Pooled results from five validation studies of dietary self-report instruments using recovery biomarkers for potassium and sodium intake

USDA-ARS?s Scientific Manuscript database

We have pooled data from five large validation studies of dietary self-report instruments that used recovery biomarkers as referents to assess food frequency questionnaires (FFQs) and 24-hour recalls. We reported on total potassium and sodium intakes, their densities, and their ratio. Results were...

Implementation of proteomic biomarkers: making it work

PubMed Central

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

2012-01-01

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

Biomarkers-a potential route for improved diagnosis and management of ongoing renal damage.

PubMed

Oberbauer, R

2008-12-01

Currently, the identification and validation of biomarkers of kidney injury is among the top priorities of many diagnostic biotechnology companies as well as academic research institutes. Specifically, in renal transplantation, validated biomarkers of tissue injury with good discriminatory power between the various renal compartments and the underlying pathophysiology are desired, because sequential allograft biopsies are limited in number and cannot be used as a screening tool. Given the high demands on these markers, it is not surprising that none of those currently under evaluation has been thoroughly validated for a specific entity. Published biomarker candidates for early tubular damage include neutrophil gelatinase-associated lipocalin (NGAL), interleukin (IL)-18, soluble CD30, perforin, and granzyme B. Recently, C4d flow panel reactive antibodies were evaluated as biomarkers for humoral alloimmune responses. Additional biomarkers such as FOXP3 and kidney injury molecule 1 have been studied in the maintenance phase of renal transplantation. Given the complex prerequisites, it is not surprising that no biomarker panel has been sufficiently validated for clinical use. However, in the near future a biomarker for use as an indicator of renal tubule cell injury will be available. Troponin T or transaminase of the kidney may then at least be used to differentiate between functional renal failure (equivalent to a rise in creatinine) and intrinsic kidney injury.

Laser scanning cytometry as a tool for biomarker validation

NASA Astrophysics Data System (ADS)

Mittag, Anja; Füldner, Christiane; Lehmann, Jörg; Tarnok, Attila

2013-03-01

Biomarkers are essential for diagnosis, prognosis, and therapy. As diverse is the range of diseases the broad is the range of biomarkers and the material used for analysis. Whereas body fluids can be relatively easily obtained and analyzed, the investigation of tissue is in most cases more complicated. The same applies for the screening and the evaluation of new biomarkers and the estimation of the binding of biomarkers found in animal models which need to be transferred into applications in humans. The latter in particular is difficult if it recognizes proteins or cells in tissue. A better way to find suitable cellular biomarkers for immunoscintigraphy or PET analyses may be therefore the in situ analysis of the cells in the respective tissue. In this study we present a method for biomarker validation using Laser Scanning Cytometry which allows the emulation of future in vivo analysis. The biomarker validation is exemplarily shown for rheumatoid arthritis (RA) on synovial membrane. Cryosections were scanned and analyzed by phantom contouring. Adequate statistical methods allowed the identification of suitable markers and combinations. The fluorescence analysis of the phantoms allowed the discrimination between synovial membrane of RA patients and non-RA control sections by using median fluorescence intensity and the "affected area". As intensity and area are relevant parameters of in vivo imaging (e.g. PET scan) too, the presented method allows emulation of a probable outcome of in vivo imaging, i.e. the binding of the target protein and hence, the validation of the potential of the respective biomarker.

Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance.

PubMed

Brouwer-Brolsma, Elske M; Brennan, Lorraine; Drevon, Christian A; van Kranen, Henk; Manach, Claudine; Dragsted, Lars Ove; Roche, Helen M; Andres-Lacueva, Cristina; Bakker, Stephan J L; Bouwman, Jildau; Capozzi, Francesco; De Saeger, Sarah; Gundersen, Thomas E; Kolehmainen, Marjukka; Kulling, Sabine E; Landberg, Rikard; Linseisen, Jakob; Mattivi, Fulvio; Mensink, Ronald P; Scaccini, Cristina; Skurk, Thomas; Tetens, Inge; Vergeres, Guy; Wishart, David S; Scalbert, Augustin; Feskens, Edith J M

2017-11-01

FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health.

Protein mass spectra data analysis for clinical biomarker discovery: a global review.

PubMed

Roy, Pascal; Truntzer, Caroline; Maucort-Boulch, Delphine; Jouve, Thomas; Molinari, Nicolas

2011-03-01

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

Design and validation of an immunoaffinity LC-MS/MS assay for the quantification of a collagen type II neoepitope peptide in human urine: application as a biomarker of osteoarthritis.

PubMed

Nemirovskiy, Olga; Li, Wenlin Wendy; Szekely-Klepser, Gabriella

2010-01-01

Biomarkers play an increasingly important role for drug efficacy and safety evaluation in all stages of drug development. It is especially important to develop and validate sensitive and selective biomarkers for diseases where the onset of the disease is very slow and/or the disease progression is hard to follow, i.e., osteoarthritis (OA). The degradation of Type II collagen has been associated with the disease state of OA. Matrix metalloproteinases (MMPs) are enzymes that catalyze the degradation of collagen and therefore pursued as potential targets for the treatment of OA. Peptide biomarkers of MMP activity related to type II collagen degradation were identified and the presence of these peptides in MMP digests of human articular cartilage (HAC) explants and human urine were confirmed. An immunoaffinity LC/MS/MS assay for the quantification of the most abundant urinary type II collagen neoepitope (uTIINE) peptide, a 45-mer with 5 HO-proline residues was developed and clinically validated. The assay has subsequently been applied to analyze human urine samples from clinical studies. We have shown that the assay is able to differentiate between symptomatic OA and normal subjects, indicating that uTIINE can be used as potential biomarker for OA. This chapter discusses the assay procedure and provides information on the validation experiments used to evaluate the accuracy, precision, and selectivity data with attention to the specific challenges related to the quantification of endogenous protein/peptide biomarker analytes. The generalized approach can be used as a follow-up to studies whereby proteomics-based urinary biomarkers are identified and an assay needs to be developed. Considerations for the validation of such an assay are described.

Current Role of Blood and Urine Biomarkers in the Clinical Care of Adults with Congenital Heart Disease.

PubMed

Rajpal, Saurabh; Alshawabkeh, Laith; Opotowsky, Alexander R

2017-06-01

There is an increasing number of adult patients with congenital heart disease (CHD). While several biomarkers have been validated and integrated into general cardiology clinical practice, these tests are often applied to adults with CHD in the absence of disease-specific validation. Although these patients are often grouped into a single population, there is heterogeneous pathophysiology, variable disease chronicity, extensive multisystem involvement, and a low event rate relative to acquired heart disease. These stand as challenges to systematic investigation and clinical application of biomarkers for adults with CHD. This paper reviews recent studies investigating the use of biomarkers in this population, with emphasis on biomarkers applied in clinical adult CHD care. A handful of biomarkers have been integrated into adult CHD practice, such as iron studies in cyanotic heart disease and stool alpha-1 antitrypsin for diagnosis of protein losing enteropathy in the Fontan circulation. Use of kidney and liver tests has been studied in prognostication of adult CHD patients. A few other biomarkers like natriuretic peptides and troponins seem likely to provide useful information in other ACHD situations based on limited disease-specific data and extrapolation from acquired heart disease. More research is needed to support the robust validity of most existing clinical biomarkers in adult congenital cardiology practice. Until data from larger, prospectively enrolled cohorts are available, clinical use of biomarkers in these patients will require careful interpretation with attention to underlying pathophysiology, as well as detailed understanding of potential pitfalls of specific assays and clinical contexts.

Estimation of AUC or Partial AUC under Test-Result-Dependent Sampling.

PubMed

Wang, Xiaofei; Ma, Junling; George, Stephen; Zhou, Haibo

2012-01-01

The area under the ROC curve (AUC) and partial area under the ROC curve (pAUC) are summary measures used to assess the accuracy of a biomarker in discriminating true disease status. The standard sampling approach used in biomarker validation studies is often inefficient and costly, especially when ascertaining the true disease status is costly and invasive. To improve efficiency and reduce the cost of biomarker validation studies, we consider a test-result-dependent sampling (TDS) scheme, in which subject selection for determining the disease state is dependent on the result of a biomarker assay. We first estimate the test-result distribution using data arising from the TDS design. With the estimated empirical test-result distribution, we propose consistent nonparametric estimators for AUC and pAUC and establish the asymptotic properties of the proposed estimators. Simulation studies show that the proposed estimators have good finite sample properties and that the TDS design yields more efficient AUC and pAUC estimates than a simple random sampling (SRS) design. A data example based on an ongoing cancer clinical trial is provided to illustrate the TDS design and the proposed estimators. This work can find broad applications in design and analysis of biomarker validation studies.

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-08-26

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. This manuscript addresses the importance of distinguishing between protein homologs and isoforms when identifying and validating cancer biomarkers in plasma or serum. Specifically, it describes the use of targeted in-depth LC-MS/MS analysis to determine the members of two protein families, chloride intracellular channel (CLIC) and tropomyosin (TPM) proteins that are detectable in sera of ovarian cancer patients. It then establishes a multiplexed isoform- and homology-specific MRM assay to quantify all observed gene products in these two protein families as well as many of the closely related tropomyosin isoforms. Using this assay, levels of all detected CLICs and TPMs were quantified in ovarian cancer patient and control subject sera. These results demonstrate that in addition to the previously known CLIC1, multiple tropomyosins and CLIC4 are promising new ovarian cancer biomarkers. Based on these initial validation studies, these new ovarian cancer biomarkers appear to be superior to most previously known ovarian cancer biomarkers. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-01-01

Predictive biomarkers can guide treatment decisions in breast cancer. Many studies are undertaken to discover and translate these biomarkers, yet few biomarkers make it to practice. Before use in clinical decision making, predictive biomarkers need to demonstrate analytical validity, clinical validity and clinical utility. While attaining analytical and clinical validity is relatively straightforward, by following methodological recommendations, the achievement of clinical utility is extremely challenging. It requires demonstrating three associations: the biomarker with the outcome (prognostic association), the effect of treatment independent of the biomarker, and the differential treatment effect between the prognostic and the predictive biomarker (predictive association). In addition, economical, ethical, regulatory, organizational and patient/doctor-related aspects are hampering the translational process. Traditionally, these aspects do not receive much attention until formal approval or reimbursement of a biomarker test (informed by Health Technology Assessment (HTA)) is at stake, at which point the clinical utility and sometimes price of the test can hardly be influenced anymore. When HTA analyses are performed earlier, during biomarker research and development, they may prevent further development of those biomarkers unlikely to ever provide sufficient added value to society, and rather facilitate translation of the promising ones. Early HTA is particularly relevant for the predictive biomarker field, as expensive medicines are under pressure and the need for biomarkers to guide their appropriate use is huge. Closer interaction between clinical researchers and HTA experts throughout the translational research process will ensure that available data and methodologies will be used most efficiently to facilitate biomarker translation. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Imaging biomarker roadmap for cancer studies

PubMed Central

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

2017-01-01

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

Predictors of chemotherapy efficacy in non-small-cell lung cancer: a challenging landscape.

PubMed

Olaussen, K A; Postel-Vinay, S

2016-11-01

Conventional cytotoxic chemotherapy (CCC) is the backbone of non-small-cell lung cancer (NSCLC) treatment since decades and still represents a key element of the therapeutic armamentarium. Contrary to molecularly targeted therapies and immune therapies, for which predictive biomarkers of activity have been actively looked for and developed in parallel to the drug development process ('companion biomarkers'), no patient selection biomarker is currently available for CCC, precluding customizing treatment. We reviewed preclinical and clinical studies that assessed potential predictive biomarkers of CCC used in NSCLC (platinum, antimetabolites, topoisomerase inhibitors, and spindle poisons). Biomarker evaluation method, analytical validity, and robustness are described and challenged for each biomarker. The best-validated predictive biomarkers for efficacy are currently ERCC1, RRM1, and TS for platinum agents, gemcitabine and pemetrexed, respectively. Other potential biomarkers include hENT1 for gemcitabine, class III β-tubulin for spindle poisons, TOP2A expression and CEP17 duplication (mostly studied for predicting anthracyclines efficacy) whose applicability concerning etoposide would deserve further evaluation. However, none of these biomarkers has till now been validated prospectively in an appropriately designed and powered randomised trial, and none of them is currently ready for implementation in routine clinical practice. The search for predictive biomarkers to CCC has been proven challenging. If a plethora of biomarkers have been evaluated either in the preclinical or in the clinical setting, none of them is ready for clinical implementation yet. Considering that most mechanisms of resistance or sensitivity to CCC are multifactorial, a combinatorial approach might be relevant and further efforts are required. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

NYU Lung Cancer Biomarker Center — EDRN Public Portal

Cancer.gov

A. SPECIFIC AIMS 1. To develop and prospectively follow a large cohort at high-risk for lung cancer. Individuals are recruited to one of two different study groups: The Screening Cohort includes people with and without increased risk for lung cancer. The Rule-Out Lung Cancer Patient Group is recruited from patients referred for evaluation of suspicious nodules. All individuals answer a questionnaire, obtain PFTs, chest CT scan, sputum induction and phlebotomy. For patients undergoing lung resections or biopsies, tissue samples are collected and banked. Individuals are recruited for research bronchoscopy. All participants are then followed prospectively. The specimens obtained are banked and used for biomarker discovery and validation studies. 2. To identify and validate biomarkers for the early detection of lung cancer, and to describe preneoplastic cellular changes and lesions. Biomarker studies include DNA adducts, DNA methylation, protein markers, and other collaborations. Preneoplasia studies include: fluorescence and Superdimension bronchoscopies to obtain biopsies of preneoplastic lesions and biomarker studies in individuals with preneoplasias.

