter provides an updated background on biomarkers research in oncology, including biomarkers clinical uses, and discusses the problems of discovery pipeline, biomarkers failures and future perspectives.

  7. Discovery and validation of blood biomarkers for suicidality

    PubMed Central

    Le-Niculescu, H; Levey, D F; Ayalew, M; Palmer, L; Gavrin, L M; Jain, N; Winiger, E; Bhosrekar, S; Shankar, G; Radel, M; Bellanger, E; Duckworth, H; Olesek, K; Vergo, J; Schweitzer, R; Yard, M; Ballew, A; Shekhar, A; Sandusky, G E; Schork, N J; Kurian, S M; Salomon, D R; Niculescu, A B

    2013-01-01

    Suicides are a leading cause of death in psychiatric patients, and in society at large. Developing more quantitative and objective ways (biomarkers) for predicting and tracking suicidal states would have immediate practical applications and positive societal implications. We undertook such an endeavor. First, building on our previous blood biomarker work in mood disorders and psychosis, we decided to identify blood gene expression biomarkers for suicidality, looking at differential expression of genes in the blood of subjects with a major mood disorder (bipolar disorder), a high-risk population prone to suicidality. We compared no suicidal ideation (SI) states and high SI states using a powerful intrasubject design, as well as an intersubject case–case design, to generate a list of differentially expressed genes. Second, we used a comprehensive Convergent Functional Genomics (CFG) approach to identify and prioritize from the list of differentially expressed gene biomarkers of relevance to suicidality. CFG integrates multiple independent lines of evidence—genetic and functional genomic data—as a Bayesian strategy for identifying and prioritizing findings, reducing the false-positives and false-negatives inherent in each individual approach. Third, we examined whether expression levels of the blood biomarkers identified by us in the live bipolar subject cohort are actually altered in the blood in an age-matched cohort of suicide completers collected from the coroner's office, and report that 13 out of the 41 top CFG scoring biomarkers (32%) show step-wise significant change from no SI to high SI states, and then to the suicide completers group. Six out of them (15%) remained significant after strict Bonferroni correction for multiple comparisons. Fourth, we show that the blood levels of SAT1 (spermidine/spermine N1–acetyltransferase 1), the top biomarker identified by us, at the time of testing for this study, differentiated future as well as past

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

    PubMed Central

    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

  9. Platform for Plasmodium vivax vaccine discovery and development.

    PubMed

    Valencia, Sócrates Herrera; Rodríguez, Diana Carolina; Acero, Diana Lucía; Ocampo, Vanessa; Arévalo-Herrera, Myriam

    2011-08-01

    Plasmodium vivax is the most prevalent malaria parasite on the American continent. It generates a global burden of 80-100 million cases annually and represents a tremendous public health problem, particularly in the American and Asian continents. A malaria vaccine would be considered the most cost-effective measure against this vector-borne disease and it would contribute to a reduction in malaria cases and to eventual eradication. Although significant progress has been achieved in the search for Plasmodium falciparum antigens that could be used in a vaccine, limited progress has been made in the search for P. vivax components that might be eligible for vaccine development. This is primarily due to the lack of in vitro cultures to serve as an antigen source and to inadequate funding. While the most advanced P. falciparum vaccine candidate is currently being tested in Phase III trials in Africa, the most advanced P. vivax candidates have only advanced to Phase I trials. Herein, we describe the overall strategy and progress in P. vivax vaccine research, from antigen discovery to preclinical and clinical development and we discuss the regional potential of Latin America to develop a comprehensive platform for vaccine development.

  10. Platform for Plasmodium vivax vaccine discovery and development

    PubMed Central

    Valencia/, Sócrates Herrera; Rodríguez, Diana Carolina; Acero, Diana Lucía; Ocampo, Vanessa; Arévalo-Herrera, Myriam

    2016-01-01

    Plasmodium vivax is the most prevalent malaria parasite on the American continent. It generates a global burden of 80–100 million cases annually and represents a tremendous public health problem, particularly in the American and Asian continents. A malaria vaccine would be considered the most cost-effective measure against this vector-borne disease and it would contribute to a reduction in malaria cases and to eventual eradication. Although significant progress has been achieved in the search for Plasmodium falciparum antigens that could be used in a vaccine, limited progress has been made in the search for P. vivax components that might be eligible for vaccine development. This is primarily due to the lack of in vitro cultures to serve as an antigen source and to inadequate funding. While the most advanced P. falciparum vaccine candidate is currently being tested in Phase III trials in Africa, the most advanced P. vivax candidates have only advanced to Phase I trials. Herein, we describe the overall strategy and progress in P. vivax vaccine research, from antigen discovery to preclinical and clinical development and we discuss the regional potential of Latin America to develop a comprehensive platform for vaccine development. PMID:21881773

  11. Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury*

    PubMed Central

    Keshishian, Hasmik; Burgess, Michael W.; Gillette, Michael A.; Mertins, Philipp; Clauser, Karl R.; Mani, D. R.; Kuhn, Eric W.; Farrell, Laurie A.; Gerszten, Robert E.; Carr, Steven A.

    2015-01-01

    -plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments. PMID:25724909

  12. Discovery of Biomarkers for Osteosarcoma by Proteomics Approaches

    PubMed Central

    Suehara, Yoshiyuki; Kubota, Daisuke; Kikuta, Kazutaka; Kaneko, Kazuo; Kawai, Akira; Kondo, Tadashi

    2012-01-01

    Osteosarcomas are the most common malignant bone tumors, and the identification of useful tumor biomarkers and target proteins is required to predict the clinical outcome of patients and therapeutic response as well as to develop novel therapeutic strategies. Global protein expression studies, namely, proteomic studies, can offer important clues to understanding the tumor biology that cannot be obtained by other approaches. These studies, such as two-dimensional gel electrophoresis and mass spectrometry, have provided protein expression profiles of osteosarcoma that can be used to develop novel diagnostic and therapeutic biomarkers, as well as to understand biology of tumor progression and malignancy. In this paper, a brief description of the methodology will be provided followed by a few examples of the recent proteomic studies that have generated new information regarding osteosarcomas. PMID:23226966

  13. Mass spectrometry-based membrane proteomics in cancer biomarker discovery.

    PubMed

    Mermelekas, George; Zoidakis, Jerome

    2014-06-01

    Membrane proteins are involved in central processes such as cell signaling, cell-cell interactions and communication, ion and metabolite transport and in general play a crucial role in cell homeostasis. Cancer and cancer metastasis have been correlated to protein expression levels and dysfunction, with membrane proteins playing an important role, and are thus used as drug targets and potential biomarkers for prognostic or diagnostic purposes. Despite the critical biological significance of membrane proteins, proteomic analysis has been a challenging task due to their hydrophobicity. In this review, recent advances in the proteomic analysis of membrane proteins are presented, focusing on membrane fraction enrichment techniques combined with labeled or label-free shotgun proteomics approaches for the identification of potential cancer biomarkers.

  14. Discovery and validation of urinary biomarkers for prostate cancer

    PubMed Central

    Theodorescu, Dan; Schiffer, Eric; Bauer, Hartwig W.; Douwes, Friedrich; Eichhorn, Frank; Polley, Reinhard; Schmidt, Thomas; Schöfer, Wolfgang; Zürbig, Petra; Good, David M.; Coon, Joshua J.

    2009-01-01

    Only 30% of patients with elevated serum prostate specific antigen (PSA) levels who undergo prostate biopsy are diagnosed with prostate cancer (PCa). Novel methods are needed to reduce the number of unnecessary biopsies. We report on the identification and validation of a panel of 12 novel biomarkers for prostate cancer (PCaP), using CE coupled MS. The biomarkers could be defined by comparing first void urine of 51 men with PCa and 35 with negative prostate biopsy. In contrast, midstream urine samples did not allow the identification of discriminatory molecules, suggesting that prostatic fluids may be the source of the defined biomarkers. Consequently, first void urine samples were tested for sufficient amounts of prostatic fluid, using a prostatic fluid indicative panel (“informative” polypeptide panel; IPP). A combination of IPP and PCaP to predict positive prostate biopsy was evaluated in a blinded prospective study. Two hundred thirteen of 264 samples matched the IPP criterion. PCa was detected with 89% sensitivity, 51% specificity. Including age and percent free PSA to the proteomic signatures resulted in 91% sensitivity, 69% specificity. PMID:19759844

  15. Manifold Learning for Biomarker Discovery in MR Imaging

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed

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

    2012-03-01

    Cholangiocarcinoma (CCA)--bile duct cancer--is associated with late presentation, poses challenges for diagnosis, and has high mortality. These features t highlight the desperate need for biomarkers than can be measured early and in accessible body fluids such as plasma of people at risk for developing this lethal cancer. In this manuscript, we address previous limitations in the discovery stage of biomarker(s) for CCA and indicate how new generation of "omics" technologies could be used for biomarker discovery in Thailand. A key factor in the success of this biomarker program for CCA is the combination of cutting edge technology with strategic sample acquisition by a biorepositories. PMID:21855650

  17. Biomarker detection for disease diagnosis using cost-effective microfluidic platforms.

    PubMed

    Sanjay, Sharma T; Fu, Guanglei; Dou, Maowei; Xu, Feng; Liu, Rutao; Qi, Hao; Li, XiuJun

    2015-11-01

    Early and timely detection of disease biomarkers can prevent the spread of infectious diseases, and drastically decrease the death rate of people suffering from different diseases such as cancer and infectious diseases. Because conventional diagnostic methods have limited application in low-resource settings due to the use of bulky and expensive instrumentation, simple and low-cost point-of-care diagnostic devices for timely and early biomarker diagnosis is the need of the hour, especially in rural areas and developing nations. The microfluidics technology possesses remarkable features for simple, low-cost, and rapid disease diagnosis. There have been significant advances in the development of microfluidic platforms for biomarker detection of diseases. This article reviews recent advances in biomarker detection using cost-effective microfluidic devices for disease diagnosis, with the emphasis on infectious disease and cancer diagnosis in low-resource settings. This review first introduces different microfluidic platforms (e.g. polymer and paper-based microfluidics) used for disease diagnosis, with a brief description of their common fabrication techniques. Then, it highlights various detection strategies for disease biomarker detection using microfluidic platforms, including colorimetric, fluorescence, chemiluminescence, electrochemiluminescence (ECL), and electrochemical detection. Finally, it discusses the current limitations of microfluidic devices for disease biomarker detection and future prospects.

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

    PubMed

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

    2013-12-01

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

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

    PubMed

    Burgess, Rob; Huang, Ruo-Pan

    2016-01-01

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

  20. LCM assisted biomarker discovery from archival neoplastic gastrointestinal tissues.

    PubMed

    Meitner, Patricia A; Resnick, Murray B

    2011-01-01

    Expression array analysis of epithelial mRNA to identify biomarkers of premalignant and malignant conditions in the gastrointestinal (GI) tract is an area of intense study. Archived formalin-fixed paraffin-embedded (FFPE) tissues documenting these changes are readily available and should be a valuable resource for retrospective analysis. Laser capture microdissection of defined areas of epithelial cells at different stages of neoplastic progression is described together with methods for prequalification of RNA in FFPE tissue blocks selected for analysis. Paradise reagents specifically designed for isolation and amplification of RNA from FFPE archival tissue specimens are used to prepare probes for the human X3P microarray from Affymetrix.

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

    PubMed Central

    Zou, Wei; She, Jianwen; Tolstikov, Vladimir V.

    2013-01-01

    Current available biomarkers lack sensitivity and/or specificity for early detection of cancer. To address this challenge, a robust and complete workflow for metabolic profiling and data mining is described in details. Three independent and complementary analytical techniques for metabolic profiling are applied: hydrophilic interaction liquid chromatography (HILIC–LC), reversed-phase liquid chromatography (RP–LC), and gas chromatography (GC). All three techniques are coupled to a mass 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. PMID:24958150

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    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.

  4. Proteomics in colorectal cancer translational research: biomarker discovery for clinical applications.

    PubMed

    de Wit, Meike; Fijneman, Remond J A; Verheul, Henk M W; Meijer, Gerrit A; Jimenez, Connie R

    2013-04-01

    Colorectal cancer (CRC) is a major cause of cancer-related death in the western world. Screening to detect the disease in an early stage is the most effective approach to tackle this problem. In addition, better diagnostic tools for assessment of prognosis and prediction of response to drug therapy will allow for personalized therapies and better outcomes. Protein biomarkers that reflect tumor biology have the potential to address a wide range of clinical needs. These include diagnostic (screening) biomarkers for early detection, prognostic biomarkers for estimation of disease outcome, predictive biomarkers for adjuvant treatment stratification, and surveillance biomarkers for disease monitoring and treatment response. An important source for the discovery of potential biomarkers comes from mass spectrometry based proteomics research of the biology of CRC development. Here, we review recent colon cancer proteomics studies directed at identification of biomarker proteins. These include studies that use preclinical models (i.e. cell lines or murine tissues) as well as clinical materials (e.g. tissue and stool samples). We separately highlight some studies that focused on identification of cancer stem cell (CSC) related proteins in tumor spheroids, an in vitro model system for investigating CRC treatment response. Recent proteomics studies have generated many new candidate protein biomarkers. However, the lack of follow-up studies that lead to biomarker verification and/or validation remains a limiting factor in the translation of these candidate biomarkers into clinical applications. This is partly due to technological limitations which are bound to diminish with new technologies, including selected reaction monitoring mass spectrometry (SRM-MS). Antibodies are still required, though, both to perform high-throughput validation as well as to develop cost-effective tests for routine use in a clinical setting.

  5. Diverse therapeutic targets and biomarkers for Alzheimer's disease and related dementias: report on the Alzheimer's Drug Discovery Foundation 2012 International Conference on Alzheimer's Drug Discovery

    PubMed Central

    2013-01-01

    The Alzheimer's Drug Discovery Foundation's 13th International Conference on Alzheimer's Drug Discovery was held on 10-11 September 2012 in Jersey City, NJ, USA. This meeting report provides an overview of Alzheimer's Drug Discovery Foundation-funded programs, ranging from novel biomarkers to accelerate clinical development to drug-discovery programs with a focus on targets related to neuroprotection, mitochondrial function, apolipoprotein E and vascular biology. PMID:23374760

  6. Advances in urinary proteome analysis and biomarker discovery.

    PubMed

    Fliser, Danilo; Novak, Jan; Thongboonkerd, Visith; Argilés, Angel; Jankowski, Vera; Girolami, Mark A; Jankowski, Joachim; Mischak, Harald

    2007-04-01

    Noninvasive diagnosis of kidney diseases and assessment of the prognosis are still challenges in clinical nephrology. Definition of biomarkers on the basis of proteome analysis, especially of the urine, has advanced recently and may provide new tools to solve those challenges. This article highlights the most promising technological approaches toward deciphering the human proteome and applications of the knowledge in clinical nephrology, with emphasis on the urinary proteome. The data in the current literature indicate that although a thorough investigation of the entire urinary proteome is still a distant goal, clinical applications are already available. Progress in the analysis of human proteome in health and disease will depend more on the standardization of data and availability of suitable bioinformatics and software solutions than on new technological advances. It is predicted that proteomics will play an important role in clinical nephrology in the very near future and that this progress will require interactive dialogue and collaboration between clinicians and analytical specialists.

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2012-04-01

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

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

    PubMed Central

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-01-01

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

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

    PubMed

    Aghagolzadeh, Parisa; Radpour, Ramin

    2016-07-01

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

  11. High-content affinity-based proteomics: unlocking protein biomarker discovery.

    PubMed

    Brody, Edward N; Gold, Larry; Lawn, Richard M; Walker, Jeffrey J; Zichi, Dom

    2010-11-01

    Single protein biomarkers measured with antibody-based affinity assays are the basis of molecular diagnostics in clinical practice today. There is great hope in discovering new protein biomarkers and combinations of protein biomarkers for advancing medicine through monitoring health, diagnosing disease, guiding treatment, and developing new therapeutics. The goal of high-content proteomics is to unlock protein biomarker discovery by measuring many (thousands) or all (∼23,000) proteins in the human proteome in an unbiased, data-driven approach. High-content proteomics has proven technically difficult due to the diversity of proteins, the complexity of relevant biological samples, such as blood and tissue, and large concentration ranges (in the order of 10(12) in blood). Mass spectrometry and affinity methods based on antibodies have dominated approaches to high-content proteomics. For technical reasons, neither has achieved adequate simultaneous performance and high-content. Here we review antibody-based protein measurement, multiplexed antibody-based protein measurement, and limitations of antibodies for high-content proteomics due to their inherent cross-reactivity. Finally, we review a new affinity-based proteomic technology developed from the ground up to solve the problem of high content with high sensitivity and specificity. Based on a new generation of slow off-rate modified aptamers (SOMAmers), this technology is unlocking biomarker discovery.

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

    PubMed

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

    2009-06-17

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

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

    PubMed Central

    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

  14. A decade of tissue microarrays: progress in the discovery and validation of cancer biomarkers.

    PubMed

    Camp, Robert L; Neumeister, Veronique; Rimm, David L

    2008-12-01

    This year, 2008, marks the 10-year anniversary of the development of the modern tissue microarray (TMA). During the last decade, the use of TMAs has grown steadily and accounts for a small but increasing percentage of all cancer biomarker studies performed. The growing popularity of TMA-based studies attests to their benefits in the discovery and validation of new biomarkers. This review will focus on these benefits, but also on the faults of TMAs and the challenges of TMA studies that have been overcome in the last decade. We will also discuss the role of TMAs in the latest revolution in cancer treatment, the use of targeted drug therapy.

  15. Separate class true discovery rate degree of association sets for biomarker identification.

    PubMed

    Crager, Michael R; Ahmed, Murat

    2014-01-01

    In 2008, Efron showed that biological features in a high-dimensional study can be divided into classes and a separate false discovery rate (FDR) analysis can be conducted in each class using information from the entire set of features to assess the FDR within each class. We apply this separate class approach to true discovery rate degree of association (TDRDA) set analysis, which is used in clinical-genomic studies to identify sets of biomarkers having strong association with clinical outcome or state while controlling the FDR. Careful choice of classes based on prior information can increase the identification power of the separate class analysis relative to the overall analysis.

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

    PubMed Central

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

    2010-01-01

    Urine has become one of the most attractive biofluids in clinical proteomics, for its procurement is easy and noninvasive and it contains sufficient proteins and peptides. Urinary proteomics has thus rapidly developed and has been extensively applied to biomarker discovery in clinical diseases, especially kidney diseases. In this review, we discuss two important aspects of urinary proteomics in detail, namely, sample preparation and proteomic technologies. In addition, data mining in urinary proteomics is also briefly introduced. At last, we present several successful examples on the application of urinary proteomics for biomarker discovery in kidney diseases, including diabetic nephropathy, IgA nephropathy, lupus nephritis, renal Fanconi syndrome, acute kidney injury, and renal allograft rejection. PMID:20349519

  17. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies.

    PubMed

    Lima, Ana Rita; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula

    2016-08-01

    Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

  18. Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies.

    PubMed

    Lima, Ana Rita; Bastos, Maria de Lourdes; Carvalho, Márcia; Guedes de Pinho, Paula

    2016-08-01

    Prostate cancer (PCa) is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA) levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection. PMID:27567960

  19. Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers

    PubMed Central

    Krumsiek, Jan; Gieger, Christian; Prehn, Cornelia; Roemisch-Margl, Werner; Polonikov, Alexey; Peters, Annette; Theis, Fabian J.; Meitinger, Thomas; Kronenberg, Florian; Weidinger, Stephan; Wichmann, Heinz Erich; Suhre, Karsten; Wang-Sattler, Rui; Adamski, Jerzy; Illig, Thomas

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    Yadav, Amit Kumar; Bhardwaj, Gourav; Basak, Trayambak; Kumar, Dhirendra; Ahmad, Shadab; Priyadarshini, Ruby; Singh, Ashish Kumar; Dash, Debasis; Sengupta, Shantanu

    2011-01-01

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

  2. Hyaluronidase treatment of synovial fluid to improve assay precision for biomarker research using multiplex immunoassay platforms.

    PubMed

    Jayadev, Chethan; Rout, Raj; Price, Andrew; Hulley, Philippa; Mahoney, David

    2012-12-14

    Synovial fluid (SF) is a difficult biological matrix to analyse due to its complex non-Newtonian nature. This can result in poor assay repeatability and potentially inefficient use of precious samples. This study assessed the impact of SF treatment by hyaluronidase and/or dilution on intra-assay precision using the Luminex and Meso Scale Discovery (MSD) multiplex platforms. SF was obtained from patients with knee osteoarthritis at the time of joint replacement surgery. Aliquots derived from the same sample were left untreated (neat), 2-fold diluted, 4-fold diluted or treated with 2mg/ml testicular hyaluronidase (with 2-fold dilution). Preparation methods were compared in a polysterene-bead Luminex 10-plex (N=16), magnetic-bead Luminex singleplex (N=7) and MSD 4-plex (N=7). Each method was assessed for coefficient of variation (CV) of replicate measurements, number of bead events (for Luminex assays) and dilution-adjusted analyte concentration. Percentage recovery was calculated for dilutions and HAse treatment. Hyaluronidase treatment significantly increased the number of wells with satisfactory bead events/region (95%) compared to neat (48%, p<0.001) in the polystyrene-bead Luminex assay, but the magnetic-bead Luminex assay achieved ≥50 bead events irrespective of treatment method. Hyaluronidase treatment resulted in lower intra-assay CVs for detectable ligands (group average CV<10%) than neat, 2-fold and 4-fold dilution (CV~25% for all, p<0.05) in both polystyrene- and magnetic-bead Luminex assays. In addition, measured sample concentrations were higher and recovery was poor (elevated) after hyaluronidase treatment. In the MSD 4-plex, within-group comparison of the intra-assay CV or concentration was not conclusively influenced by SF preparation. However, only hyaluronidase treatment resulted in CV<25% for all samples for TNF-α. There was no effect on analyte concentrations or recovery. Hyaluronidase treatment can improve intra-assay precision and assay signal

  3. Pitfalls and limitations in translation from biomarker discovery to clinical utility in predictive and personalised medicine

    PubMed Central

    2013-01-01

    Since the emergence of the so-called omics technology, thousands of putative biomarkers have been identified and published, which have dramatically increased the opportunities for developing more effective therapeutics. These opportunities can have profound benefits for patients and for the economics of healthcare. However, the transfer of biomarkers from discovery to clinical practice is still a process filled with lots of pitfalls and limitations, mostly limited by structural and scientific factors. To become a clinically approved test, a potential biomarker should be confirmed and validated using hundreds of specimens and should be reproducible, specific and sensitive. Besides the lack of quality in biomarker validation, a number of other key issues can be identified and should be addressed. Therefore, the aim of this article is to discuss a series of interpretative and practical issues that need to be understood and resolved before potential biomarkers become a clinically approved test or are already on the diagnostic market. Some of these issues are shortly discussed here. PMID:23442211

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  5. A fully integrated protein crystallization platform for small-molecule drug discovery.

    PubMed

    Hosfield, David; Palan, John; Hilgers, Mark; Scheibe, Daniel; McRee, Duncan E; Stevens, Raymond C

    2003-04-01

    Structure-based drug discovery in the pharmaceutical industry benefits from cost-efficient methodologies that quickly assess the feasibility of specific, often refractory, protein targets to form well-diffracting crystals. By tightly coupling construct and purification diversity with nanovolume crystallization, the Structural Biology Group at Syrrx has developed such a platform to support its small-molecule drug-discovery program. During the past 18 months of operation at Syrrx, the Structural Biology Group has executed several million crystallization and imaging trials on over 400 unique drug-discovery targets. Here, key components of the platform, as well as an analysis of some experimental results that allowed for platform optimization, will be described.

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

    PubMed

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

    2015-07-01

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

  7. Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery

    PubMed Central

    Lin, Xiangmin; Shi, Min; Gunasingh Masilamoni, Jeyaraj; Dator, Romel; Movius, James; Aro, Patrick; Smith, Yoland; Zhang, Jing

    2015-01-01

    Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology. PMID:25617661

  8. Emergent Transcriptomic Technologies and Their Role in the Discovery of Biomarkers of Liver Transplant Tolerance

    PubMed Central

    Mastoridis, Sotiris; Martínez-Llordella, Marc; Sanchez-Fueyo, Alberto

    2015-01-01

    Liver transplantation offers a unique window into transplant immunology due, in part, to the considerable proportion of recipients who develop immunological tolerance to their allograft. Biomarkers are able to identify and predict such a state of tolerance, and thereby able to establish suitable candidates for the minimization of hazardous immunosuppressive therapies, are not only of great potential clinical benefit but might also shed light on the immunological mechanisms underlying tolerance and rejection. Here, we review the emergent transcriptomic technologies serving as drivers of biomarker discovery, we appraise efforts to identify a molecular signature of liver allograft tolerance, and we consider the implications of this work on the mechanistic understanding of immunological tolerance. PMID:26157438

  9. Bipolar disorder: recent advances and future trends in bioanalytical developments for biomarker discovery.

    PubMed

    de Jesus, Jemmyson Romário; de Campos, Bruna Kauely; Galazzi, Rodrigo Moretto; Martinez, José Luis Capelo; Arruda, Marco Aurélio Zezzi

    2015-01-01

    In this manuscript we briefly describe bipolar disorder (a depressive and manic mental disease), its classification, its effects on the patient, which sometimes include suicidal tendencies, and the drugs used for treatment. We also address the status quo with regard to diagnosis of bipolar disorder and recent advances in bioanalytical approaches for biomarker discovery. These approaches focus on blood samples (serum and plasma) and proteins as the main biomarker targets, and use various strategies for protein depletion. Strategies include use of commercially available kits or other homemade strategies and use of classical proteomics methods for protein identification based on "bottom-up" or "top-down" approaches, which used SELDI, ESI, or MALDI as sources for mass spectrometry, and up-to-date mass analyzers, for example Orbitrap. We also discuss some future objectives for treatment of this disorder and possible directions for the correct diagnosis of this still-unclear mental illness.

  10. The Matchmaker Exchange: a platform for rare disease gene discovery.

    PubMed

    Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L

    2015-10-01

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

  11. The Matchmaker Exchange: a platform for rare disease gene discovery.

    PubMed

    Philippakis, Anthony A; Azzariti, Danielle R; Beltran, Sergi; Brookes, Anthony J; Brownstein, Catherine A; Brudno, Michael; Brunner, Han G; Buske, Orion J; Carey, Knox; Doll, Cassie; Dumitriu, Sergiu; Dyke, Stephanie O M; den Dunnen, Johan T; Firth, Helen V; Gibbs, Richard A; Girdea, Marta; Gonzalez, Michael; Haendel, Melissa A; Hamosh, Ada; Holm, Ingrid A; Huang, Lijia; Hurles, Matthew E; Hutton, Ben; Krier, Joel B; Misyura, Andriy; Mungall, Christopher J; Paschall, Justin; Paten, Benedict; Robinson, Peter N; Schiettecatte, François; Sobreira, Nara L; Swaminathan, Ganesh J; Taschner, Peter E; Terry, Sharon F; Washington, Nicole L; Züchner, Stephan; Boycott, Kym M; Rehm, Heidi L

    2015-10-01

    There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow. PMID:26295439

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

    PubMed Central

    Rossing, Kasper; Bosselmann, Helle Skovmand; Gustafsson, Finn; Zhang, Zhen-Yu; Gu, Yu-Mei; Kuznetsova, Tatiana; Nkuipou-Kenfack, Esther; Mischak, Harald; Staessen, Jan A.

    2016-01-01

    Background Biomarker discovery and new insights into the pathophysiology of heart failure with reduced ejection fraction (HFrEF) may emerge from recent advances in high-throughput urinary proteomics. This could lead to improved diagnosis, risk stratification and management of HFrEF. Methods and Results Urine samples were analyzed by on-line capillary electrophoresis coupled to electrospray ionization micro time-of-flight mass spectrometry (CE-MS) to generate individual urinary proteome profiles. In an initial biomarker discovery cohort, analysis of urinary proteome profiles from 33 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. Conclusion 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. PMID:27308822

  13. UPLC-MS(E) application in disease biomarker discovery: the discoveries in proteomics to metabolomics.

    PubMed

    Zhao, Ying-Yong; Lin, Rui-Chao

    2014-05-25

    In the last decade, proteomics and metabolomics have contributed substantially to our understanding of different diseases. Proteomics and metabolomics aims to comprehensively identify proteins and metabolites to gain insight into the cellular signaling pathways underlying disease and to discover novel biomarkers for screening, early detection and diagnosis, as well as for determining prognoses and predicting responses to specific treatments. For comprehensive analysis of cellular proteins and metabolites, analytical methods of wider dynamic range higher resolution and good sensitivity are required. Ultra performance liquid chromatography-mass spectrometry(Elevated Energy) (UPLC-MS(E)) is currently one of the most versatile techniques. UPLC-MS(E) is an established technology in proteomics studies and is now expanding into metabolite research. MS(E) was used for simultaneous acquisition of precursor ion information and fragment ion data at low and high collision energy in one analytical run, providing similar information to conventional MS(2). In this review, UPLC-MS(E) application in proteomics and metabolomics was highlighted to assess protein and metabolite changes in different diseases, including cancer, neuropsychiatric pharmacology studies from clinical trials and animal models. In addition, the future prospects for complete proteomics and metabolomics are discussed.

  14. Mass Spectrometry-based Proteomics and Peptidomics for Systems Biology and Biomarker Discovery

    PubMed Central

    Cunningham, Robert; Ma, Di; Li, Lingjun

    2013-01-01

    The scientific community has shown great interest in the field of mass spectrometry-based proteomics and peptidomics for its applications in biology. Proteomics technologies have evolved to produce large datasets of proteins or peptides involved in various biological and disease progression processes producing testable hypothesis for complex biological questions. This review provides an introduction and insight to relevant topics in proteomics and peptidomics including biological material selection, sample preparation, separation techniques, peptide fragmentation, post-translation modifications, quantification, bioinformatics, and biomarker discovery and validation. In addition, current literature and remaining challenges and emerging technologies for proteomics and peptidomics are presented. PMID:24504115

  15. Probing the O-glycoproteome of gastric cancer cell lines for biomarker discovery.

    PubMed

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

    2015-06-01

    Circulating O-glycoproteins shed from cancer cells represent important serum biomarkers for diagnostic and prognostic purposes. We have recently shown that selective detection of cancer-associated aberrant glycoforms of circulating O-glycoprotein biomarkers can increase specificity of cancer biomarker assays. However, the current knowledge of secreted and circulating O-glycoproteins is limited. Here, we used the COSMC KO "SimpleCell" (SC) strategy to characterize the O-glycoproteome of two gastric cancer SimpleCell lines (AGS, MKN45) as well as a gastric cell line (KATO III) which naturally expresses at least partially truncated O-glycans. Overall, we identified 499 O-glycoproteins and 1236 O-glycosites in gastric cancer SimpleCells, and a total 47 O-glycoproteins and 73 O-glycosites in the KATO III cell line. We next modified the glycoproteomic strategy to apply it to pools of sera from gastric cancer and healthy individuals to identify circulating O-glycoproteins with the STn glycoform. We identified 37 O-glycoproteins in the pool of cancer sera, and only nine of these were also found in sera from healthy individuals. Two identified candidate O-glycoprotein biomarkers (CD44 and GalNAc-T5) circulating with the STn glycoform were further validated as being expressed in gastric cancer tissue. A proximity ligation assay was used to show that CD44 was expressed with the STn glycoform in gastric cancer tissues. The study provides a discovery strategy for aberrantly glycosylated O-glycoproteins and a set of O-glycoprotein candidates with biomarker potential in gastric cancer. PMID:25813380

  16. Discovery of urinary metabolomic biomarkers for early detection of acute kidney injury.

    PubMed

    Won, A Jin; Kim, Siwon; Kim, Yoon Gyoon; Kim, Kyu-Bong; Choi, Wahn Soo; Kacew, Sam; Kim, Kyeong Seok; Jung, Jee H; Lee, Byung Mu; Kim, Suhkmann; Kim, Hyung Sik

    2016-01-01

    The discovery of new biomarkers for early detection of drug-induced acute kidney injury (AKI) is clinically important. In this study, sensitive metabolomic biomarkers identified in the urine of rats were used to detect cisplatin-induced AKI. Cisplatin (10 mg kg(-1), i.p.) was administered to Sprague-Dawley rats, which were subsequently euthanized after 1, 3 or 5 days. In cisplatin-treated rats, mild histopathological alterations were noted at day 1, and these changes were severe at days 3 and 5. Blood urea nitrogen (BUN) and serum creatinine (SCr) levels were significantly increased at days 3 and 5. The levels of new urinary protein-based biomarkers, including kidney injury molecule-1 (KIM-1), glutathione S-transferase-α (GST-α), tissue inhibitor of metalloproteinase-1 (TIMP-1), vascular endothelial growth factor (VEGF), calbindin, clusterin, neutrophil, neutrophil gelatinase-associated lipocalin (NGAL), and osteopontin, were significantly elevated at days 3 and 5. Among urinary metabolites, trigonelline and 3-indoxylsulfate (3-IS) levels were significantly decreased in urine collected from cisplatin-treated rats prior to histological kidney damage. However, carbon tetrachloride (CCl4), a hepatotoxicant, did not affect these urinary biomarkers. Trigonelline is closely associated with GSH depletion and results in insufficient antioxidant capacity against cisplatin-induced AKI. The predominant cisplatin-induced AKI marker appeared to be reduced in urinary 3-IS levels. Because 3-IS is predominantly excreted via active secretion in proximal tubules, a decrease is indicative of tubular damage. Further, urinary excretion of 3-IS levels was markedly reduced in patients with AKI compared to normal subjects. The area under the curve receiver operating characteristics (AUC-ROC) for 3-IS was higher than for SCr, BUN, lactate dehydrogenase (LDH), total protein, and glucose. Therefore, low urinary or high serum 3-IS levels may be more useful for early detection of AKI than

  17. MetaCoMET: a web platform for discovery and visualization of the core microbiome

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A key component of the analysis of microbiome datasets is the identification of OTUs shared between multiple experimental conditions, commonly referred to as the core microbiome. Results: We present a web platform named MetaCoMET that enables the discovery and visualization of the core microbiome an...

  18. A surface topography assisted droplet manipulation platform for biomarker detection and pathogen identification†

    PubMed Central

    Zhang, Yi; Park, Seungkyung; Liu, Kelvin; Tsuan, Jennifer; Yang, Samuel; Wang, Tza-Huei

    2015-01-01

    This paper reports a droplet microfluidic, sample-to-answer platform for the detection of disease biomarkers and infectious pathogens using crude biosamples. The platform exploited the dual functionality of silica superparamagnetic particles (SSP) for solid phase extraction of DNA and magnetic actuation. This enabled the integration of sample preparation and genetic analysis within discrete droplets, including the steps of cell lysis, DNA binding, washing, elution, amplification and detection. The microfluidic device was self contained, with all reagents stored in droplets, thereby eliminating the need for fluidic coupling to external reagent reservoirs. The device incorporated unique surface topographic features to assist droplet manipulation. Pairs of micro-elevations were created to form slits that facilitated efficient splitting of SSP from droplets. In addition, a compact sample handling stage, which integrated the magnet manipulator, the droplet microfluidic device and a Peltier thermal cycler, was built for convenient droplet manipulation and real-time detection. The feasibility of the platform was demonstrated by analysing ovarian cancer biomarker Rsf-1 and detecting Escherichia coli with real time polymerase chain reaction and real time helicase dependent amplification. PMID:21046055

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

    PubMed Central

    2011-01-01

    Recent positive clinical results in cancer immunotherapy point to the potential of immune-based strategies to provide effective treatment of a variety of cancers. In some patients, the responses to cancer immunotherapy are durable, dramatically extending survival. Extensive research efforts are being made to identify and validate biomarkers that can help identify subsets of cancer patients that will benefit most from these novel immunotherapies. In addition to the clear advantage of such predictive biomarkers, immune biomarkers are playing an important role in the development, clinical evaluation and monitoring of cancer immunotherapies. This Cancer Immunotherapy Resource Document, prepared by the Society for Immunotherapy of Cancer (SITC, formerly the International Society for Biological Therapy of Cancer, iSBTc), provides key references and online resources relevant to the discovery, evaluation and clinical application of immune biomarkers. These key resources were identified by experts in the field who are actively pursuing research in biomarker identification and validation. This organized collection of the most useful references, online resources and tools serves as a compass to guide discovery of biomarkers essential to advancing novel cancer immunotherapies. PMID:21929757

  20. Detection of cancer-specific epigenomic changes in biofluids: powerful tools in biomarker discovery and application.

    PubMed

    Nogueira da Costa, André; Herceg, Zdenko

    2012-12-01

    The genetic and epigenetic material originating from tumour that can be found in body fluids of individuals with cancer harbours tumour-specific alterations and represents an attractive target for biomarker discovery. Epigenetic changes (DNA methylation, histone modifications and non-coding RNAs) are present ubiquitously in virtually all types of human malignancies and may appear in early cancer development, and thus they provide particularly attractive markers with broad applications in diagnostics. In addition, because changes in the epigenome may constitute a signature of specific exposure to certain risk factors, they have the potential to serve as highly specific biomarkers for risk assessment. While reliable detection of cancer-specific epigenetic changes has proven to be technically challenging, a substantial progress has been made in developing the methodologies that allow an efficient and sensitive detection of epigenomic changes using the material originating from body fluids. In this review we discuss the application of epigenomics as a tool for biomarker research, with the focus on the analysis of DNA methylation in biofluids.

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

    PubMed Central

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

    2016-01-01

    Identification of sensitive and specific biomarkers with clinical and translational utility will require smart experimental strategies that would augment expanding the breadth and depth of molecular measurements within the constraints of currently available technologies. Exosomes represent an information rich matrix to discern novel disease mechanisms that are thought to contribute to pathologies such as dementia and cancer. Although proteomics and transcriptomic studies have been reported using Exosomes-Like Vesicles (ELVs) from different sources, exosomal metabolome characterization and its modulation in health and disease remains to be elucidated. Here we describe methodologies for UPLC-ESI-MS based small molecule profiling of ELVs from human plasma and cell culture media. In this study, we present evidence that indeed ELVs carry a rich metabolome that could not only augment the discovery of low abundance biomarkers but may also help explain the molecular basis of disease progression. This approach could be easily translated to other studies seeking to develop predictive biomarkers that can subsequently be used with simplified targeted approaches. PMID:26974972

  2. Development of a pharmaceutical hepatotoxicity biomarker panel using a discovery to targeted proteomics approach.

    PubMed

    Collins, Ben C; Miller, Christine A; Sposny, Alexandra; Hewitt, Phillip; Wells, Martin; Gallagher, William M; Pennington, Stephen R

    2012-08-01

    There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and

  3. Development of a Pharmaceutical Hepatotoxicity Biomarker Panel Using a Discovery to Targeted Proteomics Approach*

    PubMed Central

    Collins, Ben C.; Miller, Christine A.; Sposny, Alexandra; Hewitt, Phillip; Wells, Martin; Gallagher, William M.; Pennington, Stephen R.

    2012-01-01

    There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPARα activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis coupled to LC-MS/MS. After iterative optimization and

  4. Development of Transcriptomics-based Biomarkers for Selected Endocrine Disrupting Chemicals in Zebrafish (Danio rerio)

    EPA Science Inventory

    Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

  5. Development of transcriptomics-based biomarkers for selected endocrine disrupting chemicals in zebrafish (Danio rerio)

    EPA Science Inventory

    Genome-wide transcriptional profiling by microarrays provides a powerful platform for gene expression-based biomarker discovery. After their wide acceptance in human disease diagnosis, prognosis, and drug discovery, these gene signatures are increasingly being adopted for environ...

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

    PubMed

    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

  7. Targeted Discovery and Validation of Plasma Biomarkers of Parkinson’s Disease

    PubMed Central

    2015-01-01

    Despite extensive research, an unmet need remains for protein biomarkers of Parkinson’s disease (PD) in peripheral body fluids, especially blood, which is easily accessible clinically. The discovery of such biomarkers is challenging, however, due to the enormous complexity and huge dynamic range of human blood proteins, which are derived from nearly all organ systems, with those originating specifically from the central nervous system (CNS) being exceptionally low in abundance. In this investigation of a relatively large cohort (∼300 subjects), selected reaction monitoring (SRM) assays (a targeted approach) were used to probe plasma peptides derived from glycoproteins previously found to be altered in the CNS based on PD diagnosis or severity. Next, the detected peptides were interrogated for their diagnostic sensitivity and specificity as well as the correlation with PD severity, as determined by the Unified Parkinson’s Disease Rating Scale (UPDRS). The results revealed that 12 of the 50 candidate glycopeptides were reliably and consistently identified in plasma samples, with three of them displaying significant differences among diagnostic groups. A combination of four peptides (derived from PRNP, HSPG2, MEGF8, and NCAM1) provided an overall area under curve (AUC) of 0.753 (sensitivity: 90.4%; specificity: 50.0%). Additionally, combining two peptides (derived from MEGF8 and ICAM1) yielded significant correlation with PD severity, that is, UPDRS (r = 0.293, p = 0.004). The significance of these results is at least two-fold: (1) it is possible to use a targeted approach to identify otherwise very difficult to detect CNS related biomarkers in peripheral blood and (2) the novel biomarkers, if validated in independent cohorts, can be employed to assist with clinical diagnosis of PD as well as monitoring disease progression. PMID:24853996

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

    PubMed

    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.

  9. LOBSTAHS: An Adduct-Based Lipidomics Strategy for Discovery and Identification of Oxidative Stress Biomarkers.

    PubMed

    Collins, James R; Edwards, Bethanie R; Fredricks, Helen F; Van Mooy, Benjamin A S

    2016-07-19

    Discovery and identification of molecular biomarkers in large LC/MS data sets requires significant automation without loss of accuracy in the compound screening and annotation process. Here, we describe a lipidomics workflow and open-source software package for high-throughput annotation and putative identification of lipid, oxidized lipid, and oxylipin biomarkers in high-mass-accuracy HPLC-MS data. Lipid and oxylipin biomarker screening through adduct hierarchy sequences, or LOBSTAHS, uses orthogonal screening criteria based on adduct ion formation patterns and other properties to identify thousands of compounds while providing the user with a confidence score for each assignment. Assignments are made from one of two customizable databases; the default databases contain 14 068 unique entries. To demonstrate the software's functionality, we screened more than 340 000 mass spectral features from an experiment in which hydrogen peroxide was used to induce oxidative stress in the marine diatom Phaeodactylum tricornutum. LOBSTAHS putatively identified 1969 unique parent compounds in 21 869 features that survived the multistage screening process. While P. tricornutum maintained more than 92% of its core lipidome under oxidative stress, patterns in biomarker distribution and abundance indicated remodeling was both subtle and pervasive. Treatment with 150 μM H2O2 promoted statistically significant carbon-chain elongation across lipid classes, with the strongest elongation accompanying oxidation in moieties of monogalactosyldiacylglycerol, a lipid typically localized to the chloroplast. Oxidative stress also induced a pronounced reallocation of lipidome peak area to triacylglycerols. LOBSTAHS can be used with environmental or experimental data from a variety of systems and is freely available at https://github.com/vanmooylipidomics/LOBSTAHS . PMID:27322848

  10. Lung Cancer Serum Biomarker Discovery Using Label Free LC-MS/MS

    PubMed Central

    Zeng, Xuemei; Hood, Brian L.; Zhao, Ting; Conrads, Thomas P.; Sun, Mai; Gopalakrishnan, Vanathi; Grover, Himanshu; Day, Roger S.; Weissfeld, Joel L.; Wilson, David O.; Siegfried, Jill M.; Bigbee, William L.

    2011-01-01

    Introduction Lung cancer remains the leading cause of cancer-related death with poor survival due to the late stage at which lung cancer is typically diagnosed. Given the clinical burden from lung cancer, and the relatively favorable survival associated with early stage lung cancer, biomarkers for early detection of lung cancer are of important potential clinical benefit. Methods We performed a global lung cancer serum biomarker discovery study using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in a set of pooled non-small cell lung cancer (NSCLC) case sera and matched controls. Immunoaffinity subtraction was used to deplete the top most abundant serum proteins; the remaining serum proteins were subjected to trypsin digestion and analyzed in triplicate by LC-MS/MS. The tandem mass spectrum data were searched against the human proteome database and the resultant spectral counting data were used to estimate the relative abundance of proteins across the case/control serum pools. The spectral counting derived abundances of some candidate biomarker proteins were confirmed with multiple reaction monitoring MS assays. Results A list of 49 differentially abundant candidate proteins was compiled by applying a negative binomial regression model to the spectral counting data (p<0.01). Functional analysis with Ingenuity Pathway Analysis tools showed significant enrichment of inflammatory response proteins, key molecules in cell-cell signaling and interaction network and differential physiological responses for the two common NSCLC subtypes. Conclusions We identified a set of candidate serum biomarkers with statistically significant differential abundance across the lung cancer case/control pools which, when validated, could improve lung cancer early detection. PMID:21304412

  11. Top-Down Proteomics with Mass Spectrometry Imaging: A Pilot Study towards Discovery of Biomarkers for Neurodevelopmental Disorders

    PubMed Central

    Ye, Hui; Mandal, Rakesh; Catherman, Adam; Thomas, Paul M.; Kelleher, Neil L.; Ikonomidou, Chrysanthy; Li, Lingjun

    2014-01-01

    In the developing mammalian brain, inhibition of NMDA receptor can induce widespread neuroapoptosis, inhibit neurogenesis and cause impairment of learning and memory. Although some mechanistic insights into adverse neurological actions of these NMDA receptor antagonists exist, our understanding of the full spectrum of developmental events affected by early exposure to these chemical agents in the brain is still limited. Here we attempt to gain insights into the impact of pharmacologically induced excitatory/inhibitory imbalance in infancy on the brain proteome using mass spectrometric imaging (MSI). Our goal was to study changes in protein expression in postnatal day 10 (P10) rat brains following neonatal exposure to the NMDA receptor antagonist dizocilpine (MK801). Analysis of rat brains exposed to vehicle or MK801 and comparison of their MALDI MS images revealed differential relative abundances of several proteins. We then identified these markers such as ubiquitin, purkinje cell protein 4 (PEP-19), cytochrome c oxidase subunits and calmodulin, by a combination of reversed-phase (RP) HPLC fractionation and top-down tandem MS platform. More in-depth large scale study along with validation experiments will be carried out in the future. Overall, our findings indicate that a brief neonatal exposure to a compound that alters excitatory/inhibitory balance in the brain has a long term effect on protein expression patterns during subsequent development, highlighting the utility of MALDI-MSI as a discovery tool for potential biomarkers. PMID:24710523

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

    SciTech Connect

    Amacher, David E.

    2010-05-15

    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

  13. Identification of Candidate Serum Biomarkers for Schistosoma mansoni Infected Mice Using Multiple Proteomic Platforms

    PubMed Central

    Kardoush, Manal I.

    2016-01-01

    Background Schistosomiasis is an important helminth infection of humans. There are few reliable diagnostic biomarkers for early infection, for recurrent infection or to document successful treatment. In this study, we compared serum protein profiles in uninfected and infected mice to identify disease stage-specific biomarkers. Methods Serum collected from CD1 mice infected with 50–200 Schistosoma mansoni cercariae were analyzed before infection and at 3, 6 and 12 weeks post-infection using three mass spectrometric (MS) platforms. Results Using SELDI-TOF MS, 66 discriminating m/z peaks were detected between S. mansoni infected mice and healthy controls. Used in various combinations, these peaks could 1) reliably diagnose early-stage disease, 2) distinguish between acute and chronic infection and 3) diagnose S. mansoni infection regardless the parasite burden. The most important contributors to these diagnostic algorithms were peaks at 3.7, 13 and 46 kDa. Employing sample fractionation and differential gel electrophoresis, we analyzed gel slices either by MALDI-TOF MS or Velos Orbitrap MS. The former yielded eight differentially-expressed host proteins in the serum at different disease stages including transferrin and alpha 1- antitrypsin. The latter suggested the presence of a surprising number of parasite-origin proteins in the serum during both the acute (n = 200) and chronic (n = 105) stages. The Orbitrap platform also identified many differentially-expressed host-origin serum proteins during the acute and chronic stages (296 and 220 respectively). The presence of one of the schistosome proteins, glutathione S transferase (GST: 25 KDa), was confirmed by Western Blot. This study provides proof-of-principle for an approach that can yield a large number of novel candidate biomarkers for Schistosoma infection. PMID:27138990

  14. Functionalized nanoparticles for measurement of biomarkers using a SERS nanochannel platform

    NASA Astrophysics Data System (ADS)

    Benford, Melodie; Wang, Miao; Kameoka, Jun; Good, Theresa; Cote, Gerard

    2010-02-01

    The overall goal of this research is to develop a new point-of-care system for early detection and characterization of cardiac markers to aid in diagnosis of acute coronary syndrome. The envisioned final technology platform incorporates functionalized gold colloidal nanoparticles trapped at the entrance to a nanofluidic device providing a robust means for analyte detection at trace levels using surface enhanced Raman spectroscopy (SERS). To discriminate a specific biomarker, we designed an assay format analogous to a competitive ELISA. Notably, the biomarker would be captured by an antibody and in turn displace a peptide fragment, containing the binding epitope of the antibody labeled with a Raman reporter molecule that would not interfere with blood serum proteins. To demonstrate the feasibility of this approach, we used C-reactive protein (CRP) as a surrogate biomarker. We functionalized agarose beads with anti-CRP that were placed outside the nanochannel, then added either Rhodamine-6-G (R6G) labeled-CRP and gold (as a surrogate of a sample without analyte present), or R6G labeled CRP, gold, and unlabeled CRP (as a surrogate of a sample with analyte present). Analyzing the spectra we see an increase in peak intensity in the presence of analyte at characteristic peaks for R6G specifically, 1284 and1567 cm- 1. Further, our results illustrate the reproducibility of the Raman spectra collected for R6G-labeled CRP in the nanochannel. Overall, we believe that this method will provide the advantage of sensitivity and narrow line widths characteristic of SERS as well as the specificity toward the biomarker of interest.

  15. The role of visual analytics in asthma phenotyping and biomarker discovery.

    PubMed

    Bhavnani, Suresh K; Drake, Justin; Divekar, Rohit

    2014-01-01

    The exponential growth of biomedical data related to diseases such as asthma far exceeds our cognitive abilities to comprehend it for tasks such as biomarker discovery, pathway identification, and molecular-based phenotyping. This chapter discusses the cognitive and task-based reasons for why methods from visual analytics can help in analyzing such large and complex asthma data, and demonstrates how one such approach called network visualization and analysis can be used to reveal important translational insights related to asthma. The demonstration of the method helps to identify the strengths and limitations of network analysis, in addition to areas for future research that can enhance the use of networks to analyze vast and complex biomedical datasets related to diseases such as asthma.

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

    PubMed

    Caberlotto, Laura; Lauria, Mario

    2015-02-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens’ pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases. PMID:27579980

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

    PubMed

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

    2016-01-01

    Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases. PMID:27579980

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

    PubMed

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

    2013-06-01

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

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

    EPA Science Inventory

    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...

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

    PubMed

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

    2013-08-01

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

  3. Novel stem cell-based drug discovery platforms for cardiovascular disease.

    PubMed

    Adams, William J; García-Cardeña, Guillermo

    2012-10-01

    The complexity and diversity of many human diseases pose significant hurdles to the development of novel therapeutics. New scientific and technological advances, such as pharmacogenetics, provide valuable frameworks for understanding genetic predisposition to disease and tools for diagnosis and drug development. However, another framework is emerging based on recent scientific advances, one we suggest to call pharmacoempirics. Pharmacoempirics takes advantage of merging two nascent fields: first, the generation of induced pluripotent stem cells, which are differentiated into mature cell types and represent patient-specific genetic backgrounds, and, second, bioengineering advances allowing sophisticated re-creation of human pathophysiology in laboratory settings. The combination of these two innovative technologies should allow new experimentation on disease biology and drug discovery, efficacy, and toxicology unencumbered by hypothesis generation and testing. In this review, we discuss the challenges and promises of this exciting new type of discovery platform and outline its implementation for cardiovascular drug discovery.

  4. SANIST: a rapid mass spectrometric SACI/ESI data acquisition and elaboration platform for verifying potential candidate biomarkers

    PubMed Central

    Briga, Daniela; Conti, Matteo; Bruno, Antonino; Farioli, Daniela; Canali, Sara; Sogno, Ilaria; D'Ambrosio, Gioacchino; Consonni, Paolo; Noonan, Douglas M.

    2015-01-01

    Rationale Surface‐Activated Chemical Ionization/Electrospray Ionization mass spectrometry (SACI/ESI‐MS) is a technique with high sensitivity and low noise that allows accurate biomarker discovery studies. We developed a dedicated SACI/ESI software, named SANIST, for both biomarker fingerprint data acquisition and as a diagnostic tool, using prostate cancer (PCa) as the disease of interest. Methods Liquid chromatography (LC)/SACI/ESI‐MS technology was employed to detect a potential biomarker panel for PCa disease prediction. Serum from patients with histologically confirmed or negative prostate biopsies for PCa was employed. The biomarker data (m/z or Thompson value, retention time and extraction mass chromatogram peak area) were stored in an ascii database. SANIST software allowed identification of potential biomarkers. A Bayesian scoring algorithm developed in house allowed sample separation based on comparison with samples in the database. Results Biomarker candidates from the carnitine family were detected at significantly lower levels in patients showing histologically confirmed PCa. Using these biomarkers, the SANIST scoring algorithm allowed separation of patients with PCa from biopsy negative subjects with high accuracy and sensitivity. Conclusions SANIST was able to rapidly identify and perform a preliminary evaluation of the potential diagnostic efficiency of potential biomarkers for PCa. © 2015 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons Ltd. PMID:26331920

  5. Novel potential serological prostate cancer biomarkers using CT100+ cancer antigen microarray platform in a multi-cultural South African cohort

    PubMed Central

    Adeola, Henry A.; Smith, Muneerah; Kaestner, Lisa; Blackburn, Jonathan M.; Zerbini, Luiz F.

    2016-01-01

    There is a growing need for high throughput diagnostic tools for early diagnosis and treatment monitoring of prostate cancer (PCa) in Africa. The role of cancer-testis antigens (CTAs) in PCa in men of African descent is poorly researched. Hence, we aimed to elucidate the role of 123 Tumour Associated Antigens (TAAs) using antigen microarray platform in blood samples (N = 67) from a South African PCa, Benign prostatic hyperplasia (BPH) and disease control (DC) cohort. Linear (fold-over-cutoff) and differential expression quantitation of autoantibody signal intensities were performed. Molecular signatures of candidate PCa antigen biomarkers were identified and analyzed for ethnic group variation. Potential cancer diagnostic and immunotherapeutic inferences were drawn. We identified a total of 41 potential diagnostic/therapeutic antigen biomarkers for PCa. By linear quantitation, four antigens, GAGE1, ROPN1, SPANXA1 and PRKCZ were found to have higher autoantibody titres in PCa serum as compared with BPH where MAGEB1 and PRKCZ were highly expressed. Also, p53 S15A and p53 S46A were found highly expressed in the disease control group. Statistical analysis by differential expression revealed twenty-four antigens as upregulated in PCa samples, while 11 were downregulated in comparison to BPH and DC (FDR = 0.01). FGFR2, COL6A1and CALM1 were verifiable biomarkers of PCa analysis using urinary shotgun proteomics. Functional pathway annotation of identified biomarkers revealed similar enrichment both at genomic and proteomic level and ethnic variations were observed. Cancer antigen arrays are emerging useful in potential diagnostic and immunotherapeutic antigen biomarker discovery. PMID:26885621

  6. Automated microfluidic platform of bead-based electrochemical immunosensor integrated with bioreactor for continual monitoring of cell secreted biomarkers

    NASA Astrophysics Data System (ADS)

    Riahi, Reza; Shaegh, Seyed Ali Mousavi; Ghaderi, Masoumeh; Zhang, Yu Shrike; Shin, Su Ryon; Aleman, Julio; Massa, Solange; Kim, Duckjin; Dokmeci, Mehmet Remzi; Khademhosseini, Ali

    2016-04-01

    There is an increasing interest in developing microfluidic bioreactors and organs-on-a-chip platforms combined with sensing capabilities for continual monitoring of cell-secreted biomarkers. Conventional approaches such as ELISA and mass spectroscopy cannot satisfy the needs of continual monitoring as they are labor-intensive and not easily integrable with low-volume bioreactors. This paper reports on the development of an automated microfluidic bead-based electrochemical immunosensor for in-line measurement of cell-secreted biomarkers. For the operation of the multi-use immunosensor, disposable magnetic microbeads were used to immobilize biomarker-recognition molecules. Microvalves were further integrated in the microfluidic immunosensor chip to achieve programmable operations of the immunoassay including bead loading and unloading, binding, washing, and electrochemical sensing. The platform allowed convenient integration of the immunosensor with liver-on-chips to carry out continual quantification of biomarkers secreted from hepatocytes. Transferrin and albumin productions were monitored during a 5-day hepatotoxicity assessment in which human primary hepatocytes cultured in the bioreactor were treated with acetaminophen. Taken together, our unique microfluidic immunosensor provides a new platform for in-line detection of biomarkers in low volumes and long-term in vitro assessments of cellular functions in microfluidic bioreactors and organs-on-chips.

  7. Automated microfluidic platform of bead-based electrochemical immunosensor integrated with bioreactor for continual monitoring of cell secreted biomarkers

    PubMed Central

    Riahi, Reza; Shaegh, Seyed Ali Mousavi; Ghaderi, Masoumeh; Zhang, Yu Shrike; Shin, Su Ryon; Aleman, Julio; Massa, Solange; Kim, Duckjin; Dokmeci, Mehmet Remzi; Khademhosseini, Ali

    2016-01-01

    There is an increasing interest in developing microfluidic bioreactors and organs-on-a-chip platforms combined with sensing capabilities for continual monitoring of cell-secreted biomarkers. Conventional approaches such as ELISA and mass spectroscopy cannot satisfy the needs of continual monitoring as they are labor-intensive and not easily integrable with low-volume bioreactors. This paper reports on the development of an automated microfluidic bead-based electrochemical immunosensor for in-line measurement of cell-secreted biomarkers. For the operation of the multi-use immunosensor, disposable magnetic microbeads were used to immobilize biomarker-recognition molecules. Microvalves were further integrated in the microfluidic immunosensor chip to achieve programmable operations of the immunoassay including bead loading and unloading, binding, washing, and electrochemical sensing. The platform allowed convenient integration of the immunosensor with liver-on-chips to carry out continual quantification of biomarkers secreted from hepatocytes. Transferrin and albumin productions were monitored during a 5-day hepatotoxicity assessment in which human primary hepatocytes cultured in the bioreactor were treated with acetaminophen. Taken together, our unique microfluidic immunosensor provides a new platform for in-line detection of biomarkers in low volumes and long-term in vitro assessments of cellular functions in microfluidic bioreactors and organs-on-chips. PMID:27098564

  8. Transgenic mouse strains as platforms for the successful discovery and development of human therapeutic monoclonal antibodies.

    PubMed

    Green, Larry L

    2014-03-01

    Transgenic mice have yielded seven of the ten currently-approved human antibody drugs, making them the most successful platform for the discovery of fully human antibody therapeutics. The use of the in vivo immune system helps drive this success by taking advantage of the natural selection process that produces antibodies with desirable characteristics. Appropriately genetically-engineered mice act as robust engines for the generation of diverse repertoires of affinity- matured fully human variable regions with intrinsic properties necessary for successful antibody drug development including high potency, specificity, manufacturability, solubility and low risk of immunogenicity. A broad range of mAb drug targets are addressable in these mice, comprising both secreted and transmembrane targets, including membrane multi-spanning targets, as well as human target antigens that share high sequence identity with their mouse orthologue. Transgenic mice can routinely yield antibodies with sub-nanomolar binding affinity for their antigen, with lead candidate mAbs frequently possessing affinities for binding to their target of less than 100 picomolar, without requiring any ex vivo affinity optimization. While the originator transgenic mice platforms are no longer broadly available, a new generation of transgenic platforms is in development for discovery of the next wave of human therapeutic antibodies.

  9. Discovery of Prognostic Biomarker Candidates of Lacunar Infarction by Quantitative Proteomics of Microvesicles Enriched Plasma

    PubMed Central

    Datta, Arnab; Chen, Christopher P.; Sze, Siu Kwan

    2014-01-01

    Background Lacunar infarction (LACI) is a subtype of acute ischemic stroke affecting around 25% of all ischemic stroke cases. Despite having an excellent recovery during acute phase, certain LACI patients have poor mid- to long-term prognosis due to the recurrence of vascular events or a decline in cognitive functions. Hence, blood-based biomarkers could be complementary prognostic and research tools. Methods and Finding Plasma was collected from forty five patients following a non-disabling LACI along with seventeen matched control subjects. The LACI patients were monitored prospectively for up to five years for the occurrence of adverse outcomes and grouped accordingly (i.e., LACI-no adverse outcome, LACI-recurrent vascular event, and LACI-cognitive decline without any recurrence of vascular events). Microvesicles-enriched fractions isolated from the pooled plasma of four groups were profiled by an iTRAQ-guided discovery approach to quantify the differential proteome. The data have been deposited to the ProteomeXchange with identifier PXD000748. Bioinformatics analysis and data mining revealed up-regulation of brain-specific proteins including myelin basic protein, proteins of coagulation cascade (e.g., fibrinogen alpha chain, fibrinogen beta chain) and focal adhesion (e.g., integrin alpha-IIb, talin-1, and filamin-A) while albumin was down-regulated in both groups of patients with adverse outcome. Conclusion This data set may offer important insight into the mechanisms of poor prognosis and provide candidate prognostic biomarkers for validation on larger cohort of individual LACI patients. PMID:24752076

  10. An automated Genomes-to-Natural Products platform (GNP) for the discovery of modular natural products

    PubMed Central

    Johnston, Chad W.; Skinnider, Michael A.; Wyatt, Morgan A.; Li, Xiang; Ranieri, Michael R. M.; Yang, Lian; Zechel, David L.; Ma, Bin; Magarvey, Nathan A.

    2015-01-01

    Bacterial natural products are a diverse and valuable group of small molecules, and genome sequencing indicates that the vast majority remain undiscovered. The prediction of natural product structures from biosynthetic assembly lines can facilitate their discovery, but highly automated, accurate, and integrated systems are required to mine the broad spectrum of sequenced bacterial genomes. Here we present a genome-guided natural products discovery tool to automatically predict, combinatorialize and identify polyketides and nonribosomal peptides from biosynthetic assembly lines using LC–MS/MS data of crude extracts in a high-throughput manner. We detail the directed identification and isolation of six genetically predicted polyketides and nonribosomal peptides using our Genome-to-Natural Products platform. This highly automated, user-friendly programme provides a means of realizing the potential of genetically encoded natural products. PMID:26412281

  11. Phage antibody display libraries: a powerful antibody discovery platform for immunotherapy.

    PubMed

    Zhao, Aizhi; Tohidkia, Mohammad R; Siegel, Donald L; Coukos, George; Omidi, Yadollah

    2016-01-01

    Phage display technology (PDT), a combinatorial screening approach, provides a molecular diversity tool for creating libraries of peptides/proteins and discovery of new recombinant therapeutics. Expression of proteins such as monoclonal antibodies (mAbs) on the surface of filamentous phage can permit the selection of high affinity and specificity therapeutic mAbs against virtually any target antigen. Using a number of diverse selection platforms (e.g. solid phase, solution phase, whole cell and in vivo biopannings), phage antibody libraries (PALs) from the start point provides great potential for the isolation of functional mAb fragments with diagnostic and/or therapeutic purposes. Given the pivotal role of PDT in the discovery of novel therapeutic/diagnostic mAbs, in the current review, we provide an overview on PALs and discuss their impact in the advancement of engineered mAbs.

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

    PubMed Central

    Wang, Xiaojun; Su, Xiaoquan

    2015-01-01

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

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

    PubMed

    Sundarrajan, Sudharsana; Arumugam, Mohanapriya

    2016-11-15

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

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

    PubMed

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

    2016-07-21

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

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

    PubMed

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

    2016-07-21

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

  16. Capillary electrophoresis–mass spectrometry as a powerful tool in biomarker discovery and clinical diagnosis: an update of recent developments

    PubMed Central

    Mischak, Harald; Coon, Joshua J.; Novak, Jan; Weissinger, Eva M.; Schanstra, Joost; Dominiczak, Anna F.

    2009-01-01

    Proteome analysis has emerged as a powerful technology to decipher biological processes. One of the main goals is to discover biomarkers for diseases from tissues and body fluids. However, the complexity and wide dynamic range of protein expression present an enormous challenge to separation technologies and mass spectrometry (MS). In this review, we examine the limitations of proteomics, and aim towards the definition of the current key prerequisites. We focus on capillary electrophoresis coupled to mass spectrometry (CE-MS), because this technique continues to show great promise. We discuss CE-MS from an application point of view, and evaluate its merits and vices for biomarker discovery and clinical applications. Finally, we present several examples on the use of CE-MS to determine urinary biomarkers and implications for disease diagnosis, prognosis, and therapy evaluation. PMID:18973238

  17. Interferometric biosensing platform for multiplexed digital detection of viral pathogens and biomarkers

    NASA Astrophysics Data System (ADS)

    Daaboul, George

    Label-free optical biosensors have been established as proven tools for monitoring specific biomolecular interactions. However, compact and robust embodiments of such instruments have yet to be introduced in order to provide sensitive, quantitative, and high-throughput biosensing for low-cost research and clinical applications. Here we present the interferometric reflectance-imaging sensor (IRIS). IRIS allows sensitive label free analysis using an inexpensive and durable multi-color LED illumination source on a silicon based surface. IRIS monitors biomolecular interaction through measurement of biomass addition to the sensor's surface. We demonstrate the capability of this system to dynamically monitor antigen---antibody interactions with a noise floor of 5.2 pg/mm 2 and DNA single mismatch detection under isothermal melting conditions in an array format. Ensemble detection of binding events using IRIS did not provide the sensitivity needed for detection of infectious disease and biomarkers at clinically relevant concentrations. Therefore, a new approach was adapted to the IRIS platform that allowed the detection and identification of individual nanoparticles on the sensor's surface. The new detection method was termed single-particle IRIS (SP-IRIS). We developed two detection modalities for SP-IRIS. The first modality is when the target is a nanoparticle such as a virus. We verified that SP-IRIS can accurately detect and size individual viral particles. Then we demonstrated that single nanoparticle counting and sizing methodology on SP-IRIS leads to a specific and sensitive virus sensor that can be multiplexed. Finally, we developed an assay for the detection of Ebola and Marburg. A detection limit of 3 x 103 PFU/ml was demonstrated for vesicular stomatitis virus (VSV) pseudotyped with Ebola or Marburg virus glycoprotein. We have demonstrated that virus detection can be done in human whole blood directly without the need for sample preparation. The second modality

  18. Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery.

    PubMed

    Patel, Seema; Ahmed, Shadab

    2015-03-25

    Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics.

  19. A High-throughput O-Glycopeptide Discovery Platform for Seromic Profiling

    PubMed Central

    Blixt, Ola; Cló, Emiliano; Nudelman, Aaron S.; Sørensen, Kasper Kildegaard; Clausen, Thomas; Wandall, Hans H.; Livingston, Philip O.; Clausen, Henrik; Jensen, Knud J.

    2010-01-01

    Biomarker microarrays are becoming valuable tools for serological screening of disease-associated autoantibodies. Post-translational modifications (PTMs) such as glycosylation extend the range of protein function, and a variety of glycosylated proteins are known to be altered in disease progression. Here, we have developed a synthetic screening microarray platform for facile display of O-glycosylated peptides (O-PTMs). By introducing a capping step during chemical solid-phase glycopeptide synthesis, selective enrichment of N-terminal glycopeptide end products were achieved on an amine-reactive hydrogel coated microarray glass surface, allowing high-throughput display of large numbers of glycopeptides. Utilizing a repertoire of recombinant glycosyltransferases enabled further diversification of the array libraries in-situ and display of a new level of potential biomarker candidates for serological screening. As proof-of-concept we have demonstrated that MUC1 glycopeptides could be assembled and used to detect autoantibodies in vaccine induced disease free breast cancer patients and in patients, with confirmed disease at time of diagnosis. PMID:20726594

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

    Cancer.gov

    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

  1. In-depth Proteomic Analysis of Six Types of Exudative Pleural Effusions for Nonsmall Cell Lung Cancer Biomarker Discovery*

    PubMed Central

    Liu, Pei-Jun; Chen, Chi-De; Wang, Chih-Liang; Wu, Yi-Cheng; Hsu, Chia-Wei; Lee, Chien-Wei; Huang, Lien-Hung; Yu, Jau-Song; Chang, Yu-Sun; Wu, Chih-Ching; Yu, Chia-Jung

    2015-01-01

    Pleural effusion (PE), a tumor-proximal body fluid, may be a promising source for biomarker discovery in human cancers. Because a variety of pathological conditions can lead to PE, characterization of the relative PE proteomic profiles from different types of PEs would accelerate discovery of potential PE biomarkers specifically used to diagnose pulmonary disorders. Using quantitative proteomic approaches, we identified 772 nonredundant proteins from six types of exudative PEs, including three malignant PEs (MPE, from lung, breast, and gastric cancers), one lung cancer paramalignant PE, and two benign diseases (tuberculosis and pneumonia). Spectral counting was utilized to semiquantify PE protein levels. Principal component analysis, hierarchical clustering, and Gene Ontology of cellular process analyses revealed differential levels and functional profiling of proteins in each type of PE. We identified 30 candidate proteins with twofold higher levels (q<0.05) in lung cancer MPEs than in the two benign PEs. Three potential markers, MET, DPP4, and PTPRF, were further verified by ELISA using 345 PE samples. The protein levels of these potential biomarkers were significantly higher in lung cancer MPE than in benign diseases or lung cancer paramalignant PE. The area under the receiver-operator characteristic curve for three combined biomarkers in discriminating lung cancer MPE from benign diseases was 0.903. We also observed that the PE protein levels were more clearly discriminated in effusions in which the cytological examination was positive and that they would be useful in rescuing the false negative of cytological examination in diagnosis of nonsmall cell lung cancer-MPE. Western blotting analysis further demonstrated that MET overexpression in lung cancer cells would contribute to the elevation of soluble MET in MPE. Our results collectively demonstrate the utility of label-free quantitative proteomic approaches in establishing differential PE proteomes and

  2. Discovery and Validation of Predictive Biomarkers of Survival for Non-small Cell Lung Cancer Patients Undergoing Radical Radiotherapy: Two Proteins With Predictive Value.

    PubMed

    Walker, Michael J; Zhou, Cong; Backen, Alison; Pernemalm, Maria; Williamson, Andrew J K; Priest, Lynsey J C; Koh, Pek; Faivre-Finn, Corinne; Blackhall, Fiona H; Dive, Caroline; Whetton, Anthony D

    2015-08-01

    Lung cancer is the most frequent cause of cancer-related death world-wide. Radiotherapy alone or in conjunction with chemotherapy is the standard treatment for locally advanced non-small cell lung cancer (NSCLC). Currently there is no predictive marker with clinical utility to guide treatment decisions in NSCLC patients undergoing radiotherapy. Identification of such markers would allow treatment options to be considered for more effective therapy. To enable the identification of appropriate protein biomarkers, plasma samples were collected from patients with non-small cell lung cancer before and during radiotherapy for longitudinal comparison following a protocol that carries sufficient power for effective discovery proteomics. Plasma samples from patients pre- and during radiotherapy who had survived > 18 mo were compared to the same time points from patients who survived < 14 mo using an 8 channel isobaric tagging tandem mass spectrometry discovery proteomics platform. Over 650 proteins were detected and relatively quantified. Proteins which showed a change during radiotherapy were selected for validation using an orthogonal antibody-based approach. Two of these proteins were verified in a separate patient cohort: values of CRP and LRG1 combined gave a highly significant indication of extended survival post one week of radiotherapy treatment.

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

    PubMed Central

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

    2016-01-01

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

  4. Yeast Synthetic Biology Platform Generates Novel Chemical Structures as Scaffolds for Drug Discovery

    PubMed Central

    2014-01-01

    Synthetic biology has been heralded as a new bioengineering platform for the production of bulk and specialty chemicals, drugs, and fuels. Here, we report for the first time a series of 74 novel compounds produced using a combinatorial genetics approach in baker’s yeast. Based on the concept of “coevolution” with target proteins in an intracellular primary survival assay, the identified, mostly scaffold-sized (200–350 MW) compounds, which displayed excellent biological activity, can be considered as prevalidated hits. Of the molecules found, >75% have not been described previously; 20% of the compounds exhibit novel scaffolds. Their structural and physicochemical properties comply with established rules of drug- and fragment-likeness and exhibit increased structural complexities compared to synthetically produced fragments. In summary, the synthetic biology approach described here represents a completely new, complementary strategy for hit and early lead identification that can be easily integrated into the existing drug discovery process. PMID:24742115

  5. Plenario: A Spatio-Temporal Platform for Discovery and Exploration of Urban Science Data

    NASA Astrophysics Data System (ADS)

    Engler, W. H.; Malik, T.; Catlett, C.; Foster, I.; Goldstein, B.

    2015-12-01

    The past decade has seen the widespread release of open data concerning city services, conditions, and activities by government bodies and public institutions of all sizes. Hundreds of open data portals now host thousands of datasets of many different types. These new data sources represent enormous potential for improved understanding of urban dynamics and processes—and, ultimately, for more livable, efficient, and prosperous communities. However, those who seek to realize this potential quickly discover that discovering and applying those data relevant to any particular question can be extraordinarily difficult, due to decentralized storage, heterogeneous formats, and poor documentation. In this context, we introduce Plenario, a platform designed to automating time-consuming tasks associated with the discovery, exploration, and application of open city data—and, in so doing, reduce barriers to data use for researchers, policymakers, service providers, journalists, and members of the general public. Key innovations include a geospatial data warehouse that allows data from many sources to be registered into a common spatial and temporal frame; simple and intuitive interfaces that permit rapid discovery and exploration of data subsets pertaining to a particular area and time, regardless of type and source; easy export of such data subsets for further analysis; a user-configurable data ingest framework for automated importing and periodic updating of new datasets into the data warehouse; cloud hosting for elastic scaling and rapid creation of new Plenario instances; and an open source implementation to enable community contributions. We describe here the architecture and implementation of the Plenario platform, discuss lessons learned from its use by several communities, and outline plans for future work.

  6. Concepts and Principles of Photodynamic Therapy as an Alternative Antifungal Discovery Platform

    PubMed Central

    Dai, Tianhong; Fuchs, Beth B.; Coleman, Jeffrey J.; Prates, Renato A.; Astrakas, Christos; St. Denis, Tyler G.; Ribeiro, Martha S.; Mylonakis, Eleftherios; Hamblin, Michael R.; Tegos, George P.

    2012-01-01

    Opportunistic fungal pathogens may cause superficial or serious invasive infections, especially in immunocompromised and debilitated patients. Invasive mycoses represent an exponentially growing threat for human health due to a combination of slow diagnosis and the existence of relatively few classes of available and effective antifungal drugs. Therefore systemic fungal infections result in high attributable mortality. There is an urgent need to pursue and deploy novel and effective alternative antifungal countermeasures. Photodynamic therapy (PDT) was established as a successful modality for malignancies and age-related macular degeneration but photodynamic inactivation has only recently been intensively investigated as an alternative antimicrobial discovery and development platform. The concept of photodynamic inactivation requires microbial exposure to either exogenous or endogenous photosensitizer molecules, followed by visible light energy, typically wavelengths in the red/near infrared region that cause the excitation of the photosensitizers resulting in the production of singlet oxygen and other reactive oxygen species that react with intracellular components, and consequently produce cell inactivation and death. Antifungal PDT is an area of increasing interest, as research is advancing (i) to identify the photochemical and photophysical mechanisms involved in photoinactivation; (ii) to develop potent and clinically compatible photosensitizers; (iii) to understand how photoinactivation is affected by key microbial phenotypic elements multidrug resistance and efflux, virulence and pathogenesis determinants, and formation of biofilms; (iv) to explore novel photosensitizer delivery platforms; and (v) to identify photoinactivation applications beyond the clinical setting such as environmental disinfectants. PMID:22514547

  7. NETL's Energy Data Exchange (EDX) - a coordination, collaboration, and data resource discovery platform for energy science

    NASA Astrophysics Data System (ADS)

    Rose, K.; Rowan, C.; Rager, D.; Dehlin, M.; Baker, D. V.; McIntyre, D.

    2015-12-01

    Multi-organizational research teams working jointly on projects often encounter problems with discovery, access to relevant existing resources, and data sharing due to large file sizes, inappropriate file formats, or other inefficient options that make collaboration difficult. The Energy Data eXchange (EDX) from Department of Energy's (DOE) National Energy Technology Laboratory (NETL) is an evolving online research environment designed to overcome these challenges in support of DOE's fossil energy goals while offering improved access to data driven products of fossil energy R&D such as datasets, tools, and web applications. In 2011, development of NETL's Energy Data eXchange (EDX) was initiated and offers i) a means for better preserving of NETL's research and development products for future access and re-use, ii) efficient, discoverable access to authoritative, relevant, external resources, and iii) an improved approach and tools to support secure, private collaboration and coordination between multi-organizational teams to meet DOE mission and goals. EDX presently supports fossil energy and SubTER Crosscut research activities, with an ever-growing user base. EDX is built on a heavily customized instance of the open source platform, Comprehensive Knowledge Archive Network (CKAN). EDX connects users to externally relevant data and tools through connecting to external data repositories built on different platforms and other CKAN platforms (e.g. Data.gov). EDX does not download and repost data or tools that already have an online presence. This leads to redundancy and even error. If a relevant resource already has an online instance, is hosted by another online entity, EDX will point users to that external host either using web services, inventorying URLs and other methods. EDX offers users the ability to leverage private-secure capabilities custom built into the system. The team is presently working on version 3 of EDX which will incorporate big data analytical

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

    PubMed Central

    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

  9. The future of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discovery

    PubMed Central

    Metz, Thomas O.; Zhang, Qibin; Page, Jason S.; Shen, Yufeng; Callister, Stephen J.; Jacobs, Jon M.; Smith, Richard D.

    2008-01-01

    SUMMARY The future utility of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discover will be discussed, beginning with a brief description of the evolution of metabolomics and the utilization of the three most popular analytical platforms in such studies: NMR, GC-MS, and LC-MS. Emphasis is placed on recent developments in high-efficiency LC separations, sensitive electrospray ionization approaches, and the benefits to incorporating both in LC-MS-based approaches. The advantages and disadvantages of various quantitative approaches are reviewed, followed by the current LC-MS-based tools available for candidate biomarker characterization and identification. Finally, a brief prediction on the future path of LC-MS-based methods in metabolic profiling and metabolomic studies is given. PMID:19177179

  10. A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine.

    PubMed

    Stern, Andrew M; Schurdak, Mark E; Bahar, Ivet; Berg, Jeremy M; Taylor, D Lansing

    2016-07-01

    Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point.

  11. A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine.

    PubMed

    Stern, Andrew M; Schurdak, Mark E; Bahar, Ivet; Berg, Jeremy M; Taylor, D Lansing

    2016-07-01

    Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. PMID:26962875

  12. A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

    PubMed Central

    Stern, Andrew M.; Schurdak, Mark E.; Bahar, Ivet; Berg, Jeremy M.; Taylor, D. Lansing

    2016-01-01

    Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)–driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. PMID:26962875

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

    PubMed

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

    2015-02-01

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

  14. Targeted Biomarker Discovery by High Throughput Glycosylation Profiling of Human Plasma Alpha1-Antitrypsin and Immunoglobulin A

    PubMed Central

    Ruhaak, L. Renee; Koeleman, Carolien A. M.; Uh, Hae-Won; Stam, Jord C.; van Heemst, Diana; Maier, Andrea B.; Houwing-Duistermaat, Jeanine J.; Hensbergen, Paul J.; Slagboom, P. Eline; Deelder, André M.; Wuhrer, Manfred

    2013-01-01

    Protein N-glycosylation patterns are known to show vast genetic as well as physiological and pathological variation and represent a large pool of potential biomarkers. Large-scale studies are needed for the identification and validation of biomarkers, and the analytical techniques required have recently been developed. Such methods have up to now mainly been applied to complex mixtures of glycoproteins in biofluids (e.g. plasma). Here, we analyzed N-glycosylation profiles of alpha1-antitrypsin (AAT) and immunoglobulin A (IgA) enriched fractions by 96-well microtitration plate based high-throughput immuno-affinity capturing and N-glycan analysis using multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (CGE-LIF). Human plasma samples were from the Leiden Longevity Study comprising 2415 participants of different chronological and biological ages. Glycosylation patterns of AAT enriched fractions were found to be associated with chronological (calendar) age and they differed between females and males. Moreover, several glycans in the AAT enriched fraction were associated with physiological parameters marking cardiovascular and metabolic diseases. Pronounced differences were found between males and females in the glycosylation profiles of IgA enriched fractions. Our results demonstrate that large-scale immuno-affinity capturing of proteins from human plasma using a bead-based method combined with high-throughput N-glycan analysis is a powerful tool for the discovery of glycosylation-based biomarker candidates. PMID:24039863

  15. A platform for discovery: The University of Pennsylvania Integrated Neurodegenerative Disease Biobank

    PubMed Central

    Toledo, Jon B.; Van Deerlin, Vivianna M.; Lee, Edward B.; Suh, EunRan; Baek, Young; Robinson, John L.; Xie, Sharon X.; McBride, Jennifer; Wood, Elisabeth M.; Schuck, Theresa; Irwin, David J.; Gross, Rachel G.; Hurtig, Howard; McCluskey, Leo; Elman, Lauren; Karlawish, Jason; Schellenberg, Gerard; Chen-Plotkin, Alice; Wolk, David; Grossman, Murray; Arnold, Steven E.; Shaw, Leslie M.; Lee, Virginia M.-Y.; Trojanowski, John Q.

    2014-01-01

    Neurodegenerative diseases (NDs) are defined by the accumulation of abnormal protein deposits in the central nervous system (CNS), and only neuropathological examination enables a definitive diagnosis. Brain banks and their associated scientific programs have shaped the actual knowledge of NDs, identifying and characterizing the CNS deposits that define new diseases, formulating staging schemes, and establishing correlations between neuropathological changes and clinical features. However, brain banks have evolved to accommodate the banking of biofluids as well as DNA and RNA samples. Moreover, the value of biobanks is greatly enhanced if they link all the multidimensional clinical and laboratory information of each case, which is accomplished, optimally, using systematic and standardized operating procedures, and in the framework of multidisciplinary teams with the support of a flexible and user-friendly database system that facilitates the sharing of information of all the teams in the network. We describe a biobanking system that is a platform for discovery research at the Center for Neurodegenerative Disease Research at the University of Pennsylvania. PMID:23978324

  16. [Structural Study in the Platform for Drug Discovery, Informatics, and Structural Life Science].

    PubMed

    Senda, Toshiya

    2016-01-01

    The Platform for Drug Discovery, Informatics, and Structural Life Science (PDIS), which has been launched since FY2012, is a national project in the field of structural biology. The PDIS consists of three cores - structural analysis, control, and informatics - and aims to support life science researchers who are not familiar with structural biology. The PDIS project is able to provide full-scale support for structural biology research. The support provided by the PDIS project includes protein purification with various expression systems, large scale protein crystallization, crystal structure determination, small angle scattering (SAXS), NMR, electron microscopy, bioinformatics, etc. In order to utilize these methods of support, PDIS users need to submit an application form to the one-stop service office. Submitted applications will be reviewed by three referees. It is strongly encouraged that PDIS users have sufficient discussion with researchers in the PDIS project before submitting the application. This discussion is very useful in the process of project design, particularly for beginners in structural biology. In addition to this user support, the PDIS project has conducted R&D, which includes the development of synchrotron beamlines. In the PDIS project, PF and SPring-8 have developed beamlines for micro-crystallography, high-throughput data collection, supramolecular assembly, and native single anomalous dispersion (SAD) phasing. The newly developed beamlines have been open to all users, and have accelerated structural biology research. Beamlines for SAXS have also been developed, which has dramatically increased bio-SAXS users.

  17. A Small-Molecule Screening Platform for the Discovery of Inhibitors of Undecaprenyl Diphosphate Synthase.

    PubMed

    Czarny, Tomasz L; Brown, Eric D

    2016-07-01

    The bacterial cell wall has long been a celebrated target for antibacterial drug discovery due to its critical nature in bacteria and absence in mammalian systems. At the heart of the cell wall biosynthetic pathway lies undecaprenyl phosphate (Und-P), the lipid-linked carrier upon which the bacterial cell wall is built. This study exploits recent insights into the link between late-stage wall teichoic acid inhibition and Und-P production, in Gram-positive organisms, to develop a cell-based small-molecule screening platform that enriches for inhibitors of undecaprenyl diphosphate synthase (UppS). Screening a chemical collection of 142,000 small molecules resulted in the identification of 6 new inhibitors of UppS. To date, inhibitors of UppS have generally shown off-target effects on membrane potential due to their physical-chemical characteristics. We demonstrate that MAC-0547630, one of the six inhibitors identified, exhibits selective, nanomolar inhibition against UppS without off-target effects on membrane potential. Such characteristics make it a unique chemical probe for exploring the inhibition of UppS in bacterial cell systems. PMID:27626101

  18. Quantitative tissue proteomics of esophageal squamous cell carcinoma for novel biomarker discovery

    PubMed Central

    Pawar, Harsh; Kashyap, Manoj Kumar; Sahasrabuddhe, Nandini A; Renuse, Santosh; Harsha, HC; Kumar, Praveen; Sharma, Jyoti; Kandasamy, Kumaran; Marimuthu, Arivusudar; Nair, Bipin; Rajagopalan, Sudha; Maharudraiah, Jagadeesha; Premalatha, Chennagiri Shrinivasamurthy; Kumar, Kariyanakatte Veeraiah Veerendra; Vijayakumar, M; Chaerkady, Raghothama; Prasad, Thotterthodi Subrahmanya Keshava

    2011-01-01

    Esophageal squamous cell carcinoma (ESCC) is among the top ten most frequent malignancies worldwide. In this study, our objective was to identify potential biomarkers for ESCC through a quantitative proteomic approach using the isobaric tags for relative and absolute quantitation (iTRAQ) approach. We compared the protein expression profiles of ESCC tumor tissues with the corresponding adjacent normal tissue from ten patients. LC-MS/MS analysis of strong cation exchange chromatography fractions was performed on an Accurate Mass QTOF mass spectrometer, which led to the identification of 687 proteins. In all, 257 proteins were identified as differentially expressed in ESCC as compared with normal. We found several previously known protein biomarkers to be upregulated in ESCC including thrombospondin 1 (THBS1), periostin 1 (POSTN) and heat shock 70 kDa protein 9 (HSPA9) confirming the validity of our approach. In addition, several novel proteins that had not been reported previously were identified in our screen. These novel biomarker candidates included prosaposin (PSAP), plectin 1 (PLEC1) and protein disulfide isomerase A 4 (PDIA4) that were further validated to be overexpressed by immunohistochemical labeling using tissue microarrays. The success of our study shows that this mass spectrometric strategy can be applied to cancers in general to develop a panel of candidate biomarkers, which can then be validated by other techniques. PMID:21743296

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

    PubMed Central

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

    2013-01-01

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

  20. Discovery and Validation of Biomarkers That Distinguish Mucinous and Nonmucinous Pancreatic Cysts.

    PubMed

    Park, Jisook; Yun, Hwan Sic; Lee, Kwang Hyuck; Lee, Kyu Taek; Lee, Jong Kyun; Lee, Soo-Youn

    2015-08-15

    The use of advanced imaging technologies for the identification of pancreatic cysts has become widespread. However, accurate differential diagnosis between mucinous cysts (MC) and nonmucinous cysts (NMC) consisting of pseudocysts (NMC1) and nonmucinous neoplastic cysts (NMC2) remains a challenge. Thus, it is necessary to develop novel biomarkers for the differential diagnosis of pancreatic cysts. An integrated proteomics approach yielded differentially expressed proteins in MC that were verified subsequently in 99 pancreatic cysts (21 NMC1, 41 NMC2, and 37 MC) using a method termed GeLC-stable isotope dilution-multiple reaction monitoring-mass spectrometry (GeLC-SID-MRM-MS) along with established immunoassay techniques. We identified 223 proteins by nanoscale liquid chromatography coupled to tandem mass spectrometry (nano LC/MS-MS). Nine candidate biomarkers were identified, including polymeric immunoglobulin receptor (PIGR), lipocalin 2 (LCN2), Fc fragment of IgG-binding protein (FCGBP), lithostathine-1-alpha (REG1A), afamin (AFM), chymotrypsin C (caldecrin; CTRC), amylase, alpha 2B (pancreatic; AMY2B), lectin, galactoside-binding, soluble, 3 binding protein (LGALS3BP), and chymotrypsin-like elastase family, member 3A (CELA3A), which were established as biomarker candidates for MC. In particular, we have shown that a biomarker subset, including AFM, REG1A, PIGR, and LCN2, could differentiate MC not only from NMC (including NMC1) but also from NMC2. Overall, the MS-based comprehensive proteomics approach used in this study established a novel set of candidate biomarkers that address a gap in efforts to distinguish early pancreatic lesions at a time when more successful therapeutic interventions may be possible. PMID:26122842

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

    PubMed Central

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

    2015-01-01

    Hepatocellular carcinoma (HCC)-related mortality is high because early detection modalities are hampered by inaccuracy, expense and inherent procedural risks. Thus there is an urgent need for minimally invasive, highly specific and sensitive biomarkers that enable early disease detection when therapeutic intervention remains practical. Successful therapeutic intervention is predicated on the ability to detect the cancer early. Similar unmet medical needs abound in most fields of medicine and require novel methodological approaches. Proteomic profiling of body fluids presents a sensitive diagnostic tool for early cancer detection. Here we describe such a strategy of comparative proteomics to identify potential serum-based biomarkers to distinguish high-risk chronic hepatitis C virus infected patients from HCC patients. In order to compensate for the extraordinary dynamic range in serum proteins, enrichment methods that compress the dynamic range without surrendering proteome complexity can help minimize the problems associated with many depletion methods. The enriched serum can be resolved using 2D-difference in-gel electrophoresis and the spots showing statistically significant changes selected for identification by liquid chromatography-tandem mass spectrometry. Subsequent quantitative verification and validation of these candidate biomarkers represent an obligatory and rate-limiting process that is greatly enabled by selected reaction monitoring (SRM). SRM is a tandem mass spectrometry method suitable for identification and quantitation of target peptides within complex mixtures independent on peptide-specific antibodies. Ultimately, multiplexed SRM and dynamic multiple reaction monitoring can be utilized for the simultaneous analysis of a biomarker panel derived from support vector machine learning approaches, which allows monitoring a specific disease state such as early HCC. Overall, this approach yields high probability biomarkers for clinical validation in

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

    PubMed

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

    2015-02-01

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

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

    PubMed

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

    2015-02-01

    Musculoskeletal diseases such as rheumatoid arthritis are complex multifactorial disorders that are chronic in nature and debilitating for patients. A number of drug families are available to clinicians to manage these disorders but few tests exist to target these to the most responsive patients. As a consequence, drug failure and switching to drugs with alternate modes of action is common. In parallel, a limited number of laboratory tests are available which measure biological indicators or 'biomarkers' of disease activity, autoimmune status, or joint damage. There is a growing awareness that assimilating the fields of drug selection and diagnostic tests into 'companion diagnostics' could greatly advance disease management and improve outcomes for patients. This review aims to highlight: the current applications of biomarkers in rheumatology with particular focus on companion diagnostics; developments in the fields of proteomics, genomics, microbiomics, imaging and bioinformatics and how integration of these technologies into clinical practice could support therapeutic decisions. PMID:25455156

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

    PubMed

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

    2012-11-01

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

  5. Constructing tumor progression pathways and biomarker discovery with fuzzy kernel kmeans and DNA methylation data.

    PubMed

    Liu, Zhenqiu; Guo, Zhongmin; Tan, Ming

    2008-01-01

    Constructing pathways of tumor progression and discovering the biomarkers associated with cancer is critical for understanding the molecular basis of the disease and for the establishment of novel chemotherapeutic approaches and in turn improving the clinical efficiency of the drugs. It has recently received a lot of attention from bioinformatics researchers. However, relatively few methods are available for constructing pathways. This article develops a novel entropy kernel based kernel clustering and fuzzy kernel clustering algorithms to construct the tumor progression pathways using CpG island methylation data. The methylation data which come from tumor tissues diagnosed at different stages can be used to distinguish epigenotype and phenotypes the describe the molecular events of different phases. Using kernel and fuzzy kernel kmeans, we built tumor progression trees to describe the pathways of tumor progression and find the possible biomarkers associated with cancer. Our results indicate that the proposed algorithms together with methylation profiles can predict the tumor progression stages and discover the biomarkers efficiently. Software is available upon request.

  6. Total cellular glycomics allows characterizing cells and streamlining the discovery process for cellular biomarkers

    PubMed Central

    Fujitani, Naoki; Furukawa, Jun-ichi; Araki, Kayo; Fujioka, Tsuyoshi; Takegawa, Yasuhiro; Piao, Jinhua; Nishioka, Taiki; Tamura, Tomohiro; Nikaido, Toshio; Ito, Makoto; Nakamura, Yukio; Shinohara, Yasuro

    2013-01-01

    Although many of the frequently used pluripotency biomarkers are glycoconjugates, a glycoconjugate-based exploration of novel cellular biomarkers has proven difficult due to technical difficulties. This study reports a unique approach for the systematic overview of all major classes of oligosaccharides in the cellular glycome. The proposed method enabled mass spectrometry–based structurally intensive analyses, both qualitatively and quantitatively, of cellular N- and O-linked glycans derived from glycoproteins, glycosaminoglycans, and glycosphingolipids, as well as free oligosaccharides of human embryonic stem cells (hESCs), induced pluripotent stem cells (hiPSCs), and various human cells derived from normal and carcinoma cells. Cellular total glycomes were found to be highly cell specific, demonstrating their utility as unique cellular descriptors. Structures of glycans of all classes specifically observed in hESCs and hiPSCs tended to be immature in general, suggesting the presence of stem cell–specific glycosylation spectra. The current analysis revealed the high similarity of the total cellular glycome between hESCs and hiPSCs, although it was suggested that hESCs are more homogeneous than hiPSCs from a glycomic standpoint. Notably, this study enabled a priori identification of known pluripotency biomarkers such as SSEA-3, -4, and -5 and Tra-1–60/81, as well as a panel of glycans specifically expressed by hESCs and hiPSCs. PMID:23345451

  7. Mass spectrometry-based proteomics: the road to lung cancer biomarker discovery.

    PubMed

    Indovina, Paola; Marcelli, Eleonora; Pentimalli, Francesca; Tanganelli, Piero; Tarro, Giulio; Giordano, Antonio

    2013-01-01

    Lung cancer is the leading cause of cancer death in men and women in Western nations, and is among the deadliest cancers with a 5-year survival rate of 15%. The high mortality caused by lung cancer is attributable to a late-stage diagnosis and the lack of effective treatments. So, it is crucial to identify new biomarkers that could function not only to detect lung cancer at an early stage but also to shed light on the molecular mechanisms that underlie cancer development and serve as the basis for the development of novel therapeutic strategies. Considering that DNA-based biomarkers for lung cancer showed inadequate sensitivity, specificity, and reproducibility, proteomics could represent a better tool for the identification of useful biomarkers and therapeutic targets for this cancer type. Among the proteomics technologies, the most powerful tool is mass spectrometry. In this review, we describe studies that use mass spectrometry-based proteomics technologies to analyze tumor proteins and peptides, which might represent new diagnostic, prognostic, and predictive markers for lung cancer. We focus in particular on those findings that hold promise to impact significantly on the clinical management of this disease.