Biomarkers of systemic lupus erythematosus identified using mass spectrometry-based proteomics: a systematic review.

PubMed

Nicolaou, Orthodoxia; Kousios, Andreas; Hadjisavvas, Andreas; Lauwerys, Bernard; Sokratous, Kleitos; Kyriacou, Kyriacos

2017-05-01

Advances in mass spectrometry technologies have created new opportunities for discovering novel protein biomarkers in systemic lupus erythematosus (SLE). We performed a systematic review of published reports on proteomic biomarkers identified in SLE patients using mass spectrometry-based proteomics and highlight their potential disease association and clinical utility. Two electronic databases, MEDLINE and EMBASE, were systematically searched up to July 2015. The methodological quality of studies included in the review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Twenty-five studies were included in the review, identifying 241 SLE candidate proteomic biomarkers related to various aspects of the disease including disease diagnosis and activity or pinpointing specific organ involvement. Furthermore, 13 of the 25 studies validated their results for a selected number of biomarkers in an independent cohort, resulting in the validation of 28 candidate biomarkers. It is noteworthy that 11 candidate biomarkers were identified in more than one study. A significant number of potential proteomic biomarkers that are related to a number of aspects of SLE have been identified using mass spectrometry proteomic approaches. However, further studies are required to assess the utility of these biomarkers in routine clinical practice. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume II - clinical validation and regulatory considerations.

PubMed

Dobbin, Kevin K; Cesano, Alessandra; Alvarez, John; Hawtin, Rachael; Janetzki, Sylvia; Kirsch, Ilan; Masucci, Giuseppe V; Robbins, Paul B; Selvan, Senthamil R; Streicher, Howard Z; Zhang, Jenny; Butterfield, Lisa H; Thurin, Magdalena

2016-01-01

There is growing recognition that immunotherapy is likely to significantly improve health outcomes for cancer patients in the coming years. Currently, while a subset of patients experience substantial clinical benefit in response to different immunotherapeutic approaches, the majority of patients do not but are still exposed to the significant drug toxicities. Therefore, a growing need for the development and clinical use of predictive biomarkers exists in the field of cancer immunotherapy. Predictive cancer biomarkers can be used to identify the patients who are or who are not likely to derive benefit from specific therapeutic approaches. In order to be applicable in a clinical setting, predictive biomarkers must be carefully shepherded through a step-wise, highly regulated developmental process. Volume I of this two-volume document focused on the pre-analytical and analytical phases of the biomarker development process, by providing background, examples and "good practice" recommendations. In the current Volume II, the focus is on the clinical validation, validation of clinical utility and regulatory considerations for biomarker development. Together, this two volume series is meant to provide guidance on the entire biomarker development process, with a particular focus on the unique aspects of developing immune-based biomarkers. Specifically, knowledge about the challenges to clinical validation of predictive biomarkers, which has been gained from numerous successes and failures in other contexts, will be reviewed together with statistical methodological issues related to bias and overfitting. The different trial designs used for the clinical validation of biomarkers will also be discussed, as the selection of clinical metrics and endpoints becomes critical to establish the clinical utility of the biomarker during the clinical validation phase of the biomarker development. Finally, the regulatory aspects of submission of biomarker assays to the U.S. Food and Drug Administration as well as regulatory considerations in the European Union will be covered.

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

PubMed Central

2012-01-01

Background Alzheimer’s Disease (AD) is the most widespread form of dementia in the elderly but despite progress made in recent years towards a mechanistic understanding, there is still an urgent need for disease modification therapy and for early diagnostic tests. Substantial international efforts are being made to discover and validate biomarkers for AD using candidate analytes and various data-driven 'omics' approaches. Cerebrospinal fluid is in many ways the tissue of choice for biomarkers of brain disease but is limited by patient and clinician acceptability, and increasing attention is being paid to the search for blood-based biomarkers. The aim of this study was to use a novel in silico approach to discover a set of candidate biomarkers for AD. Methods We used an in silico literature mining approach to identify potential biomarkers by creating a summarized set of assertional metadata derived from relevant legacy information. We then assessed the validity of this approach using direct assays of the identified biomarkers in plasma by immunodetection methods. Results Using this in silico approach, we identified 25 biomarker candidates, at least three of which have subsequently been reported to be altered in blood or CSF from AD patients. Two further candidate biomarkers, indicated from the in silico approach, were choline acetyltransferase and urokinase-type plasminogen activator receptor. Using immunodetection, we showed that, in a large sample set, these markers are either altered in disease or correlate with MRI markers of atrophy. Conclusions These data support as a proof of concept the use of data mining and in silico analyses to derive valid biomarker candidates for AD and, by extension, for other disorders. PMID:23113945

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

Cancer.gov

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

Peripheral blood sampling for the detection of allograft rejection: biomarker identification and validation.

PubMed

Heidt, Sebastiaan; San Segundo, David; Shankar, Sushma; Mittal, Shruti; Muthusamy, Anand S R; Friend, Peter J; Fuggle, Susan V; Wood, Kathryn J

2011-07-15

Currently, acute allograft rejection can only be detected reliably by deterioration of graft function confirmed by allograft biopsy. A huge drawback of this method of diagnosis is that substantial organ damage has already taken place at the time that rejection is diagnosed. Discovering and validating noninvasive biomarkers that predict acute rejection, and chronic allograft dysfunction, is of great importance. Many studies have investigated changes in the peripheral blood in an attempt to find biomarkers that reflect changes in the graft directly or indirectly. Herein, we will review the promises and limitations of the peripheral blood biomarkers that have been described in the literature so far.

Protein isoform-specific validation defines multiple chloride intracellular channel and tropomyosin isoforms as serological biomarkers of ovarian cancer

PubMed Central

Tang, Hsin-Yao; Beer, Lynn A.; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

New serological biomarkers for early detection and clinical management of ovarian cancer are urgently needed, and many candidates have been reported. A major challenge frequently encountered when validating candidates in patients is establishing quantitative assays that distinguish between highly homologous proteins. The current study tested whether multiple members of two recently discovered ovarian cancer biomarker protein families, chloride intracellular channel (CLIC) proteins and tropomyosins (TPM), were detectable in ovarian cancer patient sera. A multiplexed, label-free multiple reaction monitoring (MRM) assay was established to target peptides specific to all detected CLIC and TPM family members, and their serum levels were quantitated for ovarian cancer patients and non-cancer controls. In addition to CLIC1 and TPM1, which were the proteins initially discovered in a xenograft mouse model, CLIC4, TPM2, TPM3, and TPM4 were present in ovarian cancer patient sera at significantly elevated levels compared with controls. Some of the additional biomarkers identified in this homolog-centric verification and validation approach may be superior to the previously identified biomarkers at discriminating between ovarian cancer and non-cancer patients. This demonstrates the importance of considering all potential protein homologs and using quantitative assays for cancer biomarker validation with well-defined isoform specificity. PMID:23792823

Validation of beverage intake methods vs. hydration biomarkers; a short review.

PubMed

Nissensohn, Mariela; Ruano, Cristina; Serra-Majem, Lluis

2013-11-01

Fluid intake is difficult to monitor. Biomarkers of beverage intake are able to assess dietary intake/hydration status without the bias of self-reported dietary intake errors and also the intra-individual variability. Various markers have been proposed to assess hydration, however, to date; there is a lack of universally accepted biomarker that reflects changes of hydration status in response to changes in beverage intake. We conduct a review to find out the questionnaires of beverage intake available in the scientific literature to assess beverage intake and hydration status and their validation against hydration biomarkers. A scientific literature search was conducted. Only two articles were selected, in which, two different beverage intake questionnaires designed to capture the usual beverage intake were validated against Urine Specific Gravidity biomarker (Usg). Water balance questionnaire (WBQ) reported no correlations in the first study and the Beverage Intake Questionnaire (BEVQ), a quantitative Food frequency questionnaire (FFQ) in the second study, also found a negative correlation. FFQ appears to measure better beverage intake than WBQ when compared with biomarkers. However, the WBQ seems to be a more complete method to evaluate the hydration balance of a given population. Further research is needed to understand the meaning of the different correlations between intake estimates and biomarkers of beverage in distinct population groups and environments. Copyright AULA MEDICA EDICIONES 2013. Published by AULA MEDICA. All rights reserved.

ALS Biomarkers for Therapy Development: State of the Field & Future Directions

PubMed Central

Benatar, Michael; Boylan, Kevin; Jeromin, Andreas; Rutkove, Seward B.; Berry, James; Atassi, Nazem; Bruijn, Lucie

2015-01-01

Biomarkers have become the focus of intense research in the field of amyotrophic lateral sclerosis (ALS), with the hope that they might aid therapy development efforts. Notwithstanding the discovery of many candidate biomarkers, none have yet emerged as validated tools for drug development. In this review we present a nuanced view of biomarkers based on the perspective of the FDA; highlight the distinction between discovery and validation; describe existing and emerging resources; review leading biological fluid-based, electrophysiological and neuroimaging candidates relevant to therapy development efforts; discuss lessons learned from biomarker initiatives in related neurodegenerative diseases; and outline specific steps that we, as a field, might take in order to hasten the development and validation of biomarkers that will prove useful in enhancing efforts to develop effective treatments for ALS patients. Most important among these perhaps is the proposal to establish a federated ALS Biomarker Consortium (ABC) in which all interested and willing stakeholders may participate with equal opportunity to contribute to the broader mission of biomarker development and validation. PMID:26574709

Biomarkers Predicting Progression of Human Immunodeficiency Virus-Related Disease

PubMed Central

Kanekar, Amar

2010-01-01

Biomarkers in predicting the progression of HIV infected individuals to a state of HIV disease (AIDS) are studied over more than a decade. Use of surrogate markers in the past for tracking clinical progression of the disease was limited, as little knowledge existed about the disease. The aim of this review was to address various changes in biomarker related studies taking place over the last five years, especially the trend towards use of newer biomarkers and experimentation with novel molecules in a quest for halting HIV disease progression. An open search of PUBMED database was made with search 'key words' such as 'Biomarkers' and 'AIDS (Acquired Immunodeficiency Syndrome)'.The following were the inclusion criteria for articles: a) all articles published in English language, b) years of publication between 2002-2008 and c) articles limited to adult population. This yielded a total of 417 articles. The criteria used for further judging these studies considered a) type of research design, b) number of biomarkers studied, c) validity of the biomarkers, d) techniques to assess the biomarkers and the impact of the studies in furthering biomarker research, e) sample size for the studies and f) article title or abstracts having the following key words 'biomarker' or 'biomarkers' and 'predict progression to AIDS'. A total of 27 abstracts were reviewed and 12 studies met the above criteria. These 12 different studies consisted of three reviews, four cohort designs, three cross-sectional designs, one each of an observational, and an in-vitro design. The various biomarkers emerging as a results were primarily a mix of viral, neural, immunological, HLA (human leukocyte antigen) markers along with lymphocyte counts. Although there have been quite a few advancements in biomarker-related studies, majority of the novel biomarkers discovered need to be further evaluated and replicated in bigger, long-term efficacy trials. Efforts should also be made to discover newer genetic markers of disease progression. Biomarker feedback, a new concept, can be utilized in future studies addressing prevention of HIV infection or halting disease progression. Keywords Biomarkers; Progression; Designs; HIV; AIDS; Validity PMID:21811520

Molecular epidemiology: new rules for new tools?