  8. Urinary candidate biomarker discovery in a rat unilateral ureteral obstruction model

    PubMed Central

    Yuan, Yuan; Zhang, Fanshuang; Wu, Jianqiang; Shao, Chen; Gao, Youhe

    2015-01-01

    Urine has the potential to become a better source of biomarkers. Urinary proteins are affected by many factors; therefore, differentiating between the variables associated with any particular pathophysiological condition in clinical samples is challenging. To circumvent these problems, simpler systems, such as animal models, should be used to establish a direct relationship between disease progression and urine changes. In this study, a unilateral ureteral obstruction (UUO) model was used to observe tubular injury and the eventual development of renal fibrosis, as well as to identify differential urinary proteins in this process. Urine samples were collected from the residuary ureter linked to the kidney at 1 and 3 weeks after UUO. Five hundred proteins were identified and quantified by LC-MS/MS, out of which 7 and 19 significantly changed in the UUO 1- and 3-week groups, respectively, compared with the sham-operation group. Validation by western blot showed increased levels of Alpha-actinin-1 and Moesin in the UUO 1-week group, indicating that they may serve as candidate biomarkers of renal tubular injury, and significantly increased levels of Vimentin, Annexin A1 and Clusterin in the UUO 3-week group, indicating that they may serve as candidate biomarkers of interstitial fibrosis. PMID:25791774

  9. Evaluation of database-derived pathway development for enabling biomarker discovery for hepatotoxicity.

    PubMed

    Hebels, Dennie G A; Jetten, Marlon J A; Aerts, Hugo J W; Herwig, Ralf; Theunissen, Daniël H J; Gaj, Stan; van Delft, Joost H; Kleinjans, Jos C S

    2014-01-01

    Current testing models for predicting drug-induced liver injury are inadequate, as they basically under-report human health risks. We present here an approach towards developing pathways based on hepatotoxicity-associated gene groups derived from two types of publicly accessible hepatotoxicity databases, in order to develop drug-induced liver injury biomarker profiles. One human liver 'omics-based and four text-mining-based databases were explored for hepatotoxicity-associated gene lists. Over-representation analysis of these gene lists with a hepatotoxicant-exposed primary human hepatocytes data set showed that human liver 'omics gene lists performed better than text-mining gene lists and the results of the latter differed strongly between databases. However, both types of databases contained gene lists demonstrating biomarker potential. Visualizing those in pathway format may aid in interpreting the biomolecular background. We conclude that exploiting existing and openly accessible databases in a dedicated manner seems promising in providing venues for translational research in toxicology and biomarker development.

  10. Hi-Fi SELEX: A High-Fidelity Digital-PCR Based Therapeutic Aptamer Discovery Platform.

    PubMed

    Ouellet, Eric; Foley, Jonathan H; Conway, Edward M; Haynes, Charles

    2015-08-01

    Current technologies for aptamer discovery typically leverage the systematic evolution of ligands by exponential enrichment (SELEX) concept by recursively panning semi-combinatorial ssDNA or RNA libraries against a molecular target. The expectation is that this iterative selection process will be sufficiently stringent to identify a candidate pool of specific high-affinity aptamers. However, failure of this process to yield promising aptamers is common, due in part to (i) limitations in library designs, (ii) retention of non-specific aptamers during screening rounds, (iii) excessive accumulation of amplification artifacts, and (iv) the use of screening criteria (binding affinity) that does not reflect therapeutic activity. We report a new selection platform, High-Fidelity (Hi-Fi) SELEX, that introduces fixed-region blocking elements to safeguard the functional diversity of the library. The chemistry of the target-display surface and the composition of the equilibration solvent are engineered to strongly inhibit non-specific retention of aptamers. Partition efficiencies approaching 10(6) are thereby realized. Retained members are amplified in Hi-Fi SELEX by digital PCR in a manner that ensures both elimination of amplification artifacts and stoichiometric conversion of amplicons into the single-stranded library required for the next selection round. Improvements to aptamer selections are first demonstrated using human α-thrombin as the target. Three clinical targets (human factors IXa, X, and D) are then subjected to Hi-Fi SELEX. For each, rapid enrichment of ssDNA aptamers offering an order-nM mean equilibrium dissociation constant (Kd) is achieved within three selection rounds, as quantified by a new label-free qPCR assay reported here. Therapeutic candidates against factor D are identified.

  11. Creating a Discovery Platform for Confined-Space Chemistry and Materials: Metal-Organic Frameworks.

    SciTech Connect

    Allendorf, Mark D.; Greathouse, Jeffery A.; Simmons, Blake

    2008-09-01

    Metal organic frameworks (MOF) are a recently discovered class of nanoporous, defect-free crystalline materials that enable rational design and exploration of porous materials at the molecular level. MOFs have tunable monolithic pore sizes and cavity environments due to their crystalline nature, yielding properties exceeding those of most other porous materials. These include: the lowest known density (91% free space); highest surface area; tunable photoluminescence; selective molecular adsorption; and methane sorption rivaling gas cylinders. These properties are achieved by coupling inorganic metal complexes such as ZnO4 with tunable organic ligands that serve as struts, allowing facile manipulation of pore size and surface area through reactant selection. MOFs thus provide a discovery platform for generating both new understanding of chemistry in confined spaces and novel sensors and devices based on their unique properties. At the outset of this project in FY06, virtually nothing was known about how to couple MOFs to substrates and the science of MOF properties and how to tune them was in its infancy. An integrated approach was needed to establish the required knowledge base for nanoscale design and develop methodologies integrate MOFs with other materials. This report summarizes the key accomplishments of this project, which include creation of a new class of radiation detection materials based on MOFs, luminescent MOFs for chemical detection, use of MOFs as templates to create nanoparticles of hydrogen storage materials, MOF coatings for stress-based chemical detection using microcantilevers, and "flexible" force fields that account for structural changes in MOFs that occur upon molecular adsorption/desorption. Eight journal articles, twenty presentations at scientific conferences, and two patent applications resulted from the work. The project created a basis for continuing development of MOFs for many Sandia applications and succeeded in securing $2.75 M in

  12. Hi-Fi SELEX: A High-Fidelity Digital-PCR Based Therapeutic Aptamer Discovery Platform.

    PubMed

    Ouellet, Eric; Foley, Jonathan H; Conway, Edward M; Haynes, Charles

    2015-08-01

    Current technologies for aptamer discovery typically leverage the systematic evolution of ligands by exponential enrichment (SELEX) concept by recursively panning semi-combinatorial ssDNA or RNA libraries against a molecular target. The expectation is that this iterative selection process will be sufficiently stringent to identify a candidate pool of specific high-affinity aptamers. However, failure of this process to yield promising aptamers is common, due in part to (i) limitations in library designs, (ii) retention of non-specific aptamers during screening rounds, (iii) excessive accumulation of amplification artifacts, and (iv) the use of screening criteria (binding affinity) that does not reflect therapeutic activity. We report a new selection platform, High-Fidelity (Hi-Fi) SELEX, that introduces fixed-region blocking elements to safeguard the functional diversity of the library. The chemistry of the target-display surface and the composition of the equilibration solvent are engineered to strongly inhibit non-specific retention of aptamers. Partition efficiencies approaching 10(6) are thereby realized. Retained members are amplified in Hi-Fi SELEX by digital PCR in a manner that ensures both elimination of amplification artifacts and stoichiometric conversion of amplicons into the single-stranded library required for the next selection round. Improvements to aptamer selections are first demonstrated using human α-thrombin as the target. Three clinical targets (human factors IXa, X, and D) are then subjected to Hi-Fi SELEX. For each, rapid enrichment of ssDNA aptamers offering an order-nM mean equilibrium dissociation constant (Kd) is achieved within three selection rounds, as quantified by a new label-free qPCR assay reported here. Therapeutic candidates against factor D are identified. PMID:25727321

  13. Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC-MS for biomarker discovery.

    PubMed

    Christin, Christin; Bischoff, Rainer; Horvatovich, Péter

    2011-01-30

    Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments. Special emphasis is devoted to quality control methods, performance assessment of complete workflows and algorithms of individual modules. Finally, the review discusses the current state and trends in high throughput data processing and analysis solutions for users with little bioinformatics knowledge.

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

    PubMed

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

    2016-07-01

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

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

    PubMed

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

    2013-02-01

    Sample preparation is the rate-limiting step in glycan analysis workflows. Among all of the steps, enzymatic digestions, which are usually performed overnight, are the most time-consuming. In the current study, we report an economical and fast preparation of N-glycans from serum, including microwave-assisted enzymatic digestion in the absence of denaturing chemicals and solvents during the release. To this end, we used a household microwave oven to accelerate both pronase and endo-β-N-acetylglucosaminidase H (Endo H) digestions. Purification was then performed using self-made SP20SS and carbon tips. We were able to prepare samples in 55 min instead of 21 h. Finally, the method was applied in the context of oncological biomarker discovery exemplarily to ovarian and colon cancer. We observed a significant downregulation of sialylated hybrid structures in ovarian cancer samples using capillary electrophoresis-laser-induced fluorescence (CE-LIF). Furthermore, sepsis, a systemic inflammatory response syndrome, was also included in the study to understand whether the changes observed in ovarian cancer patients were due to the cancer itself or to the inflammation that usually accompanies its development. Because sialylated hybrid structures were upregulated in sepsis samples, the downregulation of these structures in ovarian cancer is specific to the cancer itself and, therefore, could be used as a biomarker. PMID:23088875

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

    PubMed

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

    2013-02-01

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

  17. Discovery of human urinary biomarkers of aronia-citrus juice intake by HPLC-q-TOF-based metabolomic approach.

    PubMed

    Llorach, Rafael; Medina, Sonia; García-Viguera, Cristina; Zafrilla, Pilar; Abellán, José; Jauregui, Olga; Tomás-Barberán, Francisco A; Gil-Izquierdo, Angel; Andrés-Lacueva, Cristina

    2014-06-01

    Metabolomics has emerged in the field of food and nutrition sciences as a powerful tool for doing profiling approaches. In this context, HPLC-q-TOF-based metabolomics approach was applied to unveil changes in the urinary metabolome in human subjects (n = 51, 23 men and 28 women) after regular aronia-citrus juice (AC-juice) intake (250 mL/day) during 16 weeks compared to individuals given a placebo beverage. Samples were analyzed by HPLC-q-TOF followed by multivariate data analysis (orthogonal signal filtering-partial least square discriminant analysis) that discriminated relevant mass features related to AC-juice intake. The results showed that biomarkers of AC-juice intake including metabolites coming from metabolism of food components as proline betaine, ferulic acid, and two unknown mercapturate derivatives were identified. Discovery of new biomarkers of food intake will help in the building up of the food metabolome and facilitate future insights into the mechanisms of action of dietary components in population health.

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

    SciTech Connect

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

    2008-09-01

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

  19. Cancer serum biomarkers based on aberrant post-translational modifications of glycoproteins: Clinical value and discovery strategies.

    PubMed

    Silva, M Luísa S

    2015-12-01

    Due to the increase in life expectancy in the last decades, as well as changes in lifestyle, cancer has become one of the most common diseases both in developed and developing countries. Early detection remains the most promising approach to improve long-term survival of cancer patients and this may be achieved by efficient screening of biomarkers in biological fluids. Great efforts have been made to identify specific alterations during oncogenesis. Changes at the cellular glycosylation profiles are among such alterations. The "glycosylation machinery" of cells is affected by malignant transformation due to the altered expression of glycogens, leading to changes in glycan biosynthesis and diversity. Alterations in the post-translational modifications of proteins that occur in cancer result in the expression of antigenically distinct glycoproteins. Therefore, these aberrant and cancer-specific glycoproteins and the autoantibodies that are produced in response to their presence constitute targets for cancer biomarkers' search. Different strategies have been implemented for the discovery of cancer glycobiomarkers and are herein reviewed, along with their potentialities and limitations. Practical issues related with serum analysis are also addressed, as well as the challenges that this area faces in the near future.

  20. Integrated use of biomarkers in the mussel Mytilus galloprovincialis for assessing off-shore gas platforms in the Adriatic Sea: results of a two-year biomonitoring program.

    PubMed

    Gomiero, Alessio; Da Ros, Luisa; Nasci, Cristina; Meneghetti, Francesca; Spagnolo, Alessandra; Fabi, Gianna

    2011-11-01

    Despite a large number of gas platforms existing in the Adriatic Sea, which is a semi-enclosed basin characterized by a slow turnover rate and increasing industrial as well as other anthropogenic activities, the effects of these structures on the aquatic ecosystem require further investigation. Since 1998, multidisciplinary studies have been performed by CNR-ISMAR to comply with legislation and to support the development of protocols for the monitoring of offshore activities in the Adriatic Sea. The present study was developed to implement a biomonitoring plan to assess the ecotoxicological effects of the extraction activities of an off-shore gas platform. Biomarkers were evaluated in mussels collected from the platform in relation to physiological stress, DNA damage, cellular damage, oxidative stress and exposure effects. Organic contaminants and trace element bioaccumulation were also assessed in the soft body of the mussels to correlate bioaccumulation of pollutants with biomarker responses. The results indicate an absence of platform-related environmental stress.

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

    PubMed

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

    2015-02-01

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

  2. Biomarker Discovery for Early Detection of Hepatocellular Carcinoma in Hepatitis C–infected Patients*

    PubMed Central

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

    2013-01-01

    Chronic hepatic disease damages the liver, and the resulting wound-healing process leads to liver fibrosis and the subsequent development of cirrhosis. The leading cause of hepatic fibrosis and cirrhosis is infection with hepatitis C virus (HCV), and of the patients with HCV-induced cirrhosis, 2% to 5% develop hepatocellular carcinoma (HCC), with a survival rate of 7%. HCC is one of the leading causes of cancer-related death worldwide, and the poor survival rate is largely due to late-stage diagnosis, which makes successful intervention difficult, if not impossible. The lack of sensitive and specific diagnostic tools and the urgent need for early-stage diagnosis prompted us to discover new candidate biomarkers for HCV and HCC. We used aptamer-based fractionation technology to reduce serum complexity, differentially labeled samples (six HCV and six HCC) with fluorescent dyes, and resolved proteins in pairwise two-dimensional difference gel electrophoresis. DeCyder software was used to identify differentially expressed proteins and spots picked, and MALDI-MS/MS was used to determine that ApoA1 was down-regulated by 22% (p < 0.004) in HCC relative to HCV. Differential expression quantified via two-dimensional difference gel electrophoresis was confirmed by means of 18O/16O stable isotope differential labeling with LC-MS/MS zoom scans. Technically independent confirmation was demonstrated by triple quadrupole LC-MS/MS selected reaction monitoring (SRM) assays with three peptides specific to human ApoA1 (DLATVYVDVLK, WQEEMELYR, and VSFLSALEEYTK) using 18O/16O-labeled samples and further verified with AQUA peptides as internal standards for quantification. In 50 patient samples (24 HCV and 26 HCC), all three SRM assays yielded highly similar differential expression of ApoA1 in HCC and HCV patients. These results validated the SRM assays, which were independently confirmed by Western blotting. Thus, ApoA1 is a candidate member of an SRM biomarker panel for early diagnosis

  3. Systematic ratio normalization of gas chromatography signals for biological sample discrimination and biomarker discovery.

    PubMed

    Lehallier, Benoist; Ratel, Jérémy; Hanafi, Mohamed; Engel, Erwan

    2012-07-01

    The present paper introduces a new gas chromatography data processing procedure dubbed systematic ratio normalization (SRN) enabling to improve both sample set discrimination and biomarker identification. SRN consists in (1) calculating, for each sample, all the log-ratios between abundances of chromatography-analyzed compounds, then (2) selecting the log-ratio(s) that best maximize the discrimination between sample-sets. The relevance of SRN was evaluated on two data sets acquired through gas chromatography-mass spectrometry as part of separate studies designed (i) to discriminate source-origins between vegetable oils analyzed via an analytical system exposed to instrument drift (data set 1) and (ii) to discriminate animal feed between meat samples aged for different durations (data set 2). Applying SRN to raw data made it possible to obtain robust discrimination models for the two data sets by enhancing the contribution to the data variance of the factor-of-interest while stabilizing the contribution of the disturbance factor. The most discriminant log-ratios were shown to employ the most relevant biomarkers presenting relative independence of the factor-of-interest as well as co-behavior of the disturbance effects potentially biasing the discrimination, such as instrument drift or sample biochemical changes. SRN can be run a posteriori on any data set, and might be generalizable to most of separating methods. PMID:22704370

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

    PubMed Central

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

    2015-01-01

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

  5. Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications.

    PubMed

    Ruijter, Jan M; Pfaffl, Michael W; Zhao, Sheng; Spiess, Andrej N; Boggy, Gregory; Blom, Jochen; Rutledge, Robert G; Sisti, Davide; Lievens, Antoon; De Preter, Katleen; Derveaux, Stefaan; Hellemans, Jan; Vandesompele, Jo

    2013-01-01

    RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the

  6. Evaluation of qPCR curve analysis methods for reliable biomarker discovery: bias, resolution, precision, and implications.

    PubMed

    Ruijter, Jan M; Pfaffl, Michael W; Zhao, Sheng; Spiess, Andrej N; Boggy, Gregory; Blom, Jochen; Rutledge, Robert G; Sisti, Davide; Lievens, Antoon; De Preter, Katleen; Derveaux, Stefaan; Hellemans, Jan; Vandesompele, Jo

    2013-01-01

    RNA transcripts such as mRNA or microRNA are frequently used as biomarkers to determine disease state or response to therapy. Reverse transcription (RT) in combination with quantitative PCR (qPCR) has become the method of choice to quantify small amounts of such RNA molecules. In parallel with the democratization of RT-qPCR and its increasing use in biomedical research or biomarker discovery, we witnessed a growth in the number of gene expression data analysis methods. Most of these methods are based on the principle that the position of the amplification curve with respect to the cycle-axis is a measure for the initial target quantity: the later the curve, the lower the target quantity. However, most methods differ in the mathematical algorithms used to determine this position, as well as in the way the efficiency of the PCR reaction (the fold increase of product per cycle) is determined and applied in the calculations. Moreover, there is dispute about whether the PCR efficiency is constant or continuously decreasing. Together this has lead to the development of different methods to analyze amplification curves. In published comparisons of these methods, available algorithms were typically applied in a restricted or outdated way, which does not do them justice. Therefore, we aimed at development of a framework for robust and unbiased assessment of curve analysis performance whereby various publicly available curve analysis methods were thoroughly compared using a previously published large clinical data set (Vermeulen et al., 2009) [11]. The original developers of these methods applied their algorithms and are co-author on this study. We assessed the curve analysis methods' impact on transcriptional biomarker identification in terms of expression level, statistical significance, and patient-classification accuracy. The concentration series per gene, together with data sets from unpublished technical performance experiments, were analyzed in order to assess the

  7. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study

    PubMed Central

    Nishida, Maki; Harris, Michael; Rao, Shruti; Cheema, Amrita K.; Gill, Kirandeep; Seol, Haeri; Morgenroth, Lauren P.; Henricson, Erik; McDonald, Craig; Mah, Jean K.; Clemens, Paula R.; Hoffman, Eric P.; Hathout, Yetrib; Madhavan, Subha

    2016-01-01

    Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future. PMID:27082433

  8. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.

    PubMed

    Boca, Simina M; Nishida, Maki; Harris, Michael; Rao, Shruti; Cheema, Amrita K; Gill, Kirandeep; Seol, Haeri; Morgenroth, Lauren P; Henricson, Erik; McDonald, Craig; Mah, Jean K; Clemens, Paula R; Hoffman, Eric P; Hathout, Yetrib; Madhavan, Subha

    2016-01-01

    Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.

  9. Discovery of Metabolic Biomarkers for Duchenne Muscular Dystrophy within a Natural History Study.

    PubMed

    Boca, Simina M; Nishida, Maki; Harris, Michael; Rao, Shruti; Cheema, Amrita K; Gill, Kirandeep; Seol, Haeri; Morgenroth, Lauren P; Henricson, Erik; McDonald, Craig; Mah, Jean K; Clemens, Paula R; Hoffman, Eric P; Hathout, Yetrib; Madhavan, Subha

    2016-01-01

    Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future. PMID:27082433

  10. Nanostructured Aptamer-Functionalized Black Phosphorus Sensing Platform for Label-Free Detection of Myoglobin, a Cardiovascular Disease Biomarker.

    PubMed

    Kumar, Vinod; Brent, Jack R; Shorie, Munish; Kaur, Harmanjit; Chadha, Gaganpreet; Thomas, Andrew G; Lewis, Edward A; Rooney, Aidan P; Nguyen, Lan; Zhong, Xiang Li; Burke, M Grace; Haigh, Sarah J; Walton, Alex; McNaughter, Paul D; Tedstone, Aleksander A; Savjani, Nicky; Muryn, Christopher A; O'Brien, Paul; Ganguli, Ashok K; Lewis, David J; Sabherwal, Priyanka

    2016-09-01

    We report the electrochemical detection of the redox active cardiac biomarker myoglobin (Mb) using aptamer-functionalized black phosphorus nanostructured electrodes by measuring direct electron transfer. The as-synthesized few-layer black phosphorus nanosheets have been functionalized with poly-l-lysine (PLL) to facilitate binding with generated anti-Mb DNA aptamers on nanostructured electrodes. This aptasensor platform has a record-low detection limit (∼0.524 pg mL(-1)) and sensitivity (36 μA pg(-1) mL cm(-2)) toward Mb with a dynamic response range from 1 pg mL(-1) to 16 μg mL(-1) for Mb in serum samples. This strategy opens up avenues to bedside technologies for multiplexed diagnosis of cardiovascular diseases in complex human samples.

  11. Nanostructured Aptamer-Functionalized Black Phosphorus Sensing Platform for Label-Free Detection of Myoglobin, a Cardiovascular Disease Biomarker.

    PubMed

    Kumar, Vinod; Brent, Jack R; Shorie, Munish; Kaur, Harmanjit; Chadha, Gaganpreet; Thomas, Andrew G; Lewis, Edward A; Rooney, Aidan P; Nguyen, Lan; Zhong, Xiang Li; Burke, M Grace; Haigh, Sarah J; Walton, Alex; McNaughter, Paul D; Tedstone, Aleksander A; Savjani, Nicky; Muryn, Christopher A; O'Brien, Paul; Ganguli, Ashok K; Lewis, David J; Sabherwal, Priyanka

    2016-09-01

    We report the electrochemical detection of the redox active cardiac biomarker myoglobin (Mb) using aptamer-functionalized black phosphorus nanostructured electrodes by measuring direct electron transfer. The as-synthesized few-layer black phosphorus nanosheets have been functionalized with poly-l-lysine (PLL) to facilitate binding with generated anti-Mb DNA aptamers on nanostructured electrodes. This aptasensor platform has a record-low detection limit (∼0.524 pg mL(-1)) and sensitivity (36 μA pg(-1) mL cm(-2)) toward Mb with a dynamic response range from 1 pg mL(-1) to 16 μg mL(-1) for Mb in serum samples. This strategy opens up avenues to bedside technologies for multiplexed diagnosis of cardiovascular diseases in complex human samples. PMID:27508925

  12. Enhanced Biosensor Platforms for Detecting the Atherosclerotic Biomarker VCAM1 Based on Bioconjugation with Uniformly Oriented VCAM1-Targeting Nanobodies

    PubMed Central

    Ta, Duy Tien; Guedens, Wanda; Vranken, Tom; Vanschoenbeek, Katrijn; Steen Redeker, Erik; Michiels, Luc; Adriaensens, Peter

    2016-01-01

    Surface bioconjugation of biomolecules has gained enormous attention for developing advanced biomaterials including biosensors. While conventional immobilization (by physisorption or covalent couplings using the functional groups of the endogenous amino acids) usually results in surfaces with low activity, reproducibility and reusability, the application of methods that allow for a covalent and uniformly oriented coupling can circumvent these limitations. In this study, the nanobody targeting Vascular Cell Adhesion Molecule-1 (NbVCAM1), an atherosclerotic biomarker, is engineered with a C-terminal alkyne function via Expressed Protein Ligation (EPL). Conjugation of this nanobody to azidified silicon wafers and Biacore™ C1 sensor chips is achieved via Copper(I)-catalyzed azide-alkyne cycloaddition (CuAAC) “click” chemistry to detect VCAM1 binding via ellipsometry and surface plasmon resonance (SPR), respectively. The resulting surfaces, covered with uniformly oriented nanobodies, clearly show an increased antigen binding affinity, sensitivity, detection limit, quantitation limit and reusability as compared to surfaces prepared by random conjugation. These findings demonstrate the added value of a combined EPL and CuAAC approach as it results in strong control over the surface orientation of the nanobodies and an improved detecting power of their targets—a must for the development of advanced miniaturized, multi-biomarker biosensor platforms. PMID:27399790

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

    PubMed

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

    2016-01-01

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

  14. Discovery of Biomarkers for Systemic Lupus Erythematosus Using a Library of Synthetic Autoantigen Surrogates

    PubMed Central

    Quan, Jiexia; Lakhanpal, Akshai; Reddy, M.Muralidhar; Zaman, Sayed; Li, Quan-Zhen; German, Dwight C.; Olsen, Nancy J.; Kodadek, Thomas; Karp, David R.

    2014-01-01

    Antibodies to a wide range of self-antigens, including those directed against nucleic acids or nucleic acid-binding proteins are the essential biomarkers for diseases such as systemic lupus erythematosus (SLE). Highly complex libraries of nonamers consisting of N-substituted glycines (peptoids) were screened for compounds that bound IgG from patients with SLE and earlier, incomplete autoimmune syndromes. Peptoids were identified that could identify subjects with SLE and related syndromes with a high sensitivity (70%) and specificity (97.5%). Immobilized peptoids were used to isolate IgG from both healthy subjects and SLE patients that reacted with known RNA-binding proteins. In the case of SLE patients, the peptoid-purified IgG reacted with several autoantigens, suggesting that the peptoids are capable of interacting with multiple, structurally similar molecules. These results show that the measurement of IgG binding to peptoids can identify subjects with high levels of pathogenic autoantibodies. PMID:24269750

  15. Metabolomic Discovery of Novel Urinary Galabiosylceramide Analogs as Fabry Disease Biomarkers

    NASA Astrophysics Data System (ADS)

    Boutin, Michel; Auray-Blais, Christiane

    2015-03-01

    Fabry disease is an X-linked, complex, multisystemic lysosomal storage disorder presenting marked phenotypic and genotypic variability among affected male and female patients. Glycosphingolipids, mainly globotriaosylceramide (Gb3) isoforms/analogs, globotriaosylsphingosine (lyso-Gb3) and analogs, as well as galabiosylceramide (Ga2) isoforms/analogs accumulate in the vascular endothelium, nerves, cardiomyocytes, renal glomerular and tubular epithelial cells, and biological fluids. The search for biomarkers reflecting disease severity and progression is still on-going. A metabolomic study using quadrupole time-of-flight mass spectrometry has revealed 22 galabiosylceramide isoforms/analogs in urine of untreated Fabry patients classified in seven groups according to their chemical structure: (1) Saturated fatty acid; (2) one extra double bond; (3) two extra double bonds; (4) hydroxylated saturated fatty acid; (5) hydroxylated fatty acid and one extra double bond; (6) hydrated sphingosine and hydroxylated fatty acid; (7) methylated amide linkage. Relative quantification of both Ga2 and Gb3 isoforms/analogs was performed. All these biomarkers are significantly more abundant in urine samples from untreated Fabry males compared with healthy male controls. A significant amount of Ga2 isoforms/analogs, accounting for 18% of all glycosphingolipids analyzed (Ga2 + Gb3 and respective isoforms/analogs), were present in urine of Fabry patients. Gb3 isoforms containing saturated fatty acids are the most abundant (60.9%) compared with 26.3% for Ga2. A comparison between Ga2 isoforms/analogs and their Gb3 counterparts also showed that the proportion of analogs with hydroxylated fatty acids is significantly greater for Ga2 (35.8%) compared with Gb3 (1.9%). These results suggest different biological pathways involved in the synthesis and/or degradation of Gb3 and Ga2 metabolites.

  16. Mass spectrometry-based metabolomics for the discovery of biomarkers of fruit and vegetable intake: citrus fruit as a case study.

    PubMed

    Pujos-Guillot, Estelle; Hubert, Jane; Martin, Jean-François; Lyan, Bernard; Quintana, Mercedes; Claude, Sylvain; Chabanas, Bruno; Rothwell, Joseph A; Bennetau-Pelissero, Catherine; Scalbert, Augustin; Comte, Blandine; Hercberg, Serge; Morand, Christine; Galan, Pilar; Manach, Claudine

    2013-04-01

    Elucidation of the relationships between genotype, diet, and health requires accurate dietary assessment. In intervention and epidemiological studies, dietary assessment usually relies on questionnaires, which are susceptible to recall bias. An alternative approach is to quantify biomarkers of intake in biofluids, but few such markers have been validated so far. Here we describe the use of metabolomics for the discovery of nutritional biomarkers, using citrus fruits as a case study. Three study designs were compared. Urinary metabolomes were profiled for volunteers that had (a) consumed an acute dose of orange or grapefruit juice, (b) consumed orange juice regularly for one month, and (c) reported high or low consumption of citrus products for a large cohort study. Some signals were found to reflect citrus consumption in all three studies. Proline betaine and flavanone glucuronides were identified as known biomarkers, but various other biomarkers were revealed. Further, many signals that increased after citrus intake in the acute study were not sensitive enough to discriminate high and low citrus consumers in the cohort study. We propose that urine profiling of cohort subjects stratified by consumption is an effective strategy for discovery of sensitive biomarkers of consumption for a wide range of foods.

  17. A multiplexable, microfluidic platform for the rapid quantitation of a biomarker panel for early ovarian cancer detection at the point-of-care

    PubMed Central

    Shadfan, Basil H.; Simmons, Archana R.; Simmons, Glennon W.; Ho, Andy; Wong, Jorge; Lu, Karen H.; Bast, Robert C.; McDevitt, John T.

    2015-01-01

    Point-of-care (POC) diagnostic platforms have the potential to enable low-cost, large-scale screening. As no single biomarker is shed by all ovarian cancers, multiplexed biomarker panels promise improved sensitivity and specificity to address the unmet need for early detection of ovarian cancer. We have configured the programmable bio-nano-chip (p-BNC) - a multiplexable, microfluidic, modular platform - to quantify a novel multimarker panel comprising CA125, HE4, MMP-7 and CA72-4. The p-BNC is a bead-based immunoanalyzer system with a credit-card-sized footprint that integrates automated sample metering, bubble and debris removal, reagent storage and waste disposal, permitting POC analysis. Multiplexed p-BNC immunoassays demonstrated high specificity, low cross-reactivity, low limits of detection suitable for early detection, and a short analysis time of 43 minutes. Day-to-day variability, a critical factor for longitudinally monitoring biomarkers, ranged between 5.4–10.5%, well below the biological variation for all four markers. Biomarker concentrations for 31 late-stage sera correlated well (R2 = 0.71 to 0.93 for various biomarkers) with values obtained on the Luminex® platform. In a 31 patient cohort encompassing early- and late-stage ovarian cancers along with benign and healthy controls, the multiplexed p-BNC panel was able to distinguish cases from controls with 68.7% sensitivity at 80% specificity. Utility for longitudinal biomarker monitoring was demonstrated with pre-diagnostic sera from 2 cases and 4 controls. Taken together, the p-BNC shows strong promise as a diagnostic tool for large-scale screening that takes advantage of faster results and lower costs while leveraging possible improvement in sensitivity and specificity from biomarker panels. PMID:25388014

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

    SciTech Connect

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

    2006-11-01

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

  19. Differential expression profiling of serum proteins and metabolites for biomarker discovery

    NASA Astrophysics Data System (ADS)

    Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.

    2004-11-01

    A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

  20. Low molecular weight protein enrichment on mesoporous silica thin films for biomarker discovery.

    PubMed

    Fan, Jia; Gallagher, James W; Wu, Hung-Jen; Landry, Matthew G; Sakamoto, Jason; Ferrari, Mauro; Hu, Ye

    2012-04-17

    The identification of circulating biomarkers holds great potential for non invasive approaches in early diagnosis and prognosis, as well as for the monitoring of therapeutic efficiency.(1-3) The circulating low molecular weight proteome (LMWP) composed of small proteins shed from tissues and cells or peptide fragments derived from the proteolytic degradation of larger proteins, has been associated with the pathological condition in patients and likely reflects the state of disease.(4,5) Despite these potential clinical applications, the use of Mass Spectrometry (MS) to profile the LMWP from biological fluids has proven to be very challenging due to the large dynamic range of protein and peptide concentrations in serum.(6) Without sample pre-treatment, some of the more highly abundant proteins obscure the detection of low-abundance species in serum/plasma. Current proteomic-based approaches, such as two-dimensional polyacrylamide gel-electrophoresis (2D-PAGE) and shotgun proteomics methods are labor-intensive, low throughput and offer limited suitability for clinical applications.(7-9) Therefore, a more effective strategy is needed to isolate LMWP from blood and allow the high throughput screening of clinical samples. Here, we present a fast, efficient and reliable multi-fractionation system based on mesoporous silica chips to specifically target and enrich LMWP.(10,11) Mesoporous silica (MPS) thin films with tunable features at the nanoscale were fabricated using the triblock copolymer template pathway. Using different polymer templates and polymer concentrations in the precursor solution, various pore size distributions, pore structures, connectivity and surface properties were determined and applied for selective recovery of low mass proteins. The selective parsing of the enriched peptides into different subclasses according to their physicochemical properties will enhance the efficiency of recovery and detection of low abundance species. In combination with mass

  1. A lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform for identification of multiple liver cancer biomarkers in human plasma.

    PubMed

    Ahn, Yeong Hee; Shin, Park Min; Oh, Na Ree; Park, Gun Wook; Kim, Hoguen; Yoo, Jong Shin

    2012-09-18

    Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression.

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

    PubMed Central

    2015-01-01

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

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

    PubMed

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

    2014-10-01

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

  4. Biomarker discovery and gene expression responses in Lycopersicon esculentum root exposed to lead.

    PubMed

    Hou, Jing; Bai, Lili; Xie, Yujia; Liu, Xinhui; Cui, Baoshan

    2015-12-15

    Gene expression analysis has shown particular promise for the identification of molecular biomarkers that can be used for further evaluation of potential toxicity of chemicals present in agricultural soil. In the study, we focused on the development of molecular markers to detect Pb toxicity in agricultural soil. Using the results obtained from microarray analysis, twelve Pb-responsive genes were selected and tested in different Pb concentrations to examine their concentration-response characteristics using real-time quantitative polymerase chain reaction (RT-qPCR). All the Pb treatments set in our study could generally induce the differential expression of the 12 genes, while the lowest observable adverse effect concentration (LOAEC) of Pb for seed germination, root elongation, biomass and structural modification derived from 1,297, 177, 177, and 1,297 mg Pb/kg soil, respectively, suggesting that the transcriptional approach was more sensitive than the traditional end points of death, growth, and morphology for the evaluation of Pb toxicity. The relative expression of glycoalkaloid metabolism 1 (P=-0.790), ethylene-responsive transcription factor ERF017 (P=-0.686) and CASP-like protein 4C2 (P=-0.652) demonstrates a dose-dependent response with Pb content in roots, implying that the three genes can be used as sensitive bioindicators of Pb stress in Lycopersicon esculentum.

  5. Biomarker discovery and compound evaluation using two-hybrid proteomic systems.

    PubMed

    Gillespie, Marc E

    2006-10-01

    Many proteomic technologies require a heavy investment in expertise and technology, which place these approaches beyond many labs and small companies. However, proteomic approaches are ideal for pilot experiments, identifying relevant biomarkers and protein pathways for development or analysis of therapeutic compounds. The two-hybrid proteomic systems are available and affordable to most researchers, requiring little more than standard microbiological equipment. The screens rapidly generate data, identifying protein interactions that can be used to construct small local protein networks. Using data from large-scale projects, these small local protein networks can be used to identify the larger cellular pathways that are being affected by therapeutic compounds in the screen. The foundation for the two-hybrid proteomic systems are commercially available, as are high quality cDNA libraries. The straightforwardness of the two-hybrid proteomic system allows smaller groups to focus their resources on critical cellular pathways and molecular targets by taking advantage of a trusted molecular assay and an ever growing set of postgenomic era databases.

  6. Urine metabolomics analysis for adrenal incidentaloma activity detection and biomarker discovery.

    PubMed

    Kotłowska, Alicja; Sworczak, Krzysztof; Stepnowski, Piotr

    2011-02-15

    This study describes the development of a method suitable for the analysis of nineteen major urinary steroid metabolites in human urine. The analytes of interest were isolated from urine using solid phase extraction, subjected to enzymatic hydrolysis and again extracted applying solid phase extraction. After derivatization, methyloxime-trimethylsilyl ether derivatives of steroid hormones were identified by gas chromatography-mass spectrometry (GC/MS) and quantified by gas chromatography with flame ionization detector (GC/FID). The quantification method was validated for linearity, trueness, precision and selectivity. The limits of detection were between 6.2 and 7.2 ng/mL and limits of quantification were between 12.3 and 14.8 ng/mL. The established method was applied to analyze 28 urine samples from patients diagnosed with non-functioning adrenal incidentalomas (AIs) and 30 healthy subjects. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to visualize the differences between metabolic profiles of patients and the control group and to determine possible markers of AIs activity. Both multivariate methods separated seven patients from the rest of the examined individuals. Five urinary metabolites including α-cortol, tetrahydrocorticosterone, tetrahydrocortisol, allo-tetrahydrocortisol and etiocholanolone were identified as potential biomarkers of pathological adrenal function. The altered metabolites reflected pathological metabolism mainly of cortisol and cortisone. This research proved that metabolomics is a suitable tool for disease research. PMID:21247813

  7. Microfluidic droplet-based PCR instrumentation for high-throughput gene expression profiling and biomarker discovery.

    PubMed

    Hayes, Christopher J; Dalton, Tara M

    2015-06-01

    PCR is a common and often indispensable technique used in medical and biological research labs for a variety of applications. Real-time quantitative PCR (RT-qPCR) has become a definitive technique for quantitating differences in gene expression levels between samples. Yet, in spite of this importance, reliable methods to quantitate nucleic acid amounts in a higher throughput remain elusive. In the following paper, a unique design to quantify gene expression levels at the nanoscale in a continuous flow system is presented. Fully automated, high-throughput, low volume amplification of deoxynucleotides (DNA) in a droplet based microfluidic system is described. Unlike some conventional qPCR instrumentation that use integrated fluidic circuits or plate arrays, the instrument performs qPCR in a continuous, micro-droplet flowing process with droplet generation, distinctive reagent mixing, thermal cycling and optical detection platforms all combined on one complete instrument. Detailed experimental profiling of reactions of less than 300 nl total volume is achieved using the platform demonstrating the dynamic range to be 4 order logs and consistent instrument sensitivity. Furthermore, reduced pipetting steps by as much as 90% and a unique degree of hands-free automation makes the analytical possibilities for this instrumentation far reaching. In conclusion, a discussion of the first demonstrations of this approach to perform novel, continuous high-throughput biological screens is presented. The results generated from the instrument, when compared with commercial instrumentation, demonstrate the instrument reliability and robustness to carry out further studies of clinical significance with added throughput and economic benefits. PMID:27077035

  8. Microfluidic droplet-based PCR instrumentation for high-throughput gene expression profiling and biomarker discovery

    PubMed Central

    Hayes, Christopher J.; Dalton, Tara M.

    2015-01-01

    PCR is a common and often indispensable technique used in medical and biological research labs for a variety of applications. Real-time quantitative PCR (RT-qPCR) has become a definitive technique for quantitating differences in gene expression levels between samples. Yet, in spite of this importance, reliable methods to quantitate nucleic acid amounts in a higher throughput remain elusive. In the following paper, a unique design to quantify gene expression levels at the nanoscale in a continuous flow system is presented. Fully automated, high-throughput, low volume amplification of deoxynucleotides (DNA) in a droplet based microfluidic system is described. Unlike some conventional qPCR instrumentation that use integrated fluidic circuits or plate arrays, the instrument performs qPCR in a continuous, micro-droplet flowing process with droplet generation, distinctive reagent mixing, thermal cycling and optical detection platforms all combined on one complete instrument. Detailed experimental profiling of reactions of less than 300 nl total volume is achieved using the platform demonstrating the dynamic range to be 4 order logs and consistent instrument sensitivity. Furthermore, reduced pipetting steps by as much as 90% and a unique degree of hands-free automation makes the analytical possibilities for this instrumentation far reaching. In conclusion, a discussion of the first demonstrations of this approach to perform novel, continuous high-throughput biological screens is presented. The results generated from the instrument, when compared with commercial instrumentation, demonstrate the instrument reliability and robustness to carry out further studies of clinical significance with added throughput and economic benefits. PMID:27077035

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

    PubMed

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

    2013-01-01

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

  10. Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

    PubMed Central

    2014-01-01

    Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic–based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research. PMID:24679154

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

    PubMed Central

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

    2007-01-01

    SUMMARY Strategies for removal of high-abundance proteins have been increasingly utilized in proteomic studies of serum/plasma and other body fluids to enhance the detection of low-abundance proteins and achieve broader proteome coverage; however, both the reproducibility and specificity of the high-abundance protein depletion process still represent common concerns. Here, we report a detailed evaluation of immunoaffinity subtraction performed applying the ProteomeLab IgY-12 system which is commonly used in human serum/plasma proteome characterization in combination with high resolution LC-MS/MS. Plasma samples were repeatedly processed implementing this system, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. The removal of target proteins by the immunoaffinity subtraction system and the overall process was highly reproducible. Non-target proteins, including one spiked protein standard (rabbit glyceraldehyde-3-phosphate dehydrogenase), were also observed to bind to the column at different levels, but in a reproducible manner. The results suggest that multi-protein immunoaffinity subtraction systems can be readily integrated into quantitative strategies to enhance detection of low-abundance proteins in biomarker discovery studies. PMID:16854842

  12. Transferring biomarker into molecular probe: melanin nanoparticle as a naturally active platform for multimodality imaging.

    PubMed

    Fan, Quli; Cheng, Kai; Hu, Xiang; Ma, Xiaowei; Zhang, Ruiping; Yang, Min; Lu, Xiaomei; Xing, Lei; Huang, Wei; Gambhir, Sanjiv Sam; Cheng, Zhen

    2014-10-29

    Developing multifunctional and easily prepared nanoplatforms with integrated different modalities is highly challenging for molecular imaging. Here, we report the successful transfer of an important molecular target, melanin, into a novel multimodality imaging nanoplatform. Melanin is abundantly expressed in melanotic melanomas and thus has been actively studied as a target for melanoma imaging. In our work, the multifunctional biopolymer nanoplatform based on ultrasmall (<10 nm) water-soluble melanin nanoparticle (MNP) was developed and showed unique photoacoustic property and natural binding ability with metal ions (for example, (64)Cu(2+), Fe(3+)). Therefore, MNP can serve not only as a photoacoustic contrast agent, but also as a nanoplatform for positron emission tomography (PET) and magnetic resonance imaging (MRI). Traditional passive nanoplatforms require complicated and time-consuming processes for prebuilding reporting moieties or chemical modifications using active groups to integrate different contrast properties into one entity. In comparison, utilizing functional biomarker melanin can greatly simplify the building process. We further conjugated αvβ3 integrins, cyclic c(RGDfC) peptide, to MNPs to allow for U87MG tumor accumulation due to its targeting property combined with the enhanced permeability and retention (EPR) effect. The multimodal properties of MNPs demonstrate the high potential of endogenous materials with multifunctions as nanoplatforms for molecular theranostics and clinical translation.

  13. Luminescent Nanocellulose Platform: From Controlled Graft Block Copolymerization to Biomarker Sensing.

    PubMed

    Navarro, Julien R G; Wennmalm, Stefan; Godfrey, Jamie; Breitholtz, Magnus; Edlund, Ulrica

    2016-03-14

    A strategy is devised for the conversion of cellulose nanofibrils (CNF) into fluorescently labeled probes involving the synthesis of CNF-based macroinitiators that initiate radical polymerization of methyl acrylate and acrylic acid N-hydroxysuccinimide ester producing a graft block copolymer modified CNF. Finally, a luminescent probe (Lucifer yellow derivative) was labeled onto the modified CNF through an amidation reaction. The surface modification steps were verified with solid-state (13)C nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy. Fluorescence correlation spectroscopy (FCS) confirmed the successful labeling of the CNF; the CNF have a hydrodynamic radius of about 700 nm with an average number of dye molecules per fibril of at least 6600. The modified CNF was also imaged with confocal laser scanning microscopy. Luminescent CNF proved to be viable biomarkers and allow for fluorescence-based optical detection of CNF uptake and distribution in organisms such as crustaceans. The luminescent CNF were exposed to live juvenile daphnids and microscopy analysis revealed the presence of the luminescent CNF all over D. magna's alimentary canal tissues without any toxicity effect leading to the death of the specimen. PMID:26789648

  14. Sensitive Detection of Protein and miRNA Cancer Biomarkers using Silicon-Based Photonic Crystals and A Resonance Coupling Laser Scanning Platform

    PubMed Central

    George, Sherine; Chaudhery, Vikram; Lu, Meng; Takagi, Miki; Amro, Nabil; Pokhriyal, Anusha; Tan, Yafang; Ferreira, Placid; Cunningham, Brian T.

    2013-01-01

    Enhancement of the fluorescent output of surface-based fluorescence assays by performing them upon nanostructured photonic crystal (PC) surfaces has been demonstrated to increase signal intensities by >8000×. Using the multiplicative effects of optical resonant coupling to the PC in increasing the electric field intensity experienced by fluorescent labels (“enhanced excitation”) and the spatially biased funneling of fluorophore emissions through coupling to PC resonances (“enhanced extraction”), PC enhanced fluorescence (PCEF) can be adapted to reduce the limits of detection of disease biomarker assays, and to reduce the size and cost of high sensitivity detection instrumentation. In this work, we demonstrate the first silicon-based PCEF detection platform for multiplexed biomarker assay. The sensor in this platform is a silicon-based PC structure, comprised of a SiO2 grating that is overcoated with a thin film of high refractive index TiO2 and is produced in a semiconductor foundry for low cost, uniform, and reproducible manufacturing. The compact detection instrument that completes this platform was designed to efficiently couples fluorescence excitation from a semiconductor laser to the resonant optical modes of the PC, resulting in elevated electric field strength that is highly concentrated within the region <100 nm from the PC surface. This instrument utilizes a cylindrically focused line to scan a microarray in <1 minute. To demonstrate the capabilities of this sensor-detector platform, microspot fluorescent sandwich immunoassays using secondary antibodies labeled with Cy5 for two cancer biomarkers (TNF-α and IL-3) were performed. Biomarkers were detected at concentrations as low as 0.1 pM. In a fluorescent microarray for detection of a breast cancer miRNA biomarker miR-21, the miRNA was detectable at a concentration of 0.6 pM. PMID:23963502

  15. Cerebrospinal Fluid Peptides as Potential Parkinson Disease Biomarkers: A Staged Pipeline for Discovery and Validation*

    PubMed Central

    Shi, Min; Movius, James; Dator, Romel; Aro, Patrick; Zhao, Yanchun; Pan, Catherine; Lin, Xiangmin; Bammler, Theo K.; Stewart, Tessandra; Zabetian, Cyrus P.; Peskind, Elaine R.; Hu, Shu-Ching; Quinn, Joseph F.; Galasko, Douglas R.; Zhang, Jing

    2015-01-01

    Finding robust biomarkers for Parkinson disease (PD) is currently hampered by inherent technical limitations associated with imaging or antibody-based protein assays. To circumvent the challenges, we adapted a staged pipeline, starting from our previous proteomic profiling followed by high-throughput targeted mass spectrometry (MS), to identify peptides in human cerebrospinal fluid (CSF) for PD diagnosis and disease severity correlation. In this multicenter study consisting of training and validation sets, a total of 178 subjects were randomly selected from a retrospective cohort, matching age and sex between PD patients, healthy controls, and neurological controls with Alzheimer disease (AD). From ∼14,000 unique peptides displaying differences between PD and healthy control in proteomic investigations, 126 peptides were selected based on relevance and observability in CSF using bioinformatic analysis and MS screening, and then quantified by highly accurate and sensitive selected reaction monitoring (SRM) in the CSF of 30 PD patients versus 30 healthy controls (training set), followed by diagnostic (receiver operating characteristics) and disease severity correlation analyses. The most promising candidates were further tested in an independent cohort of 40 PD patients, 38 AD patients, and 40 healthy controls (validation set). A panel of five peptides (derived from SPP1, LRP1, CSF1R, EPHA4, and TIMP1) was identified to provide an area under curve (AUC) of 0.873 (sensitivity = 76.7%, specificity = 80.0%) for PD versus healthy controls in the training set. The performance was essentially confirmed in the validation set (AUC = 0.853, sensitivity = 82.5%, specificity = 82.5%). Additionally, this panel could also differentiate the PD and AD groups (AUC = 0.990, sensitivity = 95.0%, specificity = 97.4%). Furthermore, a combination of two peptides belonging to proteins TIMP1 and APLP1 significantly correlated with disease severity as determined by the Unified Parkinson

  16. Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer

    PubMed Central

    Pérot, Philippe; Cheynet, Valérie; Decaussin-Petrucci, Myriam; Oriol, Guy; Mugnier, Nathalie; Rodriguez-Lafrasse, Claire; Ruffion, Alain; Mallet, François

    2013-01-01

    The prostate-specific antigen (PSA) is the main diagnostic biomarker for prostate cancer in clinical use, but it lacks specificity and sensitivity, particularly in low dosage values1​​. ‘How to use PSA' remains a current issue, either for diagnosis as a gray zone corresponding to a concentration in serum of 2.5-10 ng/ml which does not allow a clear differentiation to be made between cancer and noncancer2 or for patient follow-up as analysis of post-operative PSA kinetic parameters can pose considerable challenges for their practical application3,4. Alternatively, noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease, e.g. PCA3 in prostate cancer5,6 and to reveal uncharacterized aspects of tumor biology. Moreover, data from the ENCODE project published in 2012 showed that different RNA types cover about 62% of the genome. It also appears that the amount of transcriptional regulatory motifs is at least 4.5x higher than the one corresponding to protein-coding exons. Thus, long terminal repeats (LTRs) of human endogenous retroviruses (HERVs) constitute a wide range of putative/candidate transcriptional regulatory sequences, as it is their primary function in infectious retroviruses. HERVs, which are spread throughout the human genome, originate from ancestral and independent infections within the germ line, followed by copy-paste propagation processes and leading to multicopy families occupying 8% of the human genome (note that exons span 2% of our genome). Some HERV loci still express proteins that have been associated with several pathologies including cancer7-10. We have designed a high-density microarray, in Affymetrix format, aiming to optimally characterize individual HERV loci expression, in order to better understand whether they can be active, if they drive ncRNA transcription or modulate coding gene expression. This tool has been applied in the prostate cancer field (Figure 1

  17. Integrating medicinal chemistry, organic/combinatorial chemistry, and computational chemistry for the discovery of selective estrogen receptor modulators with Forecaster, a novel platform for drug discovery.

    PubMed

    Therrien, Eric; Englebienne, Pablo; Arrowsmith, Andrew G; Mendoza-Sanchez, Rodrigo; Corbeil, Christopher R; Weill, Nathanael; Campagna-Slater, Valérie; Moitessier, Nicolas

    2012-01-23

    As part of a large medicinal chemistry program, we wish to develop novel selective estrogen receptor modulators (SERMs) as potential breast cancer treatments using a combination of experimental and computational approaches. However, one of the remaining difficulties nowadays is to fully integrate computational (i.e., virtual, theoretical) and medicinal (i.e., experimental, intuitive) chemistry to take advantage of the full potential of both. For this purpose, we have developed a Web-based platform, Forecaster, and a number of programs (e.g., Prepare, React, Select) with the aim of combining computational chemistry and medicinal chemistry expertise to facilitate drug discovery and development and more specifically to integrate synthesis into computer-aided drug design. In our quest for potent SERMs, this platform was used to build virtual combinatorial libraries, filter and extract a highly diverse library from the NCI database, and dock them to the estrogen receptor (ER), with all of these steps being fully automated by computational chemists for use by medicinal chemists. As a result, virtual screening of a diverse library seeded with active compounds followed by a search for analogs yielded an enrichment factor of 129, with 98% of the seeded active compounds recovered, while the screening of a designed virtual combinatorial library including known actives yielded an area under the receiver operating characteristic (AU-ROC) of 0.78. The lead optimization proved less successful, further demonstrating the challenge to simulate structure activity relationship studies.

  18. Cellphone-based detection platform for rbST biomarker analysis in milk extracts using a microsphere fluorescence immunoassay.

    PubMed

    Ludwig, Susann K J; Zhu, Hongying; Phillips, Stephen; Shiledar, Ashutosh; Feng, Steve; Tseng, Derek; van Ginkel, Leendert A; Nielen, Michel W F; Ozcan, Aydogan

    2014-11-01

    Current contaminant and residue monitoring throughout the food chain is based on sampling, transport, administration, and analysis in specialized control laboratories. This is a highly inefficient and costly process since typically more than 99% of the samples are found to be compliant. On-site simplified prescreening may provide a scenario in which only samples that are suspect are transported and further processed. Such a prescreening can be performed using a small attachment on a cellphone. To this end, a cellphone-based imaging platform for a microsphere fluorescence immunoassay that detects the presence of anti-recombinant bovine somatotropin (rbST) antibodies in milk extracts was developed. RbST administration to cows increases their milk production, but is illegal in the EU and a public health concern in the USA. The cellphone monitors the presence of anti-rbST antibodies (rbST biomarker), which are endogenously produced upon administration of rbST and excreted in milk. The rbST biomarker present in milk extracts was captured by rbST covalently coupled to paramagnetic microspheres and labeled by quantum dot (QD)-coupled detection antibodies. The emitted fluorescence light from these captured QDs was then imaged using the cellphone camera. Additionally, a dark-field image was taken in which all microspheres present were visible. The fluorescence and dark-field microimages were analyzed using a custom-developed Android application running on the same cellphone. With this setup, the microsphere fluorescence immunoassay and cellphone-based detection were successfully applied to milk sample extracts from rbST-treated and untreated cows. An 80% true-positive rate and 95% true-negative rate were achieved using this setup. Next, the cellphone-based detection platform was benchmarked against a newly developed planar imaging array alternative and found to be equally performing versus the much more sophisticated alternative. Using cellphone-based on-site analysis in

  19. Discovery Proteomics And Nonparametric Modeling Pipeline In The Development Of A Candidate Biomarker Panel For Dengue Hemorrhagic Fever

    PubMed Central

    Brasier, Allan R; Garcia, Josefina; Wiktorowicz, John E.; Spratt, Heidi M.; Comach, Guillermo; Ju, Hyunsu; Recinos, Adrian; Soman, Kizhake; Forshey, Brett M.; Halsey, Eric S.; Blair, Patrick J.; Rocha, Claudio; Bazan, Isabel; Victor, Sundar S; Wu, Zheng; Stafford, Susan; Watts, Douglas; Morrison, Amy C.; Scott, Thomas W.; Kochel, Tadeusz J.

    2013-01-01

    Secondary Dengue viral infection can produce capillary leakage associated with increased mortality known as Dengue Hemorrhagic Fever (DHF). Because the mortality of DHF can be reduced by early detection and intensive support, improved methods for its detection are needed. We applied multidimensional protein profiling to predict outcomes in a prospective Dengue surveillance study in South America. Plasma samples taken from initial clinical presentation of acute Dengue infection were subjected to proteomics analyses using ELISA and a recently developed biofluid analysis platform. Demographics, clinical laboratory measurements, 9 cytokines and 419 plasma proteins collected at the time of initial presentation were compared between the DF and DHF outcomes. Here, the subject’s gender, clinical parameters, 2 cytokines and 42 proteins discriminated between the outcomes. These factors were reduced by multivariate adaptive regression splines (MARS) that a highly accurate classification model based on 8 discriminant features with an AUC of 0.999. Model analysis indicated that the feature-outcome relationship were non-linear. Although this DHF risk model will need validation in a larger cohort, we conclude that approaches to develop predictive biomarker models for disease outcome will need to incorporate nonparametric modeling approaches. PMID:22376251

  20. Discovery proteomics and nonparametric modeling pipeline in the development of a candidate biomarker panel for dengue hemorrhagic fever.

    PubMed

    Brasier, Allan R; Garcia, Josefina; Wiktorowicz, John E; Spratt, Heidi M; Comach, Guillermo; Ju, Hyunsu; Recinos, Adrian; Soman, Kizhake; Forshey, Brett M; Halsey, Eric S; Blair, Patrick J; Rocha, Claudio; Bazan, Isabel; Victor, Sundar S; Wu, Zheng; Stafford, Susan; Watts, Douglas; Morrison, Amy C; Scott, Thomas W; Kochel, Tadeusz J

    2012-02-01

    Secondary dengue viral infection can produce capillary leakage associated with increased mortality known as dengue hemorrhagic fever (DHF). Because the mortality of DHF can be reduced by early detection and intensive support, improved methods for its detection are needed. We applied multidimensional protein profiling to predict outcomes in a prospective dengue surveillance study in South America. Plasma samples taken from initial clinical presentation of acute dengue infection were subjected to proteomics analyses using ELISA and a recently developed biofluid analysis platform. Demographics, clinical laboratory measurements, nine cytokines, and 419 plasma proteins collected at the time of initial presentation were compared between the DF and DHF outcomes. Here, the subject's gender, clinical parameters, two cytokines, and 42 proteins discriminated between the outcomes. These factors were reduced by multivariate adaptive regression splines (MARS) that a highly accurate classification model based on eight discriminant features with an area under the receiver operator curve (AUC) of 0.999. Model analysis indicated that the feature-outcome relationship were nonlinear. Although this DHF risk model will need validation in a larger cohort, we conclude that approaches to develop predictive biomarker models for disease outcome will need to incorporate nonparametric modeling approaches.

  1. Plant endophytes as a platform for discovery-based undergraduate science education.

    PubMed

    Strobel, Scott A; Strobel, Gary A

    2007-07-01

    Project ownership is an essential but sometimes overlooked ingredient for a successful undergraduate research experience. We have embarked on an experiment in undergraduate education that targets isolation of microbes from rainforest plants and characterization of natural products as objectives for discovery-based undergraduate research.

  2. GENPLAT: an automated platform for biomass enzyme discovery and cocktail optimization.

    PubMed

    Walton, Jonathan; Banerjee, Goutami; Car, Suzana

    2011-10-24

    The high cost of enzymes for biomass deconstruction is a major impediment to the economic conversion of lignocellulosic feedstocks to liquid transportation fuels such as ethanol. We have developed an integrated high throughput platform, called GENPLAT, for the discovery and development of novel enzymes and enzyme cocktails for the release of sugars from diverse pretreatment/biomass combinations. GENPLAT comprises four elements: individual pure enzymes, statistical design of experiments, robotic pipeting of biomass slurries and enzymes, and automated colorimeteric determination of released Glc and Xyl. Individual enzymes are produced by expression in Pichia pastoris or Trichoderma reesei, or by chromatographic purification from commercial cocktails or from extracts of novel microorganisms. Simplex lattice (fractional factorial) mixture models are designed using commercial Design of Experiment statistical software. Enzyme mixtures of high complexity are constructed using robotic pipeting into a 96-well format. The measurement of released Glc and Xyl is automated using enzyme-linked colorimetric assays. Optimized enzyme mixtures containing as many as 16 components have been tested on a variety of feedstock and pretreatment combinations. GENPLAT is adaptable to mixtures of pure enzymes, mixtures of commercial products (e.g., Accellerase 1000 and Novozyme 188), extracts of novel microbes, or combinations thereof. To make and test mixtures of ˜10 pure enzymes requires less than 100 μg of each protein and fewer than 100 total reactions, when operated at a final total loading of 15 mg protein/g glucan. We use enzymes from several sources. Enzymes can be purified from natural sources such as fungal cultures (e.g., Aspergillus niger, Cochliobolus carbonum, and Galerina marginata), or they can be made by expression of the encoding genes (obtained from the increasing number of microbial genome sequences) in hosts such as E. coli, Pichia pastoris, or a filamentous fungus such

  3. A study of a self diagnostic platform for the detection of A2 biomarker for Leishmania donovani

    NASA Astrophysics Data System (ADS)

    Roche, Philip J. R.; Cheung, Maurice C.; Najih, Mohamed; McCall, Laura-Isobel; Fakih, Ibrahim; Chodavarapu, Vamsy P.; Ward, Brian; Ndao, Momar; Kirk, Andrew G.

    2012-03-01

    Visceral leishmaniasis (L.donovani) is a protozoan infection that attacks mononuclear phagocytes and causes the liver and spleen damage that can cause death. The investigation presented is a proof of concept development applying a plasmonic diagnostic platform with simple microfluidic sample delivery and optical readout. An immune-assay method is applied to the quantification of A2 protein, a highly immunogenic biomarker for the pathogen. Quantification of A2 was performed in the ng/ml range, analysis by ELISA suggested that a limit of 0.1ng/ml of A2 is approximate to 1 pathogen per ml and the sensing system shows the potential to deliver a similar level of quantification. Significant reduction in assay complexity as further enzyme linked enhancement is not required when applying a plasmonic methodology to an immunoassay. The basic instrumentation required for a portable device and potential dual optical readout where both plasmonic and photoluminescent response are assessed and investigated including consideration of the application of the device to testing where non-literate communication of results is considered and issues of performance are addressed.

  4. Harvest: an open platform for developing web-based biomedical data discovery and reporting applications.

    PubMed

    Pennington, Jeffrey W; Ruth, Byron; Italia, Michael J; Miller, Jeffrey; Wrazien, Stacey; Loutrel, Jennifer G; Crenshaw, E Bryan; White, Peter S

    2014-01-01

    Biomedical researchers share a common challenge of making complex data understandable and accessible as they seek inherent relationships between attributes in disparate data types. Data discovery in this context is limited by a lack of query systems that efficiently show relationships between individual variables, but without the need to navigate underlying data models. We have addressed this need by developing Harvest, an open-source framework of modular components, and using it for the rapid development and deployment of custom data discovery software applications. Harvest incorporates visualizations of highly dimensional data in a web-based interface that promotes rapid exploration and export of any type of biomedical information, without exposing researchers to underlying data models. We evaluated Harvest with two cases: clinical data from pediatric cardiology and demonstration data from the OpenMRS project. Harvest's architecture and public open-source code offer a set of rapid application development tools to build data discovery applications for domain-specific biomedical data repositories. All resources, including the OpenMRS demonstration, can be found at http://harvest.research.chop.edu. PMID:24131510

  5. Interesting Spatio-Temporal Region Discovery Computations Over Gpu and Mapreduce Platforms

    NASA Astrophysics Data System (ADS)

    McDermott, M.; Prasad, S. K.; Shekhar, S.; Zhou, X.

    2015-07-01

    Discovery of interesting paths and regions in spatio-temporal data sets is important to many fields such as the earth and atmospheric sciences, GIS, public safety and public health both as a goal and as a preliminary step in a larger series of computations. This discovery is usually an exhaustive procedure that quickly becomes extremely time consuming to perform using traditional paradigms and hardware and given the rapidly growing sizes of today's data sets is quickly outpacing the speed at which computational capacity is growing. In our previous work (Prasad et al., 2013a) we achieved a 50 times speedup over sequential using a single GPU. We were able to achieve near linear speedup over this result on interesting path discovery by using Apache Hadoop to distribute the workload across multiple GPU nodes. Leveraging the parallel architecture of GPUs we were able to drastically reduce the computation time of a 3-dimensional spatio-temporal interest region search on a single tile of normalized difference vegetative index for Saudi Arabia. We were further able to see an almost linear speedup in compute performance by distributing this workload across several GPUs with a simple MapReduce model. This increases the speed of processing 10 fold over the comparable sequential while simultaneously increasing the amount of data being processed by 384 fold. This allowed us to process the entirety of the selected data set instead of a constrained window.

  6. Drug discovery applications for KNIME: an open source data mining platform.

    PubMed

    Mazanetz, Michael P; Marmon, Robert J; Reisser, Catherine B T; Morao, Inaki

    2012-01-01

    Technological advances in high-throughput screening methods, combinatorial chemistry and the design of virtual libraries have evolved in the pursuit of challenging drug targets. Over the last two decades a vast amount of data has been generated within these fields and as a consequence data mining methods have been developed to extract key pieces of information from these large data pools. Much of this data is now available in the public domain. This has been helpful in the arena of drug discovery for both academic groups and for small to medium sized enterprises which previously would not have had access to such data resources. Commercial data mining software is sometimes prohibitively expensive and the alternate open source data mining software is gaining momentum in both academia and in industrial applications as the costs of research and development continue to rise. KNIME, the Konstanz Information Miner, has emerged as a leader in open source data mining tools. KNIME provides an integrated solution for the data mining requirements across the drug discovery pipeline through a visual assembly of data workflows drawing from an extensive repository of tools. This review will examine KNIME as an open source data mining tool and its applications in drug discovery.

  7. Human Biomarker Discovery and Predictive Models for Disease Progression for Idiopathic Pneumonia Syndrome Following Allogeneic Stem Cell Transplantation*

    PubMed Central

    Schlatzer, Daniela M.; Dazard, Jean-Eudes; Ewing, Rob M.; Ilchenko, Serguei; Tomcheko, Sara E.; Eid, Saada; Ho, Vincent; Yanik, Greg; Chance, Mark R.; Cooke, Kenneth R.

    2012-01-01

    Allogeneic hematopoietic stem cell transplantation (SCT) is the only curative therapy for many malignant and nonmalignant conditions. Idiopathic pneumonia syndrome (IPS) is a frequently fatal complication that limits successful outcomes. Preclinical models suggest that IPS represents an immune mediated attack on the lung involving elements of both the adaptive and the innate immune system. However, the etiology of IPS in humans is less well understood. To explore the disease pathway and uncover potential biomarkers of disease, we performed two separate label-free, proteomics experiments defining the plasma protein profiles of allogeneic SCT patients with IPS. Samples obtained from SCT recipients without complications served as controls. The initial discovery study, intended to explore the disease pathway in humans, identified a set of 81 IPS-associated proteins. These data revealed similarities between the known IPS pathways in mice and the condition in humans, in particular in the acute phase response. In addition, pattern recognition pathways were judged to be significant as a function of development of IPS, and from this pathway we chose the lipopolysaccaharide-binding protein (LBP) protein as a candidate molecular diagnostic for IPS, and verified its increase as a function of disease using an ELISA assay. In a separately designed study, we identified protein-based classifiers that could predict, at day 0 of SCT, patients who: 1) progress to IPS and 2) respond to cytokine neutralization therapy. Using cross-validation strategies, we built highly predictive classifier models of both disease progression and therapeutic response. In sum, data generated in this report confirm previous clinical and experimental findings, provide new insights into the pathophysiology of IPS, identify potential molecular classifiers of the condition, and uncover a set of markers potentially of interest for patient stratification as a basis for individualized therapy. PMID:22337588

  8. CNV Workshop: an integrated platform for high-throughput copy number variation discovery and clinical diagnostics

    PubMed Central

    2010-01-01

    Background Recent studies have shown that copy number variations (CNVs) are frequent in higher eukaryotes and associated with a substantial portion of inherited and acquired risk for various human diseases. The increasing availability of high-resolution genome surveillance platforms provides opportunity for rapidly assessing research and clinical samples for CNV content, as well as for determining the potential pathogenicity of identified variants. However, few informatics tools for accurate and efficient CNV detection and assessment currently exist. Results We developed a suite of software tools and resources (CNV Workshop) for automated, genome-wide CNV detection from a variety of SNP array platforms. CNV Workshop includes three major components: detection, annotation, and presentation of structural variants from genome array data. CNV detection utilizes a robust and genotype-specific extension of the Circular Binary Segmentation algorithm, and the use of additional detection algorithms is supported. Predicted CNVs are captured in a MySQL database that supports cohort-based projects and incorporates a secure user authentication layer and user/admin roles. To assist with determination of pathogenicity, detected CNVs are also annotated automatically for gene content, known disease loci, and gene-based literature references. Results are easily queried, sorted, filtered, and visualized via a web-based presentation layer that includes a GBrowse-based graphical representation of CNV content and relevant public data, integration with the UCSC Genome Browser, and tabular displays of genomic attributes for each CNV. Conclusions To our knowledge, CNV Workshop represents the first cohesive and convenient platform for detection, annotation, and assessment of the biological and clinical significance of structural variants. CNV Workshop has been successfully utilized for assessment of genomic variation in healthy individuals and disease cohorts and is an ideal platform for

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

    SciTech Connect

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

    2008-02-01

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

  10. NMR-based platform for fragment-based lead discovery used in screening BRD4-targeted compounds

    PubMed Central

    Yu, Jun-lan; Chen, Tian-tian; Zhou, Chen; Lian, Fu-lin; Tang, Xu-long; Wen, Yi; Shen, Jing-kang; Xu, Ye-chun; Xiong, Bing; Zhang, Nai-xia

    2016-01-01

    Aim: Fragment-based lead discovery (FBLD) is a complementary approach in drug research and development. In this study, we established an NMR-based FBLD platform that was used to screen novel scaffolds targeting human bromodomain of BRD4, and investigated the binding interactions between hit compounds and the target protein. Methods: 1D NMR techniques were primarily used to generate the fragment library and to screen compounds. The inhibitory activity of hits on the first bromodomain of BRD4 [BRD4(I)] was examined using fluorescence anisotropy binding assay. 2D NMR and X-ray crystallography were applied to characterize the binding interactions between hit compounds and the target protein. Results: An NMR-based fragment library containing 539 compounds was established, which were clustered into 56 groups (8–10 compounds in each group). Eight hits with new scaffolds were found to inhibit BRD4(I). Four out of the 8 hits (compounds 1, 2, 8 and 9) had IC50 values of 100–260 μmol/L, demonstrating their potential for further BRD4-targeted hit-to-lead optimization. Analysis of the binding interactions revealed that compounds 1 and 2 shared a common quinazolin core structure and bound to BRD4(I) in a non-acetylated lysine mimetic mode. Conclusion: An NMR-based platform for FBLD was established and used in discovery of BRD4-targeted compounds. Four potential hit-to-lead optimization candidates have been found, two of them bound to BRD4(I) in a non-acetylated lysine mimetic mode, being selective BRD4(I) inhibitors. PMID:27238211

  11. High-Throughput Screening Platform for the Discovery of New Immunomodulator Molecules from Natural Product Extract Libraries.

    PubMed

    Pérez Del Palacio, José; Díaz, Caridad; de la Cruz, Mercedes; Annang, Frederick; Martín, Jesús; Pérez-Victoria, Ignacio; González-Menéndez, Víctor; de Pedro, Nuria; Tormo, José R; Algieri, Francesca; Rodriguez-Nogales, Alba; Rodríguez-Cabezas, M Elena; Reyes, Fernando; Genilloud, Olga; Vicente, Francisca; Gálvez, Julio

    2016-07-01

    It is widely accepted that central nervous system inflammation and systemic inflammation play a significant role in the progression of chronic neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, neurotropic viral infections, stroke, paraneoplastic disorders, traumatic brain injury, and multiple sclerosis. Therefore, it seems reasonable to propose that the use of anti-inflammatory drugs might diminish the cumulative effects of inflammation. Indeed, some epidemiological studies suggest that sustained use of anti-inflammatory drugs may prevent or slow down the progression of neurodegenerative diseases. However, the anti-inflammatory drugs and biologics used clinically have the disadvantage of causing side effects and a high cost of treatment. Alternatively, natural products offer great potential for the identification and development of bioactive lead compounds into drugs for treating inflammatory diseases with an improved safety profile. In this work, we present a validated high-throughput screening approach in 96-well plate format for the discovery of new molecules with anti-inflammatory/immunomodulatory activity. The in vitro models are based on the quantitation of nitrite levels in RAW264.7 murine macrophages and interleukin-8 in Caco-2 cells. We have used this platform in a pilot project to screen a subset of 5976 noncytotoxic crude microbial extracts from the MEDINA microbial natural product collection. To our knowledge, this is the first report on an high-throughput screening of microbial natural product extracts for the discovery of immunomodulators. PMID:26962874

  12. High-Throughput Screening Platform for the Discovery of New Immunomodulator Molecules from Natural Product Extract Libraries.

    PubMed

    Pérez Del Palacio, José; Díaz, Caridad; de la Cruz, Mercedes; Annang, Frederick; Martín, Jesús; Pérez-Victoria, Ignacio; González-Menéndez, Víctor; de Pedro, Nuria; Tormo, José R; Algieri, Francesca; Rodriguez-Nogales, Alba; Rodríguez-Cabezas, M Elena; Reyes, Fernando; Genilloud, Olga; Vicente, Francisca; Gálvez, Julio

    2016-07-01

    It is widely accepted that central nervous system inflammation and systemic inflammation play a significant role in the progression of chronic neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, neurotropic viral infections, stroke, paraneoplastic disorders, traumatic brain injury, and multiple sclerosis. Therefore, it seems reasonable to propose that the use of anti-inflammatory drugs might diminish the cumulative effects of inflammation. Indeed, some epidemiological studies suggest that sustained use of anti-inflammatory drugs may prevent or slow down the progression of neurodegenerative diseases. However, the anti-inflammatory drugs and biologics used clinically have the disadvantage of causing side effects and a high cost of treatment. Alternatively, natural products offer great potential for the identification and development of bioactive lead compounds into drugs for treating inflammatory diseases with an improved safety profile. In this work, we present a validated high-throughput screening approach in 96-well plate format for the discovery of new molecules with anti-inflammatory/immunomodulatory activity. The in vitro models are based on the quantitation of nitrite levels in RAW264.7 murine macrophages and interleukin-8 in Caco-2 cells. We have used this platform in a pilot project to screen a subset of 5976 noncytotoxic crude microbial extracts from the MEDINA microbial natural product collection. To our knowledge, this is the first report on an high-throughput screening of microbial natural product extracts for the discovery of immunomodulators.

  13. A liposomal drug platform overrides peptide ligand targeting to a cancer biomarker, irrespective of ligand affinity or density.

    PubMed

    Gray, Bethany Powell; McGuire, Michael J; Brown, Kathlynn C

    2013-01-01

    One method for improving cancer treatment is the use of nanoparticle drugs functionalized with targeting ligands that recognize receptors expressed selectively by tumor cells. In theory such targeting ligands should specifically deliver the nanoparticle drug to the tumor, increasing drug concentration in the tumor and delivering the drug to its site of action within the tumor tissue. However, the leaky vasculature of tumors combined with a poor lymphatic system allows the passive accumulation, and subsequent retention, of nanosized materials in tumors. Furthermore, a large nanoparticle size may impede tumor penetration. As such, the role of active targeting in nanoparticle delivery is controversial, and it is difficult to predict how a targeted nanoparticle drug will behave in vivo. Here we report in vivo studies for αvβ6-specific H2009.1 peptide targeted liposomal doxorubicin, which increased liposomal delivery and toxicity to lung cancer cells in vitro. We systematically varied ligand affinity, ligand density, ligand stability, liposome dosage, and tumor models to assess the role of active targeting of liposomes to αvβ6. In direct contrast to the in vitro results, we demonstrate no difference in in vivo targeting or efficacy for H2009.1 tetrameric peptide liposomal doxorubicin, compared to control peptide and no peptide liposomes. Examining liposome accumulation and distribution within the tumor demonstrates that the liposome, and not the H2009.1 peptide, drives tumor accumulation, and that both targeted H2009.1 and untargeted liposomes remain in perivascular regions, with little tumor penetration. Thus H2009.1 targeted liposomes fail to improve drug efficacy because the liposome drug platform prevents the H2009.1 peptide from both actively targeting the tumor and binding to tumor cells throughout the tumor tissue. Therefore, using a high affinity and high specificity ligand targeting an over-expressed tumor biomarker does not guarantee enhanced efficacy of a

  14. Development of a carbonate platform with potential for large discoveries - an example from Vietnam

    SciTech Connect

    Mayall, M.; Bent, A.; Dale, B. )

    1996-01-01

    In offshore central and southern Vietnam a number of carbonate accumulations can be recognized. Platform carbonates form basin-wide units of carbonate characterized by strong, continuous parallel seismic reflectors. Facies are dominated by bioclastic wackestones with poor-moderate reservoir quality. On the more isolated highs, large buildups developed. These are typically 5-10 km across and 300 m thick. They unconformably overlie the platform carbonate facies which are extensively karstified. In places these are pinnacles, typically 2-5 km across, 300 m+ thick with chaotic or mounded internal seismic facies. The large carbonate buildups are characterized by steep sided slopes with talus cones, reef-margin rims usually developed around only part of the buildup, and a prominent back-stepping geometry. Buildup interior facies form the main potential reservoirs They are dominated by fine to coarse grained coralgal packstones. Fine grained carbonates are associated with deeper water events and multiple karst surfaces can also be identified. Reservoir quality is excellent, largely controlled by extensive dissolution and dolomitization believed to be related to the exposure events. Gas has been found in a number of reservoirs. Heterogeneities can be recognized which could potentially effect production. These include the extensive finer grained facies, cementation or open fissures associated with the karst surfaces, a more cemented reef rim, shallowing upwards facies cycles and faults.

  15. Development of a carbonate platform with potential for large discoveries - an example from Vietnam

    SciTech Connect

    Mayall, M.; Bent, A.; Dale, B.

    1996-12-31

    In offshore central and southern Vietnam a number of carbonate accumulations can be recognized. Platform carbonates form basin-wide units of carbonate characterized by strong, continuous parallel seismic reflectors. Facies are dominated by bioclastic wackestones with poor-moderate reservoir quality. On the more isolated highs, large buildups developed. These are typically 5-10 km across and 300 m thick. They unconformably overlie the platform carbonate facies which are extensively karstified. In places these are pinnacles, typically 2-5 km across, 300 m+ thick with chaotic or mounded internal seismic facies. The large carbonate buildups are characterized by steep sided slopes with talus cones, reef-margin rims usually developed around only part of the buildup, and a prominent back-stepping geometry. Buildup interior facies form the main potential reservoirs They are dominated by fine to coarse grained coralgal packstones. Fine grained carbonates are associated with deeper water events and multiple karst surfaces can also be identified. Reservoir quality is excellent, largely controlled by extensive dissolution and dolomitization believed to be related to the exposure events. Gas has been found in a number of reservoirs. Heterogeneities can be recognized which could potentially effect production. These include the extensive finer grained facies, cementation or open fissures associated with the karst surfaces, a more cemented reef rim, shallowing upwards facies cycles and faults.

  16. In situ studies of a platform for metastable inorganic crystal growth and materials discovery

    PubMed Central

    Shoemaker, Daniel P.; Hu, Yung-Jin; Chung, Duck Young; Halder, Gregory J.; Chupas, Peter J.; Soderholm, L.; Mitchell, J. F.; Kanatzidis, Mercouri G.

    2014-01-01

    Rapid shifts in the energy, technological, and environmental demands of materials science call for focused and efficient expansion of the library of functional inorganic compounds. To achieve the requisite efficiency, we need a materials discovery and optimization paradigm that can rapidly reveal all possible compounds for a given reaction and composition space. Here we provide such a paradigm via in situ X-ray diffraction measurements spanning solid, liquid flux, and recrystallization processes. We identify four new ternary sulfides from reactive salt fluxes in a matter of hours, simultaneously revealing routes for ex situ synthesis and crystal growth. Changing the flux chemistry, here accomplished by increasing sulfur content, permits comparison of the allowable crystalline building blocks in each reaction space. The speed and structural information inherent to this method of in situ synthesis provide an experimental complement to computational efforts to predict new compounds and uncover routes to targeted materials by design. PMID:25024201

  17. Integrating `-omics' and natural product discovery platforms to investigate metabolic exchange in microbiomes

    PubMed Central

    Yang, Jane Y; Karr, Jessica R; Watrous, Jeramie D; Dorrestein, Pieter C

    2011-01-01

    The microbiome is an abundance of microorganisms within a host (e.g. human microbiome). These microorganisms produce small molecules and metabolites that have been shown to affect and dictate the physiology of an individual. Functional knowledge of these molecules, often produced for communication or defense, will reveal the interplay between microbes and host in health and disease. The vast diversity in structure and function of microbiome-associated small molecules necessitate tools that will utilize multiple `-omics' strategies to understand the interactions within the human microbiome. This review discusses the importance of these investigations and the integration of current `-omics' technologies with tools established in natural product discovery in order to identify and characterize uncharacterized small molecules in the effort towards diagnostic modeling of the human microbiome. PMID:21087892

  18. Questioning the preclinical paradigm: natural, extreme biology as an alternative discovery platform

    PubMed Central

    Buffenstein, Rochelle; Nelson, O. Lynne; Corbit, Kevin C.

    2014-01-01

    The pace at which science continues to advance is astonishing. From cosmology, microprocessors, structural engineering, and DNA sequencing our lives are continually affected by science-based technology. However, progress in treating human ailments, especially age-related conditions such as cancer and Alzheimer's disease, moves at a relative snail's pace. Given that the amount of investment is not disproportionately low, one has to question why our hopes for the development of efficacious drugs for such grievous illnesses have been frustratingly unrealized. Here we discuss one aspect of drug development –rodent models – and propose an alternative approach to discovery research rooted in evolutionary experimentation. Our goal is to accelerate the conversation around how we can move towards more translative preclinical work. PMID:25553771

  19. Microdroplets in microfluidics: an evolving platform for discoveries in chemistry and biology.

    PubMed

    Theberge, Ashleigh B; Courtois, Fabienne; Schaerli, Yolanda; Fischlechner, Martin; Abell, Chris; Hollfelder, Florian; Huck, Wilhelm T S

    2010-08-01

    Microdroplets in microfluidics offer a great number of opportunities in chemical and biological research. They provide a compartment in which species or reactions can be isolated, they are monodisperse and therefore suitable for quantitative studies, they offer the possibility to work with extremely small volumes, single cells, or single molecules, and are suitable for high-throughput experiments. The aim of this Review is to show the importance of these features in enabling new experiments in biology and chemistry. The recent advances in device fabrication are highlighted as are the remaining technological challenges. Examples are presented to show how compartmentalization, monodispersity, single-molecule sensitivity, and high throughput have been exploited in experiments that would have been extremely difficult outside the microfluidics platform.

  20. [Strength and specificity of the CMBA screening platform for bioactive molecules discovery].

    PubMed

    Barette, Caroline; Soleilhac, Emmanuelle; Charavay, Céline; Cochet, Claude; Fauvarque, Marie-Odile

    2015-04-01

    Used as powerful chemical probes in Life science fundamental research, the application potential of new bioactive molecular entities includes but extends beyond their development as therapeutic drugs in pharmacology. In this review, we wish to point out the methodology of chemical libraries screening on living cells or purified proteins at the CMBA academic platform of Grenoble Alpes University, and strategies employed to further characterize the selected bioactive molecules by phenotypic profiling on human cells. Multiple application fields are concerned by the screening activity developed at CMBA with bioactive molecules previously selected for their potential as tools for fundamental research purpose, therapeutic candidates to treat cancer or infection, or promising compounds for production of bioenergy.

  1. Statistical search space reduction and two-dimensional data display approaches for UPLC-MS in biomarker discovery and pathway analysis.

    PubMed

    Crockford, Derek J; Lindon, John C; Cloarec, Olivier; Plumb, Robert S; Bruce, Stephen J; Zirah, Severine; Rainville, Paul; Stumpf, Chris L; Johnson, Kelly; Holmes, Elaine; Nicholson, Jeremy K

    2006-07-01

    A new analytical strategy for biomarker recovery from directly coupled ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC Tof MS) data on biofluids is presented and exemplified using a study on hydrazine-induced liver toxicity. A key step in the strategy involves a novel procedure for reducing the spectroscopic search space by differential analysis of cohorts of normal and pathological samples using an orthogonal projection to latent structures discriminant analysis (O-PLS-DA). This efficiently sorts principal discriminators of toxicity from the background of thousands of metabolic features commonly observed in data sets generated by UPLC-MS analysis of biological fluids and is thus a powerful tool for biomarker discovery. PMID:16808447

  2. Detecting Alzheimer's disease biomarkers: From antibodies to new bio-mimetic receptors and their application to established and emerging bioanalytical platforms - A critical review.

    PubMed

    Scarano, Simona; Lisi, Samuele; Ravelet, Corinne; Peyrin, Eric; Minunni, Maria

    2016-10-12

    The failure of therapeutic treatment of Alzheimer's disease (AD) patients can be related to the late onset of symptoms and, consequently, to a delayed pharmacological aid to counteract neurodegenerative progression. This is coupled to the fact that the diagnosis based on clinical criteria alone introduces high misdiagnosis rate. The availability of assessed biomarkers is therefore of crucial importance not only to counteract late diagnosis, but also to manage patients at high risk of AD development eligible for novel therapies. At the present time, amyloid-β peptides (Aβ1-40 and Aβ1-42 isoforms), alone or in combination with Tau protein (total and phosphorylated forms (p-tau)) constitute reliable AD biomarkers and result highly predictive of progression to AD dementia in patients with mild cognitive impairment (MCI), the earliest clinical presentation of AD. Improvement of existing diagnostic tools must take advantage of innovative bioanalytical approaches. In this review, starting from commercially available diagnostic platforms based on antibodies as recognition elements, we intended to provide a double point of view on the issue: 1) progresses achieved on innovative bioanalytical platforms (mainly sensors and biosensors) by using antibodies as consolidated receptors; 2) advance on promising bio-mimetic receptors alternative to antibodies in AD research, and their applications on conventional or innovative analytical platforms. In particular, we first focused on optical- (Propagating and Localized Surface Plasmon Resonance, named here SPR and LSPR) and electrochemical (voltammetric and impedimetric) transduction principles. Together with bioanalytical assays for AD biomarkers quantification, works aimed to investigate and understand their behavior, characteristics, and roles will also be considered in the discussion. An increasing interest in new emerging biomimetic receptors for AD diagnosis, as a promising alternative to antibodies is noticed, thus the

  3. Detecting Alzheimer's disease biomarkers: From antibodies to new bio-mimetic receptors and their application to established and emerging bioanalytical platforms - A critical review.

    PubMed

    Scarano, Simona; Lisi, Samuele; Ravelet, Corinne; Peyrin, Eric; Minunni, Maria

    2016-10-12

    The failure of therapeutic treatment of Alzheimer's disease (AD) patients can be related to the late onset of symptoms and, consequently, to a delayed pharmacological aid to counteract neurodegenerative progression. This is coupled to the fact that the diagnosis based on clinical criteria alone introduces high misdiagnosis rate. The availability of assessed biomarkers is therefore of crucial importance not only to counteract late diagnosis, but also to manage patients at high risk of AD development eligible for novel therapies. At the present time, amyloid-β peptides (Aβ1-40 and Aβ1-42 isoforms), alone or in combination with Tau protein (total and phosphorylated forms (p-tau)) constitute reliable AD biomarkers and result highly predictive of progression to AD dementia in patients with mild cognitive impairment (MCI), the earliest clinical presentation of AD. Improvement of existing diagnostic tools must take advantage of innovative bioanalytical approaches. In this review, starting from commercially available diagnostic platforms based on antibodies as recognition elements, we intended to provide a double point of view on the issue: 1) progresses achieved on innovative bioanalytical platforms (mainly sensors and biosensors) by using antibodies as consolidated receptors; 2) advance on promising bio-mimetic receptors alternative to antibodies in AD research, and their applications on conventional or innovative analytical platforms. In particular, we first focused on optical- (Propagating and Localized Surface Plasmon Resonance, named here SPR and LSPR) and electrochemical (voltammetric and impedimetric) transduction principles. Together with bioanalytical assays for AD biomarkers quantification, works aimed to investigate and understand their behavior, characteristics, and roles will also be considered in the discussion. An increasing interest in new emerging biomimetic receptors for AD diagnosis, as a promising alternative to antibodies is noticed, thus the

  4. High-throughput platform for the discovery of elicitors of silent bacterial gene clusters.

    PubMed

    Seyedsayamdost, Mohammad R

    2014-05-20

    Over the past decade, bacterial genome sequences have revealed an immense reservoir of biosynthetic gene clusters, sets of contiguous genes that have the potential to produce drugs or drug-like molecules. However, the majority of these gene clusters appear to be inactive for unknown reasons prompting terms such as "cryptic" or "silent" to describe them. Because natural products have been a major source of therapeutic molecules, methods that rationally activate these silent clusters would have a profound impact on drug discovery. Herein, a new strategy is outlined for awakening silent gene clusters using small molecule elicitors. In this method, a genetic reporter construct affords a facile read-out for activation of the silent cluster of interest, while high-throughput screening of small molecule libraries provides potential inducers. This approach was applied to two cryptic gene clusters in the pathogenic model Burkholderia thailandensis. The results not only demonstrate a prominent activation of these two clusters, but also reveal that the majority of elicitors are themselves antibiotics, most in common clinical use. Antibiotics, which kill B. thailandensis at high concentrations, act as inducers of secondary metabolism at low concentrations. One of these antibiotics, trimethoprim, served as a global activator of secondary metabolism by inducing at least five biosynthetic pathways. Further application of this strategy promises to uncover the regulatory networks that activate silent gene clusters while at the same time providing access to the vast array of cryptic molecules found in bacteria.

  5. A drug discovery platform: a simplified immunoassay for analyzing HIV protease activity.

    PubMed

    Kitidee, Kuntida; Nangola, Sawitree; Hadpech, Sudarat; Laopajon, Witida; Kasinrerk, Watchara; Tayapiwatana, Chatchai

    2012-12-01

    Although numerous methods for the determination of HIV protease (HIV-PR) activity have been described, new high-throughput assays are required for clinical and pharmaceutical applications due to the occurrence of resistant strains. In this study, a simple enzymatic immunoassay to identify HIV-PR activity was developed based on a Ni(2+)-immobilized His(6)-Matrix-Capsid substrate (H(6)MA-CA) is cleaved by HIV protease-His(6) (HIV-PRH(6)) which removes the CA domain and exposes the free C terminus of MA. Following this cleavage, two monoclonal antibodies specific for either the free C-terminal MA or CA epitope are used to quantify the proteolytic activity using a standard ELISA-based system. Specificity for detection of the HIV-PRH(6) activity was confirmed with addition of protease inhibitor (PI), lopinavir. In addition, the assay was able to detect an HIV-PR variant activity indicating that this assay is capable of assessing viral mutation affect HIV-PR activity. The efficacy of commercially available PIs and their 50% inhibitory concentration (IC(50)) were determined. This assay provides a high-throughput method for both validating the efficiency of new drugs in vitro and facilitating the discovery of new PIs. In addition, it could serve as a method for examining the influence of various mutations in HIV-PRs isolated from drug-resistant strains.

  6. Hexosamine template. A platform for modulating gene expression and for sugar-based drug discovery.

    PubMed

    Elmouelhi, Noha; Aich, Udayanath; Paruchuri, Venkata D P; Meledeo, M Adam; Campbell, Christopher T; Wang, Jean J; Srinivas, Raja; Khanna, Hargun S; Yarema, Kevin J

    2009-04-23

    This study investigates the breadth of cellular responses engendered by short chain fatty acid (SCFA)-hexosamine hybrid molecules, a class of compounds long used in "metabolic glycoengineering" that are now emerging as drug candidates. First, a "mix and match" strategy showed that different SCFA (n-butyrate and acetate) appended to the same core sugar altered biological activity, complementing previous results [Campbell et al. J. Med. Chem. 2008, 51, 8135-8147] where a single type of SCFA elicited distinct responses. Microarray profiling then compared transcriptional responses engendered by regioisomerically modified ManNAc, GlcNAc, and GalNAc analogues in MDA-MB-231 cells. These data, which were validated by qRT-PCR or Western analysis for ID1, TP53, HPSE, NQO1, EGR1, and VEGFA, showed a two-pronged response where a core set of genes was coordinately regulated by all analogues while each analogue simultaneously uniquely regulated a larger number of genes. Finally, AutoDock modeling supported a mechanism where the analogues directly interact with elements of the NF-kappaB pathway. Together, these results establish the SCFA-hexosamine template as a versatile platform for modulating biological activity and developing new therapeutics. PMID:19326913

  7. A technological platform to optimize combinatorial treatment design and discovery for chronic spinal cord injury.

    PubMed

    Guertin, Pierre A

    2008-11-01

    Chronic spinal cord injury (SCI) is associated with the development of serious medical concerns. In fact, it is increasingly well documented that most SCI patients who survive the first 24 hr will rapidly develop, within a few months to a few years, cardiovascular problems, type II diabetes, muscle wasting, osteoporosis, immune deficiencies, and other life-threatening problems. The cellular mechanisms underlying these so-called secondary health complications remain unclear, and no drug or standard approach has been developed to specifically treat these complications. To investigate the cellular and metabolic changes associated with chronic SCI and functional recovery, work mainly from our laboratory recently has led to the characterization of a mouse model of chronic paraplegia. This review reports cellular, systemic, and metabolic changes (associated mainly with secondary health complications) occurring within a few days to a few weeks after SCI in low-thoracic spinal cord-transected mice. We also describe our research platform developed to ease technological transfer and to accelerate drug-screening studies in animals. A global understanding of the many chronic changes occurring after SCI together with efficient tools and approaches for testing new or existing drug candidates is likely to yield the design of innovative treatments against secondary complications that combine cellular plasticity-modulating agents, locomotor network-activating drugs, hormonal therapy, and exercise training.