PubMed

Merlo, Domenico Franco; Sormani, Maria Pia; Bruzzi, Paolo

2006-08-30

Molecular epidemiology combines biological markers and epidemiological observations in the study of the environmental and genetic determinants of cancer and other diseases. The potential advantages associated with biomarkers are manifold and include: (a) increased sensitivity and specificity to carcinogenic exposures; (b) more precise evaluation of the interplay between genetic and environmental determinants of cancer; (c) earlier detection of carcinogenic effects of exposure; (d) characterization of disease subtypes-etiologies patterns; (e) evaluation of primary prevention measures. These, in turn, may translate into better tools for etiologic research, individual risk assessment, and, ultimately, primary and secondary prevention. An area that has not received sufficient attention concerns the validation of these biomarkers as surrogate endpoints for cancer risk. Validation of a candidate biomarker's surrogacy is the demonstration that it possesses the properties required for its use as a substitute for a true endpoint. The principles underlying the validation process underwent remarkable developments and discussion in therapeutic research. However, the challenges posed by the application of these principles to epidemiological research, where the basic tool for this validation (i.e., the randomized study) is seldom possible, have not been thoroughly explored. The validation process of surrogacy must be applied rigorously to intermediate biomarkers of cancer risk before using them as risk predictors at the individual as well as at the population level.

Three-Gene Immunohistochemical Panel Adds to Clinical Staging Algorithms to Predict Prognosis for Patients With Esophageal Adenocarcinoma

PubMed Central

Ong, Chin-Ann J.; Shapiro, Joel; Nason, Katie S.; Davison, Jon M.; Liu, Xinxue; Ross-Innes, Caryn; O'Donovan, Maria; Dinjens, Winand N.M.; Biermann, Katharina; Shannon, Nicholas; Worster, Susannah; Schulz, Laura K.E.; Luketich, James D.; Wijnhoven, Bas P.L.; Hardwick, Richard H.; Fitzgerald, Rebecca C.

2013-01-01

Purpose Esophageal adenocarcinoma (EAC) is a highly aggressive disease with poor long-term survival. Despite growing knowledge of its biology, no molecular biomarkers are currently used in routine clinical practice to determine prognosis or aid clinical decision making. Hence, this study set out to identify and validate a small, clinically applicable immunohistochemistry (IHC) panel for prognostication in patients with EAC. Patients and Methods We recently identified eight molecular prognostic biomarkers using two different genomic platforms. IHC scores of these biomarkers from a UK multicenter cohort (N = 374) were used in univariate Cox regression analysis to determine the smallest biomarker panel with the greatest prognostic power with potential therapeutic relevance. This new panel was validated in two independent cohorts of patients with EAC who had undergone curative esophagectomy from the United States and Europe (N = 666). Results Three of the eight previously identified prognostic molecular biomarkers (epidermal growth factor receptor [EGFR], tripartite motif-containing 44 [TRIM44], and sirtuin 2 [SIRT2]) had the strongest correlation with long-term survival in patients with EAC. Applying these three biomarkers as an IHC panel to the validation cohort segregated patients into two different prognostic groups (P < .01). Adjusting for known survival covariates, including clinical staging criteria, the IHC panel remained an independent predictor, with incremental adverse overall survival (OS) for each positive biomarker (hazard ratio, 1.20; 95% CI, 1.03 to 1.40 per biomarker; P = .02). Conclusion We identified and validated a clinically applicable IHC biomarker panel, consisting of EGFR, TRIM44, and SIRT2, that is independently associated with OS and provides additional prognostic information to current survival predictors such as stage. PMID:23509313

EDRN Pre-Validation of Metabolic Biomarkers of Prostate Cancer: Follow up EDRN Challenge — EDRN Public Portal

Cancer.gov

The goal of this EDRN set-asides proposal is to carry out pre-validation studies on sarcosine as a metabolomic biomarker of prostate cancer in urine. Not only does sarcosine have potential as a marker for the early detection of prostate cancer in post-DRE urine specimens-- but since its highest levels are in metastatic disease it might have utility in predicting aggressiveness of clinically localized disease. We will also use these funds to determine if we can add additional metabolites to sarcosine in order to develop a multiplex metabolomic biomarker panel in prostate cancer. In addition to sarcosine, we have 10-12 additional candidate metabolomic biomarkers that could be developed (as seen from our preliminary global metabolite studies).

Definitions and validation criteria for biomarkers and surrogate endpoints: development and testing of a quantitative hierarchical levels of evidence schema.

PubMed

Lassere, Marissa N; Johnson, Kent R; Boers, Maarten; Tugwell, Peter; Brooks, Peter; Simon, Lee; Strand, Vibeke; Conaghan, Philip G; Ostergaard, Mikkel; Maksymowych, Walter P; Landewe, Robert; Bresnihan, Barry; Tak, Paul-Peter; Wakefield, Richard; Mease, Philip; Bingham, Clifton O; Hughes, Michael; Altman, Doug; Buyse, Marc; Galbraith, Sally; Wells, George

2007-03-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Our objective was to review the literature on biomarkers and surrogates to develop a hierarchical schema that systematically evaluates and ranks the surrogacy status of biomarkers and surrogates; and to obtain feedback from stakeholders. After a systematic search of Medline and Embase on biomarkers, surrogate (outcomes, endpoints, markers, indicators), intermediate endpoints, and leading indicators, a quantitative surrogate validation schema was developed and subsequently evaluated at a stakeholder workshop. The search identified several classification schema and definitions. Components of these were incorporated into a new quantitative surrogate validation level of evidence schema that evaluates biomarkers along 4 domains: Target, Study Design, Statistical Strength, and Penalties. Scores derived from 3 domains the Target that the marker is being substituted for, the Design of the (best) evidence, and the Statistical strength are additive. Penalties are then applied if there is serious counterevidence. A total score (0 to 15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. It was proposed that the term "surrogate" be restricted to markers attaining Levels 1 or 2 only. Most stakeholders agreed that this operationalization of the National Institutes of Health definitions of biomarker, surrogate endpoint, and clinical endpoint was useful. Further development and application of this schema provides incentives and guidance for effective biomarker and surrogate endpoint research, and more efficient drug discovery, development, and approval.

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

DTIC Science & Technology

2016-10-01

Study (PASS). We are in the process of evaluating these three biomarker panels in tissue, blood, and urine samples with well annotated clinical and...impacting both the initial choice of therapy and decision-making during AS. The objective of the study is to utilize analytically validated assays that...predict reclassification from Gleason 6 cancer to Gleason 7 or greater. The analysis plan was determined before specimens were selected for the study

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

DTIC Science & Technology

2016-10-01

Study (PASS). We are in the process of evaluating these three biomarker panels in tissue, blood, and urine samples with well annotated clinical and...choice of therapy and decision-making during AS. The objective of the study is to utilize analytically validated assays that take into account tumor...Gleason 6 cancer to Gleason 7 or greater. The analysis plan was determined before specimens were selected for the study , and included 7 breaking

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

DTIC Science & Technology

2017-10-01

been shown in many studies to improve predictive accuracy for cancer on initial biopsy,3,7-9 and to be correlated with more aggressive cancer at...our multi-center, prospectively accrued prostate cancer active surveillance cohort – the Canary Prostate Active Surveillance Study (PASS). We are in...objective of the study is to utilize analytically validated assays that take into account tumor heterogeneity to measure biomarkers in specimens that were

Developing Biomarkers in Mood Disorders Research Through the Use of Rapid-Acting Antidepressants

PubMed Central

Niciu, Mark J.; Mathews, Daniel C.; Nugent, Allison C.; Ionescu, Dawn F.; Furey, Maura L.; Richards, Erica M.; Machado-Vieira, Rodrigo; Zarate, Carlos A.

2014-01-01

An impediment to progress in mood disorders research is the lack of analytically valid and qualified diagnostic and treatment biomarkers. Consistent with the National Institute of Mental Health (NIMH)’s Research Domain Criteria (RDoC) initiative, the lack of diagnostic biomarkers has precluded us from moving away from a purely subjective (symptom-based) towards a more objective diagnostic system. In addition, treatment response biomarkers in mood disorders would facilitate drug development and move beyond trial-and-error towards more personalized treatments. As such, biomarkers identified early in the pathophysiological process are proximal biomarkers (target engagement), while those occurring later in the disease process are distal (disease pathway components). One strategy to achieve this goal in biomarker development is to increase efforts at the initial phases of biomarker development (i.e., exploration and validation) at single sites with the capability of integrating multimodal approaches across a biological systems level. Subsequently, resultant putative biomarkers could then undergo characterization and surrogacy as these latter phases require multisite collaborative efforts. We have used multimodal approaches – genetics, proteomics/metabolomics, peripheral measures, multimodal neuroimaging, neuropsychopharmacological challenge paradigms and clinical predictors – to explore potential predictor and mediator/moderator biomarkers of the rapid-acting antidepressants ketamine and scopolamine. These exploratory biomarkers may then be used for a priori stratification in larger multisite controlled studies during the validation and characterization phases with the ultimate goal of surrogacy. In sum, the combination of target engagement and well-qualified disease-related measures are crucial to improve our pathophysiological understanding, personalize treatment selection and expand our armamentarium of novel therapeutics. PMID:24353110

Developing biomarkers in mood disorders research through the use of rapid-acting antidepressants.

PubMed

Niciu, Mark J; Mathews, Daniel C; Nugent, Allison C; Ionescu, Dawn F; Furey, Maura L; Richards, Erica M; Machado-Vieira, Rodrigo; Zarate, Carlos A

2014-04-01

An impediment to progress in mood disorders research is the lack of analytically valid and qualified diagnostic and treatment biomarkers. Consistent with the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC) initiative, the lack of diagnostic biomarkers has precluded us from moving away from a purely subjective (symptom-based) toward a more objective diagnostic system. In addition, treatment response biomarkers in mood disorders would facilitate drug development and move beyond trial-and-error toward more personalized treatments. As such, biomarkers identified early in the pathophysiological process are proximal biomarkers (target engagement), while those occurring later in the disease process are distal (disease pathway components). One strategy to achieve this goal in biomarker development is to increase efforts at the initial phases of biomarker development (i.e. exploration and validation) at single sites with the capability of integrating multimodal approaches across a biological systems level. Subsequently, resultant putative biomarkers could then undergo characterization and surrogacy as these latter phases require multisite collaborative efforts. We have used multimodal approaches - genetics, proteomics/metabolomics, peripheral measures, multimodal neuroimaging, neuropsychopharmacological challenge paradigms and clinical predictors - to explore potential predictor and mediator/moderator biomarkers of the rapid-acting antidepressants ketamine and scopolamine. These exploratory biomarkers may then be used for a priori stratification in larger multisite controlled studies during the validation and characterization phases with the ultimate goal of surrogacy. In sum, the combination of target engagement and well-qualified disease-related measures are crucial to improve our pathophysiological understanding, personalize treatment selection, and expand our armamentarium of novel therapeutics. © 2013 Wiley Periodicals, Inc.

Development of Metabolic Function Biomarkers in the Common Marmoset, Callithrix jacchus

PubMed Central

Ziegler, Toni E.; Colman, Ricki J.; Tardif, Suzette D.; Sosa, Megan E.; Wegner, Fredrick H.; Wittwer, Daniel J.; Shrestha, Hemanta

2013-01-01

Metabolic assessment of a nonhuman primate model of metabolic syndrome and obesity requires the necessary biomarkers specific to the species. While the rhesus monkey has a number of specific assays for assessing metabolic syndrome, the marmoset does not. Furthermore, the common marmoset (Callithrix jacchus) has a small blood volume that necessitates using a single blood volume for multiple analyses. The common marmoset holds a great potential as an alternative primate model for the study of human disease but assay methods need to be developed and validated for the biomarkers of metabolic syndrome. Here we report on the adaptation, development and validation of commercially available immunoassays for common marmoset samples in small volumes. We have performed biological validations for insulin, adiponectin, leptin, and ghrelin to demonstrate the use of these biomarkers in examining metabolic syndrome and other related diseases in the common marmoset. PMID:23447060

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

PubMed

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

2017-02-01

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

Development and validation of response markers to predict survival and pleurodesis success in patients with malignant pleural effusion (PROMISE): a multicohort analysis.