  8. A Sorghum Mutant Resource as an Efficient Platform for Gene Discovery in Grasses[OPEN

    PubMed Central

    Burke, John; Chen, Junping; Wang, Bo; Hayes, Chad; Emendack, Yves

    2016-01-01

    Sorghum (Sorghum bicolor) is a versatile C4 crop and a model for research in family Poaceae. High-quality genome sequence is available for the elite inbred line BTx623, but functional validation of genes remains challenging due to the limited genomic and germplasm resources available for comprehensive analysis of induced mutations. In this study, we generated 6400 pedigreed M4 mutant pools from EMS-mutagenized BTx623 seeds through single-seed descent. Whole-genome sequencing of 256 phenotyped mutant lines revealed >1.8 million canonical EMS-induced mutations, affecting >95% of genes in the sorghum genome. The vast majority (97.5%) of the induced mutations were distinct from natural variations. To demonstrate the utility of the sequenced sorghum mutant resource, we performed reverse genetics to identify eight genes potentially affecting drought tolerance, three of which had allelic mutations and two of which exhibited exact cosegregation with the phenotype of interest. Our results establish that a large-scale resource of sequenced pedigreed mutants provides an efficient platform for functional validation of genes in sorghum, thereby accelerating sorghum breeding. Moreover, findings made in sorghum could be readily translated to other members of the Poaceae via integrated genomics approaches. PMID:27354556

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

    PubMed

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

    2011-06-01

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

  10. Microplasma synthesis of sub-5 nm metal clusters: A novel platform for study and discovery

    NASA Astrophysics Data System (ADS)

    Sankaran, R. Mohan

    2013-09-01

    Homogeneous, gas-phase nucleation of particles in reactive plasmas is well known. Dust formation in chemical vapor deposition (CVD) processes is undesired and can lead to deleterious effects on device fabrication and performance. Recently, plasma systems have been developed to purposefully synthesize nanoparticles for technological applications. The advantage of plasmas over other chemical methods include the high purity, uniformity of particle size, and the possibility of accessing unique chemistries through the non-equilibrium environment. In this talk, I will present our contribution to this rapidly emerging field: the development of a new class of atmospheric-pressure, low-temperature microplasma systems that enables the synthesis of unagglomerated, sub-5 nm particles in a single step. The synthesis of clusters in this size range is of current interest for the study and discovery of novel nanomaterials. To illustrate this point, two examples will be presented. One, clusters of Ni, Fe, and other metals are produced from their corresponding organometallic precursors. Alloys with precisely controlled compositions are also obtained by tuning the relative amount of the precursors in the plasma phase. The availability of metal clusters with well-defined size and composition has allowed us to systematically study carbon nanotube nucleation and growth, and relate the properties of the catalyst to the as-grown tube diameter and chirality. Two, we have carried out studies of carbon cluster formation and observed the presence of diamond-phase carbon. The nucleation of diamond at near ambient conditions supports theoretical predictions of the stability of sp3 diamond over sp2 carbon and suggests a potential route for their existence in the cosmos. NSF Award No. CBET-0746821 and AFOSR Award No. FA9550-10-1-0160.

  11. Earthdata 3.0: A Unified Experience and Platform for Earth Science Discovery

    NASA Astrophysics Data System (ADS)

    Plofchan, P.; McLaughlin, B. D.

    2015-12-01

    NASA's EOSDIS (Earth Observing System Data and Information System) as a multitude of websites and applications focused on serving the Earth Science community's extensive data needs. With no central user interface, theme, or mechanism for accessing that data, interrelated systems are confusing and potentially disruptive in users' searches for EOSDIS data holdings. In an effort to bring consistency across these systems, an effort was undertaken to develop Earthdata 3.0: a complete information architecture overhaul of the Earthdata website, a significant update to the Earthdata user experience and user interface, and an increased focus on searching across EOSDIS data holdings, including those housed and made available through DAAC websites. As part of this effort, and in a desire to unify the user experience across related websites, the Earthdata User Interface (EUI) was developed. The EUI is a collection of responsive design components and layouts geared toward creating websites and applications within the Earthdata ecosystem. Each component and layout has been designed specifically for Earth science-related projects which eliminates some of the complexities of building a website or application from the ground up. Its adoption will ensure both consistent markup and a unified look and feel for end users, thereby increasing usability and accessibility. Additionally, through the user of a Google Search Appliance, custom Clojure code, and in cooperation with DAACs, Earthdata 3.0 presents a variety of search results upon a user's keyword(s) entry. These results are not just textual links, but also direct links to downloadable datasets, visualizations of datasets and collections of data, and related articles and videos for further research. The end result of the development of the EUI and the enhanced multi-response type search is a consistent and usable platform for Earth scientists and users to navigate and locate data to further their research.

  12. An Isogenic Human ESC Platform for Functional Evaluation of Genome-wide-Association-Study-Identified Diabetes Genes and Drug Discovery.

    PubMed

    Zeng, Hui; Guo, Min; Zhou, Ting; Tan, Lei; Chong, Chi Nok; Zhang, Tuo; Dong, Xue; Xiang, Jenny Zhaoying; Yu, Albert S; Yue, Lixia; Qi, Qibin; Evans, Todd; Graumann, Johannes; Chen, Shuibing

    2016-09-01

    Genome-wide association studies (GWASs) have increased our knowledge of loci associated with a range of human diseases. However, applying such findings to elucidate pathophysiology and promote drug discovery remains challenging. Here, we created isogenic human ESCs (hESCs) with mutations in GWAS-identified susceptibility genes for type 2 diabetes. In pancreatic beta-like cells differentiated from these lines, we found that mutations in CDKAL1, KCNQ1, and KCNJ11 led to impaired glucose secretion in vitro and in vivo, coinciding with defective glucose homeostasis. CDKAL1 mutant insulin+ cells were also hypersensitive to glucolipotoxicity. A high-content chemical screen identified a candidate drug that rescued CDKAL1-specific defects in vitro and in vivo by inhibiting the FOS/JUN pathway. Our approach of a proof-of-principle platform, which uses isogenic hESCs for functional evaluation of GWAS-identified loci and identification of a drug candidate that rescues gene-specific defects, paves the way for precision therapy of metabolic diseases. PMID:27524441

  13. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes.

    PubMed

    Piñero, Janet; Queralt-Rosinach, Núria; Bravo, Àlex; Deu-Pons, Jordi; Bauer-Mehren, Anna; Baron, Martin; Sanz, Ferran; Furlong, Laura I

    2015-01-01

    DisGeNET is a comprehensive discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET contains over 380,000 associations between >16,000 genes and 13,000 diseases, which makes it one of the largest repositories currently available of its kind. DisGeNET integrates expert-curated databases with text-mined data, covers information on Mendelian and complex diseases, and includes data from animal disease models. It features a score based on the supporting evidence to prioritize gene-disease associations. It is an open access resource available through a web interface, a Cytoscape plugin and as a Semantic Web resource. The web interface supports user-friendly data exploration and navigation. DisGeNET data can also be analysed via the DisGeNET Cytoscape plugin, and enriched with the annotations of other plugins of this popular network analysis software suite. Finally, the information contained in DisGeNET can be expanded and complemented using Semantic Web technologies and linked to a variety of resources already present in the Linked Data cloud. Hence, DisGeNET offers one of the most comprehensive collections of human gene-disease associations and a valuable set of tools for investigating the molecular mechanisms underlying diseases of genetic origin, designed to fulfill the needs of different user profiles, including bioinformaticians, biologists and health-care practitioners. Database URL: http://www.disgenet.org/ PMID:25877637

  14. An Isogenic Human ESC Platform for Functional Evaluation of Genome-wide-Association-Study-Identified Diabetes Genes and Drug Discovery.

    PubMed

    Zeng, Hui; Guo, Min; Zhou, Ting; Tan, Lei; Chong, Chi Nok; Zhang, Tuo; Dong, Xue; Xiang, Jenny Zhaoying; Yu, Albert S; Yue, Lixia; Qi, Qibin; Evans, Todd; Graumann, Johannes; Chen, Shuibing

    2016-09-01

    Genome-wide association studies (GWASs) have increased our knowledge of loci associated with a range of human diseases. However, applying such findings to elucidate pathophysiology and promote drug discovery remains challenging. Here, we created isogenic human ESCs (hESCs) with mutations in GWAS-identified susceptibility genes for type 2 diabetes. In pancreatic beta-like cells differentiated from these lines, we found that mutations in CDKAL1, KCNQ1, and KCNJ11 led to impaired glucose secretion in vitro and in vivo, coinciding with defective glucose homeostasis. CDKAL1 mutant insulin+ cells were also hypersensitive to glucolipotoxicity. A high-content chemical screen identified a candidate drug that rescued CDKAL1-specific defects in vitro and in vivo by inhibiting the FOS/JUN pathway. Our approach of a proof-of-principle platform, which uses isogenic hESCs for functional evaluation of GWAS-identified loci and identification of a drug candidate that rescues gene-specific defects, paves the way for precision therapy of metabolic diseases.

  15. Respiratory Toxicity Biomarkers

    EPA Science Inventory

    The advancement in high throughput genomic, proteomic and metabolomic techniques have accelerated pace of lung biomarker discovery. A recent growth in the discovery of new lung toxicity/disease biomarkers have led to significant advances in our understanding of pathological proce...

  16. The Discovery of Novel Genomic, Transcriptomic, and Proteomic Biomarkers in Cardiovascular and Peripheral Vascular Disease: The State of the Art

    PubMed Central

    de Franciscis, Stefano; Metzinger, Laurent; Serra, Raffaele

    2016-01-01

    Cardiovascular disease (CD) and peripheral vascular disease (PVD) are leading causes of mortality and morbidity in western countries and also responsible of a huge burden in terms of disability, functional decline, and healthcare costs. Biomarkers are measurable biological elements that reflect particular physiological or pathological states or predisposition towards diseases and they are currently widely studied in medicine and especially in CD. In this context, biomarkers can also be used to assess the severity or the evolution of several diseases, as well as the effectiveness of particular therapies. Genomics, transcriptomics, and proteomics have opened new windows on disease phenomena and may permit in the next future an effective development of novel diagnostic and prognostic medicine in order to better prevent or treat CD. This review will consider the current evidence of novel biomarkers with clear implications in the improvement of risk assessment, prevention strategies, and medical decision making in the field of CD. PMID:27298828

  17. Discovery of serum protein biomarkers in the mdx mouse model and cross-species comparison to Duchenne muscular dystrophy patients.

    PubMed

    Hathout, Yetrib; Marathi, Ramya L; Rayavarapu, Sree; Zhang, Aiping; Brown, Kristy J; Seol, Haeri; Gordish-Dressman, Heather; Cirak, Sebahattin; Bello, Luca; Nagaraju, Kanneboyina; Partridge, Terry; Hoffman, Eric P; Takeda, Shin'ichi; Mah, Jean K; Henricson, Erik; McDonald, Craig

    2014-12-15

    It is expected that serum protein biomarkers in Duchenne muscular dystrophy (DMD) will reflect disease pathogenesis, progression and aid future therapy developments. Here, we describe use of quantitative in vivo stable isotope labeling in mammals to accurately compare serum proteomes of wild-type and dystrophin-deficient mdx mice. Biomarkers identified in serum from two independent dystrophin-deficient mouse models (mdx-Δ52 and mdx-23) were concordant with those identified in sera samples of DMD patients. Of the 355 mouse sera proteins, 23 were significantly elevated and 4 significantly lower in mdx relative to wild-type mice (P-value < 0.001). Elevated proteins were mostly of muscle origin: including myofibrillar proteins (titin, myosin light chain 1/3, myomesin 3 and filamin-C), glycolytic enzymes (aldolase, phosphoglycerate mutase 2, beta enolase and glycogen phosphorylase), transport proteins (fatty acid-binding protein, myoglobin and somatic cytochrome-C) and others (creatine kinase M, malate dehydrogenase cytosolic, fibrinogen and parvalbumin). Decreased proteins, mostly of extracellular origin, included adiponectin, lumican, plasminogen and leukemia inhibitory factor receptor. Analysis of sera from 1 week to 7 months old mdx mice revealed age-dependent changes in the level of these biomarkers with most biomarkers acutely elevated at 3 weeks of age. Serum analysis of DMD patients, with ages ranging from 4 to 15 years old, confirmed elevation of 20 of the murine biomarkers in DMD, with similar age-related changes. This study provides a panel of biomarkers that reflect muscle activity and pathogenesis and should prove valuable tool to complement natural history studies and to monitor treatment efficacy in future clinical trials. PMID:25027324

  18. A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development.

    PubMed

    Perualila-Tan, Nolen; Kasim, Adetayo; Talloen, Willem; Verbist, Bie; Göhlmann, Hinrich W H; Shkedy, Ziv

    2016-08-01

    The modern drug discovery process involves multiple sources of high-dimensional data. This imposes the challenge of data integration. A typical example is the integration of chemical structure (fingerprint features), phenotypic bioactivity (bioassay read-outs) data for targets of interest, and transcriptomic (gene expression) data in early drug discovery to better understand the chemical and biological mechanisms of candidate drugs, and to facilitate early detection of safety issues prior to later and expensive phases of drug development cycles. In this paper, we discuss a joint model for the transcriptomic and the phenotypic variables conditioned on the chemical structure. This modeling approach can be used to uncover, for a given set of compounds, the association between gene expression and biological activity taking into account the influence of the chemical structure of the compound on both variables. The model allows to detect genes that are associated with the bioactivity data facilitating the identification of potential genomic biomarkers for compounds efficacy. In addition, the effect of every structural feature on both genes and pIC50 and their associations can be simultaneously investigated. Two oncology projects are used to illustrate the applicability and usefulness of the joint model to integrate multi-source high-dimensional information to aid drug discovery. PMID:27269248

  19. An evaluation of logic regression-based biomarker discovery across multiple intergenic regions for predicting host specificity in Escherichia coli.

    PubMed

    Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Banting, Graham; Edge, Thomas A; Topp, Edward; McAllister, Tim A; Neumann, Norman F

    2016-10-01

    Several studies have demonstrated that E. coli appears to display some level of host adaptation and specificity. Recent studies in our laboratory support these findings as determined by logic regression modeling of single nucleotide polymorphisms (SNP) in intergenic regions (ITGRs). We sought to determine the degree of host-specific information encoded in various ITGRs across a library of animal E. coli isolates using both whole genome analysis and a targeted ITGR sequencing approach. Our findings demonstrated that ITGRs across the genome encode various degrees of host-specific information. Incorporating multiple ITGRs (i.e., concatenation) into logic regression model building resulted in greater host-specificity and sensitivity outcomes in biomarkers, but the overall level of polymorphism in an ITGR did not correlate with the degree of host-specificity encoded in the ITGR. This suggests that distinct SNPs in ITGRs may be more important in defining host-specificity than overall sequence variation, explaining why traditional unsupervised learning phylogenetic approaches may be less informative in terms of revealing host-specific information encoded in DNA sequence. In silico analysis of 80 candidate ITGRs from publically available E. coli genomes was performed as a tool for discovering highly host-specific ITGRs. In one ITGR (ydeR-yedS) we identified a SNP biomarker that was 98% specific for cattle and for which 92% of all E. coli isolates originating from cattle carried this unique biomarker. In the case of humans, a host-specific biomarker (98% specificity) was identified in the concatenated ITGR sequences of rcsD-ompC, ydeR-yedS, and rclR-ykgE, and for which 78% of E. coli originating from humans carried this biomarker. Interestingly, human-specific biomarkers were dominant in ITGRs regulating antibiotic resistance, whereas in cattle host-specific biomarkers were found in ITGRs involved in stress regulation. These data suggest that evolution towards host

  20. An evaluation of logic regression-based biomarker discovery across multiple intergenic regions for predicting host specificity in Escherichia coli.

    PubMed

    Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Banting, Graham; Edge, Thomas A; Topp, Edward; McAllister, Tim A; Neumann, Norman F

    2016-10-01

    Several studies have demonstrated that E. coli appears to display some level of host adaptation and specificity. Recent studies in our laboratory support these findings as determined by logic regression modeling of single nucleotide polymorphisms (SNP) in intergenic regions (ITGRs). We sought to determine the degree of host-specific information encoded in various ITGRs across a library of animal E. coli isolates using both whole genome analysis and a targeted ITGR sequencing approach. Our findings demonstrated that ITGRs across the genome encode various degrees of host-specific information. Incorporating multiple ITGRs (i.e., concatenation) into logic regression model building resulted in greater host-specificity and sensitivity outcomes in biomarkers, but the overall level of polymorphism in an ITGR did not correlate with the degree of host-specificity encoded in the ITGR. This suggests that distinct SNPs in ITGRs may be more important in defining host-specificity than overall sequence variation, explaining why traditional unsupervised learning phylogenetic approaches may be less informative in terms of revealing host-specific information encoded in DNA sequence. In silico analysis of 80 candidate ITGRs from publically available E. coli genomes was performed as a tool for discovering highly host-specific ITGRs. In one ITGR (ydeR-yedS) we identified a SNP biomarker that was 98% specific for cattle and for which 92% of all E. coli isolates originating from cattle carried this unique biomarker. In the case of humans, a host-specific biomarker (98% specificity) was identified in the concatenated ITGR sequences of rcsD-ompC, ydeR-yedS, and rclR-ykgE, and for which 78% of E. coli originating from humans carried this biomarker. Interestingly, human-specific biomarkers were dominant in ITGRs regulating antibiotic resistance, whereas in cattle host-specific biomarkers were found in ITGRs involved in stress regulation. These data suggest that evolution towards host

  1. Salivary biomarkers for clinical applications.

    PubMed

    Zhang, Lei; Xiao, Hua; Wong, David T

    2009-01-01

    For clinical applications such as monitoring health status, disease onset and progression, and treatment outcome, there are three necessary prerequisites: (i) a simple method for collecting biologic samples, ideally noninvasively; (ii) specific biomarkers associated with health or disease; and (iii) a technology platform to rapidly utilize the biomarkers. Saliva, often regarded as the 'mirror of the body', is a perfect surrogate medium to be applied for clinical diagnostics. Saliva is readily accessible via a totally noninvasive method. Salivary biomarkers, whether produced by healthy individuals or by individuals affected by specific diseases, are sentinel molecules that could be used to scrutinize health and disease surveillance. The visionary investment by the US National Institute of Dental and Craniofacial Research, the discovery of salivary biomarkers, and the ongoing development of salivary diagnostic technologies have addressed its diagnostic value for clinical applications. The availability of more sophisticated analytic techniques gives optimism that saliva can eventually be placed as a biomedium for clinical diagnostics. This review presents current salivary biomarker research and technology developmental efforts for clinical applications.

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

    PubMed

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

    2016-03-01

    Many promising new cancer drugs proceed through preclinical testing and early-phase trials only to fail in late-stage clinical testing. Thus, improved models that better predict survival outcomes and enable the development of biomarkers are needed to identify patients most likely to respond to and benefit from therapy. Here, we describe a comprehensive approach in which we incorporated biobanking, xenografting, and multiplexed phospho-flow (PF) cytometric profiling to study drug response and identify predictive biomarkers in acute myeloid leukemia (AML) patients. To test the efficacy of our approach, we evaluated the investigational JAK2 inhibitor fedratinib (FED) in 64 patient samples. FED robustly reduced leukemia in mouse xenograft models in 59% of cases and was also effective in limiting the protumorigenic activity of leukemia stem cells as shown by serial transplantation assays. In parallel, PF profiling identified FED-mediated reduction in phospho-STAT5 (pSTAT5) levels as a predictive biomarker of in vivo drug response with high specificity (92%) and strong positive predictive value (93%). Unexpectedly, another JAK inhibitor, ruxolitinib (RUX), was ineffective in 8 of 10 FED-responsive samples. Notably, this outcome could be predicted by the status of pSTAT5 signaling, which was unaffected by RUX treatment. Consistent with this observed discrepancy, PF analysis revealed that FED exerted its effects through multiple JAK2-independent mechanisms. Collectively, this work establishes an integrated approach for testing novel anticancer agents that captures the inherent variability of response caused by disease heterogeneity and in parallel, facilitates the identification of predictive biomarkers that can help stratify patients into appropriate clinical trials. PMID:26833125

  3. Nonylphenol Toxicity Evaluation and Discovery of Biomarkers in Rat Urine by a Metabolomics Strategy through HPLC-QTOF-MS

    PubMed Central

    Zhang, Yan-Xin; Yang, Xin; Zou, Pan; Du, Peng-Fei; Wang, Jing; Jin, Fen; Jin, Mao-Jun; She, Yong-Xin

    2016-01-01

    Nonylphenol (NP) was quantified using liquid chromatography tandem mass spectrometry (LC-MS/MS) in the urine and plasma of rats treated with 0, 50, and 250 mg/kg/day of NP for four consecutive days. A urinary metabolomic strategy was originally implemented by high performance liquid chromatography time of flight mass spectrometry (HPLC-QTOF-MS) to explore the toxicological effects of NP and determine the overall alterations in the metabolite profiles so as to find potential biomarkers. It is essential to point out that from the observation, the metabolic data were clearly clustered and separated for the three groups. To further identify differentiated metabolites, multivariate analysis, including principal component analysis (PCA), orthogonal partial least-squares discriminant analysis (OPLS-DA), high-resolution MS/MS analysis, as well as searches of Metlin and Massbank databases, were conducted on a series of metabolites between the control and dose groups. Finally, five metabolites, including glycine, glycerophosphocholine, 5-hydroxytryptamine, malonaldehyde (showing an upward trend), and tryptophan (showing a downward trend), were identified as the potential urinary biomarkers of NP-induced toxicity. In order to validate the reliability of these potential biomarkers, an independent validation was performed by using the multiple reaction monitoring (MRM)-based targeted approach. The oxidative stress reflected by urinary 8-oxo-deoxyguanosine (8-oxodG) levels was elevated in individuals highly exposed to NP, supporting the hypothesis that mitochondrial dysfunction was a result of xenoestrogen accumulation. This study reveals a promising approach to find biomarkers to assist researchers in monitoring NP. PMID:27187439

  4. Metabolic profiling of yeast culture using gas chromatography coupled with orthogonal acceleration accurate mass time-of-flight mass spectrometry: application to biomarker discovery.

    PubMed

    Kondo, Elsuida; Marriott, Philip J; Parker, Rhiannon M; Kouremenos, Konstantinos A; Morrison, Paul; Adams, Mike

    2014-01-01

    Yeast and yeast cultures are frequently used as additives in diets of dairy cows. Beneficial effects from the inclusion of yeast culture in diets for dairy mammals have been reported, and the aim of this study was to develop a comprehensive analytical method for the accurate mass identification of the 'global' metabolites in order to differentiate a variety of yeasts at varying growth stages (Diamond V XP, Yea-Sacc and Levucell). Microwave-assisted derivatization for metabolic profiling is demonstrated through the analysis of differing yeast samples developed for cattle feed, which include a wide range of metabolites of interest covering a large range of compound classes. Accurate identification of the components was undertaken using GC-oa-ToFMS (gas chromatography-orthogonal acceleration-time-of-flight mass spectrometry), followed by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for data reduction and biomarker discovery. Semi-quantification (fold changes in relative peak areas) was reported for metabolites identified as possible discriminative biomarkers (p-value <0.05, fold change >2), including D-ribose (four fold decrease), myo-inositol (five fold increase), L-phenylalanine (three fold increase), glucopyranoside (two fold increase), fructose (three fold increase) and threitol (three fold increase) respectively. PMID:24356230

  5. Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity.

    PubMed

    Li, Zuojing; Li, Qing; Geng, Lulu; Chen, Xiaohui; Bi, Kaishun

    2013-01-01

    Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR) and HPLC/MS (high-performance liquid chromatography with mass spectrometry). Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR) is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF) treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA), LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

  6. A Multidisciplinary Biospecimen Bank of Renal Cell Carcinomas Compatible with Discovery Platforms at Mayo Clinic, Scottsdale, Arizona.

    PubMed

    Ho, Thai H; Nateras, Rafael Nunez; Yan, Huihuang; Park, Jin G; Jensen, Sally; Borges, Chad; Lee, Jeong Heon; Champion, Mia D; Tibes, Raoul; Bryce, Alan H; Carballido, Estrella M; Todd, Mark A; Joseph, Richard W; Wong, William W; Parker, Alexander S; Stanton, Melissa L; Castle, Erik P

    2015-01-01

    To address the need to study frozen clinical specimens using next-generation RNA, DNA, chromatin immunoprecipitation (ChIP) sequencing and protein analyses, we developed a biobank work flow to prospectively collect biospecimens from patients with renal cell carcinoma (RCC). We describe our standard operating procedures and work flow to annotate pathologic results and clinical outcomes. We report quality control outcomes and nucleic acid yields of our RCC submissions (N=16) to The Cancer Genome Atlas (TCGA) project, as well as newer discovery platforms, by describing mass spectrometry analysis of albumin oxidation in plasma and 6 ChIP sequencing libraries generated from nephrectomy specimens after histone H3 lysine 36 trimethylation (H3K36me3) immunoprecipitation. From June 1, 2010, through January 1, 2013, we enrolled 328 patients with RCC. Our mean (SD) TCGA RNA integrity numbers (RINs) were 8.1 (0.8) for papillary RCC, with a 12.5% overall rate of sample disqualification for RIN <7. Banked plasma had significantly less albumin oxidation (by mass spectrometry analysis) than plasma kept at 25 °C (P<.001). For ChIP sequencing, the FastQC score for average read quality was at least 30 for 91% to 95% of paired-end reads. In parallel, we analyzed frozen tissue by RNA sequencing; after genome alignment, only 0.2% to 0.4% of total reads failed the default quality check steps of Bowtie2, which was comparable to the disqualification ratio (0.1%) of the 786-O RCC cell line that was prepared under optimal RNA isolation conditions. The overall correlation coefficients for gene expression between Mayo Clinic vs TCGA tissues ranged from 0.75 to 0.82. These data support the generation of high-quality nucleic acids for genomic analyses from banked RCC. Importantly, the protocol does not interfere with routine clinical care. Collections over defined time points during disease treatment further enhance collaborative efforts to integrate genomic information with outcomes.

  7. A Multidisciplinary Biospecimen Bank of Renal Cell Carcinomas Compatible with Discovery Platforms at Mayo Clinic, Scottsdale, Arizona

    PubMed Central

    Ho, Thai H.; Nateras, Rafael Nunez; Yan, Huihuang; Park, Jin G.; Jensen, Sally; Borges, Chad; Lee, Jeong Heon; Champion, Mia D.; Tibes, Raoul; Bryce, Alan H.; Carballido, Estrella M.; Todd, Mark A.; Joseph, Richard W.; Wong, William W.; Parker, Alexander S.; Stanton, Melissa L.; Castle, Erik P.

    2015-01-01

    To address the need to study frozen clinical specimens using next-generation RNA, DNA, chromatin immunoprecipitation (ChIP) sequencing and protein analyses, we developed a biobank work flow to prospectively collect biospecimens from patients with renal cell carcinoma (RCC). We describe our standard operating procedures and work flow to annotate pathologic results and clinical outcomes. We report quality control outcomes and nucleic acid yields of our RCC submissions (N=16) to The Cancer Genome Atlas (TCGA) project, as well as newer discovery platforms, by describing mass spectrometry analysis of albumin oxidation in plasma and 6 ChIP sequencing libraries generated from nephrectomy specimens after histone H3 lysine 36 trimethylation (H3K36me3) immunoprecipitation. From June 1, 2010, through January 1, 2013, we enrolled 328 patients with RCC. Our mean (SD) TCGA RNA integrity numbers (RINs) were 8.1 (0.8) for papillary RCC, with a 12.5% overall rate of sample disqualification for RIN <7. Banked plasma had significantly less albumin oxidation (by mass spectrometry analysis) than plasma kept at 25°C (P<.001). For ChIP sequencing, the FastQC score for average read quality was at least 30 for 91% to 95% of paired-end reads. In parallel, we analyzed frozen tissue by RNA sequencing; after genome alignment, only 0.2% to 0.4% of total reads failed the default quality check steps of Bowtie2, which was comparable to the disqualification ratio (0.1%) of the 786-O RCC cell line that was prepared under optimal RNA isolation conditions. The overall correlation coefficients for gene expression between Mayo Clinic vs TCGA tissues ranged from 0.75 to 0.82. These data support the generation of high-quality nucleic acids for genomic analyses from banked RCC. Importantly, the protocol does not interfere with routine clinical care. Collections over defined time points during disease treatment further enhance collaborative efforts to integrate genomic information with outcomes. PMID

  8. Phospholipid fatty acid biomarkers in a freshwater periphyton community exposed to uranium: discovery by non-linear statistical learning

    SciTech Connect

    Webb-Robertson, Bobbie-Jo M.; Bunn, Amoret L.; Bailey, Vanessa L.

    2011-01-01

    Phospholipid fatty acids (PLFA) have been widely used to characterize environmental microbial communities, generating community profiles that can distinguish phylogenetic or functional groups within the community. The poor specificity of organism groups with fatty acid biomarkers in the classic PLFA-microorganism associations is a confounding factor in many of the statistical classification/clustering approaches traditionally used to interpret PLFA profiles. In this paper we demonstrate that non-linear statistical learning methods, such as a support vector machine (SVM), can more accurately find patterns related to uranyl nitrate exposure in a freshwater periphyton community than linear methods, such as partial least squares discriminant analysis. In addition, probabilistic models of exposure can be derived from the identified lipid biomarkers to demonstrate the potential model-based approach that could be used in remediation. The SVM probability model separates dose groups at accuracies of ~87.0%, ~71.4%, ~87.5%, and 100% for the four groups; Control (non-amended system), low-dose (amended at 10 µg U L-1), medium dose (amended at 100 µg U L-1), and high dose (500 µg U L-1). The SVM model achieved an overall cross-validated classification accuracy of ~87% in contrast to ~59% for the best linear classifier.

  9. Differential integrative omic analysis for mechanism insights and biomarker discovery of abnormal Savda syndrome and its unique Munziq prescription.

    PubMed

    Guo, Xia; Bakri, Iskandar; Abudula, Abulizi; Arken, Kalbinur; Mijit, Mahmut; Mamtimin, Batur; Upur, Halmurat

    2016-01-01

    Research has shown that many cancers have acommon pathophysiological origin and often present with similar symptoms. In terms of Traditional Uighur Medicine (TUM) Hilit (body fluid) theory, abnormal Savda syndrome (ASS) formed by abnormal Hilit is the common phenotype of complex diseases and in particular tumours. Abnormal Savda Munziq (ASMq), one representative of TUM, has been effective in the treatment of cancer since ancient times. Despite the physiopathology of ASS, the relationship between causative factors and the molecular mechanism of ASMq are not fully understood. The current study expanded upon earlier work by integrating traditional diagnostic approaches with others utilizing systems biology technology for the analysis of proteomic (iTRAQ) and metabolomic ((1)H-NMR) profiles of Uighur Medicine target organ lesion (liver) tumours. The candidate proteins were analyzed by enrichment analysis of the biological process and biomarker filters. Subsequently, 3Omics web-based tools were used to determine the relationships between proteins and appropriate metabolites. ELISA assay and IHC methods were used to verify the proteomic result; the protein von Willebrand factor (vWF) may be the "therapeutic window" of ASMq and biomarkers of ASS. This study is likely to be of great significance for the standardization and modernization of TUM. PMID:27296761

  10. Discovery of SLC3A2 Cell Membrane Protein as a Potential Gastric Cancer Biomarker: Implications in Molecular Imaging

    PubMed Central

    Yang, Yixuan; Toy, Weiyi; Choong, Lee Yee; Hou, Peiling; Ashktorab, Hassan; Smoot, Duane T; Yeoh, Khay Guan; Lim, Yoon Pin

    2013-01-01

    Despite decreasing incidence and mortality, gastric cancer remains the second leading cause of cancer-related deaths in the world. Successful management of gastric cancer is hampered by lack of highly sensitive and specific biomarkers especially for early cancer detection. Cell surface proteins that are aberrantly expressed between normal and cancer cells are potentially useful for cancer imaging and therapy due to easy accessibility of these targets. Combining two-phase partition and isobaric tags for relative and absolute quantification methods, we compared the relative expression levels of membrane proteins between noncancer and gastric cancer cells. About 33% of the data set was found to be plasma membrane and associated proteins using this approach (compared to only 11% in whole cell analysis), several of which have never been previously implicated in gastric cancer. Upregulation of SLC3A2 in gastric cancer cells was validated by immunoblotting of a panel of 13 gastric cancer cell lines and immunohistochemistry on tissue microarrays comprising 85 matched pairs of normal and tumor tissues. Immunofluorescence and immunohistochemistry both confirmed the plasma membrane localization of SLC3A2 in gastric cancer cells. The data supported the notion that SLC3A2 is a potential biomarker that could be exploited for molecular imaging-based detection of gastric cancer. PMID:23116296

  11. Differential integrative omic analysis for mechanism insights and biomarker discovery of abnormal Savda syndrome and its unique Munziq prescription

    PubMed Central

    Guo, Xia; Bakri, Iskandar; Abudula, Abulizi; Arken, Kalbinur; Mijit, Mahmut; Mamtimin, Batur; Upur, Halmurat

    2016-01-01

    Research has shown that many cancers have acommon pathophysiological origin and often present with similar symptoms. In terms of Traditional Uighur Medicine (TUM) Hilit (body fluid) theory, abnormal Savda syndrome (ASS) formed by abnormal Hilit is the common phenotype of complex diseases and in particular tumours. Abnormal Savda Munziq (ASMq), one representative of TUM, has been effective in the treatment of cancer since ancient times. Despite the physiopathology of ASS, the relationship between causative factors and the molecular mechanism of ASMq are not fully understood. The current study expanded upon earlier work by integrating traditional diagnostic approaches with others utilizing systems biology technology for the analysis of proteomic (iTRAQ) and metabolomic (1H-NMR) profiles of Uighur Medicine target organ lesion (liver) tumours. The candidate proteins were analyzed by enrichment analysis of the biological process and biomarker filters. Subsequently, 3Omics web-based tools were used to determine the relationships between proteins and appropriate metabolites. ELISA assay and IHC methods were used to verify the proteomic result; the protein von Willebrand factor (vWF) may be the “therapeutic window” of ASMq and biomarkers of ASS. This study is likely to be of great significance for the standardization and modernization of TUM. PMID:27296761

  12. Zebrafish swimming behavior as a biomarker for ototoxicity-induced hair cell damage: a high-throughput drug development platform targeting hearing loss.

    PubMed

    Niihori, Maki; Platto, Terry; Igarashi, Suzu; Hurbon, Audriana; Dunn, Allison M; Tran, Phi; Tran, Hung; Mudery, Jordan A; Slepian, Marvin J; Jacob, Abraham

    2015-11-01

    Hearing loss is one of the most common human sensory disabilities, adversely affecting communication, socialization, mood, physical functioning, and quality of life. In addition to age and noise-induced damage, ototoxicity is a common cause of sensorineural hearing loss with chemotherapeutic agents, for example, cisplatin, being a major contributor. Zebrafish (Danio rerio) are an excellent model to study hearing loss as they have neurosensory hair cells on their body surface that are structurally similar to those within the human inner ear. Anatomic assays of toxin-mediated hair cell damage in zebrafish have been established; however, using fish swimming behavior--rheotaxis--as a biomarker for this anatomic damage was only recently described. We hypothesized that, in parallel, multilane measurements of rheotaxis could be used to create a high-throughput platform for drug development assessing both ototoxic and potentially otoprotective compounds in real time. Such a device was created, and results demonstrated a clear dose response between cisplatin exposure, progressive hair cell damage, and reduced rheotaxis in zebrafish. Furthermore, pre-exposure to the otoprotective medication dexamethasone, before cisplatin exposure, partially rescued rheotaxis swimming behavior and hair cell integrity. These results provide the first evidence that rescued swimming behavior can serve as a biomarker for rescued hair cell function. Developing a drug against hearing loss represents an unmet clinical need with global implications. Because hearing loss from diverse etiologies may result from common end-effects at the hair cell level, lessons learned from the present study may be broadly used.

  13. Discovery and Validation of Prognostic Biomarker Models to Guide Triage among Adult Dengue Patients at Early Infection

    PubMed Central

    Tolfvenstam, Thomas; Thein, Tun-Linn; Naim, Ahmad Nazri Mohamed; Ling, Ling; Chow, Angelia; Chen, Mark I-Cheng; Ooi, Eng Eong; Leo, Yee Sin; Hibberd, Martin L.

    2016-01-01

    Background Dengue results in a significant public health burden in endemic regions. The World Health Organization (WHO) recommended the use of warning signs (WS) to stratify patients at risk of severe dengue disease in 2009. However, WS is limited in stratifying adult dengue patients at early infection (Day 1–3 post fever), who require close monitoring in hospitals to prevent severe dengue. The aim of this study is to identify and validate prognostic models, built with differentially expressed biomarkers, that enable the early identification of those with early dengue infection that require close clinical monitoring. Methods RNA microarray and protein assays were performed to identify differentially expressed biomarkers of severity among 92 adult dengue patients recruited at early infection from years 2005–2008. This comprised 47 cases who developed WS after first presentation and required hospitalization (WS+Hosp), as well as 45 controls who did not develop WS after first presentation and did not require hospitalization (Non-WS+Non-Hosp). Independent validation was conducted with 80 adult dengue patients recruited from years 2009–2012. Prognostic models were developed based on forward stepwise and backward elimination estimation, using multiple logistic regressions. Prognostic power was estimated by the area under the receiver operating characteristic curve (AUC). Results The WS+Hosp group had significantly higher viral load (P<0.001), lower platelet (P<0.001) and lymphocytes counts (P = 0.004) at early infection compared to the Non-WS+Non-Hosp group. From the RNA microarray and protein assays, the top single RNA and protein prognostic models at early infection were CCL8 RNA (AUC:0.73) and IP-10 protein (AUC:0.74), respectively. The model with CCL8, VPS13C RNA, uPAR protein, and with CCL8, VPS13C RNA and platelets were the best biomarker models for stratifying adult dengue patients at early infection, with sensitivity and specificity up to 83% and 84

  14. Academic College of Emergency Experts in India's INDO-US Joint Working Group and OPUS12 Foundation Consensus Statement on Creating A Coordinated, Multi-Disciplinary, Patient-Centered, Global Point-of-Care Biomarker Discovery Network

    PubMed Central

    Stawicki, Stanislaw P.; Stoltzfus, Jill C.; Aggarwal, Praveen; Bhoi, Sanjeev; Bhatt, Shashi; Kalra, O. P.; Bhalla, Ashish; Hoey, Brian A.; Galwankar, Sagar C.; Paladino, Lorenzo; Papadimos, Thomas J.

    2014-01-01

    Biomarker science brings great promise to clinical medicine. This is especially true in the era of technology miniaturization, rapid dissemination of knowledge, and point-of-care (POC) implementation of novel diagnostics. Despite this tremendous progress, the journey from a candidate biomarker to a scientifically validated biomarker continues to be an arduous one. In addition to substantial financial resources, biomarker research requires considerable expertise and a multidisciplinary approach. Investigational designs must also be taken into account, with the randomized controlled trial remaining the “gold standard”. The authors present a condensed overview of biomarker science and associated investigational methods, followed by specific examples from clinical areas where biomarker development and/or implementation resulted in tangible enhancements in patient care. This manuscript also serves as a call to arms for the establishment of a truly global, well-coordinated infrastructure dedicated to biomarker research and development, with focus on delivery of the latest discoveries directly to the patient via point-of-care technology. PMID:25337481

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  17. SELDI-TOF MS-based discovery of a biomarker in Cucumis sativus seeds exposed to CuO nanoparticles.

    PubMed

    Moon, Young-Sun; Park, Eun-Sil; Kim, Tae-Oh; Lee, Hoi-Seon; Lee, Sung-Eun

    2014-11-01

    Metal oxide nanoparticles (NPs) can inhibit plant seed germination and root elongation via the release of metal ions. In the present study, two acute phytotoxicity tests, seed germination and root elongation tests, were conducted on cucumber seeds (Cucumis sativus) treated with bulk copper oxide (CuO) and CuO NPs. Two concentrations of bulk CuO and CuO NPs, 200 and 600ppm, were used to test the inhibition rate of root germination; both concentrations of bulk CuO weakly inhibited seed germination, whereas CuO NPs significantly inhibited germination, showing a low germination rate of 23.3% at 600ppm. Root elongation tests demonstrated that CuO NPs were much stronger inhibitors than bulk CuO. SELDI-TOF MS analysis showed that 34 proteins were differentially expressed in cucumber seeds after exposure to CuO NPs, with the expression patterns of at least 9 proteins highly differing from those in seeds treated with bulk CuO and in control plants. Therefore, these 9 proteins were used to identify CuO NP-specific biomarkers in cucumber plants exposed to CuO NPs. A 5977-m/z protein was the most distinguishable biomarker for determining phytotoxicity by CuO NPs. Principal component analysis (PCA) of the SELDI-TOF MS results showed variability in the modes of inhibitory action on cucumber seeds and roots. To our knowledge, this is the first study to demonstrate that the phytotoxic effect of metal oxide NPs on plants is not caused by the same mode of action as other toxins.

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

    PubMed Central

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

    2015-01-01

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

  19. Highly sensitive electrochemiluminescenc assay of acetylcholinesterase activity based on dual biomarkers using Pd-Au nanowires as immobilization platform.

    PubMed

    Ye, Cui; Wang, Min-Qiang; Zhong, Xia; Chen, Shihong; Chai, Yaqin; Yuan, Ruo

    2016-05-15

    One-dimensional Pd-Au nanowires (Pd-Au NWs) were prepared and applied to fabricate an electrochemiluminescence (ECL) biosensor for the detection of acetylcholinesterase (AChE) activity. Compared with single-component of Pd or Au, the bimetallic nanocomposite of Pd-Au NWs offers a larger surface area for the immobilization of enzyme, and displays superior electrocatalytic activity and efficient electron transport capacity. In the presence of AChE and choline oxidase (ChOx), acetylcholine (ATCl) is hydrolyzed by AChE to generate thiocholine, then thiocholine is catalyzed by ChOx to produce H2O2 in situ, which serves as the coreactant to effectively enhance the ECL intensity in luminol-ECL system. The detection principle is based on the inhibited AChE and reactivated AChE as dual biomarkers, in which AChE was inhibited by organophosphorus (OP) agents, and then reactivated by obidoxime. Such dual biomarkers method can achieve credible evaluation for AChE activity via providing AChE activity before and after reactivation. The liner range for AChE activity detection was from 0.025 U L(-1) to 25 KU L(-1) with a low detection limit down to 0.0083 U L(-1). PMID:26686921

  20. Highly sensitive electrochemiluminescenc assay of acetylcholinesterase activity based on dual biomarkers using Pd-Au nanowires as immobilization platform.

    PubMed

    Ye, Cui; Wang, Min-Qiang; Zhong, Xia; Chen, Shihong; Chai, Yaqin; Yuan, Ruo

    2016-05-15

    One-dimensional Pd-Au nanowires (Pd-Au NWs) were prepared and applied to fabricate an electrochemiluminescence (ECL) biosensor for the detection of acetylcholinesterase (AChE) activity. Compared with single-component of Pd or Au, the bimetallic nanocomposite of Pd-Au NWs offers a larger surface area for the immobilization of enzyme, and displays superior electrocatalytic activity and efficient electron transport capacity. In the presence of AChE and choline oxidase (ChOx), acetylcholine (ATCl) is hydrolyzed by AChE to generate thiocholine, then thiocholine is catalyzed by ChOx to produce H2O2 in situ, which serves as the coreactant to effectively enhance the ECL intensity in luminol-ECL system. The detection principle is based on the inhibited AChE and reactivated AChE as dual biomarkers, in which AChE was inhibited by organophosphorus (OP) agents, and then reactivated by obidoxime. Such dual biomarkers method can achieve credible evaluation for AChE activity via providing AChE activity before and after reactivation. The liner range for AChE activity detection was from 0.025 U L(-1) to 25 KU L(-1) with a low detection limit down to 0.0083 U L(-1).

  1. Ratiometric fluorescence transduction by hybridization after isothermal amplification for determination of zeptomole quantities of oligonucleotide biomarkers with a paper-based platform and camera-based detection.

    PubMed

    Noor, M Omair; Hrovat, David; Moazami-Goudarzi, Maryam; Espie, George S; Krull, Ulrich J

    2015-07-23

    Paper is a promising platform for the development of decentralized diagnostic assays owing to the low cost and ease of use of paper-based analytical devices (PADs). It can be challenging to detect on PADs very low concentrations of nucleic acid biomarkers of lengths as used in clinical assays. Herein we report the use of thermophilic helicase-dependent amplification (tHDA) in combination with a paper-based platform for fluorescence detection of probe-target hybridization. Paper substrates were patterned using wax printing. The cellulosic fibers were chemically derivatized with imidazole groups for the assembly of the transduction interface that consisted of immobilized quantum dot (QD)-probe oligonucleotide conjugates. Green-emitting QDs (gQDs) served as donors with Cy3 as the acceptor dye in a fluorescence resonance energy transfer (FRET)-based transduction method. After probe-target hybridization, a further hybridization event with a reporter sequence brought the Cy3 acceptor dye in close proximity to the surface of immobilized gQDs, triggering a FRET sensitized emission that served as an analytical signal. Ratiometric detection was evaluated using both an epifluorescence microscope and a low-cost iPad camera as detectors. Addition of the tHDA method for target amplification to produce sequences of ∼100 base length allowed for the detection of zmol quantities of nucleic acid targets using the two detection platforms. The ratiometric QD-FRET transduction method not only offered improved assay precision, but also lowered the limit of detection of the assay when compared with the non-ratiometric QD-FRET transduction method. The selectivity of the hybridization assays was demonstrated by the detection of single nucleotide polymorphism.

  2. Biomarkers of safety and immune protection for genetically modified live attenuated leishmania vaccines against visceral leishmaniasis - discovery and implications.

    PubMed

    Gannavaram, Sreenivas; Dey, Ranadhir; Avishek, Kumar; Selvapandiyan, Angamuthu; Salotra, Poonam; Nakhasi, Hira L

    2014-01-01

    Despite intense efforts there is no safe and efficacious vaccine against visceral leishmaniasis, which is fatal and endemic in many tropical countries. A major shortcoming in the vaccine development against blood-borne parasitic agents such as Leishmania is the inadequate predictive power of the early immune responses mounted in the host against the experimental vaccines. Often immune correlates derived from in-bred animal models do not yield immune markers of protection that can be readily extrapolated to humans. The limited efficacy of vaccines based on DNA, subunit, heat killed parasites has led to the realization that acquisition of durable immunity against the protozoan parasites requires a controlled infection with a live attenuated organism. Recent success of irradiated malaria parasites as a vaccine candidate further strengthens this approach to vaccination. We developed several gene deletion mutants in Leishmania donovani as potential live attenuated vaccines and reported extensively on the immunogenicity of LdCentrin1 deleted mutant in mice, hamsters, and dogs. Additional limited studies using genetically modified live attenuated Leishmania parasites as vaccine candidates have been reported. However, for the live attenuated parasite vaccines, the primary barrier against widespread use remains the absence of clear biomarkers associated with protection and safety. Recent studies in evaluation of vaccines, e.g., influenza and yellow fever vaccines, using systems biology tools demonstrated the power of such strategies in understanding the immunological mechanisms that underpin a protective phenotype. Applying similar tools in isolated human tissues such as PBMCs from healthy individuals infected with live attenuated parasites such as LdCen(-/-) in vitro followed by human microarray hybridization experiments will enable us to understand how early vaccine-induced gene expression profiles and the associated immune responses are coordinately regulated in normal

  3. Breast Cancer Biomarker Discovery in the Functional Genomic Age: A Systematic Review of 42 Gene Expression Signatures

    PubMed Central

    Abba, M.C; Lacunza, E; Butti, M; Aldaz, C.M

    2010-01-01

    In this review we provide a systematic analysis of transcriptomic signatures derived from 42 breast cancer gene expression studies, in an effort to identify the most relevant breast cancer biomarkers using a meta-analysis method. Meta-data revealed a set of 117 genes that were the most commonly affected ranging from 12% to 36% of overlap among breast cancer gene expression studies. Data mining analysis of transcripts and protein-protein interactions of these commonly modulated genes indicate three functional modules significantly affected among signatures, one module related with the response to steroid hormone stimulus, and two modules related to the cell cycle. Analysis of a publicly available gene expression data showed that the obtained meta-signature is capable of predicting overall survival (P < 0.0001) and relapse-free survival (P < 0.0001) in patients with early-stage breast carcinomas. In addition, the identified meta-signature improves breast cancer patient stratification independently of traditional prognostic factors in a multivariate Cox proportional-hazards analysis. PMID:21082037

  4. Metabolomics-Based Discovery of Small Molecule Biomarkers in Serum Associated with Dengue Virus Infections and Disease Outcomes

    PubMed Central

    Voge, Natalia V.; Perera, Rushika; Mahapatra, Sebabrata; Gresh, Lionel; Balmaseda, Angel; Loroño-Pino, María A.; Hopf-Jannasch, Amber S.; Belisle, John T.; Harris, Eva; Blair, Carol D.; Beaty, Barry J.

    2016-01-01

    Background Epidemic dengue fever (DF) and dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS) are overwhelming public health capacity for diagnosis and clinical care of dengue patients throughout the tropical and subtropical world. The ability to predict severe dengue disease outcomes (DHF/DSS) using acute phase clinical specimens would be of enormous value to physicians and health care workers for appropriate triaging of patients for clinical management. Advances in the field of metabolomics and analytic software provide new opportunities to identify host small molecule biomarkers (SMBs) in acute phase clinical specimens that differentiate dengue disease outcomes. Methodology/Principal Findings Exploratory metabolomic studies were conducted to characterize the serum metabolome of patients who experienced different dengue disease outcomes. Serum samples from dengue patients from Nicaragua and Mexico were retrospectively obtained, and hydrophilic interaction liquid chromatography (HILIC)-mass spectrometry (MS) identified small molecule metabolites that were associated with and statistically differentiated DHF/DSS, DF, and non-dengue (ND) diagnosis groups. In the Nicaraguan samples, 191 metabolites differentiated DF from ND outcomes and 83 differentiated DHF/DSS and DF outcomes. In the Mexican samples, 306 metabolites differentiated DF from ND and 37 differentiated DHF/DSS and DF outcomes. The structural identities of 13 metabolites were confirmed using tandem mass spectrometry (MS/MS). Metabolomic analysis of serum samples from patients diagnosed as DF who progressed to DHF/DSS identified 65 metabolites that predicted dengue disease outcomes. Differential perturbation of the serum metabolome was demonstrated following infection with different DENV serotypes and following primary and secondary DENV infections. Conclusions/Significance These results provide proof-of-concept that a metabolomics approach can be used to identify metabolites or SMBs in serum

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

    PubMed Central

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

    2016-01-01

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

  6. Using reverse-phase protein arrays as pharmacodynamic assays for functional proteomics, biomarker discovery, and drug development in cancer.

    PubMed

    Lu, Yiling; Ling, Shiyun; Hegde, Apurva M; Byers, Lauren A; Coombes, Kevin; Mills, Gordon B; Akbani, Rehan

    2016-08-01

    The majority of the targeted therapeutic agents in clinical use target proteins and protein function. Although DNA and RNA analyses have been used extensively to identify novel targets and patients likely to benefit from targeted therapies, these are indirect measures of the levels and functions of most therapeutic targets. More importantly, DNA and RNA analysis is ill-suited for determining the pharmacodynamic effects of target inhibition. Assessing changes in protein levels and function is the most efficient way to evaluate the mechanisms underlying sensitivity and resistance to targeted agents. Understanding these mechanisms is necessary to identify patients likely to benefit from treatment and to develop rational drug combinations to prevent or bypass therapeutic resistance. There is an urgent need for a robust approach to assess protein levels and protein function in model systems and across patient samples. While "shot gun" mass spectrometry can provide in-depth analysis of proteins across a limited number of samples, and emerging approaches such as multiple reaction monitoring have the potential to analyze candidate markers, mass spectrometry has not entered into general use because of the high cost, requirement of extensive analysis and support, and relatively large amount of material needed for analysis. Rather, antibody-based technologies, including immunohistochemistry, radioimmunoassays, enzyme-linked immunosorbent assays (ELISAs), and more recently protein arrays, remain the most common approaches for multiplexed protein analysis. Reverse-phase protein array (RPPA) technology has emerged as a robust, sensitive, cost-effective approach to the analysis of large numbers of samples for quantitative assessment of key members of functional pathways that are affected by tumor-targeting therapeutics. The RPPA platform is a powerful approach for identifying and validating targets, classifying tumor subsets, assessing pharmacodynamics, and identifying prognostic

  7. Biomarker discovery to improve prediction of breast cancer survival: using gene expression profiling, meta-analysis, and tissue validation

    PubMed Central

    Meng, Liwei; Xu, Yingchun; Xu, Chaoyang; Zhang, Wei

    2016-01-01

    approach, we have identified a three-gene signature with independent prognostic impact. Furthermore, CLDN11 may offer a biomarker to predict prognosis as well as a new target for prognostic and therapeutic intervention for human breast IDC. PMID:27785066

  8. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

    PubMed

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org.

  9. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

    PubMed

    Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. PMID:26989145

  10. An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

    PubMed Central

    Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

    2016-01-01

    Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

  11. ICan: An Optimized Ion-Current-Based Quantification Procedure with Enhanced Quantitative Accuracy and Sensitivity in Biomarker Discovery

    PubMed Central

    2015-01-01

    The rapidly expanding availability of high-resolution mass spectrometry has substantially enhanced the ion-current-based relative quantification techniques. Despite the increasing interest in ion-current-based methods, quantitative sensitivity, accuracy, and false discovery rate remain the major concerns; consequently, comprehensive evaluation and development in these regards are urgently needed. Here we describe an integrated, new procedure for data normalization and protein ratio estimation, termed ICan, for improved ion-current-based analysis of data generated by high-resolution mass spectrometry (MS). ICan achieved significantly better accuracy and precision, and lower false-positive rate for discovering altered proteins, over current popular pipelines. A spiked-in experiment was used to evaluate the performance of ICan to detect small changes. In this study E. coli extracts were spiked with moderate-abundance proteins from human plasma (MAP, enriched by IgY14-SuperMix procedure) at two different levels to set a small change of 1.5-fold. Forty-five (92%, with an average ratio of 1.71 ± 0.13) of 49 identified MAP protein (i.e., the true positives) and none of the reference proteins (1.0-fold) were determined as significantly altered proteins, with cutoff thresholds of ≥1.3-fold change and p ≤ 0.05. This is the first study to evaluate and prove competitive performance of the ion-current-based approach for assigning significance to proteins with small changes. By comparison, other methods showed remarkably inferior performance. ICan can be broadly applicable to reliable and sensitive proteomic survey of multiple biological samples with the use of high-resolution MS. Moreover, many key features evaluated and optimized here such as normalization, protein ratio determination, and statistical analyses are also valuable for data analysis by isotope-labeling methods. PMID:25285707

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

    PubMed

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

    2016-01-01

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

  13. Discovery and analysis of time delay sources in the USGS personal computer data collection platform (PCDCP) system

    USGS Publications Warehouse

    White, Timothy C.; Sauter, Edward A.; Stewart, Duff C.

    2014-01-01

    Intermagnet is an international oversight group which exists to establish a global network for geomagnetic observatories. This group establishes data standards and standard operating procedures for members and prospective members. Intermagnet has proposed a new One-Second Data Standard, for that emerging geomagnetic product. The standard specifies that all data collected must have a time stamp accuracy of ±10 milliseconds of the top-of-the-second Coordinated Universal Time. Therefore, the U.S. Geological Survey Geomagnetism Program has designed and executed several tests on its current data collection system, the Personal Computer Data Collection Platform. Tests are designed to measure the time shifts introduced by individual components within the data collection system, as well as to measure the time shift introduced by the entire Personal Computer Data Collection Platform. Additional testing designed for Intermagnet will be used to validate further such measurements. Current results of the measurements showed a 5.0–19.9 millisecond lag for the vertical channel (Z) of the Personal Computer Data Collection Platform and a 13.0–25.8 millisecond lag for horizontal channels (H and D) of the collection system. These measurements represent a dynamically changing delay introduced within the U.S. Geological Survey Personal Computer Data Collection Platform.

  14. Quick identification of xanthine oxidase inhibitor and antioxidant from Erycibe obtusifolia by a drug discovery platform composed of multiple mass spectrometric platforms and thin-layer chromatography bioautography.

    PubMed

    Chen, Zhiyong; Tao, Hongxun; Liao, Liping; Zhang, Zijia; Wang, Zhengtao

    2014-08-01

    As a final step of the purine metabolism process, xanthine oxidase catalyzes the oxidation of hypoxanthine and xanthine into uric acid. Our research has demonstrated that Erycibe obtusifolia has xanthine oxidase inhibitory properties. The purpose of this paper is to describe a new strategy based on a combination of multiple mass spectrometric platforms and thin-layer chromatography bioautography for effectively screening the xanthine oxidase inhibitory and antioxidant properties of E. obtusifolia. This strategy was accomplished through the following steps. (i) Separate the extract of E. obtusifolia into fractions by an autopurification system controlled by liquid chromatography with mass spectrometry. (ii) Determine the active fractions of E. obtusifolia by thin-layer chromatography bioautography. (iii) Identify the structure of the main active compounds with the information provided by direct analysis in real time mass spectrometry. (iv) Calculate the IC50 value of each compound against xanthine oxidase using high-performance liquid chromatography. Using the caulis of E. obtusifolia as the experimental material, seven target peaks were screened out as xanthine oxidase inhibitors or antioxidants. Our screening strategy allows for rapid analysis of small molecules with almost no sample preparation and can be completed within a week, making it a useful assay to identify unstable compounds and provide the empirical foundation for E. obtusifolia as a natural remedy for gout and oxidative-stress-related diseases.

  15. An in vivo large-scale chemical screening platform using Drosophila for anti-cancer drug discovery

    PubMed Central

    Willoughby, Lee F.; Schlosser, Tanja; Manning, Samuel A.; Parisot, John P.; Street, Ian P.; Richardson, Helena E.; Humbert, Patrick O.; Brumby, Anthony M.

    2013-01-01

    SUMMARY Anti-cancer drug development involves enormous expenditure and risk. For rapid and economical identification of novel, bioavailable anti-tumour chemicals, the use of appropriate in vivo tumour models suitable for large-scale screening is key. Using a Drosophila Ras-driven tumour model, we demonstrate that tumour overgrowth can be curtailed by feeding larvae with chemicals that have the in vivo pharmacokinetics essential for drug development and known efficacy against human tumour cells. We then develop an in vivo 96-well plate chemical screening platform to carry out large-scale chemical screening with the tumour model. In a proof-of-principle pilot screen of 2000 compounds, we identify the glutamine analogue, acivicin, a chemical with known activity against human tumour cells, as a potent and specific inhibitor of Drosophila tumour formation. RNAi-mediated knockdown of candidate acivicin target genes implicates an enzyme involved in pyrimidine biosynthesis, CTP synthase, as a possible crucial target of acivicin-mediated inhibition. Thus, the pilot screen has revealed that Drosophila tumours are glutamine-dependent, which is an emerging feature of many human cancers, and has validated the platform as a powerful and economical tool for in vivo chemical screening. The platform can also be adapted for use with other disease models, thus offering widespread applications in drug development. PMID:22996645

  16. Biomarkers for prostate cancer.

    PubMed

    Makarov, Danil V; Loeb, Stacy; Getzenberg, Robert H; Partin, Alan W

    2009-01-01

    The development of biomarkers for prostate cancer screening, detection, and prognostication has revolutionized the management of this disease. Prostate-specific antigen (PSA) is a useful, though not specific, biomarker for detecting prostate cancer. We review the literature on prostate cancer biomarkers, including serum markers (PAP, tPSA, fPSA, proPSA, PSAD, PSAV, PSADT, EPCA, and EPCA-2), tissue markers (AMACR, methylated GSTP1, and the TMPRSS2-ETS gene rearrangement), and a urine marker (DD3PCA3/UPM-3). Future research should focus on validation of already existing biomarkers and the discovery of new markers to identify men with aggressive prostate cancer.

  17. Proteomic Discovery and Development of a Multiplexed Targeted MRM-LC-MS/MS Assay for Urine Biomarkers of Extracellular Matrix Disruption in Mucopolysaccharidoses I, II, and VI.

    PubMed

    Heywood, Wendy E; Camuzeaux, Stephane; Doykov, Ivan; Patel, Nina; Preece, Rhian-Lauren; Footitt, Emma; Cleary, Maureen; Clayton, Peter; Grunewald, Stephanie; Abulhoul, Lara; Chakrapani, Anupam; Sebire, Neil J; Hindmarsh, Peter; de Koning, Tom J; Heales, Simon; Burke, Derek; Gissen, Paul; Mills, Kevin

    2015-12-15

    The mucopolysaccharidoses (MPS) are lysosomal storage disorders that result from defects in the catabolism of glycosaminoglycans. Impaired muscle, bone, and connective tissue are typical clinical features of MPS due to disruption of the extracellular matrix. Markers of MPS disease pathology are needed to determine disease severity and monitor effects of existing and emerging new treatments on disease mechanisms. Urine samples from a small cohort of MPS-I, -II, and -VI patients (n = 12) were analyzed using label-free quantative proteomics. Fifty-three proteins including many associated with extracellular matrix organization were differently expressed. A targeted multiplexed peptide MRM LC-MS/MS assay was used on a larger validation cohort of patient samples (MPS-I n = 18, MPS-II n = 12, MPS-VI n = 6, control n = 20). MPS-I and -II groups were further subdivided according to disease severity. None of the markers assessed were altered significantly in the mild disease groups compared to controls. β-galactosidase, a lysosomal protein, was elevated 3.6-5.7-fold significantly (p < 0.05) in all disease groups apart from mild MPS-I and -II. Collagen type Iα, fatty-acid-binding-protein 5, nidogen-1, cartilage oligomeric matrix protein, and insulin-like growth factor binding protein 7 concentrations were elevated in severe MPS I and II groups. Cartilage oligomeric matrix protein, insulin-like growth factor binding protein 7, and β-galactosidase were able to distinguish the severe neurological form of MPS-II from the milder non-neurological form. Protein Heg1 was significantly raised only in MPS-VI. This work describes the discovery of new biomarkers of MPS that represent disease pathology and allows the stratification of MPS-II patients according to disease severity. PMID:26537538

  18. Urine Proteome Analysis Reflects Atherosclerotic Disease in an ApoE−/− Mouse Model and Allows the Discovery of New Candidate Biomarkers in Mouse and Human Atherosclerosis*

    PubMed Central

    von zur Muhlen, Constantin; Schiffer, Eric; Sackmann, Christine; Zürbig, Petra; Neudorfer, Irene; Zirlik, Andreas; Htun, Nay; Iphöfer, Alexander; Jänsch, Lothar; Mischak, Harald; Bode, Christoph; Chen, Yung C.; Peter, Karlheinz

    2012-01-01

    Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE−/− mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE−/− mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE−/− mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of α1-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, α1-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE−/− mice on HFD. Urinary excretion levels of collagen and α1-antitrypsin fragments also significantly correlated with intraplaque collagen and α1-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, α1-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in murine

  19. Urine proteome analysis reflects atherosclerotic disease in an ApoE-/- mouse model and allows the discovery of new candidate biomarkers in mouse and human atherosclerosis.

    PubMed

    von zur Muhlen, Constantin; Schiffer, Eric; Sackmann, Christine; Zürbig, Petra; Neudorfer, Irene; Zirlik, Andreas; Htun, Nay; Iphöfer, Alexander; Jänsch, Lothar; Mischak, Harald; Bode, Christoph; Chen, Yung C; Peter, Karlheinz

    2012-07-01

    Noninvasive diagnosis of atherosclerosis via single biomarkers has been attempted but remains elusive. However, a previous polymarker or pattern approach of urine polypeptides in humans reflected coronary artery disease with high accuracy. The aim of the current study is to use urine proteomics in ApoE(-/-) mice to discover proteins with pathophysiological roles in atherogenesis and to identify urinary polypeptide patterns reflecting early stages of atherosclerosis. Urine of ApoE(-/-) mice either on high fat diet (HFD) or chow diet was collected over 12 weeks; urine of wild type mice on HFD was used to exclude diet-related proteome changes. Capillary electrophoresis coupled to mass spectrometry (CE-MS) of samples identified 16 polypeptides specific for ApoE(-/-) mice on HFD. In a blinded test set, these polypeptides allowed identification of atherosclerosis at a sensitivity of 90% and specificity of 100%, as well as monitoring of disease progression. Sequencing of the discovered polypeptides identified fragments of α(1)-antitrypsin, epidermal growth factor (EGF), kidney androgen-regulated protein, and collagen. Using immunohistochemistry, α(1)-antitrypsin, EGF, and collagen type I were shown to be highly expressed in atherosclerotic plaques of ApoE(-/-) mice on HFD. Urinary excretion levels of collagen and α(1)-antitrypsin fragments also significantly correlated with intraplaque collagen and α(1)-antitrypsin content, mirroring plaque protein expression in the urine proteome. To provide further confirmation that the newly identified proteins are relevant in humans, the presence of collagen type I, α(1)-antitrypsin, and EGF was also confirmed in human atherosclerotic disease. Urine proteome analysis in mice exemplifies the potential of a novel multimarker approach for the noninvasive detection of atherosclerosis and monitoring of disease progression. Furthermore, this approach represents a novel discovery tool for the identification of proteins relevant in

  20. Mass spectrometry for biomarker development

    SciTech Connect

    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.

  1. False-positive rate determination of protein target discovery using a covalent modification- and mass spectrometry-based proteomics platform.

    PubMed

    Strickland, Erin C; Geer, M Ariel; Hong, Jiyong; Fitzgerald, Michael C

    2014-01-01

    Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2% and <0.8% are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

  2. False-Positive Rate Determination of Protein Target Discovery using a Covalent Modification- and Mass Spectrometry-Based Proteomics Platform

    NASA Astrophysics Data System (ADS)

    Strickland, Erin C.; Geer, M. Ariel; Hong, Jiyong; Fitzgerald, Michael C.

    2014-01-01

    Detection and quantitation of protein-ligand binding interactions is important in many areas of biological research. Stability of proteins from rates of oxidation (SPROX) is an energetics-based technique for identifying the proteins targets of ligands in complex biological mixtures. Knowing the false-positive rate of protein target discovery in proteome-wide SPROX experiments is important for the correct interpretation of results. Reported here are the results of a control SPROX experiment in which chemical denaturation data is obtained on the proteins in two samples that originated from the same yeast lysate, as would be done in a typical SPROX experiment except that one sample would be spiked with the test ligand. False-positive rates of 1.2-2.2 % and <0.8 % are calculated for SPROX experiments using Q-TOF and Orbitrap mass spectrometer systems, respectively. Our results indicate that the false-positive rate is largely determined by random errors associated with the mass spectral analysis of the isobaric mass tag (e.g., iTRAQ®) reporter ions used for peptide quantitation. Our results also suggest that technical replicates can be used to effectively eliminate such false positives that result from this random error, as is demonstrated in a SPROX experiment to identify yeast protein targets of the drug, manassantin A. The impact of ion purity in the tandem mass spectral analyses and of background oxidation on the false-positive rate of protein target discovery using SPROX is also discussed.

  3. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities.

    PubMed

    Rubio, Gregorio; Martínez, José Fernán; Gómez, David; Li, Xin

    2016-06-24

    Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a "system of systems" could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method.

  4. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities

    PubMed Central

    Rubio, Gregorio; Martínez, José Fernán; Gómez, David; Li, Xin

    2016-01-01

    Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a “system of systems” could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method. PMID:27347965

  5. Semantic Registration and Discovery System of Subsystems and Services within an Interoperable Coordination Platform in Smart Cities.

    PubMed

    Rubio, Gregorio; Martínez, José Fernán; Gómez, David; Li, Xin

    2016-01-01

    Smart subsystems like traffic, Smart Homes, the Smart Grid, outdoor lighting, etc. are built in many urban areas, each with a set of services that are offered to citizens. These subsystems are managed by self-contained embedded systems. However, coordination and cooperation between them are scarce. An integration of these systems which truly represents a "system of systems" could introduce more benefits, such as allowing the development of new applications and collective optimization. The integration should allow maximum reusability of available services provided by entities (e.g., sensors or Wireless Sensor Networks). Thus, it is of major importance to facilitate the discovery and registration of available services and subsystems in an integrated way. Therefore, an ontology-based and automatic system for subsystem and service registration and discovery is presented. Using this proposed system, heterogeneous subsystems and services could be registered and discovered in a dynamic manner with additional semantic annotations. In this way, users are able to build customized applications across different subsystems by using available services. The proposed system has been fully implemented and a case study is presented to show the usefulness of the proposed method. PMID:27347965

  6. High-throughput screening platform for natural product-based drug discovery against 3 neglected tropical diseases: human African trypanosomiasis, leishmaniasis, and Chagas disease.

    PubMed

    Annang, F; Pérez-Moreno, G; García-Hernández, R; Cordon-Obras, C; Martín, J; Tormo, J R; Rodríguez, L; de Pedro, N; Gómez-Pérez, V; Valente, M; Reyes, F; Genilloud, O; Vicente, F; Castanys, S; Ruiz-Pérez, L M; Navarro, M; Gamarro, F; González-Pacanowska, D

    2015-01-01

    African trypanosomiasis, leishmaniasis, and Chagas disease are 3 neglected tropical diseases for which current therapeutic interventions are inadequate or toxic. There is an urgent need to find new lead compounds against these diseases. Most drug discovery strategies rely on high-throughput screening (HTS) of synthetic chemical libraries using phenotypic and target-based approaches. Combinatorial chemistry libraries contain hundreds of thousands of compounds; however, they lack the structural diversity required to find entirely novel chemotypes. Natural products, in contrast, are a highly underexplored pool of unique chemical diversity that can serve as excellent templates for the synthesis of novel, biologically active molecules. We report here a validated HTS platform for the screening of microbial extracts against the 3 diseases. We have used this platform in a pilot project to screen a subset (5976) of microbial extracts from the MEDINA Natural Products library. Tandem liquid chromatography-mass spectrometry showed that 48 extracts contain potentially new compounds that are currently undergoing de-replication for future isolation and characterization. Known active components included actinomycin D, bafilomycin B1, chromomycin A3, echinomycin, hygrolidin, and nonactins, among others. The report here is, to our knowledge, the first HTS of microbial natural product extracts against the above-mentioned kinetoplastid parasites.

  7. The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

    PubMed Central

    Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark

    2016-01-01

    ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479

  8. Rapid, non-targeted discovery of biochemical transformation and biomarker candidates in oncovirus-infected cell lines using LAESI mass spectrometry.

    PubMed

    Shrestha, Bindesh; Sripadi, Prabhakar; Walsh, Callee M; Razunguzwa, Trust T; Powell, Matthew J; Kehn-Hall, Kylene; Kashanchi, Fatah; Vertes, Akos

    2012-04-18

    Finding insights into how viruses hijack metabolic processes and biomarkers for viral diseases often require hypotheses about target compounds and/or labelling techniques. Here we present a method based on laser ablation electrospray ionization mass spectrometry to rapidly identify potential protein and metabolite biomarkers of oncovirus infection in B lymphocytes.

  9. HydroDesktop: An Open Source GIS-Based Platform for Hydrologic Data Discovery, Visualization, and Analysis

    NASA Astrophysics Data System (ADS)

    Ames, D. P.; Kadlec, J.; Cao, Y.; Grover, D.; Horsburgh, J. S.; Whiteaker, T.; Goodall, J. L.; Valentine, D. W.

    2010-12-01

    A growing number of hydrologic information servers are being deployed by government agencies, university networks, and individual researchers using the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS). The CUAHSI HIS Project has developed a standard software stack, called HydroServer, for publishing hydrologic observations data. It includes the Observations Data Model (ODM) database and Water Data Service web services, which together enable publication of data on the Internet in a standard format called Water Markup Language (WaterML). Metadata describing available datasets hosted on these servers is compiled within a central metadata catalog called HIS Central at the San Diego Supercomputer Center and is searchable through a set of predefined web services based queries. Together, these servers and central catalog service comprise a federated HIS of a scale and comprehensiveness never previously available. This presentation will briefly review/introduce the CUAHSI HIS system with special focus on a new HIS software tool called "HydroDesktop" and the open source software development web portal, www.HydroDesktop.org, which supports community development and maintenance of the software. HydroDesktop is a client-side, desktop software application that acts as a search and discovery tool for exploring the distributed network of HydroServers, downloading specific data series, visualizing and summarizing data series and exporting these to formats needed for analysis by external software. HydroDesktop is based on the open source DotSpatial GIS developer toolkit which provides it with map-based data interaction and visualization, and a plug-in interface that can be used by third party developers and researchers to easily extend the software using Microsoft .NET programming languages. HydroDesktop plug-ins that are presently available or currently under development within the project and by third party

  10. Dissecting the Syndrome of Schizophrenia: Progress toward Clinically Useful Biomarkers.

    PubMed

    Dean, Brian

    2011-01-01

    The search for clinically useful biomarkers has been one of the holy grails of schizophrenia research. This paper will outline the evolving notion of biomarkers and then outline outcomes from a variety of biomarkers discovery strategies. In particular, the impact of high-throughput screening technologies on biomarker discovery will be highlighted and how new or improved technologies may allow the discovery of either diagnostic biomarkers for schizophrenia or biomarkers that will be useful in determining appropriate treatments for people with the disorder. History tells those involved in biomarker research that the discovery and validation of useful biomarkers is a long process and current progress must always be viewed in that light. However, the approval of the first biomarker screen with some value in predicting responsiveness to antipsychotic drugs suggests that biomarkers can be identified and that these biomarkers that will be useful in diagnosing and treating people with schizophrenia.

  11. Advantages of Crystallographic Fragment Screening: Functional and Mechanistic Insights from a Powerful Platform for Efficient Drug Discovery

    PubMed Central

    Patel, Disha; Bauman, Joseph D.; Arnold, Eddy

    2015-01-01

    X-ray crystallography has been an under-appreciated screening tool for fragment-based drug discovery due to the perception of low throughput and technical difficulty. Investigators in industry and academia have overcome these challenges by taking advantage of key factors that contribute to a successful crystallographic screening campaign. Efficient cocktail design and soaking methodologies have evolved to maximize throughput while minimizing false positives/negatives. In addition, technical improvements at synchrotron beamlines have dramatically increased data collection rates thus enabling screening on a timescale comparable to other techniques. The combination of available resources and efficient experimental design has resulted in many successful crystallographic screening campaigns. The three-dimensional crystal structure of the bound fragment complexed to its target, a direct result of the screening effort, enables structure-based drug design while revealing insights regarding protein dynamics and function not readily obtained through other experimental approaches. Furthermore, this “chemical interrogation” of the target protein crystals can lead to the identification of useful reagents for improving diffraction resolution or compound solubility. PMID:25117499

  12. The Hexosamine Template – A Platform for Modulating Gene Expression and for Sugar-based Drug Discovery

    PubMed Central

    Elmouelhi, Noha; Aich, Udayanath; Paruchuri, Venkata D.P.; Meledeo, M. Adam; Campbell, Christopher T.; Wang, Jean J.; Srinivas, Raja; Khanna, Hargun S.; Yarema, Kevin J.

    2009-01-01

    This study investigates the breadth of cellular responses engendered by short chain fatty acid (SCFA)-hexosamine hybrid molecules, a class of compounds long used in ‘metabolic glycoengineering’ that are now emerging as drug candidates. First, a ‘mix-and-match’ strategy showed that different SCFA (n-butyrate and acetate) appended to the same core sugar altered biological activity, complementing previous results [Campbell et al., (2008) J. Med. Chem. 51, 8135–8147] where a single type of SCFA elicited distinct responses. Microarray profiling then compared transcriptional responses engendered by regioisomerically-modified ManNAc, GlcNAc, and GalNAc analogs in MDA-MB-231 cells. These data – which were validated by qRT-PCR or Western analysis for ID1, TP53, HPSE, NQO1, EGR1 and VEGFA – showed a two-pronged response where a core set of genes was coordinately regulated by all analogs while each analog simultaneously uniquely regulated a larger number of genes. Finally, AutoDock modeling supported a mechanism where the analogs directly interact with elements of the NF-κB pathway. Together, these results establish the SCFA-hexosamine template as a versatile platform for modulating biological activity and developing new therapeutics. PMID:19326913

  13. A novel antibody discovery platform identifies anti-influenza A broadly neutralizing antibodies from human memory B cells.

    PubMed

    Xiao, Xiaodong; Chen, Yan; Varkey, Reena; Kallewaard, Nicole; Koksal, Adem C; Zhu, Qing; Wu, Herren; Chowdhury, Partha S; Dall'Acqua, William F

    2016-07-01

    Monoclonal antibody isolation directly from circulating human B cells is a powerful tool to delineate humoral responses to pathological conditions and discover antibody therapeutics. We have developed a platform aimed at improving the efficiencies of B cell selection and V gene recovery. Here, memory B cells are activated and amplified using Epstein-Barr virus infection, co-cultured with CHO-muCD40L cells, and then assessed by functional screenings. An in vitro transcription and translation (IVTT) approach was used to analyze variable (V) genes recovered from each B cell sample and identify the relevant heavy/light chain pair(s). We achieved efficient amplification and activation of memory B cells, and eliminated the need to: 1) seed B cells at clonal level (≤1 cell/well) or perform limited dilution cloning; 2) immortalize B cells; or 3) assemble V genes into an IgG expression vector to confirm the relevant heavy/light chain pairing. Cross-reactive antibodies targeting a conserved epitope on influenza A hemagglutinin were successfully isolated from a healthy donor. In-depth analysis of the isolated antibodies suggested their potential uses as anti-influenza A antibody therapeutics and uncovered a distinct affinity maturation pathway. Importantly, our results showed that cognate heavy/light chain pairings contributed to both the expression level and binding abilities of our newly isolated VH1-69 family, influenza A neutralizing antibodies, contrasting with previous observations that light chains do not significantly contribute to the function of this group of antibodies. Our results further suggest the potential use of the IVTT as a powerful antibody developability assessment tool. PMID:27049174

  14. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

    PubMed

    Tian, Jun-Sheng; Xia, Xiao-Tao; Wu, Yan-Fei; Zhao, Lei; Xiang, Huan; Du, Guan-Hua; Zhang, Xiang; Qin, Xue-Mei

    2016-01-01

    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method. PMID:27650680

  15. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

    PubMed

    Tian, Jun-Sheng; Xia, Xiao-Tao; Wu, Yan-Fei; Zhao, Lei; Xiang, Huan; Du, Guan-Hua; Zhang, Xiang; Qin, Xue-Mei

    2016-09-21

    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

  16. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using 1H-NMR-based metabolomics profiles

    PubMed Central

    Tian, Jun-sheng; Xia, Xiao-tao; Wu, Yan-fei; Zhao, Lei; Xiang, Huan; Du, Guan-hua; Zhang, Xiang; Qin, Xue-mei

    2016-01-01

    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance (1H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method. PMID:27650680

  17. A Short Survey on the State of the Art in Architectures and Platforms for Large Scale Data Analysis and Knowledge Discovery from Data

    SciTech Connect

    Begoli, Edmon

    2012-01-01

    Intended as a survey for practicing architects and researchers seeking an overview of the state-of-the-art architectures for data analysis, this paper provides an overview of the emerg- ing data management and analytic platforms including par- allel databases, Hadoop-based systems, High Performance Computing (HPC) platforms and platforms popularly re- ferred to as NoSQL platforms. Platforms are presented based on their relevance, analysis they support and the data organization model they support.

  18. Methodological and analytic considerations for blood biomarkers.

    PubMed

    Christenson, Robert H; Duh, Show-Hong

    2012-01-01

    Biomarkers typically evolve from a research setting to use in clinical care as evidence for their independent contribution to patient management accumulates. This evidence relies heavily on knowledge of the preanalytical, analytical, and postanalytical characteristics of the biomarker's measurement. For the preanalytical phase, considerations such specimen type, acceptable anticoagulants for blood samples, biologic variation and stability of the biomarker under various conditions are key. The analytical phase entails critical details for development and maintenance of assays having performance characteristics that are "fit for service" for the clinical application at hand. Often, these characteristics describe the ability to measure minute quantities in the biologic matrix used for measurement. Although techniques such as mass spectrometry are used effectively for biomarker discovery, routine quantification often relies on use of immunoassays; early in development, the most common immunoassay used is the enzyme-linked immunosorbent assay format. As biomarkers evolve successfully, they will be adapted to large main laboratory platforms or, depending on the need for speed, point-of-care devices. Users must pay particular attention to performance parameters of assays they are considering for clinical implementation. These parameters include the limit of blank, a term used to describe the limit of analytical noise for an assay; limit of detection, which describes the lowest concentration that can reliably be discriminated from analytical noise; and perhaps most importantly, the limit of quantitation, which is the lowest concentration at which a biomarker can be reliably measured within some predefined specifications for total analytical error that is based on clinical requirements of the test. The postanalytical phase involves reporting biomarker values, which includes reporting units, any normalization factors, and interpretation. Standardization, a process that

  19. Sepsis biomarkers.

    PubMed

    Prucha, Miroslav; Bellingan, Geoff; Zazula, Roman

    2015-02-01

    Sepsis is the most frequent cause of death in non-coronary intensive care units (ICUs). In the past 10 years, progress has been made in the early identification of septic patients and in their treatment and these improvements in support and therapy mean that the mortality is gradually decreasing but it still remains unacceptably high. Leaving clinical diagnosis aside, the laboratory diagnostics represent a complex range of investigations that can place significant demands on the system given the speed of response required. There are hundreds of biomarkers which could be potentially used for diagnosis and prognosis in septic patients. The main attributes of successful markers would be high sensitivity, specificity, possibility of bed-side monitoring, and financial accessibility. Only a fraction is used in routine clinical practice because many lack sufficient sensitivity or specificity. The following review gives a short overview of the current epidemiology of sepsis, its pathogenesis and state-of-the-art knowledge on the use of specific biochemical, hematological and immunological parameters in its diagnostics. Prospective approaches towards discovery of new diagnostic biomarkers have been shortly mentioned.

  20. Prostate cancer proteomics: The urgent need for clinically validated biomarkers.

    PubMed

    Evans, Caroline A; Glen, Adam; Eaton, Colby L; Larré, Stéphane; Catto, James W F; Hamdy, Freddie C; Wright, Phillip C; Rehman, Ishtiaq

    2009-02-01

    Prostate cancer (PCa) is the most common cancer diagnosis and the second most common cause of cancer-related deaths in men. Currently, serum prostate-specific antigen (PSA) is the only biomarker widely used in the diagnosis and management of patients with PCa. However, PSA lacks diagnostic sensitivity and specificity, leading to false-negative and false-positive test results. PSA cannot distinguish indolent from aggressive disease, leading to many patients being over-treated with associated side-effects. Furthermore, PSA is unable to identify which tumors are likely to become unresponsive to treatment at an early stage. Thus, there is an urgent need for clinically validated biomarkers which will improve the diagnosis and management of PCa. Given the heterogeneity of PCa it is likely that a panel of biomarkers will be required. In the quest for PCa biomarkers, a wide range of samples including urine, serum, tissues, and cell lines have been studied using proteomic approaches such as 2-DE, SELDI-TOF, SILAC, ICAT, iTRAQ, and MALDI-IMS. The value of these technologies, and other emerging platforms such as selected reaction monitoring (SRM) and multiple reaction monitoring (MRM), are discussed in the context of biomarker discovery, validation and addressing the "bottle-necks" that exist prior to clinical translation. PMID:26238619

  1. Implementation of a protein profiling platform developed as an academic-pharmaceutical industry collaborative effort.

    PubMed

    Végvári, Akos; Magnusson, Mattias; Wallman, Lars; Ekström, Simon; Bolmsjö, Gunnar; Nilsson, Johan; Miliotis, Tasso; Ostling, Jörgen; Kjellström, Sven; Ottervald, Jan; Franzén, Bo; Hultberg, Hans; Marko-Varga, György; Laurell, Thomas

    2008-06-01

    As much attention has devoted to the proteome research during the last few years, biomarker discovery has become an increasingly hot area, potentially enabling the development of new assays for diagnosis and prognosis of severe diseases. This is the field of research interest where efforts originating from both academic and industrial groups should jointly work on solutions. In this paper, we would like to demonstrate the fruitful combination of both research domains where the scientific crossroads sprout fresh ideas from the basic research domain and how these are refined and tethered to industrial standards. We will present an approach that is based on novel microfluidic devices, utilizing their benefits in processing small-volume samples. Our biomarker discovery strategy, built around this platform, involves optimized samples processing (based on SPE and sample enrichment) and fast MALDI-MS readout. The identification of novel biomarkers at low-abundance level has been achieved by the utilization of a miniaturized sample handling platform, which offers clean-up and enrichment of proteins in one step. Complete automation has been realized in the form of a unique robotic instrumentation that is able to extract and transfer 96 samples onto standard MALDI target plates with high throughput. The developed platform was operated with a 60 sample turnaround per hour allowing sensitivities in femtomol regions of medium- and low-abundant target proteins from clinical studies on samples of multiple sclerosis and gastroesophageal reflux disease. Several proteins have been identified as new biomarkers from cerebrospinal fluid and esophagus epithelial cells.

  2. Biomarker analysis for oncology.

    PubMed

    Ma, Yinfa; Gamagedara, Sanjeewa

    2015-01-01

    Cancer biomarkers are biological, chemical or biophysical entities that are present in tumor tissues or body fluids which give valuable information about current and future behavior of cancer. This review discusses the applicability of biomarkers in different stages of cancer from cancer risk assessment to recurrence. In medical practice, biomarkers can be helpful in finding out one's potential cancer risk, confirming whether or not one is already affected with a particular type of cancer, to which drug will the cancer respond best and in what doses should it be administered, the effectiveness of the treatment and whether the cancer will recur. Although biomarker discovery and validation is a very challenging process, when considering its applications and advantages, it is well worth the effort.

  3. IgY14 and SuperMix immunoaffinity separations coupled with liquid chromatography-mass spectrometry for human plasma proteomic biomarker discovery

    SciTech Connect

    Shi, Tujin; Zhou, Jianying; Gritsenko, Marina A.; Hossain, Mahmud; Camp, David G.; Smith, Richard D.; Qian, Weijun

    2012-02-01

    Interest in the application of advanced proteomics technologies to human blood plasma- or serum-based clinical samples for the purpose of discovering disease biomarkers continues to grow; however, the enormous dynamic range of protein concentrations in these types of samples (often >10 orders of magnitude) represents a significant analytical challenge, particularly for detecting low-abundance candidate biomarkers. In response, immunoaffinity separation methods for depleting multiple high- and moderate-abundance proteins have become key tools for enriching low-abundance proteins and enhancing detection of these proteins in plasma proteomics. Herein, we describe IgY14 and tandem IgY14-Supermix separation methods for removing 14 high-abundance and up to 60 moderate-abundance proteins, respectively, from human blood plasma and highlight their utility when combined with liquid chromatography-tandem mass spectrometry for interrogating the human plasma proteome.

  4. Nanostructured optical microchips for cancer biomarker detection.

    PubMed

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

    2012-01-01

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

  5. Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues.

    PubMed

    Tyekucheva, Svitlana; Martin, Neil E; Stack, Edward C; Wei, Wei; Vathipadiekal, Vinod; Waldron, Levi; Fiorentino, Michelangelo; Lis, Rosina T; Stampfer, Meir J; Loda, Massimo; Parmigiani, Giovanni; Mucci, Lorelei A; Birrer, Michael

    2015-07-01

    Archival formalin-fixed, paraffin-embedded (FFPE) tissue specimens represent a readily available but largely untapped resource for gene expression profiling-based biomarker discovery. Several technologies have been proposed to cope with the bias from RNA cross-linking and degradation associated with archival specimens to generate data comparable with RNA from fresh-frozen materials. Direct comparison studies of these RNA expression platforms remain rare. We compared two commercially available platforms for RNA expression profiling of archival FFPE specimens from clinical studies of prostate and ovarian cancer: the Affymetrix Human Gene 1.0ST Array following whole-transcriptome amplification using the NuGen WT-Ovation FFPE System V2, and the NanoString nCounter without amplification. For each assay, we profiled 7 prostate and 11 ovarian cancer specimens, with a block age of 4 to 21 years. Both platforms produced gene expression profiles with high sensitivity and reproducibility through technical repeats from FFPE materials. Sensitivity and reproducibility remained high across block age within each cohort. A strong concordance was shown for the transcript expression values for genes detected by both platforms. We showed the biological validity of specific gene signatures generated by both platforms for both cohorts. Our study supports the feasibility of gene expression profiling and large-scale signature validation on archival prostate and ovarian tumor specimens using commercial platforms. These approaches have the potential to aid precision medicine with biomarker discovery and validation.

  6. Comparing Platforms for Messenger RNA Expression Profiling of Archival Formalin-Fixed, Paraffin-Embedded Tissues.

    PubMed

    Tyekucheva, Svitlana; Martin, Neil E; Stack, Edward C; Wei, Wei; Vathipadiekal, Vinod; Waldron, Levi; Fiorentino, Michelangelo; Lis, Rosina T; Stampfer, Meir J; Loda, Massimo; Parmigiani, Giovanni; Mucci, Lorelei A; Birrer, Michael

    2015-07-01

    Archival formalin-fixed, paraffin-embedded (FFPE) tissue specimens represent a readily available but largely untapped resource for gene expression profiling-based biomarker discovery. Several technologies have been proposed to cope with the bias from RNA cross-linking and degradation associated with archival specimens to generate data comparable with RNA from fresh-frozen materials. Direct comparison studies of these RNA expression platforms remain rare. We compared two commercially available platforms for RNA expression profiling of archival FFPE specimens from clinical studies of prostate and ovarian cancer: the Affymetrix Human Gene 1.0ST Array following whole-transcriptome amplification using the NuGen WT-Ovation FFPE System V2, and the NanoString nCounter without amplification. For each assay, we profiled 7 prostate and 11 ovarian cancer specimens, with a block age of 4 to 21 years. Both platforms produced gene expression profiles with high sensitivity and reproducibility through technical repeats from FFPE materials. Sensitivity and reproducibility remained high across block age within each cohort. A strong concordance was shown for the transcript expression values for genes detected by both platforms. We showed the biological validity of specific gene signatures generated by both platforms for both cohorts. Our study supports the feasibility of gene expression profiling and large-scale signature validation on archival prostate and ovarian tumor specimens using commercial platforms. These approaches have the potential to aid precision medicine with biomarker discovery and validation. PMID:25937617

  7. Aberrant glycosylation associated with enzymes as cancer biomarkers

    PubMed Central

    2011-01-01

    Background One of the new roles for enzymes in personalized medicine builds on a rational approach to cancer biomarker discovery using enzyme-associated aberrant glycosylation. A hallmark of cancer, aberrant glycosylation is associated with differential expressions of enzymes such as glycosyltransferase and glycosidases. The aberrant expressions of the enzymes in turn cause cancer cells to produce glycoproteins with specific cancer-associated aberrations in glycan structures. Content In this review we provide examples of cancer biomarker discovery using aberrant glycosylation in three areas. First, changes in glycosylation machinery such as glycosyltransferases/glycosidases could be used as cancer biomarkers. Second, most of the clinically useful cancer biomarkers are glycoproteins. Discovery of specific cancer-associated aberrations in glycan structures of these existing biomarkers could improve their cancer specificity, such as the discovery of AFP-L3, fucosylated glycoforms of AFP. Third, cancer-associated aberrations in glycan structures provide a compelling rationale for discovering new biomarkers using glycomic and glycoproteomic technologies. Summary As a hallmark of cancer, aberrant glycosylation allows for the rational design of biomarker discovery efforts. But more important, we need to translate these biomarkers from discovery to clinical diagnostics using good strategies, such as the lessons learned from translating the biomarkers discovered using proteomic technologies to OVA 1, the first FDA-cleared In Vitro Diagnostic Multivariate Index Assay (IVDMIA). These lessons, providing important guidance in current efforts in biomarker discovery and translation, are applicable to the discovery of aberrant glycosylation associated with enzymes as cancer biomarkers as well. PMID:21906357

  8. A multi-platform metabolomics approach identifies highly specific biomarkers of bacterial diversity in the vagina of pregnant and non-pregnant women

    PubMed Central

    McMillan, Amy; Rulisa, Stephen; Sumarah, Mark; Macklaim, Jean M.; Renaud, Justin; Bisanz, Jordan E.; Gloor, Gregory B.; Reid, Gregor

    2015-01-01

    Bacterial vaginosis (BV) increases transmission of HIV, enhances the risk of preterm labour, and is associated with malodour. Clinical diagnosis often relies on microscopy, which may not reflect the microbiota composition accurately. We use an untargeted metabolomics approach, whereby we normalize the weight of samples prior to analysis, to obtained precise measurements of metabolites in vaginal fluid. We identify biomarkers for BV with high sensitivity and specificity (AUC = 0.99) in a cohort of 131 pregnant and non-pregnant Rwandan women, and demonstrate that the vaginal metabolome is strongly associated with bacterial diversity. Metabolites associated with high diversity and clinical BV include 2-hydroxyisovalerate and γ-hydroxybutyrate (GHB), but not succinate, which is produced by both Lactobacillus crispatus and BV-associated anaerobes in vitro. Biomarkers associated with high diversity and clinical BV are independent of pregnancy status, and were validated in a blinded replication cohort from Tanzania (n = 45), where we predicted clinical BV with 91% accuracy. Correlations between the metabolome and microbiota identified Gardnerella vaginalis as a putative producer of GHB, and we demonstrate production by this species in vitro. This work illustrates how changes in community structure alter the chemical composition of the vagina, and identifies highly specific biomarkers for a common condition. PMID:26387596

  9. Large-Scale Glycomics of Livestock: Discovery of Highly Sensitive Serum Biomarkers Indicating an Environmental Stress Affecting Immune Responses and Productivity of Holstein Dairy Cows.

    PubMed

    Rehan, Ibrahim F; Ueda, Koichiro; Mitani, Tomohiro; Amano, Maho; Hinou, Hiroshi; Ohashi, Tetsu; Kondo, Seiji; Nishimura, Shin-Ichiro

    2015-12-01

    Because various stresses strongly influence the food productivity of livestock, biomarkers to indicate unmeasurable environmental stress in domestic animals are of increasing importance. Thermal comfort is one of the basic principles of dairy cow welfare that enhances productivity. To discover sensitive biomarkers that monitor such environmental stresses in dairy cows, we herein performed, for the first time, large-scale glycomics on 336 lactating Holstein cow serum samples over 9 months between February and October. Glycoblotting combined with MALDI-TOF/MS and DMB/HPLC allowed for comprehensive glycomics of whole serum glycoproteins. The results obtained revealed seasonal alterations in serum N-glycan levels and their structural characteristics, such as an increase in high-mannose type N-glycans in spring, the occurrence of di/triantennary complex type N-glycans terminating with two or three Neu5Gc residues in summer and autumn, and N-glycans in winter dominantly displaying Neu5Ac. A multivariate analysis revealed a correlation between the serum expression levels of these season-specific glycoforms and productivity.

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

    PubMed

    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.

  11. Precise quantitation of 136 urinary proteins by LC/MRM-MS using stable isotope labeled peptides as internal standards for biomarker discovery and/or verification studies.

    PubMed

    Percy, Andrew J; Yang, Juncong; Hardie, Darryl B; Chambers, Andrew G; Tamura-Wells, Jessica; Borchers, Christoph H

    2015-06-15

    Spurred on by the growing demand for panels of validated disease biomarkers, increasing efforts have focused on advancing qualitative and quantitative tools for more highly multiplexed and sensitive analyses of a multitude of analytes in various human biofluids. In quantitative proteomics, evolving strategies involve the use of the targeted multiple reaction monitoring (MRM) mode of mass spectrometry (MS) with stable isotope-labeled standards (SIS) used for internal normalization. Using that preferred approach with non-invasive urine samples, we have systematically advanced and rigorously assessed the methodology toward the precise quantitation of the largest, multiplexed panel of candidate protein biomarkers in human urine to date. The concentrations of the 136 proteins span >5 orders of magnitude (from 8.6 μg/mL to 25 pg/mL), with average CVs of 8.6% over process triplicate. Detailed here is our quantitative method, the analysis strategy, a feasibility application to prostate cancer samples, and a discussion of the utility of this method in translational studies.

  12. Large-Scale Glycomics of Livestock: Discovery of Highly Sensitive Serum Biomarkers Indicating an Environmental Stress Affecting Immune Responses and Productivity of Holstein Dairy Cows.