PubMed

Psallidas, Ioannis; Kanellakis, Nikolaos I; Gerry, Stephen; Thézénas, Marie Laëtitia; Charles, Philip D; Samsonova, Anastasia; Schiller, Herbert B; Fischer, Roman; Asciak, Rachelle; Hallifax, Robert J; Mercer, Rachel; Dobson, Melissa; Dong, Tao; Pavord, Ian D; Collins, Gary S; Kessler, Benedikt M; Pass, Harvey I; Maskell, Nick; Stathopoulos, Georgios T; Rahman, Najib M

2018-06-13

The prevalence of malignant pleural effusion is increasing worldwide, but prognostic biomarkers to plan treatment and to understand the underlying mechanisms of disease progression remain unidentified. The PROMISE study was designed with the objectives to discover, validate, and prospectively assess biomarkers of survival and pleurodesis response in malignant pleural effusion and build a score that predicts survival. In this multicohort study, we used five separate and independent datasets from randomised controlled trials to investigate potential biomarkers of survival and pleurodesis. Mass spectrometry-based discovery was used to investigate pleural fluid samples for differential protein expression in patients from the discovery group with different survival and pleurodesis outcomes. Clinical, radiological, and biological variables were entered into least absolute shrinkage and selection operator regression to build a model that predicts 3-month mortality. We evaluated the model using internal and external validation. 17 biomarker candidates of survival and seven of pleurodesis were identified in the discovery dataset. Three independent datasets (n=502) were used for biomarker validation. All pleurodesis biomarkers failed, and gelsolin, macrophage migration inhibitory factor, versican, and tissue inhibitor of metalloproteinases 1 (TIMP1) emerged as accurate predictors of survival. Eight variables (haemoglobin, C-reactive protein, white blood cell count, Eastern Cooperative Oncology Group performance status, cancer type, pleural fluid TIMP1 concentrations, and previous chemotherapy or radiotherapy) were validated and used to develop a survival score. Internal validation with bootstrap resampling and external validation with 162 patients from two independent datasets showed good discrimination (C statistic values of 0·78 [95% CI 0·72-0·83] for internal validation and 0·89 [0·84-0·93] for external validation of the clinical PROMISE score). To our knowledge, the PROMISE score is the first prospectively validated prognostic model for malignant pleural effusion that combines biological and clinical parameters to accurately estimate 3-month mortality. It is a robust, clinically relevant prognostic score that can be applied immediately, provide important information on patient prognosis, and guide the selection of appropriate management strategies. European Respiratory Society, Medical Research Funding-University of Oxford, Slater & Gordon Research Fund, and Oxfordshire Health Services Research Committee Research Grants. Copyright © 2018 Elsevier Ltd. All rights reserved.

Urinary Collagen Fragments Are Significantly Altered in Diabetes: A Link to Pathophysiology

PubMed Central

Argilés, Àngel; Cerna, Marie; Delles, Christian; Dominiczak, Anna F.; Gayrard, Nathalie; Iphöfer, Alexander; Jänsch, Lothar; Jerums, George; Medek, Karel; Mischak, Harald; Navis, Gerjan J.; Roob, Johannes M.; Rossing, Kasper; Rossing, Peter; Rychlík, Ivan; Schiffer, Eric; Schmieder, Roland E.; Wascher, Thomas C.; Winklhofer-Roob, Brigitte M.; Zimmerli, Lukas U.; Zürbig, Petra; Snell-Bergeon, Janet K.

2010-01-01

Background The pathogenesis of diabetes mellitus (DM) is variable, comprising different inflammatory and immune responses. Proteome analysis holds the promise of delivering insight into the pathophysiological changes associated with diabetes. Recently, we identified and validated urinary proteomics biomarkers for diabetes. Based on these initial findings, we aimed to further validate urinary proteomics biomarkers specific for diabetes in general, and particularity associated with either type 1 (T1D) or type 2 diabetes (T2D). Methodology/Principal Findings Therefore, the low-molecular-weight urinary proteome of 902 subjects from 10 different centers, 315 controls and 587 patients with T1D (n = 299) or T2D (n = 288), was analyzed using capillary-electrophoresis mass-spectrometry. The 261 urinary biomarkers (100 were sequenced) previously discovered in 205 subjects were validated in an additional 697 subjects to distinguish DM subjects (n = 382) from control subjects (n = 315) with 94% (95% CI: 92–95) accuracy in this study. To identify biomarkers that differentiate T1D from T2D, a subset of normoalbuminuric patients with T1D (n = 68) and T2D (n = 42) was employed, enabling identification of 131 biomarker candidates (40 were sequenced) differentially regulated between T1D and T2D. These biomarkers distinguished T1D from T2D in an independent validation set of normoalbuminuric patients (n = 108) with 88% (95% CI: 81–94%) accuracy, and in patients with impaired renal function (n = 369) with 85% (95% CI: 81–88%) accuracy. Specific collagen fragments were associated with diabetes and type of diabetes indicating changes in collagen turnover and extracellular matrix as one hallmark of the molecular pathophysiology of diabetes. Additional biomarkers including inflammatory processes and pro-thrombotic alterations were observed. Conclusions/Significance These findings, based on the largest proteomic study performed to date on subjects with DM, validate the previously described biomarkers for DM, and pinpoint differences in the urinary proteome of T1D and T2D, indicating significant differences in extracellular matrix remodeling. PMID:20927192

Validation of Immunohistochemical Assays for Integral Biomarkers in the NCI-MATCH EAY131 Clinical Trial.

PubMed

Khoury, Joseph D; Wang, Wei-Lien; Prieto, Victor G; Medeiros, L Jeffrey; Kalhor, Neda; Hameed, Meera; Broaddus, Russell; Hamilton, Stanley R

2018-02-01

Biomarkers that guide therapy selection are gaining unprecedented importance as targeted therapy options increase in scope and complexity. In conjunction with high-throughput molecular techniques, therapy-guiding biomarker assays based upon immunohistochemistry (IHC) have a critical role in cancer care in that they inform about the expression status of a protein target. Here, we describe the validation procedures for four clinical IHC biomarker assays-PTEN, RB, MLH1, and MSH2-for use as integral biomarkers in the nationwide NCI-Molecular Analysis for Therapy Choice (NCI-MATCH) EAY131 clinical trial. Validation procedures were developed through an iterative process based on collective experience and adaptation of broad guidelines from the FDA. The steps included primary antibody selection; assay optimization; development of assay interpretation criteria incorporating biological considerations; and expected staining patterns, including indeterminate results, orthogonal validation, and tissue validation. Following assay lockdown, patient samples and cell lines were used for analytic and clinical validation. The assays were then approved as laboratory-developed tests and used for clinical trial decisions for treatment selection. Calculations of sensitivity and specificity were undertaken using various definitions of gold-standard references, and external validation was required for the PTEN IHC assay. In conclusion, validation of IHC biomarker assays critical for guiding therapy in clinical trials is feasible using comprehensive preanalytic, analytic, and postanalytic steps. Implementation of standardized guidelines provides a useful framework for validating IHC biomarker assays that allow for reproducibility across institutions for routine clinical use. Clin Cancer Res; 24(3); 521-31. ©2017 AACR . ©2017 American Association for Cancer Research.

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

Construct Validation of the Dietary Inflammatory Index among Postmenopausal Women

PubMed Central

Tabung, Fred K.; Steck, Susan E.; Zhang, Jiajia; Ma, Yunsheng; Liese, Angela D.; Agalliu, Ilir; Hingle, Melanie; Hou, Lifang; Hurley, Thomas G.; Jiao, Li; Martin, Lisa W.; Millen, Amy E.; Park, Hannah L.; Rosal, Milagros C.; Shikany, James M.; Shivappa, Nitin; Ockene, Judith K.; Hebert, James R.

2015-01-01

Purpose Many dietary factors have either pro- or anti-inflammatory properties. We previously developed a dietary inflammatory index (DII) to assess the inflammatory potential of diet. In this study we conducted a construct validation of the DII based on data from a food frequency questionnaire and three inflammatory biomarkers in a subsample of 2,567 postmenopausal women in the Women’s Health Initiative Observational Study. Methods We used multiple linear and logistic regression models, controlling for potential confounders, to test whether baseline DII predicted concentrations of interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor alpha receptor 2 (TNFα-R2), or an overall biomarker score combining all three inflammatory biomarkers. Results The DII was associated with the four biomarkers with beta estimates (95%CI) comparing the highest with lowest DII quintiles as follows: IL-6: 1.26 (1.15, 1.38), Ptrend<0.0001; TNFα-R2: 81.43 (19.15, 143.71), Ptrend=0.004; dichotomized hs-CRP (odds ratio for higher versus lower hs-CRP): 1.30 (0.97, 1.67), Ptrend=0.34); and the combined inflammatory biomarker score: 0.26 (0.12, 0.40), Ptrend=0.0001. Conclusion The DII was significantly associated with inflammatory biomarkers. Construct validity of the DII indicates its utility for assessing the inflammatory potential of diet and for expanding its use to include associations with common chronic diseases in future studies. PMID:25900255

Biomarkers of Exposure to Toxic Substances. Volume 5: Biomarker Pre-validation Studies Prevalidation of Urine and Serum Biomarkers Indicative of Subclinical Kidney Damage in a Nephrotoxin Model

DTIC Science & Technology

2009-05-01

demonstrated to degrade a specific kidney segment (proximal tubule and glomerulus, respectively). In this study a total of seventeen protein biomarkers were...exposure. Two experimental nephrotoxins were interrogated, D-serine and puromycin, each previously demonstrated to degrade a specific kidney segment...to degradation during isolation from sample render it unlikely to develop into a fieldable, self-contained assay system within the near future

Biomarkers of sepsis and their potential value in diagnosis, prognosis and treatment

PubMed Central

Sandquist, Mary; Wong, Hector R

2015-01-01

Biomarkers have great potential to improve the diagnosis and treatment of sepsis. The available literature supports the potential utility of sTREM-1, IL-27, suPAR, neutrophil CD64, presepsin, cfDNA and miRNAs as novel diagnostic, prognostic and treatment response biomarkers. The future of sepsis biomarkers lies in extensive validation studies of such novel biomarkers across heterogeneous populations and exploration of their power in combination. Furthermore, the use of a companion diagnostics model may augment the ability of investigators to identify novel sepsis biomarkers and develop specific therapeutic strategies based on biomarker information. PMID:25142036

MRM validation of targeted nonglycosylated peptides from N-glycoprotein biomarkers using direct trypsin digestion of undepleted human plasma.

PubMed

Lee, Ju Yeon; Kim, Jin Young; Cheon, Mi Hee; Park, Gun Wook; Ahn, Yeong Hee; Moon, Myeong Hee; Yoo, Jong Shin

2014-02-26

A rapid, simple, and reproducible MRM-based validation method for serological glycoprotein biomarkers in clinical use was developed by targeting the nonglycosylated tryptic peptides adjacent to N-glycosylation sites. Since changes in protein glycosylation are known to be associated with a variety of diseases, glycoproteins have been major targets in biomarker discovery. We previously found that nonglycosylated tryptic peptides adjacent to N-glycosylation sites differed in concentration between normal and hepatocellular carcinoma (HCC) plasma due to differences in steric hindrance of the glycan moiety in N-glycoproteins to tryptic digestion (Lee et al., 2011). To increase the feasibility and applicability of clinical validation of biomarker candidates (nonglycosylated tryptic peptides), we developed a method to effectively monitor nonglycosylated tryptic peptides from a large number of plasma samples and to reduce the total analysis time with maximizing the effect of steric hindrance by the glycans during digestion of glycoproteins. The AUC values of targeted nonglycosylated tryptic peptides were excellent (0.955 for GQYCYELDEK, 0.880 for FEDGVLDPDYPR and 0.907 for TEDTIFLR), indicating that these could be effective biomarkers for hepatocellular carcinoma. This method provides the necessary throughput required to validate glycoprotein biomarkers, as well as quantitative accuracy for human plasma analysis, and should be amenable to clinical use. Difficulties in verifying and validating putative protein biomarkers are often caused by complex sample preparation procedures required to determine their concentrations in a large number of plasma samples. To solve the difficulties, we developed MRM-based protein biomarker assays that greatly reduce complex, time-consuming, and less reproducible sample pretreatment steps in plasma for clinical implementation. First, we used undepleted human plasma samples without any enrichment procedures. Using nanoLC/MS/MS, we targeted nonglycosylated tryptic peptides adjacent to N-linked glycosylation sites in N-linked glycoprotein biomarkers, which could be detected in human plasma samples without depleting highly abundant proteins. Second, human plasma proteins were digested with trypsin without reduction and alkylation procedures to minimize sample preparation. Third, trypsin digestion times were shortened so as to obtain reproducible results with maximization of the steric hindrance effect of the glycans during enzyme digestion. Finally, this rapid and simple sample preparation method was applied to validate targeted nonglycosylated tryptic peptides as liver cancer biomarker candidates for diagnosis in 40 normal and 41 hepatocellular carcinoma (HCC) human plasma samples. This strategy provided the necessary throughput required to monitor protein biomarkers, as well as quantitative accuracy in human plasma analysis. From biomarker discovery to clinical implementation, our method will provide a biomarker study platform that is suitable for clinical deployment, and can be applied to high-throughput approaches. Copyright © 2014 Elsevier B.V. All rights reserved.