    PubMed

    Rehan, Ibrahim F; Ueda, Koichiro; Mitani, Tomohiro; Amano, Maho; Hinou, Hiroshi; Ohashi, Tetsu; Kondo, Seiji; Nishimura, Shin-Ichiro

    2015-12-01

    Because various stresses strongly influence the food productivity of livestock, biomarkers to indicate unmeasurable environmental stress in domestic animals are of increasing importance. Thermal comfort is one of the basic principles of dairy cow welfare that enhances productivity. To discover sensitive biomarkers that monitor such environmental stresses in dairy cows, we herein performed, for the first time, large-scale glycomics on 336 lactating Holstein cow serum samples over 9 months between February and October. Glycoblotting combined with MALDI-TOF/MS and DMB/HPLC allowed for comprehensive glycomics of whole serum glycoproteins. The results obtained revealed seasonal alterations in serum N-glycan levels and their structural characteristics, such as an increase in high-mannose type N-glycans in spring, the occurrence of di/triantennary complex type N-glycans terminating with two or three Neu5Gc residues in summer and autumn, and N-glycans in winter dominantly displaying Neu5Ac. A multivariate analysis revealed a correlation between the serum expression levels of these season-specific glycoforms and productivity. PMID:26595672

  13. Biomarkers for neuromyelitis optica.

    PubMed

    Chang, Kuo-Hsuan; Ro, Long-Sun; Lyu, Rong-Kuo; Chen, Chiung-Mei

    2015-02-01

    Neuromyelitis optica (NMO) is an acquired, heterogeneous inflammatory disorder, which is characterized by recurrent optic neuritis and longitudinally extensive spinal cord lesions. The discovery of the serum autoantibody marker, anti-aquaporin 4 (anti-AQP4) antibody, revolutionizes our understanding of pathogenesis of NMO. In addition to anti-AQP4 antibody, other biomarkers for NMO are also reported. These candidate biomarkers are particularly involved in T helper (Th)17 and astrocytic damages, which play a critical role in the development of NMO lesions. Among them, IL-6 in the peripheral blood is associated with anti-AQP4 antibody production. Glial fibrillary acidic protein (GFAP) in CSF demonstrates good correlations with clinical severity of NMO relapses. Detecting these useful biomarkers may be useful in the diagnosis and evaluation of disease activity of NMO. Development of compounds targeting these biomarkers may provide novel therapeutic strategies for NMO. This article will review the related biomarker studies in NMO and discuss the potential therapeutics targeting these biomarkers.

  14. Biomarkers to guide clinical therapeutics in rheumatology?

    PubMed Central

    Robinson, William H.; Mao, Rong

    2016-01-01

    Purpose of review The use of biomarkers in rheumatology can help identify disease risk, improve diagnosis and prognosis, target therapy, assess response to treatment, and further our understanding of the underlying pathogenesis of disease. Here, we discuss the recent advances in biomarkers for rheumatic disorders, existing impediments to progress in this field, and the potential of biomarkers to enable precision medicine and thereby transform rheumatology. Recent findings Although significant challenges remain, progress continues to be made in biomarker discovery and development for rheumatic diseases. The use of next-generation technologies, including large-scale sequencing, proteomic technologies, metabolomic technologies, mass cytometry, and other single-cell analysis and multianalyte analysis technologies, has yielded a slew of new candidate biomarkers. Nevertheless, these biomarkers still require rigorous validation and have yet to make their way into clinical practice and therapeutic development. This review focuses on advances in the biomarker field in the last 12 months as well as the challenges that remain. Summary Better biomarkers, ideally mechanistic ones, are needed to guide clinical decision making in rheumatology. Although the use of next-generation techniques for biomarker discovery is making headway, it is imperative that the roadblocks in our search for new biomarkers are overcome to enable identification of biomarkers with greater diagnostic and predictive utility. Identification of biomarkers with robust diagnostic and predictive utility would enable precision medicine in rheumatology. PMID:26720904

  15. Discovery and Verification of Head-and-neck Cancer Biomarkers by Differential Protein Expression Analysis Using iTRAQ Labeling, Multidimensional Liquid Chromatography, and Tandem Mass Spectrometry*S⃞

    PubMed Central

    Ralhan, Ranju; DeSouza, Leroi V.; Matta, Ajay; Chandra Tripathi, Satyendra; Ghanny, Shaun; Datta Gupta, Siddartha; Bahadur, Sudhir; Siu, K. W. Michael

    2008-01-01

    Multidimensional LC-MS/MS has been used for the analysis of biological samples labeled with isobaric mass tags for relative and absolute quantitation (iTRAQ) to identify proteins that are differentially expressed in human head-and-neck squamous cell carcinomas (HNSCCs) in relation to non-cancerous head-and-neck tissues (controls) for cancer biomarker discovery. Fifteen individual samples (cancer and non-cancerous tissues) were compared against a pooled non-cancerous control (prepared by pooling equal amounts of proteins from six non-cancerous tissues) in five sets by on-line and off-line separation. We identified 811 non-redundant proteins in HNSCCs, including structural proteins, signaling components, enzymes, receptors, transcription factors, and chaperones. A panel of proteins showing consistent differential expression in HNSCC relative to the non-cancerous controls was discovered. Some of the proteins include stratifin (14-3-3σ); YWHAZ (14-3-3ζ); three calcium-binding proteins of the S100 family, S100-A2, S100-A7 (psoriasin), and S100-A11 (calgizarrin); prothymosin α (PTHA); l-lactate dehydrogenase A chain; glutathione S-transferase Pi; APC-binding protein EB1; and fascin. Peroxiredoxin2, carbonic anhydrase I, flavin reductase, histone H3, and polybromo-1D (BAF180) were underexpressed in HNSCCs. A panel of the three best performing biomarkers, YWHAZ, stratifin, and S100-A7, achieved a sensitivity of 0.92 and a specificity of 0.91 in discriminating cancerous from non-cancerous head-and-neck tissues. Verification of differential expression of YWHAZ, stratifin, and S100-A7 proteins in clinical samples of HNSCCs and paired and non-paired non-cancerous tissues by immunohistochemistry, immunoblotting, and RT-PCR confirmed their overexpression in head-and-neck cancer. Verification of YWHAZ, stratifin, and S100-A7 in an independent set of HNSCCs achieved a sensitivity of 0.92 and a specificity of 0.87 in discriminating cancerous from non-cancerous head

  16. Discovery of a biomarker and lead small molecules to target r(GGGGCC)-associated defects in c9FTD/ALS.

    PubMed

    Su, Zhaoming; Zhang, Yongjie; Gendron, Tania F; Bauer, Peter O; Chew, Jeannie; Yang, Wang-Yong; Fostvedt, Erik; Jansen-West, Karen; Belzil, Veronique V; Desaro, Pamela; Johnston, Amelia; Overstreet, Karen; Oh, Seok-Yoon; Todd, Peter K; Berry, James D; Cudkowicz, Merit E; Boeve, Bradley F; Dickson, Dennis; Floeter, Mary Kay; Traynor, Bryan J; Morelli, Claudia; Ratti, Antonia; Silani, Vincenzo; Rademakers, Rosa; Brown, Robert H; Rothstein, Jeffrey D; Boylan, Kevin B; Petrucelli, Leonard; Disney, Matthew D

    2014-09-01

    A repeat expansion in C9ORF72 causes frontotemporal dementia and amyotrophic lateral sclerosis (c9FTD/ALS). RNA of the expanded repeat (r(GGGGCC)exp) forms nuclear foci or undergoes repeat-associated non-ATG (RAN) translation, producing "c9RAN proteins." Since neutralizing r(GGGGCC)exp could inhibit these potentially toxic events, we sought to identify small-molecule binders of r(GGGGCC)exp. Chemical and enzymatic probing of r(GGGGCC)8 indicate that it adopts a hairpin structure in equilibrium with a quadruplex structure. Using this model, bioactive small molecules targeting r(GGGGCC)exp were designed and found to significantly inhibit RAN translation and foci formation in cultured cells expressing r(GGGGCC)66 and neurons transdifferentiated from fibroblasts of repeat expansion carriers. Finally, we show that poly(GP) c9RAN proteins are specifically detected in c9ALS patient cerebrospinal fluid. Our findings highlight r(GGGGCC)exp-binding small molecules as a possible c9FTD/ALS therapeutic and suggest that c9RAN proteins could potentially serve as a pharmacodynamic biomarker to assess efficacy of therapies that target r(GGGGCC)exp. PMID:25132468

  17. Multiplex assays for biomarker research and clinical application: translational science coming of age.

    PubMed

    Fu, Qin; Schoenhoff, Florian S; Savage, William J; Zhang, Pingbo; Van Eyk, Jennifer E

    2010-03-01

    Over the last decade, translational science has come into the focus of academic medicine, and significant intellectual and financial efforts have been made to initiate a multitude of bench-to-bedside projects. The quest for suitable biomarkers that will significantly change clinical practice has become one of the biggest challenges in translational medicine. Quantitative measurement of proteins is a critical step in biomarker discovery. Assessing a large number of potential protein biomarkers in a statistically significant number of samples and controls still constitutes a major technical hurdle. Multiplexed analysis offers significant advantages regarding time, reagent cost, sample requirements and the amount of data that can be generated. The two contemporary approaches in multiplexed and quantitative biomarker validation, antibody-based immunoassays and MS-based multiple (or selected) reaction monitoring, are based on different assay principles and instrument requirements. Both approaches have their own advantages and disadvantages and therefore have complementary roles in the multi-staged biomarker verification and validation process. In this review, we discuss quantitative immunoassay and multiple reaction monitoring/selected reaction monitoring assay principles and development. We also discuss choosing an appropriate platform, judging the performance of assays, obtaining reliable, quantitative results for translational research and clinical applications in the biomarker field. PMID:21137048

  18. Biomarker Discovery and Redundancy Reduction towards Classification using a Multi-factorial MALDI-TOF MS T2DM Mouse Model Dataset

    PubMed Central

    2011-01-01

    Background Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics. Results We present a comprehensive work-flow tailored for analyzing complex data including data from multi-factorial studies. The developed approach aims at revealing effects caused by a distinct combination of experimental factors, in our case genotype and diet. Applying the developed work-flow to the analysis of an established polygenic mouse model for diet-induced type 2 diabetes, we found peptides with significant fold changes exclusively for the combination of a particular strain and diet. Exploitation of redundancy enables the visualization of peptide correlation and provides a natural way of feature selection for classification and prediction. Classification based on the features selected using our approach performs similar to classifications based on more complex feature selection methods. Conclusions The combination of ANOVA and redundancy exploitation allows for identification of biomarker candidates in multi-dimensional MALDI-TOF MS profiling studies with complex experimental design. With respect to feature selection our method provides a fast and intuitive alternative to global optimization strategies with comparable performance. The method is implemented in R and the scripts are available by contacting the corresponding author. PMID:21554713

  19. Biomarker discovery and identification in laser microdissected head and neck squamous cell carcinoma with ProteinChip technology, two-dimensional gel electrophoresis, tandem mass spectrometry, and immunohistochemistry.

    PubMed

    Melle, Christian; Ernst, Gunther; Schimmel, Bettina; Bleul, Annett; Koscielny, Sven; Wiesner, Andreas; Bogumil, Ralf; Moller, Ursula; Osterloh, Dirk; Halbhuber, Karl-Jurgen; von Eggeling, Ferdinand

    2003-07-01

    Head and neck cancer is a frequent malignancy with a complex, and up to now not clear etiology. Therefore, despite of improvements in diagnosis and therapy, the survival rate with head and neck squamous-cell carcinomas is poor. For a better understanding of the molecular mechanisms behind the process of tumorigenesis and tumor progression, we have analyzed changes of protein expression between microdissected normal pharyngeal epithelium and tumor tissue by ProteinChip technology. For this, cryostat sections from head and neck tumors (n = 57) and adjacent mucosa (n = 44) were laser-microdissected and analyzed on ProteinChip arrays. The derived mass spectrometry profiles exhibited numerous statistical differences. One peak significantly higher expressed in the tumor (p = 0.000029) was isolated by two-dimensional gel electrophoresis and identified as annexin V by in-gel proteolytic digestion, peptide mapping, tandem mass spectrometry analysis, and immuno-deplete assay. The relevance of this single marker protein was further evaluated by immunohistochemistry. Annexin-positive tissue areas were re-analyzed on ProteinChip arrays to confirm the identity of this protein. In this study, we could show that biomarker in head and neck cancer can be found, identified, and assessed by combination of ProteinChip technology, two-dimensional gel electrophoresis, and immunohistochemistry. In our experience, however, such studies only make sense if a relatively pure microdissected tumor tissue is used. Only then minute changes in protein expression between normal pharyngeal epithelium and tumor tissue can be detected, and it will become possible to educe a tumor-associated protein pattern that might be used as a marker for tumorigenesis and progression. PMID:12824440

  20. Biomarkers: A Challenging Conundrum in Cardiovascular Disease.

    PubMed

    Libby, Peter; King, Kevin

    2015-12-01

    The use of biomarkers has proven utility in cardiovascular medicine and holds great promise for future advances, but their application requires considerable rigor in thinking and methodology. Numerous confounding factors can cloud the clinical and investigative uses of biomarkers. Yet, the thoughtful and critical use of biomarkers can doubtless aid discovery of new pathogenic pathways, identify novel therapeutic targets, and provide a bridge between the laboratory and the clinic. Biomarkers can provide diagnostic and prognostic tools to the practitioner. The careful application of biomarkers can also help design and guide clinical trials required to establish the efficacy of novel interventions to improve patient outcomes. Point of care testing, technological advances, such as microfluidic and wearable devices, and the power of omics approaches all promise to elevate the potential contributions of biomarkers to discovery science, translation, clinical trials, and the practice of cardiovascular medicine.

  1. Biomarkers for antipsychotic therapies.

    PubMed

    Pich, Emilio Merlo; Vargas, Gabriel; Domenici, Enrico

    2012-01-01

    Molecular biomarkers for antipsychotic treatments have been conceptually linked to the measurements of dopamine functions, mostly D(2) receptor occupancy, either by imaging using selective PET/SPECT radioactive tracers or by assessing plasma prolactin levels. A quest for novel biomarkers was recently proposed by various academic, health service, and industrial institutions driven by the need for better treatments of psychoses. In this review we conceptualize biomarkers within the Translational Medicine paradigm whose goal was to provide support to critical decision-making in drug discovery. At first we focused on biomarkers as outcome measure of clinical studies by searching into the database clinicaltrial.gov. The results were somewhat disappointing, showing that out of 1,659 antipsychotic trials only 18 used a biomarker as an outcome measure. Several of these trials targeted plasma lipids as sentinel marker for metabolic adverse effects associated with the use of atypical antipsychotics, while only few studies were aimed to new disease specific biological markers. As an example of a mechanistic biomarker, we described the work done to progress the novel class of glycine transporter inhibitors as putative treatment for negative symptoms of schizophrenia. We also review how large-scale multiplex biological assays were applied to samples from tissues of psychiatric patients, so to learn from changes of numerous analytes (metabolic products, lipids, proteins, RNA transcripts) about the substrates involved in the disease. We concluded that a stringent implementation of these techniques could contribute to the endophenotypic characterization of patients, helping in the identification of key biomarkers to drive personalized medicine and new treatment development. PMID:23129338

  2. Immunohistochemistry in the Diagnosis of Mucinous Neoplasms Involving the Ovary: The Added Value of SATB2 and Biomarker Discovery Through Protein Expression Database Mining.

    PubMed

    Strickland, Sarah; Wasserman, Jason K; Giassi, Ana; Djordjevic, Bojana; Parra-Herran, Carlos

    2016-05-01

    77.1% sensitivity and 99% specificity, outperforming tumor laterality and size. Second-line markers such as CDX2, MUC2, estrogen receptor, MUC1, and β-catenin increased the sensitivity of immunohistochemistry in excluding lower GI origin. Biomarker search using proteomic databases has a value in diagnostic pathology, as shown with SATB2; however, as seen with POF1B, expression profiles in these databases are not always reproduced in larger cohorts.

  3. Proteomic response of mussels Mytilus galloprovincialis exposed to CuO NPs and Cu²⁺: an exploratory biomarker discovery.

    PubMed

    Gomes, Tânia; Chora, Suze; Pereira, Catarina G; Cardoso, Cátia; Bebianno, Maria João

    2014-10-01

    absence of the mussel genome precluded the identification of other proteins relevant to clarify the effects of CuO NPs in mussels' tissues, proteomics analysis provided additional knowledge of their potential effects at the protein level that after confirmation and validation can be used as putative new biomarkers in nanotoxicology.

  4. A platform for discovery and quantification of modified ribonucleosides in RNA: Application to stress-induced reprogramming of tRNA modifications

    PubMed Central

    Cai, Weiling Maggie; Chionh, Yok Hian; Hia, Fabian; Gu, Chen; Kellner, Stefanie; McBee, Megan E.; Ng, Chee Sheng; Pang, Yan Ling Joy; Prestwich, Erin G.; Lim, Kok Seong; Babu, I. Ramesh; Begley, Thomas J.; Dedon, Peter C.

    2016-01-01

    Here we describe an analytical platform for systems-level quantitative analysis of modified ribonucleosides in any RNA species, with a focus on stress-induced reprogramming of tRNA as part of a system of translational control of cell stress response. The chapter emphasizes strategies and caveats for each of the seven steps of the platform workflow: 1) RNA isolation, 2) RNA purification, 3) RNA hydrolysis to individual ribonucleosides, 4) chromatographic resolution of ribonucleosides, 5) identification of the full set of modified ribonucleosides, 6) mass spectrometric quantification of ribonucleosides, 6) interrogation of ribonucleoside datasets, and 7) mapping the location of stress-sensitive modifications in individual tRNA molecules. We have focused on the critical determinants of analytical sensitivity, specificity, precision and accuracy in an effort to ensure the most biologically meaningful data on mechanisms of translational control of cell stress response. The methods described here should find wide use in virtually any analysis involving RNA modifications. PMID:26253965

  5. The cancer secretome: a reservoir of biomarkers

    PubMed Central

    Xue, Hua; Lu, Bingjian; Lai, Maode

    2008-01-01

    Biomarkers are pivotal for cancer detection, diagnosis, prognosis and therapeutic monitoring. However, currently available cancer biomarkers have the disadvantage of lacking specificity and/or sensitivity. Developing effective cancer biomarkers becomes a pressing and permanent need. The cancer secretome, the totality of proteins released by cancer cells or tissues, provides useful tools for the discovery of novel biomarkers. The focus of this article is to review the recent advances in cancer secretome analysis. We aim to elaborate the approaches currently employed for cancer secretome studies, as well as its applications in the identification of biomarkers and the clarification of carcinogenesis mechanisms. Challenges encountered in this newly emerging field, including sample preparation, in vivo secretome analysis and biomarker validation, are also discussed. Further improvements on strategies and technologies will continue to drive forward cancer secretome research and enable development of a wealth of clinically valuable cancer biomarkers. PMID:18796163

  6. Viral surveillance and discovery

    PubMed Central

    Lipkin, Walter Ian; Firth, Cadhla

    2014-01-01

    The field of virus discovery has burgeoned with the advent of high throughput sequencing platforms and bioinformatics programs that enable rapid identification and molecular characterization of known and novel agents, investments in global microbial surveillance that include wildlife and domestic animals as well as humans, and recognition that viruses may be implicated in chronic as well as acute diseases. Here we review methods for viral surveillance and discovery, strategies and pitfalls in linking discoveries to disease, and identify opportunities for improvements in sequencing instrumentation and analysis, the use of social media and medical informatics that will further advance clinical medicine and public health. PMID:23602435

  7. Discovery of a new genus and new species of Indo-West Pacific pilumnoidid crab from a semisubmersible oil platform (Crustacea: Brachyura: Pseudozioidea).

    PubMed

    Ng, Peter K L; Ahyong, Shane T

    2013-01-01

    A new genus and new species of pseudozioid crab of the family Pilumnoididae is described from a fouling community on a semisubmersible oil platform in Singapore that had been operating in the Timor Sea and South China Sea. Setozius incertus gen. et sp. nov. superficially resembles species of Pilumnus (Pilumnidae, Pilumnoidea) but has male first and second gonopod structures characteristic of the Pseudozioidea. The form of the carapace, male anterior thoracic sternum and male abdomen indicates that it should be classified in the Pilumnoididae. Setozius is the first member of the family to be recorded from the Indo-West Pacific; all other known pilumnoidids occur in the Atlantic and eastern Pacific.

  8. Discovery of human Golgi β-galactosidase with no identified glycosidase using a QMC substrate design platform for exo-glycosidase.

    PubMed

    Miura, Kazuki; Hakamata, Wataru; Tanaka, Ayako; Hirano, Takako; Nishio, Toshiyuki

    2016-03-15

    Post-translational modifications (PTMs) of proteins play important roles in the physiology of eukaryotes. In the PTMs, non-reversible glycosylations are classified as N-glycosylations and O-glycosylations, and are catalyzed by various glycosidases and glycosyltransferases. However, β-glycosidases are not known to play a role in N- and O-glycan processing, although both glycans provide partial structures as substrates for β-galactosidase and β-N-acetylglucosaminidase in the Golgi apparatus of human cells. We explored human Golgi β-galactosidase using fluorescent substrates based on a quinone methide cleavage (QMC) substrate design platform that was previously developed to image exo-type glycosidases in living cells. As a result, we discovered a novel Golgi β-galactosidase in human cells. It is possible to predict a novel and important function in glycan processing of this β-galactosidase, because various β-galactosyl linkages in N- and O-glycans exist in Golgi apparatus. In addition, these results show that the QMC platform is excellent for imaging exo-type glycosidases.

  9. The Utility of Metabolomics in Natural Product and Biomarker Characterization

    PubMed Central

    Cox, Daniel G.; Oh, Joonseok; Keasling, Adam; Colson, Kim

    2014-01-01

    Background Metabolomics is a well-established rapidly developing research field involving quantitative and qualitative metabolite assessment within biological systems. Recent improvements in metabolomics technologies reveal the unequivocal value of metabolomics tools in natural products discovery, gene-function analysis, systems biology and diagnostic platforms. Scope of review We review of some of the prominent metabolomics methodologies employed in data acquisition and analysis of natural products and disease-related biomarkers. Major conclusions This review demonstrates that metabolomics represents a highly adaptable technology with diverse applications ranging from environmental toxicology to disease diagnosis. Metabolomic analysis is shown to provide a unique snapshot of the functional genetic status of an organism by examining its biochemical profile, with relevance toward resolving phylogenetic associations involving horizontal gene transfer and distinguishing subgroups of genera possessing high genetic homology, as well as an increasing role in both elucidating biosynthetic transformations of natural products and detecting preclinical biomarkers of numerous disease states. General significance This review expands the interest in multiplatform combinatorial metabolomic analysis. The applications reviewed range from phylogenetic assignment, biosynthetic transformations of natural products, and the detection of preclinical biomarkers. PMID:25151044

  10. [Novel biomarkers for diabetic nephropathy].

    PubMed

    Araki, Shin-ichi

    2014-02-01

    Diabetic nephropathy is a leading cause of end-stage renal disease worldwide. An early clinical sign of this complication is an increase of urinary albumin excretion, called microalbuminuria, which is not only a predictor of the progression of nephropathy, but also an independent risk factor for cardiovascular disease. Although microalbuminuria is clinically important to assess the prognosis of diabetic patients, it may be insufficient as an early and specific biomarker of diabetic nephropathy because of a large day-to-day variation and lack of a good correlation of microalbuminuria with renal dysfunction and pathohistological changes. Thus, more sensitive and specific biomarkers are needed to improve the diagnostic capability of identifying patients at high risk. The factors involved in renal tubulo-interstitial damage, the production and degradation of extracellular matrix, microinflammation, etc., are investigated as candidate molecules. Despite numerous efforts so far, the assessment of these biomarkers is still a subject of ongoing investigations. Recently, a variety of omics and quantitative techniques in systems biology are rapidly emerging in the field of biomarker discovery, including proteomics, transcriptomics, and metabolomics, and they have been applied to search for novel putative biomarkers of diabetic nephropathy. Novel biomarkers or their combination with microalbuminuria provide a better diagnostic accuracy than microalbuminuria alone, and may be useful for establishing personal medicine. Furthermore, the identification of novel biomarkers may provide insight into the mechanisms underlying diabetic nephropathy.

  11. Biomarkers in Cervical Cancer

    PubMed Central

    Yim, Eun-Kyoung; Park, Jong-Sup

    2006-01-01

    Cervical cancer, a potentially preventable disease, remains the second most common malignancy in women worldwide. Human papillomavirus (HPV) is the single most important etiological agent in cervical cancer, contributing to neoplastic progression through the action of viral oncoproteins, mainly E6 and E7. Cervical screening programs using Pap smear testing have dramatically improved cervical cancer incidence and reduced deaths, but cervical cancer still remains a global health burden. The biomarker discovery for accurate detection and diagnosis of cervical carcinoma and its malignant precursors (collectively referred to as high-grade cervical disease) represents one of the current challenges in clinical medicine and cytopathology. PMID:19690652

  12. Candidate-based proteomics in the search for biomarkers of cardiovascular disease

    PubMed Central

    Anderson, Leigh

    2005-01-01

    The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

  13. An Integrative Approach to Biomarker Development in Psoriatic Arthritis.

    PubMed

    Ritchlin, Christopher T

    2015-11-01

    The recent discovery that the interleukin 23/Th17 pathway is pivotal in the pathogenesis of psoriatic arthritis (PsA) creates new opportunities for the development of mechanistic biomarkers that will assist in the diagnosis and management of this disorder. While biomarkers are still in the discovery phase, new approaches including multiplex panels, fine sequencing of epigenetic and genetic data in non-coding regions of the human genome, and improved imaging modalities will likely foster the development of actionable biomarkers in PsA. In this report, I review the field of biomarkers, underscore the importance of an integrative approach that incorporates both descriptive and mechanistic biomarkers, and discuss the status of biomarker discovery in PsA.

  14. Proteomic Approaches for Biomarker Panels in Cancer.

    PubMed

    Tanase, Cristiana; Albulescu, Radu; Neagu, Monica

    2016-01-01

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

  15. Perspective: Proteomic approach to detect biomarkers of human growth hormone

    PubMed Central

    Ding, Juan; List, Edward O.; Okada, Shigeru; Kopchick, John J.

    2009-01-01

    Several serum biomarkers for recombinant human growth hormone (rhGH) have been established, however, none alone or in combination have generate a specific, sensitive, and reproducible ‘kit’ for the detection of rhGH abuse. Thus, the search for additional GH specific biomarkers continues. In this review, we focus on the use of proteomics in general and 2-dimensional electrophoresis (2-DE) in particular for the discovery of new GH induced serum biomarkers. Also, we review some of the protocols involved in 2DE. Finally, the possibility of tissues other than blood for biomarker discovery is discussed. PMID:19501004

  16. The value of translational biomarkers to phenotypic assays

    PubMed Central

    Swinney, David C.

    2014-01-01

    Phenotypic assays are tools essential for drug discovery. Phenotypic assays have different types of endpoints depending on the goals; (1) empirical endpoints for basic research to understand the underlying biology that will lead to identification of translation biomarkers, (2) empirical endpoints to identify undesired effects related to toxicity of drug candidates, and (3) knowledge-based endpoints (biomarkers) for drug discovery which ideally are translational biomarkers that will be used to identify new drug candidates and their corresponding molecular mechanisms of action. The value of phenotypic assays is increased through effective alignment of phenotypic assay endpoints with the objectives of the relevant stage in the drug discovery and development cycle. PMID:25076910

  17. Protein biomarkers of alcohol abuse

    PubMed Central

    Torrente, Mariana P; Freeman, Willard M; Vrana, Kent E

    2012-01-01

    Alcohol abuse can lead to a number of health and social issues. Our current inability to accurately assess long-term drinking behaviors is an important obstacle to its diagnosis and treatment. Biomarkers for chronic alcohol consumption have made a number of important advances but have yet to become highly accurate and as accepted as objective tests for other diseases. Thus, there is a crucial need for the development of more sensitive and specific markers of alcohol abuse. Recent advancements in proteomic technologies have greatly increased the potential for alcohol abuse biomarker discovery. Here, the authors review established and novel protein biomarkers for long-term alcohol consumption and the proteomic technologies that have been used in their study. PMID:22967079

  18. Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets.

    PubMed

    Amar, David; Hait, Tom; Izraeli, Shai; Shamir, Ron

    2015-09-18

    Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case-control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14,000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis.

  19. Searching for ‘omic’ biomarkers

    PubMed Central

    Lin, David; Hollander, Zsuzsanna; Meredith, Anna; McManus, Bruce M

    2009-01-01

    Cardiovascular diseases impose enormous social and economic burdens on both individual citizens and on society as a whole. Clinical indicators such as high blood pressure, blood cholesterol and obesity have had some utility in identifying those who are at increased risk of cardiovascular events. However, there remains an urgent need for sensitive and specific indicators, preferably acquired through minimally invasive means, to help stratify patients for more personalized health care. As such, there has been a steadily growing interest in searching for ‘omic’ biomarkers of cardiovascular diseases. Historically, the transition of cardiac biomarker discovery to implementation has been a lengthy and somewhat unregulated process. Recent technological advancements, as well as concurrent efforts by regulatory agencies such as the Food and Drug Administration (United States) and Health Canada to establish policies and guidelines in the ‘omic’ arena, have helped propel the discovery and validation of biomarkers forward. The present paper provides perspective on current strategies in the bio-marker development pathway, as well as the potential limitations associated with each step from discovery to clinical uptake. Canadian biomarker studies now underway illustrate the possibilities for assessment of risk, diagnosis, prognosis and response to therapy, and for the drug discovery process. PMID:19521568

  20. Guided Discoveries.

    ERIC Educational Resources Information Center

    Ehrlich, Amos

    1991-01-01

    Presented are four mathematical discoveries made by students on an arithmetical function using the Fibonacci sequence. Discussed is the nature of the role of the teacher in directing the students' discovery activities. (KR)

  1. Microfossils, biominerals, and chemical biomarkers in meteorites

    NASA Astrophysics Data System (ADS)

    Hoover, Richard B.; Rozanov, Alexei Y.

    2003-01-01

    The discovery of biominerals, chemical biomarkers and evidence of microfossils in the Mars meteorite (ALH84001) stimulated research into biomarkers, microbial extremophiles and provided impetus to the newly emerging fields of Astrobiology and Bacterial Paleontology. The debate following the ALH84001 results has highlighted the importance of developing methodologies for recognition of mineral and elemental bioindicators, chemical biomarkers and microfossils in terrestrial rocks and meteorites prior to sample return missions to comets, asteroids, and Mars. Comparative studies of living and fossil micro-organisms and biomarkers are vital to developing expertise needed to recognize indigenous biosignatures and recent contaminants. This paper reviews elemental and mineral bioindicators, chemical biomarkers and keropgen in terrestrial rocks and meteorites. Electron Microscopy images of hyperthermophilic nanobacteria, sulfur and sulfate reducing bacteria, and mineralized microfossils and kerogen found in-situ in carbonaceous meteorite rock matrix are presented.

  2. Impact of non-profit organizations on drug discovery: opportunities, gaps, solutions.

    PubMed

    Matter, Alex; Keller, Thomas H

    2008-04-01

    Non-profit organizations (NPO) play an increasingly important role in drug discovery and development for diseases that are neglected by the pharmaceutical industry because of low or absent commercial incentives. Governments and major private foundations such as the Wellcome Trust and the Bill & Melinda Gates Foundation increasingly step in to provide strategic direction, communication platforms and major resources, motivated by the fact that major healthcare problems remain unsolved. Drug discovery in the field of neglected diseases is fraught with complexities since, in many cases, important tools are lacking including readily available diagnostics, molecular epidemiology, appropriate model systems, representative strain collections, biomarkers, up-to-date trial methodologies and regulatory strategies. On top of this, the high hurdles addressing novel drug targets must be cleared.

  3. Exploring Biomarkers for Alzheimer's Disease.

    PubMed

    Sharma, Neeti; Singh, Anshika Nikita

    2016-07-01

    Alzheimer's Disease (AD) is one of the most common form of dementia occurring in elderly population worldwide. Currently Aβ42, tau and p-tau in the cerebrospinal fluid is estimated for confirmation of AD. CSF which is being used as the potent source for biomarker screening is obtained by invasive lumbar punctures. Thus, there is an urgent need of minimal invasive methods for identification of diagnostic markers for early detection of AD. Blood serum and plasma serves as an appropriate source, due to minimal discomfort to the patients, promoting frequent testing, better follow-up and better consent to clinical trials. Hence, the need of the hour demands discovery of diagnostic and prognostic patient specific signature biomarkers by using emerging technologies of mass spectrometry, microarrays and peptidomics. In this review we summarize the present scenario of AD biomarkers such as circulatory biomarkers, blood based amyloid markers, inflammatory markers and oxidative stress markers being investigated and also some of the potent biomarkers which might be able to predict early onset of Alzheimer's and delay cognitive impairment. PMID:27630867

  4. Automated, high-throughput IgG-antibody glycoprofiling platform.

    PubMed

    Stöckmann, Henning; Adamczyk, Barbara; Hayes, Jerrard; Rudd, Pauline M

    2013-09-17

    One of today's key challenges is the ability to decode the functions of complex carbohydrates in various biological contexts. To generate high-quality glycomics data in a high-throughput fashion, we developed a robotized and low-cost N-glycan analysis platform for glycoprofiling of immunoglobulin G antibodies (IgG), which are central players of the immune system and of vital importance in the biopharmaceutical industry. The key features include (a) rapid IgG affinity purification and sample concentration, (b) protein denaturation and glycan release on a multiwell filtration device, (c) glycan purification on solid-supported hydrazide, and (d) glycan quantification by ultra performance liquid chromatography. The sample preparation workflow was automated using a robotic liquid-handling workstation, allowing the preparation of 96 samples (or multiples thereof) in 22 h with excellent reproducibility and, thus, should greatly facilitate biomarker discovery and glycosylation monitoring of therapeutic IgGs.

  5. Immune biomarkers in the spectrum of childhood noncommunicable diseases.

    PubMed

    Skevaki, Chrysanthi; Van den Berg, Jolice; Jones, Nicholas; Garssen, Johan; Vuillermin, Peter; Levin, Michael; Landay, Alan; Renz, Harald; Calder, Philip C; Thornton, Catherine A

    2016-05-01

    A biomarker is an accurately and reproducibly quantifiable biological characteristic that provides an objective measure of health status or disease. Benefits of biomarkers include identification of therapeutic targets, monitoring of clinical interventions, and development of personalized (or precision) medicine. Challenges to the use of biomarkers include optimizing sample collection, processing and storage, validation, and often the need for sophisticated laboratory and bioinformatics approaches. Biomarkers offer better understanding of disease processes and should benefit the early detection, treatment, and management of multiple noncommunicable diseases (NCDs). This review will consider the utility of biomarkers in patients with allergic and other immune-mediated diseases in childhood. Typically, biomarkers are used currently to provide mechanistic insight or an objective measure of disease severity, with their future role in risk stratification/disease prediction speculative at best. There are many lessons to be learned from the biomarker strategies used for cancer in which biomarkers are in routine clinical use and industry-wide standardized approaches have been developed. Biomarker discovery and validation in children with disease lag behind those in adults; given the early onset and therefore potential lifelong effect of many NCDs, there should be more studies incorporating cohorts of children. Many pediatric biomarkers are at the discovery stage, with a long path to evaluation and clinical implementation. The ultimate challenge will be optimization of prevention strategies that can be implemented in children identified as being at risk of an NCD through the use of biomarkers. PMID:27155027

  6. Immune biomarkers in the spectrum of childhood noncommunicable diseases.

    PubMed

    Skevaki, Chrysanthi; Van den Berg, Jolice; Jones, Nicholas; Garssen, Johan; Vuillermin, Peter; Levin, Michael; Landay, Alan; Renz, Harald; Calder, Philip C; Thornton, Catherine A

    2016-05-01

    A biomarker is an accurately and reproducibly quantifiable biological characteristic that provides an objective measure of health status or disease. Benefits of biomarkers include identification of therapeutic targets, monitoring of clinical interventions, and development of personalized (or precision) medicine. Challenges to the use of biomarkers include optimizing sample collection, processing and storage, validation, and often the need for sophisticated laboratory and bioinformatics approaches. Biomarkers offer better understanding of disease processes and should benefit the early detection, treatment, and management of multiple noncommunicable diseases (NCDs). This review will consider the utility of biomarkers in patients with allergic and other immune-mediated diseases in childhood. Typically, biomarkers are used currently to provide mechanistic insight or an objective measure of disease severity, with their future role in risk stratification/disease prediction speculative at best. There are many lessons to be learned from the biomarker strategies used for cancer in which biomarkers are in routine clinical use and industry-wide standardized approaches have been developed. Biomarker discovery and validation in children with disease lag behind those in adults; given the early onset and therefore potential lifelong effect of many NCDs, there should be more studies incorporating cohorts of children. Many pediatric biomarkers are at the discovery stage, with a long path to evaluation and clinical implementation. The ultimate challenge will be optimization of prevention strategies that can be implemented in children identified as being at risk of an NCD through the use of biomarkers.

  7. Cross-Disciplinary Biomarkers Research: Lessons Learned by the CKD Biomarkers Consortium

    PubMed Central

    Hsu, Chi-yuan; Ballard, Shawn; Batlle, Daniel; Bonventre, Joseph V.; Böttinger, Erwin P.; Feldman, Harold I.; Klein, Jon B.; Coresh, Josef; Eckfeldt, John H.; Inker, Lesley A.; Kimmel, Paul L.; Kusek, John W.; Liu, Kathleen D.; Mauer, Michael; Mifflin, Theodore E.; Molitch, Mark E.; Nelsestuen, Gary L.; Rebholz, Casey M.; Rovin, Brad H.; Sabbisetti, Venkata S.; Van Eyk, Jennifer E.; Vasan, Ramachandran S.; Waikar, Sushrut S.; Whitehead, Krista M.

    2015-01-01

    Significant advances are needed to improve the diagnosis, prognosis, and management of persons with CKD. Discovery of new biomarkers and improvements in currently available biomarkers for CKD hold great promise to achieve these necessary advances. Interest in identification and evaluation of biomarkers for CKD has increased substantially over the past decade. In 2009, the National Institute of Diabetes and Digestive and Kidney Diseases established the CKD Biomarkers Consortium (http://www.ckdbiomarkersconsortium.org/), a multidisciplinary, collaborative study group located at over a dozen academic medical centers. The main objective of the consortium was to evaluate new biomarkers for purposes related to CKD in established prospective cohorts, including those enriched for CKD. During the first 5 years of the consortium, many insights into collaborative biomarker research were gained that may be useful to other investigators involved in biomarkers research. These lessons learned are outlined in this Special Feature and include a wide range of issues related to biospecimen collection, storage, and retrieval, and the internal and external quality assessment of laboratories that performed the assays. The authors propose that investigations involving biomarker discovery and validation are greatly enhanced by establishing and following explicit quality control metrics, including the use of blind replicate and proficiency samples, by carefully considering the conditions under which specimens are collected, handled, and stored, and by conducting pilot and feasibility studies when there are concerns about the condition of the specimens or the accuracy or reproducibility of the assays. PMID:25739849

  8. Molecular Pathology and Biomarkers.

    PubMed

    Ha, Patrick K; Stenman, Göran

    2016-01-01

    The field of salivary gland tumor biology is quite broad, given the numerous subtypes of both benign and malignant tumors originating from the major and minor salivary glands. Knowledge about the molecular pathology of these lesions is still limited, and there are few clinically useful diagnostic and prognostic biomarkers. However, recent discoveries of certain key genomic alterations, such as chromosome translocations, copy number alterations, and mutations, provide new insights into the molecular pathogenesis of these lesions and may help to better define them. It is also hoped that this new knowledge can help to guide therapy, but this translation has been somewhat slow to develop, perhaps due to the rarity of these tumors and the lack of large, randomized studies. However, because of the limitations inherent in what surgery and radiation can provide, there is an urgent need for understanding of the mechanisms of carcinogenesis in these tumors individually, so that chemotherapy and/or targeted therapy can be rationally selected.

  9. Biomarkers in melanoma.

    PubMed

    Griewank, Klaus G

    2016-01-01

    Malignant melanoma remains the skin cancer with the highest number of mortalities worldwide. While early diagnosis and complete surgical excision remain the best possibility for curing disease, prognosis at the stage of metastasis is still poor. Recent years have brought about considerable advances in terms of understanding the pathogenesis of melanoma and treating advanced disease. The discovery of activating BRAF mutations in around 50% of tumors has led to the introduction of targeted therapies downregulating BRAF signaling output. These have been further refined as combination therapies, which by targeting multiple targets have further improved the clinical outcome. A comparable, potentially even superior therapeutic alternative has been the introduction of immunotherapeutic approaches, including PD-1 and CTLA-4 checkpoint blockade therapies. Despite all genetic knowledge acquired in recent years, a clearly applicable prognostic signature of clinical value has not been established. General prognostic assessment of cutaneous melanoma remains based on clinical and pathological criteria (most importantly tumor thickness). The main challenges lying ahead are to establish a reliable prognostic test effectively determining which tumors will metastasize. Additionally establishing biomarkers which will allow patients to be stratified according to the most promising systemic therapy (immunotherapies and/or BRAF inhibitor therapies) is of utmost importance for patients with metastasized disease. Identifying serum biomarkers enabling disease to be monitored as well as determining tumor properties (i.e. resistance) would also be of great value. While initial results have proven promising, there remains much work to be done. PMID:27467728

  10. Novel diagnostic biomarkers for prostate cancer

    PubMed Central

    Madu, Chikezie O.; Lu, Yi

    2010-01-01

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

  11. Novel diagnostic biomarkers for prostate cancer.

    PubMed

    Madu, Chikezie O; Lu, Yi

    2010-10-06

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

  12. DNA methylation biomarkers: cancer and beyond.

    PubMed

    Mikeska, Thomas; Craig, Jeffrey M

    2014-01-01

    Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient's response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease.

  13. DNA Methylation Biomarkers: Cancer and Beyond

    PubMed Central

    Mikeska, Thomas; Craig, Jeffrey M.

    2014-01-01

    Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease. PMID:25229548

  14. Drug discovery FAQs: workflows for answering multidomain drug discovery questions.

    PubMed

    Chichester, Christine; Digles, Daniela; Siebes, Ronald; Loizou, Antonis; Groth, Paul; Harland, Lee

    2015-04-01

    Modern data-driven drug discovery requires integrated resources to support decision-making and enable new discoveries. The Open PHACTS Discovery Platform (http://dev.openphacts.org) was built to address this requirement by focusing on drug discovery questions that are of high priority to the pharmaceutical industry. Although complex, most of these frequently asked questions (FAQs) revolve around the combination of data concerning compounds, targets, pathways and diseases. Computational drug discovery using workflow tools and the integrated resources of Open PHACTS can deliver answers to most of these questions. Here, we report on a selection of workflows used for solving these use cases and discuss some of the research challenges. The workflows are accessible online from myExperiment (http://www.myexperiment.org) and are available for reuse by the scientific community.

  15. Cytokines as potential biomarkers for Parkinson's disease: a multiplex approach.

    PubMed

    Litteljohn, Darcy; Hayley, Shawn

    2012-01-01

    Cytokines, which are immunological messengers facilitating both intra- and inter-system communication, are considered central players in the neuroinflammatory cascades associated with the neurodegenerative process in Parkinson's disease (PD) and other neurological disorders. They have also been implicated in depression and other cognitive (e.g., memory impairment, dementia) and affective disturbances (e.g., anxiety) that show high co-morbidity with neurodegenerative diseases. As such, cytokines may hold great promise as serological biomarkers in PD, with potential applications ranging from early diagnosis and disease staging, to prognosis, drug discovery, and tracking the response to treatment. Subclassification or risk stratification in PD could be based (among other things) on reliably determined cytokine panel profiles or "signatures" of particular co-morbid disease states or at-risk groups (e.g., PD alone, PD with depression and/or dementia). Researchers and clinicians seeking to describe cytokine variations in health vs. disease will benefit greatly from technologies that allow a high degree of multiplexing and thus permit the simultaneous determination of a large roster of cytokines in single small-volume samples. The need for such highly paralleled assays is underscored by the fact that cytokines do not act in isolation but rather against a backdrop of complementary and antagonistic cytokine effects; ascribing valence to the actions of any one cytokine thus requires specific knowledge about the larger cytokine milieu. This chapter provides a technological overview of the major cytokine multiplex assay platforms before discussing the implications of such tools for biomarker discovery and related applications in PD and its depressive and cognitive co-morbidities.

  16. Diabetes Mellitus: Channeling Care through Cellular Discovery

    PubMed Central

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

    2010-01-01

    Diabetes mellitus (DM) impacts a significant portion of the world’s population and care for this disorder places an economic burden on the gross domestic product for any particular country. Furthermore, both Type 1 and Type 2 DM are becoming increasingly prevalent and there is increased incidence of impaired glucose tolerance in the young. The complications of DM are protean and can involve multiple systems throughout the body that are susceptible to the detrimental effects of oxidative stress and apoptotic cell injury. For these reasons, innovative strategies are necessary for the implementation of new treatments for DM that are generated through the further understanding of cellular pathways that govern the pathological consequences of DM. In particular, both the precursor for the coenzyme β-nicotinamide adenine dinucleotide (NAD+), nicotinamide, and the growth factor erythropoietin offer novel platforms for drug discovery that involve cellular metabolic homeostasis and inflammatory cell control. Interestingly, these agents and their tightly associated pathways that consist of cell cycle regulation, protein kinase B, forkhead transcription factors, and Wnt signaling also function in a broader sense as biomarkers for disease onset and progression. PMID:20158461

  17. IMMUNOASSAYS FOR BIOMARKERS AND NEUTRACEUTICALS/PHARMACEUTICALS

    EPA Science Inventory

    Product is an abstract for an invited oral platform presentation to be given at the Pittsburgh Conference to be held February 25 - March 2, 2007 in Chicago, Ilinois. The presentation will describe methods research for the development of bioanalytical methods to measure biomarker...