Urinary biomarkers of smokers’ exposure to tobacco smoke constituents in tobacco products assessment: a fit for purpose approach

PubMed Central

Gregg, Evan O.; Minet, Emmanuel

2013-01-01

There are established guidelines for bioanalytical assay validation and qualification of biomarkers. In this review, they were applied to a panel of urinary biomarkers of tobacco smoke exposure as part of a “fit for purpose” approach to the assessment of smoke constituents exposure in groups of tobacco product smokers. Clinical studies have allowed the identification of a group of tobacco exposure biomarkers demonstrating a good doseresponse relationship whilst others such as dihydroxybutyl mercapturic acid and 2-carboxy-1-methylethylmercapturic acid – did not reproducibly discriminate smokers and non-smokers. Furthermore, there are currently no agreed common reference standards to measure absolute concentrations and few inter-laboratory trials have been performed to establish consensus values for interim standards. Thus, we also discuss in this review additional requirements for the generation of robust data on urinary biomarkers, including toxicant metabolism and disposition, method validation and qualification for use in tobacco products comparison studies. PMID:23902266

Standard Specimen Reference Set: Pancreatic — EDRN Public Portal

Cancer.gov

The primary objective of the EDRN Pancreatic Cancer Working Group Proposal is to create a reference set consisting of well-characterized serum/plasma specimens to use as a resource for the development of biomarkers for the early detection of pancreatic adenocarcinoma. The testing of biomarkers on the same sample set permits direct comparison among them; thereby, allowing the development of a biomarker panel that can be evaluated in a future validation study. Additionally, the establishment of an infrastructure with core data elements and standardized operating procedures for specimen collection, processing and storage, will provide the necessary preparatory platform for larger validation studies when the appropriate marker/panel for pancreatic adenocarcinoma has been identified.

Opportunities and challenges of disease biomarkers: a new section in the Journal of Translational Medicine.

PubMed

Wang, Xiangdong; Ward, Peter A

2012-12-05

Disease biomarkers are defined to diagnose various phases of diseases, monitor severities of diseases and responses to therapies, or predict prognosis of patients. Disease-specific biomarkers should benefit drug discovery and development, integrate multidisciplinary sciences, be validated by molecular imaging. The opportunities and challenges in biomarker development are emphasized and considered. The Journal of Translational Medicine opens a new Section of Disease Biomarkers to bridge identification and validation of gene or protein-based biomarkers, network biomarkers, dynamic network biomarkers in human diseases, patient phenotypes, and clinical applications. Disease biomarkers are also important for determining drug effects, target specificities and binding, dynamic metabolism and pharmacological kinetics, or toxicity profiles.

Biomarkers of Oxidative Stress Study IV. Are Antioxidants Markers of Ozone Exposure?

EPA Science Inventory

To determine whether the oxidative effects of ozone would result in losses of antioxidants from plasma, and possibly bronchoalveolar lavage fluid (BALF). This research is part of a comprehensive, multilaboratory validation study searching for noninvasive biomarkers of oxidative ...

A Biomarker Bakeoff in Early Stage Pancreatic Cancer — EDRN Public Portal

Cancer.gov

Previous research in EDRN laboratories and elsewhere has produced several candidate biomarker(s) for the detection of early-stage pancreatic ductal adenocarcinoma (PDAC), many of which show promise for significantly improving upon the performance of the current best marker, CA19-9. As yet, the relative performance of the markers in combination is not known because a rigorous comparison using a common sample set has not been performed. A direct comparison of the potential biomarkers in a comparative study (“biomarker bakeoff”) would enable an objective determination of which candidates should move forward for further validation, as well as an assessment of the potential value of using novel combinations of the biomarkers. The gastrointestinal collaborative group within the EDRN is in an optimal position to carry out such a study given its shared resources and interactive structure. In this project, the two pancreatic CVCs in the EDRN will provide samples to be distributed to four laboratories with promising biomarkers. The laboratories will run their own assays and perform initial analyses on the blinded PDAC and control samples. Our biostatistical collaborator, Dr. Huang at FHCRC, will perform the statistical evaluations. Biomarkers meeting the predetermined performance criteria will move forward to further validation using the EDRN reference set. In addition, we will determine whether any novel combinations of biomarkers should be further tested.

NCI Awards 18 Grants to Continue the Early Detection Research Network (EDRN) Biomarkers Effort | Division of Cancer Prevention

Cancer.gov

The NCI has awarded 18 grants to continue the Early Detection Research Network (EDRN), a national infrastructure that supports the integrated development, validation, and clinical application of biomarkers for the early detection of cancer. The awards fund 7 Biomarker Developmental Laboratories, 8 Clinical Validation Centers, 2 Biomarker Reference Laboratories, and a Data

PENN Biomarker Core of the Alzheimer’s Disease Neuroimaging Initiative

PubMed Central

Shaw, Leslie M.

2009-01-01

There is a pressing need to develop effective prevention and disease-modifying treatments for Alzheimer’s disease (AD), a dreaded affliction whose incidence increases almost logarithmically with age starting at about 65 years. A key need in the field of AD research is the validation of imaging and biochemical biomarkers. Biomarker tests that are shown to reliably predict the disease before it is clinically expressed would permit testing of new therapeutics at the earliest time point possible in order to give the best chance for delaying the onset of dementia in these patients. In this review the current state of AD biochemical biomarker research is discussed. A new set of guidelines for the diagnosis of AD in the research setting places emphasis on the inclusion of selected imaging and biochemical biomarkers, in addition to neuropsychological behavioral testing. Importantly, the revised guidelines were developed to identify patients at the earliest stages prior to full-blown dementia as well as patients with the full spectrum of the disease. The Alzheimer’s Disease Neuroimaging Initiative is a multicenter consortium study that includes as one of its primary goals the development of standardized neuroimaging and biochemical biomarker methods for AD clinical trials, as well as using these to measure changes over time in mildly cognitively impaired patients who convert to AD as compared to the natural variability of these in control subjects and their further change over time in AD patients. Validation of the biomarker results by correlation analyses with neuropsychological and neurobehavioral test data is one of the primary outcomes of this study. This validation data will hopefully provide biomarker test performance needed for effective measurement of the efficacy of new treatment and prevention therapeutic agents. PMID:18097156

A Systematic Review of the Diagnostic and Prognostic Value of Urinary Protein Biomarkers in Urothelial Bladder Cancer

PubMed Central

D’Costa, Jamie J.; Goldsmith, James C.; Wilson, Jayne S.; Bryan, Richard T.; Ward, Douglas G.

2016-01-01

For over 80 years, cystoscopy has remained the gold-standard for detecting tumours of the urinary bladder. Since bladder tumours have a tendency to recur and progress, many patients are subjected to repeated cystoscopies during long-term surveillance, with the procedure being both unpleasant for the patient and expensive for healthcare providers. The identification and validation of bladder tumour specific molecular markers in urine could enable tumour detection and reduce reliance on cystoscopy, and numerous classes of biomarkers have been studied. Proteins represent the most intensively studied class of biomolecule in this setting. As an aid to researchers searching for better urinary biomarkers, we report a comprehensive systematic review of the literature and a searchable database of proteins that have been investigated to date. Our objective was to classify these proteins as: 1) those with robustly characterised sensitivity and specificity for bladder cancer detection; 2) those that show potential but further investigation is required; 3) those unlikely to warrant further investigation; and 4) those investigated as prognostic markers. This work should help to prioritise certain biomarkers for rigorous validation, whilst preventing wasted effort on proteins that have shown no association whatsoever with the disease, or only modest biomarker performance despite large-scale efforts at validation. PMID:27500198

Multiple reaction monitoring (MRM) of plasma proteins in cardiovascular proteomics.

PubMed

Dardé, Verónica M; Barderas, Maria G; Vivanco, Fernando

2013-01-01

Different methodologies have been used through years to discover new potential biomarkers related with cardiovascular risk. The conventional proteomic strategy involves a discovery phase that requires the use of mass spectrometry (MS) and a validation phase, usually on an alternative platform such as immunoassays that can be further implemented in clinical practice. This approach is suitable for a single biomarker, but when large panels of biomarkers must be validated, the process becomes inefficient and costly. Therefore, it is essential to find an alternative methodology to perform the biomarker discovery, validation, and -quantification. The skills provided by quantitative MS turn it into an extremely attractive alternative to antibody-based technologies. Although it has been traditionally used for quantification of small molecules in clinical chemistry, MRM is now emerging as an alternative to traditional immunoassays for candidate protein biomarker validation.

Updating the OMERACT Filter: Implications for imaging and soluble biomarkers

PubMed Central

D’Agostino, Maria-Antonietta; Boers, Maarten; Kirwan, John; van der Heijde, Desirée; Østergaard, Mikkel; Schett, Georg; Landewé, Robert B.M.; Maksymowych, Walter P.; Naredo, Esperanza; Dougados, Maxime; Iagnocco, Annamaria; Bingham, Clifton O.; Brooks, Peter; Beaton, Dorcas; Gandjbakhch, Frederique; Gossec, Laure; Guillemin, Francis; Hewlett, Sarah; Kloppenburg, Margreet; March, Lyn; Mease, Philip J; Moller, Ingrid; Simon, Lee S; Singh, Jasvinder A; Strand, Vibeke; Wakefield, Richard J; Wells, George; Tugwell, Peter; Conaghan, Philip G

2014-01-01

Objective The OMERACT Filter provides a framework for the validation of outcome measures for use in rheumatology clinical research. However, imaging and biochemical measures may face additional validation challenges due to their technical nature. The Imaging and Soluble Biomarker Session at OMERACT 11 aimed to provide a guide for the iterative development of an imaging or biochemical measurement instrument so it can be used in therapeutic assessment. Methods A hierarchical structure was proposed, reflecting 3 dimensions needed for validating an imaging or biochemical measurement instrument: outcome domain(s), study setting and performance of the instrument. Movement along the axes in any dimension reflects increasing validation. For a given test instrument, the 3-axis structure assesses the extent to which the instrument is a validated measure for the chosen domain, whether it assesses a patient or disease centred-variable, and whether its technical performance is adequate in the context of its application. Some currently used imaging and soluble biomarkers for rheumatoid arthritis, spondyloarthritis and knee osteoarthritis were then evaluated using the original OMERACT filter and the newly proposed structure. Break-out groups critically reviewed the extent to which the candidate biomarkers complied with the proposed step-wise approach, as a way of examining the utility of the proposed 3 dimensional structure. Results Although there was a broad acceptance of the value of the proposed structure in general, some areas for improvement were suggested including clarification of criteria for achieving a certain level of validation and how to deal with extension of the structure to areas beyond clinical trials. Conclusion General support was obtained for a proposed tri-axis structure to assess validation of imaging and soluble biomarkers; nevertheless, additional work is required to better evaluate its place within the OMERACT Filter 2.0. PMID:24584916

Updating the OMERACT filter: implications for imaging and soluble biomarkers.

PubMed

D'Agostino, Maria-Antonietta; Boers, Maarten; Kirwan, John; van der Heijde, Désirée; Østergaard, Mikkel; Schett, Georg; Landewé, Robert B; Maksymowych, Walter P; Naredo, Esperanza; Dougados, Maxime; Iagnocco, Annamaria; Bingham, Clifton O; Brooks, Peter M; Beaton, Dorcas E; Gandjbakhch, Frederique; Gossec, Laure; Guillemin, Francis; Hewlett, Sarah E; Kloppenburg, Margreet; March, Lyn; Mease, Philip J; Moller, Ingrid; Simon, Lee S; Singh, Jasvinder A; Strand, Vibeke; Wakefield, Richard J; Wells, George A; Tugwell, Peter; Conaghan, Philip G

2014-05-01

The Outcome Measures in Rheumatology (OMERACT) Filter provides a framework for the validation of outcome measures for use in rheumatology clinical research. However, imaging and biochemical measures may face additional validation challenges because of their technical nature. The Imaging and Soluble Biomarker Session at OMERACT 11 aimed to provide a guide for the iterative development of an imaging or biochemical measurement instrument so it can be used in therapeutic assessment. A hierarchical structure was proposed, reflecting 3 dimensions needed for validating an imaging or biochemical measurement instrument: outcome domain(s), study setting, and performance of the instrument. Movement along the axes in any dimension reflects increasing validation. For a given test instrument, the 3-axis structure assesses the extent to which the instrument is a validated measure for the chosen domain, whether it assesses a patient-centered or disease-centered variable, and whether its technical performance is adequate in the context of its application. Some currently used imaging and soluble biomarkers for rheumatoid arthritis, spondyloarthritis, and knee osteoarthritis were then evaluated using the original OMERACT Filter and the newly proposed structure. Breakout groups critically reviewed the extent to which the candidate biomarkers complied with the proposed stepwise approach, as a way of examining the utility of the proposed 3-dimensional structure. Although there was a broad acceptance of the value of the proposed structure in general, some areas for improvement were suggested including clarification of criteria for achieving a certain level of validation and how to deal with extension of the structure to areas beyond clinical trials. General support was obtained for a proposed tri-axis structure to assess validation of imaging and soluble biomarkers; nevertheless, additional work is required to better evaluate its place within the OMERACT Filter 2.0.

Stable Isotope Ratios as Biomarkers of Diet for Health Research

PubMed Central

O’Brien, Diane M.

2016-01-01

Diet is a leading modifiable risk factor for chronic disease, but it remains difficult to measure accurately due to the error and bias inherent in self-reported methods of diet assessment. Consequently there is a pressing need for more objective biomarkers of diet for use in health research. The stable isotope ratios of light elements are a promising set of candidate biomarkers because they vary naturally and reproducibly among foods, and those variations are captured in molecules and tissues with high fidelity. Recent studies have identified valid isotopic measures of short and long-term sugar intake, meat intake, and fish intake in specific populations. These studies provide a strong foundation for validating stable isotopic biomarkers in the general United States population. Approaches to improve specificity for specific foods are needed, for example, by modeling intake using multiple stable isotope ratios, or by isolating and measuring specific molecules linked to foods of interest. PMID:26048703

Global Metabolomic Identification of Long-Term Dose-Dependent Urinary Biomarkers in Nonhuman Primates Exposed to Ionizing Radiation.

PubMed

Pannkuk, Evan L; Laiakis, Evagelia C; Authier, Simon; Wong, Karen; Fornace, Albert J

2015-08-01

Due to concerns surrounding potential large-scale radiological events, there is a need to determine robust radiation signatures for the rapid identification of exposed individuals, which can then be used to guide the development of compact field deployable instruments to assess individual dose. Metabolomics provides a technology to process easily accessible biofluids and determine rigorous quantitative radiation biomarkers with mass spectrometry (MS) platforms. While multiple studies have utilized murine models to determine radiation biomarkers, limited studies have profiled nonhuman primate (NHP) metabolic radiation signatures. In addition, these studies have concentrated on short-term biomarkers (i.e., <72 h). The current study addresses the need for biomarkers beyond 72 h using a NHP model. Urine samples were collected at 7 days postirradiation (2, 4, 6, 7 and 10 Gy) and processed with ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (QTOF) MS, acquiring global metabolomic radiation signatures. Multivariate data analysis revealed clear separation between control and irradiated groups. Thirteen biomarkers exhibiting a dose response were validated with tandem MS. There was significantly higher excretion of l-carnitine, l-acetylcarnitine, xanthine and xanthosine in males versus females. Metabolites validated in this study suggest perturbation of several pathways including fatty acid β oxidation, tryptophan metabolism, purine catabolism, taurine metabolism and steroid hormone biosynthesis. In this novel study we detected long-term biomarkers in a NHP model after exposure to radiation and demonstrate differences between sexes using UPLC-QTOF-MS-based metabolomics technology.

Diagnostic and prognostic epigenetic biomarkers in cancer.

PubMed

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

2015-01-01

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

Major depressive disorder: insight into candidate cerebrospinal fluid protein biomarkers from proteomics studies.

PubMed

Al Shweiki, Mhd Rami; Oeckl, Patrick; Steinacker, Petra; Hengerer, Bastian; Schönfeldt-Lecuona, Carlos; Otto, Markus

2017-06-01

Major Depressive Disorder (MDD) is the leading cause of global disability, and an increasing body of literature suggests different cerebrospinal fluid (CSF) proteins as biomarkers of MDD. The aim of this review is to summarize the suggested CSF biomarkers and to analyze the MDD proteomics studies of CSF and brain tissues for promising biomarker candidates. Areas covered: The review includes the human studies found by a PubMed search using the following terms: 'depression cerebrospinal fluid biomarker', 'major depression biomarker CSF', 'depression CSF biomarker', 'proteomics depression', 'proteomics biomarkers in depression', 'proteomics CSF biomarker in depression', and 'major depressive disorder CSF'. The literature analysis highlights promising biomarker candidates and demonstrates conflicting results on others. It reveals 42 differentially regulated proteins in MDD that were identified in more than one proteomics study. It discusses the diagnostic potential of the biomarker candidates and their association with the suggested pathologies. Expert commentary: One ultimate goal of finding biomarkers for MDD is to improve the diagnostic accuracy to achieve better treatment outcomes; due to the heterogeneous nature of MDD, using bio-signatures could be a good strategy to differentiate MDD from other neuropsychiatric disorders. Notably, further validation studies of the suggested biomarkers are still needed.

The role of biomarkers in evaluating human health concerns from fungal contaminants in food.

PubMed

Turner, Paul C; Flannery, Brenna; Isitt, Catherine; Ali, Mariyam; Pestka, James

2012-06-01

Mycotoxins are toxic secondary metabolites that globally contaminate an estimated 25 % of cereal crops and thus exposure is frequent in many populations. Aflatoxins, fumonisins and deoxynivalenol are amongst those mycotoxins of particular concern from a human health perspective. A number of risks to health are suggested including cancer, growth faltering, immune suppression and neural tube defects; though only the demonstrated role for aflatoxin in the aetiology of liver cancer is widely recognised. The heterogeneous distribution of mycotoxins in food restricts the usefulness of food sampling and intake estimates; instead biomarkers provide better tools for informing epidemiological investigations. Validated exposure biomarkers for aflatoxin (urinary aflatoxin M(1), aflatoxin-N7-guaunine, serum aflatoxin-albumin) were established almost 20 years ago and were critical in confirming aflatoxins as potent liver carcinogens. Validation has included demonstration of assay robustness, intake v. biomarker level, and stability of stored samples. More recently, aflatoxin exposure biomarkers are revealing concerns of growth faltering and immune suppression; importantly, they are being used to assess the effectiveness of intervention strategies. For fumonisins and deoxynivalenol these steps of development and validation have significantly advanced in recent years. Such biomarkers should better inform epidemiological studies and thus improve our understanding of their potential risk to human health.

Targeted Mass Spectrometric Approach for Biomarker Discovery and Validation with Nonglycosylated Tryptic Peptides from N-linked Glycoproteins in Human Plasma*

PubMed Central

Lee, Ju Yeon; Kim, Jin Young; Park, Gun Wook; Cheon, Mi Hee; Kwon, Kyung-Hoon; Ahn, Yeong Hee; Moon, Myeong Hee; Lee, Hyoung–Joo; Paik, Young Ki; Yoo, Jong Shin

2011-01-01

A simple mass spectrometric approach for the discovery and validation of biomarkers in human plasma was developed by targeting nonglycosylated tryptic peptides adjacent to glycosylation sites in an N-linked glycoprotein, one of the most important biomarkers for early detection, prognoses, and disease therapies. The discovery and validation of novel biomarkers requires complex sample pretreatment steps, such as depletion of highly abundant proteins, enrichment of desired proteins, or the development of new antibodies. The current study exploited the steric hindrance of glycan units in N-linked glycoproteins, which significantly affects the efficiency of proteolytic digestion if an enzymatically active amino acid is adjacent to the N-linked glycosylation site. Proteolytic digestion then results in quantitatively different peptide products in accordance with the degree of glycosylation. The effect of glycan steric hindrance on tryptic digestion was first demonstrated using alpha-1-acid glycoprotein (AGP) as a model compound versus deglycosylated alpha-1-acid glycoprotein. Second, nonglycosylated tryptic peptide biomarkers, which generally show much higher sensitivity in mass spectrometric analyses than their glycosylated counterparts, were quantified in human hepatocellular carcinoma plasma using a label-free method with no need for N-linked glycoprotein enrichment. Finally, the method was validated using a multiple reaction monitoring analysis, demonstrating that the newly discovered nonglycosylated tryptic peptide targets were present at different levels in normal and hepatocellular carcinoma plasmas. The area under the receiver operating characteristic curve generated through analyses of nonglycosylated tryptic peptide from vitronectin precursor protein was 0.978, the highest observed in a group of patients with hepatocellular carcinoma. This work provides a targeted means of discovering and validating nonglycosylated tryptic peptides as biomarkers in human plasma, without the need for complex enrichment processes or expensive antibody preparations. PMID:21940909

Biomarkers of tolerance: searching for the hidden phenotype.

PubMed

Perucha, Esperanza; Rebollo-Mesa, Irene; Sagoo, Pervinder; Hernandez-Fuentes, Maria P

2011-08-01

Induction of transplantation tolerance remains the ideal long-term clinical and logistic solution to the current challenges facing the management of renal allograft recipients. In this review, we describe the recent studies and advances made in identifying biomarkers of renal transplant tolerance, from study inceptions, to the lessons learned and their implications for current and future studies with the same goal. With the age of biomarker discovery entering a new dimension of high-throughput technologies, here we also review the current approaches, developments, and pitfalls faced in the subsequent statistical analysis required to identify valid biomarker candidates.

BluePen Biomarkers LLC: integrated biomarker solutions

PubMed Central

Blair, Ian A; Mesaros, Clementina; Lilley, Patrick; Nunez, Matthew

2016-01-01

BluePen Biomarkers provides a unique comprehensive multi-omics biomarker discovery and validation platform. We can quantify, integrate and analyze genomics, proteomics, metabolomics and lipidomics biomarkers, alongside clinical data, demographics and other phenotypic data. A unique bio-inspired signal processing analytic approach is used that has the proven ability to identify biomarkers in a wide variety of diseases. The resulting biomarkers can be used for diagnosis, prognosis, mechanistic studies and predicting treatment response, in contexts from core research through clinical trials. BluePen Biomarkers provides an additional groundbreaking research goal: identifying surrogate biomarkers from different modalities. This not only provides new biological insights, but enables least invasive, least-cost tests that meet or exceed the predictive quality of current tests. PMID:28031971

Systematic Review of Pancreatic Cyst Fluid Biomarkers: The Path Forward

PubMed Central

Thiruvengadam, Nikhil; Park, Walter G

2015-01-01

There is significant research interest in developing and validating novel pancreatic cyst-fluid biomarkers given the increasing recognition of the prevalence of pancreatic cysts and their associated malignant potential. Although current international consensus guidelines are helpful, they fail to diagnose with certainty the cyst type and the level of epithelial dysplasia. They also fall short in predicting the future likelihood of malignant transformation. A systematic review was performed with the objective of summarizing cyst-fluid-based biomarkers that have been published in the medical literature over the past 10 years and characterizing the current quality of evidence. Our review demonstrates that there is an increasing interest in this topic with several different and innovative approaches including DNA, RNA, proteomic, and metabolomics profiling. Further techniques to improve upon cytological yield have also been studied. Besides identifying potentially useful clinical biomarkers, these empiric approaches have provided further insight into their pathogenesis. The level of evidence for the vast majority of these studies, however, is limited to retrospective early validation studies. The path forward will be to select out the most promising biomarkers and develop multicenter consortiums capable of capturing adequate sample sizes with appropriate study designs. PMID:26065716

The quest for fragile X biomarkers.

PubMed

Westmark, Cara J

2014-12-01

Fragile X is the most common form of inherited intellectual disability and the leading known genetic cause of autism. There is currently no cure or approved medication for fragile X although various drugs target specific disease symptoms and a large number of therapeutics are in various stages of clinical development. Multiple recent clinical trials have failed on their primary endpoints indicating that there is a compelling need for validated biomarkers and outcome measures in fragile X. There are currently no validated blood-based biomarkers to assess disease severity or to monitor drug efficacy in fragile X syndrome. Herein, we review candidate blood protein biomarkers including extracellular-regulated kinase, phosphoinositide 3-kinase, matrix metalloproteinase 9, amyloid-beta and amyloid-beta protein precursor. Bench-to-bedside plans for fragile X syndrome are severely limited by the lack of validated outcome measures. The reviewed candidate biomarkers are at early stages of validation and deserve further investigation.