  18. Novel Biomarkers in Glomerular Disease

    PubMed Central

    Caliskan, Yasar; Kiryluk, Krzysztof

    2014-01-01

    Glomerular diseases are major contributors to the global burden of end stage kidney disease. The clinical course and outcome of these disorders are extremely variable and difficult to predict. The clinical trajectories range from a benign and spontaneously remitting condition to a symptomatic and rapidly progressive disease. The diagnosis is based entirely on the evaluation of kidney biopsy, but this invasive procedure carries multiple risks and often fails to predict the clinical course or responsiveness to treatment. However, more recent advances in genetics and molecular biology facilitated elucidation of novel pathogenic mechanisms of these disorders. These discoveries fuel the development of novel biomarkers and offer prospects of non-invasive diagnosis and improved prognostication. Our review focuses on the most promising novel biomarkers that have recently emerged for the major types of glomerular diseases, including IgA nephropathy, membranous nephropathy, focal segmental glomerulosclerosis, and membranoproliferative glomerulonephritis. PMID:24602470

  19. Cancer Biomarkers: Can We Turn Recent Failures into Success?

    PubMed Central

    2010-01-01

    Disease biomarkers are used widely in medicine. But very few biomarkers are useful for cancer diagnosis and monitoring. Over the past 15 years, major investments have been made to discover and validate cancer biomarkers. Despite such investments, no new major cancer biomarkers have been approved for clinical use for at least 25 years. In the last decade, many reports have described new cancer biomarkers that promised to revolutionize the diagnosis of cancer and the management of cancer patients. However, many initially promising biomarkers have not been validated for clinical use. In this commentary, a plethora of parameters before sample analysis, during sample analysis, and after sample analysis that can complicate biomarker discovery and validation and lead to “false discovery” are discussed. Several examples of biomarker discoveries that were published in high-profile journals are also presented, as well as why they were not validated and the lessons learned from these false discoveries, so that similar mistakes can be avoided in the future. PMID:20705936

  20. Biomarkers in inflammatory bowel disease: current practices and recent advances.

    PubMed

    Iskandar, Heba N; Ciorba, Matthew A

    2012-04-01

    Crohn's disease and ulcerative colitis represent the two main forms of the idiopathic chronic inflammatory bowel diseases (IBD). Currently available blood and stool based biomarkers provide reproducible, quantitative tools that can complement clinical assessment to aid clinicians in IBD diagnosis and management. C-reactive protein and fecal based leukocyte markers can help the clinician distinguish IBD from noninflammatory diarrhea and assess disease activity. The ability to differentiate between forms of IBD and predict risk for disease complications is specific to serologic tests including antibodies against Saccharomyces cerevisiae and perinuclear antineutrophil cytoplasmic proteins. Advances in genomic, proteomic, and metabolomic array based technologies are facilitating the development of new biomarkers for IBD. The discovery of novel biomarkers, which can correlate with mucosal healing or predict long-term disease course has the potential to significantly improve patient care. This article reviews the uses and limitations of currently available biomarkers and highlights recent advances in IBD biomarker discovery. PMID:22424434

  1. Discovering cancer biomarkers from clinical samples by protein microarrays.

    PubMed

    Hu, Bin; Niu, Xin; Cheng, Li; Yang, Li-Na; Li, Qing; Wang, Yang; Tao, Sheng-Ce; Zhou, Shu-Min

    2015-02-01

    Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives. PMID:25523829

  2. Parkinson's disease plasma biomarkers: an automated literature analysis followed by experimental validation.

    PubMed

    Alberio, Tiziana; Bucci, Enrico M; Natale, Massimo; Bonino, Dario; Di Giovanni, Marco; Bottacchi, Edo; Fasano, Mauro

    2013-09-01

    Diagnosis of Parkinson's disease (PD) is currently assessed by the clinical evaluation of extrapyramidal signs. The identification of specific biomarkers would be advisable, however most studies stop at the discovery phase, with no biomarkers reaching clinical exploitation. To this purpose, we developed an automated literature analysis procedure to retrieve all the background knowledge available in public databases. The bioinformatic platform allowed us to analyze more than 51,000 scientific papers dealing with PD, containing information on 4121 proteins. Out of these, we could track back 35 PD-related proteins as present in at least two published 2-DE maps of human plasma. Then, 9 different proteins (haptoglobin, transthyretin, apolipoprotein A-1, serum amyloid P component, apolipoprotein E, complement factor H, fibrinogen γ, thrombin, complement C3) split into 32 spots were identified as a potential diagnostic pattern. Eventually, we compared the collected literature data to experimental gels from 90 subjects (45 PD patients, 45 non-neurodegenerative control subjects) to experimentally verify their potential as plasma biomarkers of PD.

  3. microRNAs as neuroregulators, biomarkers and therapeutic agents in neurodegenerative diseases.

    PubMed

    Basak, Indranil; Patil, Ketan S; Alves, Guido; Larsen, Jan Petter; Møller, Simon Geir

    2016-02-01

    The last decade has experienced the emergence of microRNAs as a key molecular tool for the diagnosis and prognosis of human diseases. Although the focus has mostly been on cancer, neurodegenerative diseases present an exciting, yet less explored, platform for microRNA research. Several studies have highlighted the significance of microRNAs in neurogenesis and neurodegeneration, and pre-clinical studies have shown the potential of microRNAs as biomarkers. Despite this, no bona fide microRNAs have been identified as true diagnostic or prognostic biomarkers for neurodegenerative disease. This is mainly due to the lack of precisely defined patient cohorts and the variability within and between individual cohorts. However, the discovery that microRNAs exist as stable molecules at detectable levels in body fluids has opened up new avenues for microRNAs as potential biomarker candidates. Furthermore, technological developments in microRNA biology have contributed to the possible design of microRNA-mediated disease intervention strategies. The combination of these advancements, with the availability of well-defined longitudinal patient cohort, promises to not only assist in developing invaluable diagnostic tools for clinicians, but also to increase our overall understanding of the underlying heterogeneity of neurodegenerative diseases. In this review, we present a comprehensive overview of the existing knowledge of microRNAs in neurodegeneration and provide a perspective of the applicability of microRNAs as a basis for future therapeutic intervention strategies.

  4. microRNAs as neuroregulators, biomarkers and therapeutic agents in neurodegenerative diseases.

    PubMed

    Basak, Indranil; Patil, Ketan S; Alves, Guido; Larsen, Jan Petter; Møller, Simon Geir

    2016-02-01

    The last decade has experienced the emergence of microRNAs as a key molecular tool for the diagnosis and prognosis of human diseases. Although the focus has mostly been on cancer, neurodegenerative diseases present an exciting, yet less explored, platform for microRNA research. Several studies have highlighted the significance of microRNAs in neurogenesis and neurodegeneration, and pre-clinical studies have shown the potential of microRNAs as biomarkers. Despite this, no bona fide microRNAs have been identified as true diagnostic or prognostic biomarkers for neurodegenerative disease. This is mainly due to the lack of precisely defined patient cohorts and the variability within and between individual cohorts. However, the discovery that microRNAs exist as stable molecules at detectable levels in body fluids has opened up new avenues for microRNAs as potential biomarker candidates. Furthermore, technological developments in microRNA biology have contributed to the possible design of microRNA-mediated disease intervention strategies. The combination of these advancements, with the availability of well-defined longitudinal patient cohort, promises to not only assist in developing invaluable diagnostic tools for clinicians, but also to increase our overall understanding of the underlying heterogeneity of neurodegenerative diseases. In this review, we present a comprehensive overview of the existing knowledge of microRNAs in neurodegeneration and provide a perspective of the applicability of microRNAs as a basis for future therapeutic intervention strategies. PMID:26608596

  5. The ups and downs of DNA repair biomarkers for PARP inhibitor therapies

    PubMed Central

    Wang, XiaoZhe; Weaver, David T

    2011-01-01

    PARP inhibitors are emerging as a valuable new drug class in the treatment of cancer. Recent discoveries make a compelling case for the complexity of DNA repair biomarker evaluation and underscore the need to examine at multiple biomarkers in a relational manner. This review updates the current trends in DNA repair biomarker strategies in use for the PARP inhibitors and describes the impact of many DNA repair biomarkers on PARP inhibitor benefit in the cancer clinic. PMID:21968427

  6. Biomarkers of An Autoimmune Skin Disease—Psoriasis

    PubMed Central

    Jiang, Shan; Hinchliffe, Taylor E.; Wu, Tianfu

    2015-01-01

    Psoriasis is one of the most prevalent autoimmune skin diseases. However, its etiology and pathogenesis are still unclear. Over the last decade, omics-based technologies have been extensively utilized for biomarker discovery. As a result, some promising markers for psoriasis have been identified at the genome, transcriptome, proteome, and metabolome level. These discoveries have provided new insights into the underlying molecular mechanisms and signaling pathways in psoriasis pathogenesis. More importantly, some of these markers may prove useful in the diagnosis of psoriasis and in the prediction of disease progression once they have been validated. In this review, we summarize the most recent findings in psoriasis biomarker discovery. In addition, we will discuss several emerging technologies and their potential for novel biomarker discovery and diagnostics for psoriasis. PMID:26362816

  7. [Research and development for cancer biomarker].

    PubMed

    Nakagawa, Hidewaki

    2012-05-01

    Cancer is a very heterogeneous group of diseases whose pathogenesis, aggressiveness, metastatic potential, and response to treatment can be different among individual patients. Personalized medicine should be practiced to take care of these cancer patients to improve medical care quality and reduce health care cost. Biomarker discovery and development are one of the cores of personalized medicine for cancer, which encompasses screening, early diagnosis, prognosis, cancer stratification, prediction of treatment efficacy and adverse reaction. Thanks to the emergence of new innovated high-throughput technologies, biomarker research and development are now efficiently performed in many laboratories and several candidates have been identified and applied to cancer patient care. To perform biomarker research and development more efficiently, we need to determine the endpoint of biomarkers clearly, to obtain a number of high-quality clinical samples with solid clinical information, and to performed high-throughput analysis in non-bias way. Once we discover biomarker candidates, we definitely need to validate their potential as biomarkers by analyzing independent sample sets with more accurate and focusing methods. Recently, pharmaceutical companies are trying to develop a drug-specific companion biomarker kits that can predict the efficacy or side effect of drugs in the early stage of development of anti-cancer drugs.

  8. Ensuring continued progress in biomarkers for amyotrophic lateral sclerosis

    PubMed Central

    Turner, Martin R; Benatar, Michael

    2015-01-01

    Multiple candidate biomarkers for amyotrophic lateral sclerosis (ALS) have emerged across a range of platforms. Replication of results, however, has been absent in all but a few cases, and the range of control samples has been limited. If progress toward clinical translation is to continue, the specific biomarker needs of ALS, which differ from those of other neurodegenerative disorders, as well as the challenges inherent to longitudinal ALS biomarker cohorts, must be understood. Appropriate application of multimodal approaches, international collaboration, presymptomatic studies, and biomarker integration into future therapeutic trials are among the essential priorities going forward. PMID:25288265

  9. Biomarkers of (osteo)arthritis

    PubMed Central

    Mobasheri, Ali; Henrotin, Yves

    2015-01-01

    Abstract Arthritic diseases are a major cause of disability and morbidity, and cause an enormous burden for health and social care systems globally. Osteoarthritis (OA) is the most common form of arthritis. The key risk factors for the development of OA are age, obesity, joint trauma or instability. Metabolic and endocrine diseases can also contribute to the pathogenesis of OA. There is accumulating evidence to suggest that OA is a whole-organ disease that is influenced by systemic mediators, inflammaging, innate immunity and the low-grade inflammation induced by metabolic syndrome. Although all joint tissues are implicated in disease progression in OA, articular cartilage has received the most attention in the context of aging, injury and disease. There is increasing emphasis on the early detection of OA as it has the capacity to target and treat the disease more effectively. Indeed it has been suggested that this is the era of “personalized prevention” for OA. However, the development of strategies for the prevention of OA require new and sensitive biomarker tools that can detect the disease in its molecular and pre-radiographic stage, before structural and functional alterations in cartilage integrity have occurred. There is also evidence to support a role for biomarkers in OA drug discovery, specifically the development of disease modifying osteoarthritis drugs. This Special Issue of Biomarkers is dedicated to recent progress in the field of OA biomarkers. The papers in this Special Issue review the current state-of-the-art and discuss the utility of OA biomarkers as diagnostic and prognostic tools. PMID:26954784

  10. Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

    PubMed

    Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

    2013-08-01

    A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

  11. Biomarkers in Parkinson's disease (recent update).

    PubMed

    Sharma, Sushil; Moon, Carolyn Seungyoun; Khogali, Azza; Haidous, Ali; Chabenne, Anthony; Ojo, Comfort; Jelebinkov, Miriana; Kurdi, Yousef; Ebadi, Manuchair

    2013-09-01

    Parkinson's disease (PD) is the second most common neurodegenerative disorder mostly affecting the aging population over sixty. Cardinal symptoms including, tremors, muscle rigidity, drooping posture, drooling, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons are already destroyed. Hence we need early, sensitive, specific, and economical peripheral and/or central biomarker(s) for the differential diagnosis, prognosis, and treatment of PD. These can be classified as clinical, biochemical, genetic, proteomic, and neuroimaging biomarkers. Novel discoveries of genetic as well as nongenetic biomarkers may be utilized for the personalized treatment of PD during preclinical (premotor) and clinical (motor) stages. Premotor biomarkers including hyper-echogenicity of substantia nigra, olfactory and autonomic dysfunction, depression, hyposmia, deafness, REM sleep disorder, and impulsive behavior may be noticed during preclinical stage. Neuroimaging biomarkers (PET, SPECT, MRI), and neuropsychological deficits can facilitate differential diagnosis. Single-cell profiling of dopaminergic neurons has identified pyridoxal kinase and lysosomal ATPase as biomarker genes for PD prognosis. Promising biomarkers include: fluid biomarkers, neuromelanin antibodies, pathological forms of α-Syn, DJ-1, amyloid β and tau in the CSF, patterns of gene expression, metabolomics, urate, as well as protein profiling in the blood and CSF samples. Reduced brain regional N-acetyl-aspartate is a biomarker for the in vivo assessment of neuronal loss using magnetic resonance spectroscopy and T2 relaxation time with MRI. To confirm PD diagnosis, the PET biomarkers include [(18)F]-DOPA for estimating dopaminergic neurotransmission, [(18)F]dG for mitochondrial bioenergetics, [(18)F]BMS for mitochondrial complex-1, [(11)C](R)-PK11195 for microglial activation, SPECT imaging with (123)Iflupane and βCIT for dopamine transporter, and urinary

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

    PubMed

    Orsini, M; Travaglione, A; Capobianco, E

    2013-07-01

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

  13. Role of biomarkers in sepsis care.

    PubMed

    Samraj, Ravi S; Zingarelli, Basilia; Wong, Hector R

    2013-11-01

    Sepsis is one of the leading causes of mortality and morbidity, even with the current availability of extended-spectrum antibiotics and advanced medical care. Biomarkers offer a tool in facilitating early diagnosis, in identifying patient populations at high risk of complications, and in monitoring progression of the disease, which are critical assessments for appropriate therapy and improvement in patient outcomes. Several biomarkers are already available for clinical use in sepsis; however, their effectiveness in many instances is limited by the lack of specificity and sensitivity to characterize the presence of an infection and the complexity of the inflammatory and immune processes and to stratify patients into homogenous groups for specific treatments. Current advances in molecular techniques have provided new tools facilitating the discovery of novel biomarkers, which can vary from metabolites and chemical products present in body fluids to genes and proteins in circulating blood cells. The purpose of this review was to examine the current status of sepsis biomarkers, with special emphasis on emerging markers, which are undergoing validation and may transition into clinical practice for their informative value in diagnosis, prognosis, or response to therapy. We will also discuss the new concept of combination biomarkers and biomarker risk models, their existing challenges, and their potential use in the daily management of patients with sepsis.

  14. Statistical consideration for clinical biomarker research in bladder cancer

    PubMed Central

    Shariat, Shahrokh F.; Lotan, Yair; Vickers, Andrew; Karakiewicz, Pierre I.; Schmitz-Dräger, Bernd J.; Goebell, Peter J.; Malats, Nuria

    2012-01-01

    Purpose To critically review and illustrate current methodologic and statistical considerations for bladder cancer biomarker discovery and evaluation. Methods Original, review, and methodological articles, and editorials were reviewed and summarized. Results Biomarkers may be useful at multiple stages of bladder cancer management: early detection, diagnosis, staging, prognosis, and treatment; however, few novel biomarkers are currently used in clinical practice. The reasons for this disjunction are manifold and reflect the long and difficult pathway from candidate biomarker discovery to clinical assay, and the lack of coherent and comprehensive processes (pipelines) for biomarker development. Conceptually, the development of new biomarkers should be a process that is similar to therapeutic drug evaluation - a highly regulated process with carefully regulated phases from discovery to human applications. In a further effort to address the pervasive problem of inadequacies in the design, analysis, and reporting of biomarker prognostic studies, a set of reporting recommendations are discussed. For example, biomarkers should provide unique information that adds to known clinical and pathologic information. Conventional multivariable analyses are not sufficient to demonstrate improved prediction of outcomes. Predictive models, including or excluding any new putative biomarker, needs to show clinically significant improvement of performance in order to claim any real benefit. Towards this end, proper model building, avoidance of overfitting, and external validation are crucial. In addition, it is important to choose appropriate performance measures dependent on outcome and prediction type and to avoid use of cut-points. Biomarkers providing a continuous score provide potentially more useful information than cut-points since risk fits a continuum model. Combination of complementary and independent biomarkers is likely to better capture the biologic potential of a tumor

  15. Space Discovery.

    ERIC Educational Resources Information Center

    Blackman, Joan

    1998-01-01

    Describes one teacher's experience taking Space Discovery courses that were sponsored by the United States Space Foundation (USSF). These courses examine the history of space science, theory of orbits and rocketry, the effects of living in outer space on humans, and space weather. (DDR)

  16. BIOMARKERS OF REPRODUCTIVE TOXICITY

    EPA Science Inventory

    Identification and verification of anatomical, endocrine, cellular and molecular biomarkers is crucial for successful clinical diagnosis and treatment of toxicity and disease, as well as basic toxicological, epidemiological and other research. Various in situ biomarkers of repro...

  17. Biomarkers in Computational Toxicology

    EPA Science Inventory

    Biomarkers are a means to evaluate chemical exposure and/or the subsequent impacts on toxicity pathways that lead to adverse health outcomes. Computational toxicology can integrate biomarker data with knowledge of exposure, chemistry, biology, pharmacokinetics, toxicology, and e...

  18. Fluid biomarkers in multiple system atrophy: A review of the MSA Biomarker Initiative.

    PubMed

    Laurens, Brice; Constantinescu, Radu; Freeman, Roy; Gerhard, Alexander; Jellinger, Kurt; Jeromin, Andreas; Krismer, Florian; Mollenhauer, Brit; Schlossmacher, Michael G; Shaw, Leslie M; Verbeek, Marcel M; Wenning, Gregor K; Winge, Kristian; Zhang, Jing; Meissner, Wassilios G

    2015-08-01

    Despite growing research efforts, no reliable biomarker currently exists for the diagnosis and prognosis of multiple system atrophy (MSA). Such biomarkers are urgently needed to improve diagnostic accuracy, prognostic guidance and also to serve as efficacy measures or surrogates of target engagement for future clinical trials. We here review candidate fluid biomarkers for MSA and provide considerations for further developments and harmonization of standard operating procedures. A PubMed search was performed until April 24, 2015 to review the literature with regard to candidate blood and cerebrospinal fluid (CSF) biomarkers for MSA. Abstracts of 1760 studies were retrieved and screened for eligibility. The final list included 60 studies assessing fluid biomarkers in patients with MSA. Most studies have focused on alpha-synuclein, markers of axonal degeneration or catecholamines. Their results suggest that combining several CSF fluid biomarkers may be more successful than using single markers, at least for the diagnosis. Currently, the clinically most useful markers may comprise a combination of the light chain of neurofilament (which is consistently elevated in MSA compared to controls and Parkinson's disease), metabolites of the catecholamine pathway and proteins such as α-synuclein, DJ-1 and total-tau. Beyond future efforts in biomarker discovery, the harmonization of standard operating procedures will be crucial for future success.

  19. Coronary Artery-Bypass-Graft Surgery Increases the Plasma Concentration of Exosomes Carrying a Cargo of Cardiac MicroRNAs: An Example of Exosome Trafficking Out of the Human Heart with Potential for Cardiac Biomarker Discovery

    PubMed Central

    Emanueli, Costanza; Fiorentino, Francesca; Reeves, Barnaby C.; Beltrami, Cristina; Mumford, Andrew; Clayton, Aled; Gurney, Mark; Shantikumar, Saran; Angelini, Gianni D.

    2016-01-01

    Introduction Exosome nanoparticles carry a composite cargo, including microRNAs (miRs). Cultured cardiovascular cells release miR-containing exosomes. The exosomal trafficking of miRNAs from the heart is largely unexplored. Working on clinical samples from coronary-artery by-pass graft (CABG) surgery, we investigated if: 1) exosomes containing cardiac miRs and hence putatively released by cardiac cells increase in the circulation after surgery; 2) circulating exosomes and exosomal cardiac miRs correlate with cardiac troponin (cTn), the current “gold standard” surrogate biomarker of myocardial damage. Methods and Results The concentration of exosome-sized nanoparticles was determined in serial plasma samples. Cardiac-expressed (miR-1, miR-24, miR-133a/b, miR-208a/b, miR-210), non-cardiovascular (miR-122) and quality control miRs were measured in whole plasma and in plasma exosomes. Linear regression analyses were employed to establish the extent to which the circulating individual miRs, exosomes and exosomal cardiac miR correlated with cTn-I. Cardiac-expressed miRs and the nanoparticle number increased in the plasma on completion of surgery for up to 48 hours. The exosomal concentration of cardiac miRs also increased after CABG. Cardiac miRs in the whole plasma did not correlate significantly with cTn-I. By contrast cTn-I was positively correlated with the plasma exosome level and the exosomal cardiac miRs. Conclusions The plasma concentrations of exosomes and their cargo of cardiac miRs increased in patients undergoing CABG and were positively correlated with hs-cTnI. These data provide evidence that CABG induces the trafficking of exosomes from the heart to the peripheral circulation. Future studies are necessary to investigate the potential of circulating exosomes as clinical biomarkers in cardiac patients. PMID:27128471

  20. Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges.

    PubMed

    Füzéry, Anna K; Levin, Joshua; Chan, Maria M; Chan, Daniel W

    2013-01-01

    Tremendous efforts have been made over the past few decades to discover novel cancer biomarkers for use in clinical practice. However, a striking discrepancy exists between the effort directed toward biomarker discovery and the number of markers that make it into clinical practice. One of the confounding issues in translating a novel discovery into clinical practice is that quite often the scientists working on biomarker discovery have limited knowledge of the analytical, diagnostic, and regulatory requirements for a clinical assay. This review provides an introduction to such considerations with the aim of generating more extensive discussion for study design, assay performance, and regulatory approval in the process of translating new proteomic biomarkers from discovery into cancer diagnostics. We first describe the analytical requirements for a robust clinical biomarker assay, including concepts of precision, trueness, specificity and analytical interference, and carryover. We next introduce the clinical considerations of diagnostic accuracy, receiver operating characteristic analysis, positive and negative predictive values, and clinical utility. We finish the review by describing components of the FDA approval process for protein-based biomarkers, including classification of biomarker assays as medical devices, analytical and clinical performance requirements, and the approval process workflow. While we recognize that the road from biomarker discovery, validation, and regulatory approval to the translation into the clinical setting could be long and difficult, the reward for patients, clinicians and scientists could be rather significant. PMID:24088261

  1. Translation of proteomic biomarkers into FDA approved cancer diagnostics: issues and challenges

    PubMed Central

    2013-01-01

    Tremendous efforts have been made over the past few decades to discover novel cancer biomarkers for use in clinical practice. However, a striking discrepancy exists between the effort directed toward biomarker discovery and the number of markers that make it into clinical practice. One of the confounding issues in translating a novel discovery into clinical practice is that quite often the scientists working on biomarker discovery have limited knowledge of the analytical, diagnostic, and regulatory requirements for a clinical assay. This review provides an introduction to such considerations with the aim of generating more extensive discussion for study design, assay performance, and regulatory approval in the process of translating new proteomic biomarkers from discovery into cancer diagnostics. We first describe the analytical requirements for a robust clinical biomarker assay, including concepts of precision, trueness, specificity and analytical interference, and carryover. We next introduce the clinical considerations of diagnostic accuracy, receiver operating characteristic analysis, positive and negative predictive values, and clinical utility. We finish the review by describing components of the FDA approval process for protein-based biomarkers, including classification of biomarker assays as medical devices, analytical and clinical performance requirements, and the approval process workflow. While we recognize that the road from biomarker discovery, validation, and regulatory approval to the translation into the clinical setting could be long and difficult, the reward for patients, clinicians and scientists could be rather significant. PMID:24088261

  2. Glycan-based biomarkers for mucopolysaccharidoses

    PubMed Central

    Lawrence, Roger; Brown, Jillian R.; Lorey, Fred; Dickson, Patricia I.; Crawford, Brett E.; Esko, Jeffrey D.

    2013-01-01

    The mucopolysaccharidoses (MPS) result from attenuation or loss of enzyme activities required for lysosomal degradation of the glycosaminoglycans, hyaluronan, heparan sulfate, chondroitin/dermatan sulfate, and keratan sulfate. This review provides a summary of glycan biomarkers that have been used to characterize animal models of MPS, for diagnosis of patients, and for monitoring therapy based on hematopoietic stem cell transplantation and enzyme replacement therapy. Recent advances have focused on the non-reducing terminus of the glycosaminoglycans that accumulate as biomarkers, using a combination of enzymatic digestion with bacterial enzymes followed by quantitative liquid chromatography/mass spectrometry. These new methods provide a simple, rapid diagnostic strategy that can be applied to samples of urine, blood, cerebrospinal fluid, cultured cells and dried blood spots from newborn infants. Analysis of the non-reducing end glycans provides a method for monitoring enzyme replacement and substrate reduction therapies and serves as a discovery tool for uncovering novel biomarkers and new forms of mucopolysaccharidoses. PMID:23958290

  3. microRNAs as cancer biomarkers.

    PubMed

    Flatmark, Kjersti; Høye, Eirik; Fromm, Bastian

    2016-01-01

    Since their discovery in 1993, microRNAs (miRNAs) have been identified as important gene regulators in many biological processes and as key molecular players in human disease, including cancer where they show specific pathogenic deregulation. Their remarkable chemical stability, the availability of very sensitive miRNA detection methods and the fact that miRNAs can be extracted from and detected in various kinds of clinically relevant samples, such as solid tissues, body fluids and secretions make them excellent candidate biomarkers. However, no miRNA has yet entered the level of practical clinical relevance. We present a brief background and some key aspects and challenges of miRNAs as cancer biomarkers, we discuss shortfalls and identify possible routes towards the use of miRNAs as reliable biomarkers for cancer. PMID:27542003

  4. Circulating Non-coding RNA as Biomarkers in Colorectal Cancer.

    PubMed

    Ferracin, Manuela; Lupini, Laura; Mangolini, Alessandra; Negrini, Massimo

    2016-01-01

    Recent studies suggested that colorectal cancer influences the types and quantity of nucleic acids - especially microRNAs - detected in the bloodstream. Concentration of circulating (cell-free) microRNAs, and possibly of other non-coding RNAs, could therefore serve as valuable colorectal cancer biomarker and could deliver insight into the disease process. This chapter addresses the recent discoveries on circulating microRNA and long non-coding RNA as diagnostic or prognostic biomarkers in colorectal cancer. PMID:27573900

  5. Disease Biomarker Query from RNA-Seq Data

    PubMed Central

    Han, Henry; Jiang, Xiaoqian

    2014-01-01

    As a revolutionary way to unveil transcription, RNA-Seq technologies are challenging bioinformatics for its large data volumes and complexities. A large number of computational models have been proposed for differential expression (DE) analysis and normalization from different standing points. However, there were no studies available yet to conduct disease biomarker discovery for this type of high-resolution digital gene expression data, which will actually be essential to explore its potential in clinical bioinformatics. Although there were many biomarker discovery algorithms available in traditional omics communities, they cannot be applied to RNA-Seq count data to seek biomarkers directly for its special characteristics. In this work, we have presented a biomarker discovery algorithm, SEQ-Marker for RNA-Seq data, which is built on a novel data-driven feature selection algorithm, nonnegative singular value approximation (NSVA), which contributes to the robustness and sensitivity of the following DE analysis by taking advantages of the built-in characteristics of RNA-Seq count data. As a biomarker discovery algorithm built on network marker topology, the proposed SEQ-Marker not only bridges transcriptomics and systems biology but also contributes to clinical diagnostics. PMID:25392686

  6. A Framework for Evaluating Biomarkers for Early Detection: Validation of Biomarker Panels for Ovarian Cancer

    PubMed Central

    Zhu, Claire S.; Pinsky, Paul F.; Cramer, Daniel W.; Ransohoff, David F.; Hartge, Patricia; Pfeiffer, Ruth M.; Urban, Nicole; Mor, Gil; Bast, Robert C.; Moore, Lee E.; Lokshin, Anna E.; McIntosh, Martin W.; Skates, Steven J.; Vitonis, Allison; Zhang, Zhen; Ward, David C.; Symanowski, James T.; Lomakin, Aleksey; Fung, Eric T.; Sluss, Patrick M.; Scholler, Nathalie; Lu, Karen H.; Marrangoni, Adele M.; Patriotis, Christos; Srivastava, Sudhir; Buys, Saundra S.; Berg, Christine D.

    2011-01-01

    A panel of biomarkers may improve predictive performance over individual markers. Although many biomarker panels have been described for ovarian cancer, few studies used pre-diagnostic samples to assess the potential of the panels for early detection. We conducted a multi-site systematic evaluation of biomarker panels using pre-diagnostic serum samples from the Prostate, Lung, Colorectal, and Ovarian Cancer (PLCO) screening trial. Using a nested case-control design, levels of 28 biomarkers were measured laboratory-blinded in 118 serum samples obtained before cancer diagnosis and 951 serum samples from matched controls. Five predictive models, each containing 6–8 biomarkers, were evaluated according to a pre-determined analysis plan. Three sequential analyses were conducted: blinded validation of previously established models (Step 1); simultaneous split-sample discovery and validation of models (Step 2); and exploratory discovery of new models (Step 3). Sensitivity, specificity, sensitivity at 98% specificity, and AUC were computed for the models and CA125 alone among 67 cases diagnosed within one year of blood draw and 476 matched controls. In Step 1, one model showed comparable performance to CA125, with sensitivity, specificity and AUC at 69.2%, 96.6% and 0.892, respectively. Remaining models had poorer performance than CA125 alone. In Step 2, we observed a similar pattern. In Step 3, a model derived from all 28 markers failed to show improvement over CA125. Thus, biomarker panels discovered in diagnostic samples may not validate in pre-diagnostic samples; utilizing pre-diagnostic samples for discovery may be helpful in developing validated early detection panels. PMID:21372037

  7. Cosmic Discovery

    NASA Astrophysics Data System (ADS)

    Harwit, Martin

    1984-04-01

    In the remarkable opening section of this book, a well-known Cornell astronomer gives precise thumbnail histories of the 43 basic cosmic discoveries - stars, planets, novae, pulsars, comets, gamma-ray bursts, and the like - that form the core of our knowledge of the universe. Many of them, he points out, were made accidentally and outside the mainstream of astronomical research and funding. This observation leads him to speculate on how many more major phenomena there might be and how they might be most effectively sought out in afield now dominated by large instruments and complex investigative modes and observational conditions. The book also examines discovery in terms of its political, financial, and sociological context - the role of new technologies and of industry and the military in revealing new knowledge; and methods of funding, of peer review, and of allotting time on our largest telescopes. It concludes with specific recommendations for organizing astronomy in ways that will best lead to the discovery of the many - at least sixty - phenomena that Harwit estimates are still waiting to be found.

  8. Stable-isotope dilution LC–MS for quantitative biomarker analysis

    PubMed Central

    Ciccimaro, Eugene; Blair, Ian A

    2010-01-01

    The ability to conduct validated analyses of biomarkers is critically important in order to establish the sensitivity and selectivity of the biomarker in identifying a particular disease. The use of stable-isotope dilution (SID) methodology in combination with LC–MS/MS provides the highest possible analytical specificity for quantitative determinations. This methodology is now widely used in the discovery and validation of putative exposure and disease biomarkers. This review will describe the application of SID LC–MS methodology for the analysis of small-molecule and protein biomarkers. It will also discuss potential future directions for the use of this methodology for rigorous biomarker analysis. PMID:20352077

  9. The ongoing quest for biomarkers in Ankylosing Spondylitis.

    PubMed

    Danve, Abhijeet; O'Dell, James

    2015-11-01

    Ankylosing Spondylitis poses significant challenges in terms of early diagnosis, assessment of disease activity, predicting response to the treatment and monitoring radiographic progression. With better understanding of underlying immunopathogenesis, effective targeted therapies are available which improve symptoms, quality of life and possibly slow the radiographic progression. There has been a growing interest in the discovery of biomarkers for defining various aspects of disease assessment and management in Ankylosing Spondylitis. The C-reactive protein and HLA-B27 are most commonly used biomarkers. This review describes many other newer biomarkers which have potential clinical applications in this chronic inflammatory disease.

  10. Translational biomarkers of acetaminophen-induced acute liver injury.

    PubMed

    Beger, Richard D; Bhattacharyya, Sudeepa; Yang, Xi; Gill, Pritmohinder S; Schnackenberg, Laura K; Sun, Jinchun; James, Laura P

    2015-09-01

    Acetaminophen (APAP) is a commonly used analgesic drug that can cause liver injury, liver necrosis and liver failure. APAP-induced liver injury is associated with glutathione depletion, the formation of APAP protein adducts, the generation of reactive oxygen and nitrogen species and mitochondrial injury. The systems biology omics technologies (transcriptomics, proteomics and metabolomics) have been used to discover potential translational biomarkers of liver injury. The following review provides a summary of the systems biology discovery process, analytical validation of biomarkers and translation of omics biomarkers from the nonclinical to clinical setting in APAP-induced liver injury.

  11. Biomarkers of Helicobacter pylori-associated gastric cancer

    PubMed Central

    Cooke, Cara L; Torres, Javier; Solnick, Jay V

    2013-01-01

    Helicobacter pylori-associated gastric cancer is a major cause of morbidity and mortality worldwide, and is predicted to become even more common in developing countries as the population ages. Since gastric cancer develops slowly over years to decades, and typically progresses though a series of well-defined histologic stages, cancer biomarkers have potential to identify asymptomatic individuals in whom surgery might be curative, or even those for whom antibiotics to eradicate H. pylori could prevent neoplastic transformation. Here we describe some of the challenges of biomarker discovery, summarize current approaches to biomarkers of gastric cancer, and explore some recent novel strategies. PMID:23851317

  12. Impact of biomarker development on drug safety assessment

    SciTech Connect

    Marrer, Estelle; Dieterle, Frank

    2010-03-01

    Drug safety has always been a key aspect of drug development. Recently, the Vioxx case and several cases of serious adverse events being linked to high-profile products have increased the importance of drug safety, especially in the eyes of drug development companies and global regulatory agencies. Safety biomarkers are increasingly being seen as helping to provide the clarity, predictability, and certainty needed to gain confidence in decision making: early-stage projects can be stopped quicker, late-stage projects become less risky. Public and private organizations are investing heavily in terms of time, money and manpower on safety biomarker development. An illustrative and 'door opening' safety biomarker success story is the recent recognition of kidney safety biomarkers for pre-clinical and limited translational contexts by FDA and EMEA. This milestone achieved for kidney biomarkers and the 'know how' acquired is being transferred to other organ toxicities, namely liver, heart, vascular system. New technologies and molecular-based approaches, i.e., molecular pathology as a complement to the classical toolbox, allow promising discoveries in the safety biomarker field. This review will focus on the utility and use of safety biomarkers all along drug development, highlighting the present gaps and opportunities identified in organ toxicity monitoring. A last part will be dedicated to safety biomarker development in general, from identification to diagnostic tests, using the kidney safety biomarkers success as an illustrative example.

  13. Towards the identification of tissue-based proxy biomarkers.

    PubMed

    Popovici, Vlad

    2016-01-01

    Accurate patient population stratification is a key requirement for a personalized medicine and more precise biomarkers are expected to be obtained by better exploiting the available data. We introduce a novel computational framework that exploits both the information from gene expression data and histopathology images for constructing a tissue-based biomarker, which can be used for identifying a high-risk patient population. Its utility is demonstrated in the context of colorectal cancer data and we show that the resulting biomarker can be used as a proxy for a prognostic gene expression signature. These results are important for both the computational discovery of new biomarkers and clinical practice, as they demonstrate a possible approach for multimodal biomedical data mining and since the new tissue-based biomarker could easily be implemented in the routine pathology practice. PMID:27570655

  14. Towards the identification of tissue-based proxy biomarkers

    PubMed Central

    Popovici, Vlad

    2016-01-01

    Accurate patient population stratification is a key requirement for a personalized medicine and more precise biomarkers are expected to be obtained by better exploiting the available data. We introduce a novel computational framework that exploits both the information from gene expression data and histopathology images for constructing a tissue-based biomarker, which can be used for identifying a high-risk patient population. Its utility is demonstrated in the context of colorectal cancer data and we show that the resulting biomarker can be used as a proxy for a prognostic gene expression signature. These results are important for both the computational discovery of new biomarkers and clinical practice, as they demonstrate a possible approach for multimodal biomedical data mining and since the new tissue-based biomarker could easily be implemented in the routine pathology practice. PMID:27570655

  15. Association of oil seeps and chemosynthetic communities with oil discoveries, upper continental slope, Gulf of Mexico

    SciTech Connect

    Sassen, R.; Brooks, J.M.; MacDonald, I.R.; Kennicutt, M.C. II; Guinasso, N.L. Jr. )

    1993-09-01

    A belt of sea-floor oil seeps and chemosynthetic communities has been mapped across the upper continental slope, offshore Louisiana, at depths ranging from 2000 to 1000 m. Visibly oil-stained sediments and thelmogenic gas hydrates have been recovered using piston cores and research submarines. Biomarker fingerprinting of seep oils suggests an origin from deeply buried Cretaceous or Jurassic source rocks characterized by marine kerogen. The abundance of seeps provides a unique opportunity to define their relationship to oil discoveries including Auger, Cooper, Jolliet, Marquette, Vancouver, Popeye, and Mars. Seeps are preferentially distributed over shallow salt ridges that rim intrasalt basin cooking pots, over salt diapirs, and along shallow fault traces near discoveries. Diagnostic seep-related features on the sea floor include gas hydrate mounds and outcrops, pockmarks and craters, mud volcanoes, and carbonate buildups. Many of the 50 chemosynthetic communities including tube worms, mussels, or clams thus far documented in the gulf occur near discoveries. Recent imagery from orbital platforms, including the space shuttle, shows that natural oil slicks are common on the sea surface in this area. Additional mapping of seep distributions should contribute to better defining of the limits of the deep Gulf play fairway.

  16. An integrated chinmedomics strategy for discovery of effective constituents from traditional herbal medicine

    PubMed Central

    Wang, Xijun; Zhang, Aihua; Zhou, Xiaohang; Liu, Qi; Nan, Yang; Guan, Yu; Kong, Ling; Han, Ying; Sun, Hui; Yan, Guangli

    2016-01-01

    Traditional natural product discovery affords no information about compound structure or pharmacological activities until late in the discovery process, and leads to low probabilities of finding compounds with unique biological properties. By integrating serum pharmacochemistry-based screening with high-resolution metabolomics analysis, we have developed a new platform, termed chinmedomics which is capable of directly discovering the bioactive constituents. In this work, the focus is on ShenQiWan (SQW) treatment of ShenYangXu (SYX, kidney-yang deficiency syndrome) as a case study, as determined by chinmedomics. With serum pharmacochemistry, a total of 34 peaks were tentatively characterised in vivo, 24 of which were parent components and 10 metabolites were detected. The metabolic profiling and potential biomarkers of SYX were also investigated and 23 differential metabolites were found. 20 highly correlated components were screened by the plotting of correlation between marker metabolites and serum constituents and considered as the main active components of SQW. These compounds are imported into a database to predict the action targets: 14 importantly potential targets were found and related to aldosterone-regulated sodium reabsorption and adrenergic signaling pathways. Our study showed that integrated chinmedomics is a powerful strategy for discovery and screening of effective constituents from herbal medicines. PMID:26750403

  17. A pharmaceutical company user's perspective on the potential of high content screening in drug discovery.

    PubMed

    Hoffman, Ann F; Garippa, Ralph J

    2007-01-01

    It is early to fully reflect on the state of the art in high content screening (HCS), because it is still a relatively new approach in drug discovery. Although the development of the first microscopes are a century old and the first confocal microscope is only 20 yr old, the fluorescent probes used within HCS along with the combination of robotic automation and integrated software technologies are quite new. HCS will require a few more years to fully demonstrate its potential power in drug discovery. Within the last year, however, one has seen this ever-expanding field lure participants in from all areas of science, introducing newer versions of instruments and reagents such that the combined efforts result in platforms and tools that meet many organizational goals in multiple ways. The potential of HCS today lies in its versatility. HCS can be used for primary screening, basic research, target identification, biomarkers, cytotoxicity, and helping to predict clinical outcomes. HCS is being applied to stem cells, patient cells, primary hepatocytes, and immortalized cultured cells. We have noted for individual specialized assays, there are multiple solutions just as there are for those standardized universally accepted assays. Whether we have needed to query cellular processes under live conditions or wanted to follow kinetically the course of a compound's effects on particular cellular reactions, we have been hampered by only a few limitations. This chapter offers a glimpse inside the use of HCS in our drug discovery environment.

  18. Fragment-based ligand discovery.

    PubMed

    Fischer, Marcus; Hubbard, Roderick E

    2009-02-01

    From home building and decor to mass production, modular design is a standard feature of the modern age. The concept also promises to define drug discovery efforts in the near future, as a wide range of methodologies, from NMR to X-ray crystallography, are being adapted to high-throughput platforms. In particular, "fragment-based ligand discovery" describes the laboratory-driven evolution of drugs from libraries of chemical building blocks. "Evolution" is an apt word for the process, as a wide array of methods are used to define how compound fragments can be best fit into the binding sites of medically relevant target biomolecules. A number of compounds that evolved from fragments have entered the clinic, and the approach is increasingly accepted as an additional route to identifying new hit compounds in pharmaceutical discovery and inhibitor design. PMID:19299661

  19. Organic Biomarker Preservation in Silica-Rich Hydrothermal Systems with Implications to Mars

    NASA Astrophysics Data System (ADS)

    Jahnke, L. L.; Parenteau, M. N.; Farmer, J. D.

    2016-05-01

    Microbial community structure and preservation of organic matter in siliceous hydrothermal environments is a critical issue given the discovery of hydrothermal vents and silica on Mars. Here we discuss preservation of cyanobacterial biomarker lipid.

  20. Fish metalloproteins as biomarkers of environmental contamination.

    PubMed

    Hauser-Davis, Rachel Ann; de Campos, Reinaldo Calixto; Ziolli, Roberta Lourenço

    2012-01-01

    Fish are well-recognized bioindicators of environmental contamination. Several recent proteomic studies have demonstrated the validity and value of using fish in the search and discovery of new biomarkers. Certain analytical tools, such as comparative protein expression analyses, both in field and lab exposure studies, have been used to improve the understanding of the potential for chemical pollutants to cause harmful effects. The metallomic approach is in its early stages of development, but has already shown great potential for use in ecological and environmental monitoring contexts. Besides discovering new metalloproteins that may be used as biomarkers for environmental contamination, metallomics can be used to more comprehensively elucidate existing biomarkers, which may enhance their effectiveness. Unfortunately, metallomic profiling for fish has not been explored, because only a few fish metalloproteins have thus far been discovered and studied. Of those that have, some have shown ecological importance, and are now successfully used as biomarkers of environmental contamination. These biomarkers have been shown to respond to several types of environmental contamination, such as cyanotoxins, metals, and sewage effluents, although many do not yet possess any known function. Examples of successes include MMPs, superoxide dismutases, selenoproteins, and iron-bound proteins. Unfortunately, none of these have, as yet, been extensively studied. As data are developed for them, valuable new information on their roles in fish physiology and in inducing environmental effects should become available.

  1. Exploring Biomarkers for Alzheimer’s Disease

    PubMed Central

    Singh, Anshika Nikita

    2016-01-01

    Alzheimer’s Disease (AD) is one of the most common form of dementia occurring in elderly population worldwide. Currently Aβ42, tau and p-tau in the cerebrospinal fluid is estimated for confirmation of AD. CSF which is being used as the potent source for biomarker screening is obtained by invasive lumbar punctures. Thus, there is an urgent need of minimal invasive methods for identification of diagnostic markers for early detection of AD. Blood serum and plasma serves as an appropriate source, due to minimal discomfort to the patients, promoting frequent testing, better follow-up and better consent to clinical trials. Hence, the need of the hour demands discovery of diagnostic and prognostic patient specific signature biomarkers by using emerging technologies of mass spectrometry, microarrays and peptidomics. In this review we summarize the present scenario of AD biomarkers such as circulatory biomarkers, blood based amyloid markers, inflammatory markers and oxidative stress markers being investigated and also some of the potent biomarkers which might be able to predict early onset of Alzheimer’s and delay cognitive impairment. PMID:27630867

  2. Exploring Biomarkers for Alzheimer’s Disease

    PubMed Central

    Singh, Anshika Nikita

    2016-01-01

    Alzheimer’s Disease (AD) is one of the most common form of dementia occurring in elderly population worldwide. Currently Aβ42, tau and p-tau in the cerebrospinal fluid is estimated for confirmation of AD. CSF which is being used as the potent source for biomarker screening is obtained by invasive lumbar punctures. Thus, there is an urgent need of minimal invasive methods for identification of diagnostic markers for early detection of AD. Blood serum and plasma serves as an appropriate source, due to minimal discomfort to the patients, promoting frequent testing, better follow-up and better consent to clinical trials. Hence, the need of the hour demands discovery of diagnostic and prognostic patient specific signature biomarkers by using emerging technologies of mass spectrometry, microarrays and peptidomics. In this review we summarize the present scenario of AD biomarkers such as circulatory biomarkers, blood based amyloid markers, inflammatory markers and oxidative stress markers being investigated and also some of the potent biomarkers which might be able to predict early onset of Alzheimer’s and delay cognitive impairment.

  3. Gas platform

    SciTech Connect

    Mo, O.

    1981-11-24

    The invention is related to an offshore platform with storage facilities for natural resources, such as LNG. The invention is particularly concerned with the problem of providing sufficient safety in storing such products, e.g., protection against collision with tankers.

  4. The FOCUS4 design for biomarker stratified trials.

    PubMed

    Kaplan, Richard

    2015-09-01

    Randomised clinical trials (RCTs) remain the gold standard of evidence for the benefit of new therapeutics but standard designs fit awkwardly with key developments in biomarker-stratified drug development. Firstly, the unprecedented number of new agents being developed in oncology (usually with specific targets for which there may be predictive biomarkers) mandates a need for new trial designs that are more efficient in screening out new agents with modest likelihood of benefit, concentrating resources on the most promising ones. The multi-arm multi-stage (MAMS) design developed some years ago addresses this need. Secondly, biomarker-stratified trials, when tackled one biomarker/drug pairing at a time, are inherently highly inefficient. The FOCUS4 trial design was developed to overcome this problem, using a platform that incorporates multiple parallel biomarker-stratified RCTs in individual cohorts, and capable of adapting its design in response to developing evidence.

  5. Blood platelets contain tumor-derived RNA biomarkers.

    PubMed

    Nilsson, R Jonas A; Balaj, Leonora; Hulleman, Esther; van Rijn, Sjoerd; Pegtel, D Michiel; Walraven, Maudy; Widmark, Anders; Gerritsen, Winald R; Verheul, Henk M; Vandertop, W Peter; Noske, David P; Skog, Johan; Würdinger, Thomas

    2011-09-29

    Diagnostic platforms providing biomarkers that are highly predictive for diagnosing, monitoring, and stratifying cancer patients are key instruments in the development of personalized medicine. We demonstrate that tumor cells transfer (mutant) RNA into blood platelets in vitro and in vivo, and show that blood platelets isolated from glioma and prostate cancer patients contain the cancer-associated RNA biomarkers EGFRvIII and PCA3, respectively. In addition, gene-expression profiling revealed a distinct RNA signature in platelets from glioma patients compared with normal control subjects. Because platelets are easily accessible and isolated, they may form an attractive platform for the companion diagnostics of cancer.

  6. Blood platelets contain tumor-derived RNA biomarkers.

    PubMed

    Nilsson, R Jonas A; Balaj, Leonora; Hulleman, Esther; van Rijn, Sjoerd; Pegtel, D Michiel; Walraven, Maudy; Widmark, Anders; Gerritsen, Winald R; Verheul, Henk M; Vandertop, W Peter; Noske, David P; Skog, Johan; Würdinger, Thomas

    2011-09-29

    Diagnostic platforms providing biomarkers that are highly predictive for diagnosing, monitoring, and stratifying cancer patients are key instruments in the development of personalized medicine. We demonstrate that tumor cells transfer (mutant) RNA into blood platelets in vitro and in vivo, and show that blood platelets isolated from glioma and prostate cancer patients contain the cancer-associated RNA biomarkers EGFRvIII and PCA3, respectively. In addition, gene-expression profiling revealed a distinct RNA signature in platelets from glioma patients compared with normal control subjects. Because platelets are easily accessible and isolated, they may form an attractive platform for the companion diagnostics of cancer. PMID:21832279

  7. Expanding the Reper