About the Cancer Biomarkers Research Group | Division of Cancer Prevention

Cancer.gov

The Cancer Biomarkers Research Group promotes research to identify, develop, and validate biological markers for early cancer detection and cancer risk assessment. Activities include development and validation of promising cancer biomarkers, collaborative databases and informatics systems, and new technologies or the refinement of existing technologies. NCI DCP News Note

Development of Diagnostic Biomarkers for Detecting Diabetic Retinopathy at Early Stages Using Quantitative Proteomics

PubMed Central

Min, Hophil; Kim, Sang Jin; Oh, Sohee; Kim, Kyunggon; Yu, Hyeong Gon; Park, Taesung; Kim, Youngsoo

2016-01-01

Diabetic retinopathy (DR) is a common microvascular complication caused by diabetes mellitus (DM) and is a leading cause of vision impairment and loss among adults. Here, we performed a comprehensive proteomic analysis to discover biomarkers for DR. First, to identify biomarker candidates that are specifically expressed in human vitreous, we performed data-mining on both previously published DR-related studies and our experimental data; 96 proteins were then selected. To confirm and validate the selected biomarker candidates, candidates were selected, confirmed, and validated using plasma from diabetic patients without DR (No DR) and diabetics with mild or moderate nonproliferative diabetic retinopathy (Mi or Mo NPDR) using semiquantitative multiple reaction monitoring (SQ-MRM) and stable-isotope dilution multiple reaction monitoring (SID-MRM). Additionally, we performed a multiplex assay using 15 biomarker candidates identified in the SID-MRM analysis, which resulted in merged AUC values of 0.99 (No DR versus Mo NPDR) and 0.93 (No DR versus Mi and Mo NPDR). Although further validation with a larger sample size is needed, the 4-protein marker panel (APO4, C7, CLU, and ITIH2) could represent a useful multibiomarker model for detecting the early stages of DR. PMID:26665153

Clinical evidence supporting pharmacogenomic biomarker testing provided in US Food and Drug Administration drug labels.

PubMed

Wang, Bo; Canestaro, William J; Choudhry, Niteesh K

2014-12-01

Genetic biomarkers that predict a drug's efficacy or likelihood of toxicity are assuming increasingly important roles in the personalization of pharmacotherapy, but concern exists that evidence that links use of some biomarkers to clinical benefit is insufficient. Nevertheless, information about the use of biomarkers appears in the labels of many prescription drugs, which may add confusion to the clinical decision-making process. To evaluate the evidence that supports pharmacogenomic biomarker testing in drug labels and how frequently testing is recommended. Publicly available US Food and Drug Administration databases. We identified drug labels that described the use of a biomarker and evaluated whether the label contained or referenced convincing evidence of its clinical validity (ie, the ability to predict phenotype) and clinical utility (ie, the ability to improve clinical outcomes) using guidelines published by the Evaluation of Genomic Applications in Practice and Prevention Working Group. We graded the completeness of the citation of supporting studies and determined whether the label recommended incorporation of biomarker test results in therapeutic decision making. Of the 119 drug-biomarker combinations, only 43 (36.1%) had labels that provided convincing clinical validity evidence, whereas 18 (15.1%) provided convincing evidence of clinical utility. Sixty-one labels (51.3%) made recommendations about how clinical decisions should be based on the results of a biomarker test; 36 (30.3%) of these contained convincing clinical utility data. A full description of supporting studies was included in 13 labels (10.9%). Fewer than one-sixth of drug labels contained or referenced convincing evidence of clinical utility of biomarker testing, whereas more than half made recommendations based on biomarker test results. It may be premature to include biomarker testing recommendations in drug labels when convincing data that link testing to patient outcomes do not exist.

Validation of standard operating procedures in a multicenter retrospective study to identify -omics biomarkers for chronic low back pain.

PubMed

Dagostino, Concetta; De Gregori, Manuela; Gieger, Christian; Manz, Judith; Gudelj, Ivan; Lauc, Gordan; Divizia, Laura; Wang, Wei; Sim, Moira; Pemberton, Iain K; MacDougall, Jane; Williams, Frances; Van Zundert, Jan; Primorac, Dragan; Aulchenko, Yurii; Kapural, Leonardo; Allegri, Massimo

2017-01-01

Chronic low back pain (CLBP) is one of the most common medical conditions, ranking as the greatest contributor to global disability and accounting for huge societal costs based on the Global Burden of Disease 2010 study. Large genetic and -omics studies provide a promising avenue for the screening, development and validation of biomarkers useful for personalized diagnosis and treatment (precision medicine). Multicentre studies are needed for such an effort, and a standardized and homogeneous approach is vital for recruitment of large numbers of participants among different centres (clinical and laboratories) to obtain robust and reproducible results. To date, no validated standard operating procedures (SOPs) for genetic/-omics studies in chronic pain have been developed. In this study, we validated an SOP model that will be used in the multicentre (5 centres) retrospective "PainOmics" study, funded by the European Community in the 7th Framework Programme, which aims to develop new biomarkers for CLBP through three different -omics approaches: genomics, glycomics and activomics. The SOPs describe the specific procedures for (1) blood collection, (2) sample processing and storage, (3) shipping details and (4) cross-check testing and validation before assays that all the centres involved in the study have to follow. Multivariate analysis revealed the absolute specificity and homogeneity of the samples collected by the five centres for all genetics, glycomics and activomics analyses. The SOPs used in our multicenter study have been validated. Hence, they could represent an innovative tool for the correct management and collection of reliable samples in other large-omics-based multicenter studies.

Statistical Design for Biospecimen Cohort Size in Proteomics-based Biomarker Discovery and Verification Studies

PubMed Central

Skates, Steven J.; Gillette, Michael A.; LaBaer, Joshua; Carr, Steven A.; Anderson, N. 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.

2014-01-01

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 towards building a consensus on quantitative criteria for statistical design of proteomics biomarker discovery and verification research. PMID:24063748

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

2013-12-06

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

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

PubMed Central

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

2017-01-01

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

Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

PubMed

Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

2013-01-01

A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal and reactive cellular mechanisms, transcriptomic changes may thus have future potential in the diagnosis of a wide array of heterogeneous diseases that result from genetic disturbances.

ELISA microarray technology as a high-throughput system for cancer biomarker validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zangar, Richard C.; Daly, Don S.; White, Amanda M.

A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. Another major challenge with cancer screening is that most cancers are rare in the general population, meaning that the specificity of an assay must be very high if the number of false positive is notmore » going to be much greater than the number of true positives. Because of these challenges with biomarker validation, it is necessary to analysis of thousands of samples before a clear idea of the utility of a screening assay can be determined. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and has the potential to accelerate biomarker validation. In this review, we discuss current ELISA microarray technology and the enabling advances needed to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.« less

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

PubMed Central

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria del Carmen Bisi

2016-01-01

Introduction Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. Objective To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. Subjects/Methods A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. Results The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food. PMID:28030625

Use of the Method of Triads in the Validation of Sodium and Potassium Intake in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Pereira, Taísa Sabrina Silva; Cade, Nágela Valadão; Mill, José Geraldo; Sichieri, Rosely; Molina, Maria Del Carmen Bisi

2016-01-01

Biomarkers are a good choice to be used in the validation of food frequency questionnaire due to the independence of their random errors. To assess the validity of the potassium and sodium intake estimated using the Food Frequency Questionnaire ELSA-Brasil. A subsample of participants in the ELSA-Brasil cohort was included in this study in 2009. Sodium and potassium intake were estimated using three methods: Semi-quantitative food frequency questionnaire, 12-hour nocturnal urinary excretion and three 24-hour food records. Correlation coefficients were calculated between the methods, and the validity coefficient was calculated using the method of triads. The 95% confidence intervals for the validity coefficient were estimated using bootstrap sampling. Exact and adjacent agreement and disagreement of the estimated sodium and potassium intake quintiles were compared among three methods. The sample consisted of 246 participants, aged 53±8 years, 52% of women. Validity coefficient for sodium were considered weak (рfood frequency questionnaire actual intake = 0.37 and рbiomarker actual intake = 0.21) and moderate (рfood records actual intake 0.56). The validity coefficient were higher for potassium (рfood frequency questionnaire actual intake = 0.60; рbiomarker actual intake = 0.42; рfood records actual intake = 0.79). Conclusions: The Food Frequency Questionnaire ELSA-Brasil showed good validity in estimating potassium intake in epidemiological studies. For sodium validity was weak, likely due to the non-quantification of the added salt to prepared food.

Workshop Report: Crystal City VI-Bioanalytical Method Validation for Biomarkers.

PubMed

Arnold, Mark E; Booth, Brian; King, Lindsay; Ray, Chad

2016-11-01

With the growing focus on translational research and the use of biomarkers to drive drug development and approvals, biomarkers have become a significant area of research within the pharmaceutical industry. However, until the US Food and Drug Administration's (FDA) 2013 draft guidance on bioanalytical method validation included consideration of biomarker assays using LC-MS and LBA, those assays were created, validated, and used without standards of performance. This lack of expectations resulted in the FDA receiving data from assays of varying quality in support of efficacy and safety claims. The AAPS Crystal City VI (CC VI) Workshop in 2015 was held as the first forum for industry-FDA discussion around the general issues of biomarker measurements (e.g., endogenous levels) and specific technology strengths and weaknesses. The 2-day workshop served to develop a common understanding among the industrial scientific community of the issues around biomarkers, informed the FDA of the current state of the science, and will serve as a basis for further dialogue as experience with biomarkers expands with both groups.

Lipidomic analysis of plasma in patients with lacunar infarction using normal-phase/reversed-phase two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry.

PubMed

Yang, Li; Lv, Pu; Ai, Wanpeng; Li, Linnan; Shen, Sensen; Nie, Honggang; Shan, Yabing; Bai, Yu; Huang, Yining; Liu, Huwei

2017-05-01

Stroke is a major cause of mortality and long-term disability worldwide. The study of biomarkers and pathogenesis is vital for early diagnosis and treatment of stroke. In the present study, a continuous-flow normal-phase/reversed-phase two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry (NP/RP 2D LC-QToF/MS) method was employed to measure lipid species in human plasma, including healthy controls and lacunar infarction (LI) patients. As a result, 13 lipid species were demonstrated with significant difference between the two groups, and a "plasma biomarker model" including glucosylceramide (38:2), phosphatidylethanolamine (35:2), free fatty acid (16:1), and triacylglycerol (56:5) was finally established. This model was evaluated as an effective tool in that area under the receiver operating characteristic curve reached 1.000 in the discovery set and 0.947 in the validation set for diagnosing LI patients from healthy controls. Besides, the sensitivity and specificity of disease diagnosis in validation set were 93.3% and 96.6% at the best cutoff value, respectively. This study demonstrates the promising potential of NP/RP 2D LC-QToF/MS-based lipidomics approach in finding bio-markers for disease diagnosis and providing special insights into the metabolism of stroke induced by small vessel disease. Graphical abstract Flow-chart of the plasma biomarker model establishment through biomarker screening and validation.

Phase II cancer clinical trials for biomarker-guided treatments.

PubMed

Jung, Sin-Ho

2018-01-01

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

Empirical evaluation demonstrated importance of validating biomarkers for early detection of cancer in screening settings to limit the number of false-positive findings.

PubMed

Chen, Hongda; Knebel, Phillip; Brenner, Hermann

2016-07-01

Search for biomarkers for early detection of cancer is a very active area of research, but most studies are done in clinical rather than screening settings. We aimed to empirically evaluate the role of study setting for early detection marker identification and validation. A panel of 92 candidate cancer protein markers was measured in 35 clinically identified colorectal cancer patients and 35 colorectal cancer patients identified at screening colonoscopy. For each case group, we selected 38 controls without colorectal neoplasms at screening colonoscopy. Single-, two- and three-marker combinations discriminating cases and controls were identified in each setting and subsequently validated in the alternative setting. In all scenarios, a higher number of predictive biomarkers were initially detected in the clinical setting, but a substantially lower proportion of identified biomarkers could subsequently be confirmed in the screening setting. Confirmation rates were 50.0%, 84.5%, and 74.2% for one-, two-, and three-marker algorithms identified in the screening setting and were 42.9%, 18.6%, and 25.7% for algorithms identified in the clinical setting. Validation of early detection markers of cancer in a true screening setting is important to limit the number of false-positive findings. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Development and validation of a scoring index to predict the presence of lesions in capsule endoscopy in patients with suspected Crohn's disease of the small bowel: a Spanish multicenter study.

PubMed

Egea-Valenzuela, Juan; González Suárez, Begoña; Sierra Bernal, Cristian; Juanmartiñena Fernández, José Francisco; Luján-Sanchís, Marisol; San Juan Acosta, Mileidis; Martínez Andrés, Blanca; Pons Beltrán, Vicente; Sastre Lozano, Violeta; Carretero Ribón, Cristina; de Vera Almenar, Félix; Sánchez Cuenca, Joaquín; Alberca de Las Parras, Fernando; Rodríguez de Miguel, Cristina; Valle Muñoz, Julio; Férnandez-Urién Sainz, Ignacio; Torres González, Carolina; Borque Barrera, Pilar; Pérez-Cuadrado Robles, Enrique; Alonso Lázaro, Noelia; Martínez García, Pilar; Prieto de Frías, César; Carballo Álvarez, Fernando

2018-05-01

Capsule endoscopy (CE) is the first-line investigation in cases of suspected Crohn's disease (CD) of the small bowel, but the factors associated with a higher diagnostic yield remain unclear. Our aim is to develop and validate a scoring index to assess the risk of the patients in this setting on the basis of biomarkers. Data on fecal calprotectin, C-reactive protein, and other biomarkers from a population of 124 patients with suspected CD of the small bowel studied by CE and included in a PhD study were used to build a scoring index. This was first used on this population (internal validation process) and after that on a different set of patients from a multicenter study (external validation process). An index was designed in which every biomarker is assigned a score. Three risk groups have been established (low, intermediate, and high). In the internal validation analysis (124 individuals), patients had a 10, 46.5, and 81% probability of showing inflammatory lesions in CE in the low-risk, intermediate-risk, and high-risk groups, respectively. In the external validation analysis, including 410 patients from 12 Spanish hospitals, this probability was 15.8, 49.7, and 80.6% for the low-risk, intermediate-risk, and high-risk groups, respectively. Results from the internal validation process show that the scoring index is coherent, and results from the external validation process confirm its reliability. This index can be a useful tool for selecting patients before CE studies in cases of suspected CD of the small bowel.

Potential serum biomarkers from a metabolomics study of autism

PubMed Central

Wang, Han; Liang, Shuang; Wang, Maoqing; Gao, Jingquan; Sun, Caihong; Wang, Jia; Xia, Wei; Wu, Shiying; Sumner, Susan J.; Zhang, Fengyu; Sun, Changhao; Wu, Lijie

2016-01-01

Background Early detection and diagnosis are very important for autism. Current diagnosis of autism relies mainly on some observational questionnaires and interview tools that may involve a great variability. We performed a metabolomics analysis of serum to identify potential biomarkers for the early diagnosis and clinical evaluation of autism. Methods We analyzed a discovery cohort of patients with autism and participants without autism in the Chinese Han population using ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF MS/MS) to detect metabolic changes in serum associated with autism. The potential metabolite candidates for biomarkers were individually validated in an additional independent cohort of cases and controls. We built a multiple logistic regression model to evaluate the validated biomarkers. Results We included 73 patients and 63 controls in the discovery cohort and 100 cases and 100 controls in the validation cohort. Metabolomic analysis of serum in the discovery stage identified 17 metabolites, 11 of which were validated in an independent cohort. A multiple logistic regression model built on the 11 validated metabolites fit well in both cohorts. The model consistently showed that autism was associated with 2 particular metabolites: sphingosine 1-phosphate and docosahexaenoic acid. Limitations While autism is diagnosed predominantly in boys, we were unable to perform the analysis by sex owing to difficulty recruiting enough female patients. Other limitations include the need to perform test–retest assessment within the same individual and the relatively small sample size. Conclusion Two metabolites have potential as biomarkers for the clinical diagnosis and evaluation of autism. PMID:26395811

Decreased serum 5-oxoproline in TB patients is associated with pathological damage of the lung.

PubMed

Che, Nanying; Cheng, Jianhua; Li, Haijing; Zhang, Zhiguo; Zhang, Xuxia; Ding, Zhixin; Dong, Fangting; Li, Chuanyou

2013-08-23

Tuberculosis (TB) is a serious world-wide health problem, causing millions of deaths every year. Metabolomics is a relatively new approach to identify disease specific biomarkers. However, there is little information available on metabolite biomarkers in TB. In this study, we used gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS) to identify serum metabolite biomarkers associated with the active state of TB. Potential biomarkers were selected by comparing serum metabolites in 10 healthy donors with 10TB patients, and in 6TB patients before and after treatment. Selected biomarkers were then validated using a larger population of samples from 120 healthy donors and 120TB patients derived from different clinical backgrounds The 5-oxoproline level was consistently low in patients with active TB. Further validation in larger population of clinical samples showed that 5-oxoproline was associated with pathological damage of the lung but not with age, sex, or bacterial burden in TB patients. Serum 5-oxoproline may be a useful biomarker for active TB and pathological damage of the lung. Copyright © 2013 Elsevier B.V. All rights reserved.

Protein biomarker validation via proximity ligation assays.

PubMed

Blokzijl, A; Nong, R; Darmanis, S; Hertz, E; Landegren, U; Kamali-Moghaddam, M

2014-05-01

The ability to detect minute amounts of specific proteins or protein modifications in blood as biomarkers for a plethora of human pathological conditions holds great promise for future medicine. Despite a large number of plausible candidate protein biomarkers published annually, the translation to clinical use is impeded by factors such as the required size of the initial studies, and limitations of the technologies used. The proximity ligation assay (PLA) is a versatile molecular tool that has the potential to address some obstacles, both in validation of biomarkers previously discovered using other techniques, and for future routine clinical diagnostic needs. The enhanced specificity of PLA extends the opportunities for large-scale, high-performance analyses of proteins. Besides advantages in the form of minimal sample consumption and an extended dynamic range, the PLA technique allows flexible assay reconfiguration. The technology can be adapted for detecting protein complexes, proximity between proteins in extracellular vesicles or in circulating tumor cells, and to address multiple post-translational modifications in the same protein molecule. We discuss herein requirements for biomarker validation, and how PLA may play an increasing role in this regard. We describe some recent developments of the technology, including proximity extension assays, the use of recombinant affinity reagents suitable for use in proximity assays, and the potential for single cell proteomics. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge. © 2013.

Clinical Translation and Validation of a Predictive Biomarker for Patritumab, an Anti-human Epidermal Growth Factor Receptor 3 (HER3) Monoclonal Antibody, in Patients With Advanced Non-small Cell Lung Cancer

PubMed Central

Mendell, Jeanne; Freeman, Daniel J.; Feng, Wenqin; Hettmann, Thore; Schneider, Matthias; Blum, Sabine; Ruhe, Jens; Bange, Johannes; Nakamaru, Kenji; Chen, Shuquan; Tsuchihashi, Zenta; von Pawel, Joachim; Copigneaux, Catherine; Beckman, Robert A.

2015-01-01

Background During early clinical development, prospective identification of a predictive biomarker and validation of an assay method may not always be feasible. Dichotomizing a continuous biomarker measure to classify responders also leads to challenges. We present a case study of a prospective–retrospective approach for a continuous biomarker identified after patient enrollment but defined prospectively before the unblinding of data. An analysis of the strengths and weaknesses of this approach and the challenges encountered in its practical application are also provided. Methods HERALD (NCT02134015) was a double-blind, phase 2 study in patients with non-small cell lung cancer (NSCLC) randomized to erlotinib with placebo or with high or low doses of patritumab, a monoclonal antibody targeted against human epidermal growth factor receptor 3 (HER3). While the primary objective was to assess safety and progression-free survival (PFS), a secondary objective was to determine a single predictive biomarker hypothesis to identify subjects most likely to benefit from the addition of patritumab. Although not identified as the primary biomarker in the study protocol, on the basis of preclinical results from 2 independent laboratories, expression levels of the HER3 ligand heregulin (HRG) were prospectively declared the predictive biomarker before data unblinding but after subject enrollment. An assay to measure HRG mRNA was developed and validated. Other biomarkers, such as epidermal growth factor receptor (EGFR) mutation status, were also evaluated in an exploratory fashion. The cutoff value for high vs. low HRG mRNA levels was set at the median delta threshold cycle. A maximum likelihood analysis was performed to evaluate the provisional cutoff. The relationship of HRG values to PFS hazard ratios (HRs) was assessed as a measure of internal validation. Additional NSCLC samples were analyzed to characterize HRG mRNA distribution. Results The subgroup of patients with high HRG mRNA levels (“HRG-high”) demonstrated clinical benefit from patritumab treatment with HRs of 0.37 (P = 0.0283) and 0.29 (P = 0.0027) in the high- and low-dose patritumab arms, respectively. However, only 102 of the 215 randomized patients (47.4%) had sufficient tumor samples for HRG mRNA measurement. Maximum likelihood analysis showed that the provisional cutoff was within the optimal range. In the placebo arm, the HRG-high subgroup demonstrated worse prognosis compared with HRG-low. A continuous relationship was observed between increased HRG mRNA levels and lower HR. Additional NSCLC samples (N = 300) demonstrated a similar unimodal distribution to that observed in this study, suggesting that the defined cutoff may be applicable to future NSCLC studies. Conclusions The prospective–retrospective approach was successful in clinically validating a probable predictive biomarker. Post hoc in vitro studies and statistical analyses permitted further testing of the underlying assumptions. However, limitations of this analysis include the incomplete collection of adequate tumor tissue and a lack of stratification. In a phase 3 study, findings are being confirmed, and the HRG cutoff value is being further refined. ClinicalTrials.gov Number NCT02134015. PMID:26137564

Reverse-translational biomarker validation of Abnormal Repetitive Behaviors in mice: an illustration of the 4P's modeling approach

PubMed Central

Garner, Joseph P.; Thogerson, Collette M.; Dufour, Brett D.; Würbel, Hanno; Murray, James D.; Mench, Joy A.

2011-01-01

The NIMH's new strategic plan, with its emphasis on the “4P's” (Prediction, Preemption, Personalization, & Populations) and biomarker-based medicine requires a radical shift in animal modeling methodology. In particular 4P's models will be non-determinant (i.e. disease severity will depend on secondary environmental and genetic factors); and validated by reverse-translation of animal homologues to human biomarkers. A powerful consequence of the biomarker approach is that different closely-related disorders have a unique fingerprint of biomarkers. Animals can be validated as a highly-specific model of a single disorder by matching this `fingerprint'; or as a model of a symptom seen in multiple disorders by matching common biomarkers. Here we illustrate this approach with two Abnormal Repetitive Behaviors (ARBs) in mice: stereotypies; and barbering (hair pulling). We developed animal versions of the neuropsychological biomarkers that distinguish human ARBs, and tested the fingerprint of the different mouse ARBs. As predicted, the two mouse ARBs were associated with different biomarkers. Both barbering and stereotypy could be discounted as models of OCD (even though they are widely used as such), due to the absence of limbic biomarkers which are characteristic of OCD and hence are necessary for a valid model. Conversely barbering matched the fingerprint of trichotillomania (i.e. selective deficits in set-shifting), suggesting it may be a highly specific model of this disorder. In contrast stereotypies were correlated only with a biomarker (deficits in response shifting) correlated with stereotypies in multiple disorders, suggesting that animal stereotypies model stereotypies in multiple disorders. PMID:21219937

Definitive Characterization of CA 19-9 in Resectable Pancreatic Cancer Using a Reference Set of Serum and Plasma Specimens.

PubMed

Haab, Brian B; Huang, Ying; Balasenthil, Seetharaman; Partyka, Katie; Tang, Huiyuan; Anderson, Michelle; Allen, Peter; Sasson, Aaron; Zeh, Herbert; Kaul, Karen; Kletter, Doron; Ge, Shaokui; Bern, Marshall; Kwon, Richard; Blasutig, Ivan; Srivastava, Sudhir; Frazier, Marsha L; Sen, Subrata; Hollingsworth, Michael A; Rinaudo, Jo Ann; Killary, Ann M; Brand, Randall E

2015-01-01

The validation of candidate biomarkers often is hampered by the lack of a reliable means of assessing and comparing performance. We present here a reference set of serum and plasma samples to facilitate the validation of biomarkers for resectable pancreatic cancer. The reference set includes a large cohort of stage I-II pancreatic cancer patients, recruited from 5 different institutions, and relevant control groups. We characterized the performance of the current best serological biomarker for pancreatic cancer, CA 19-9, using plasma samples from the reference set to provide a benchmark for future biomarker studies and to further our knowledge of CA 19-9 in early-stage pancreatic cancer and the control groups. CA 19-9 distinguished pancreatic cancers from the healthy and chronic pancreatitis groups with an average sensitivity and specificity of 70-74%, similar to previous studies using all stages of pancreatic cancer. Chronic pancreatitis patients did not show CA 19-9 elevations, but patients with benign biliary obstruction had elevations nearly as high as the cancer patients. We gained additional information about the biomarker by comparing two distinct assays. The two CA 9-9 assays agreed well in overall performance but diverged in measurements of individual samples, potentially due to subtle differences in antibody specificity as revealed by glycan array analysis. Thus, the reference set promises be a valuable resource for biomarker validation and comparison, and the CA 19-9 data presented here will be useful for benchmarking and for exploring relationships to CA 19-9.

Definitive Characterization of CA 19-9 in Resectable Pancreatic Cancer Using a Reference Set of Serum and Plasma Specimens

PubMed Central

Haab, Brian B.; Huang, Ying; Balasenthil, Seetharaman; Partyka, Katie; Tang, Huiyuan; Anderson, Michelle; Allen, Peter; Sasson, Aaron; Zeh, Herbert; Kaul, Karen; Kletter, Doron; Ge, Shaokui; Bern, Marshall; Kwon, Richard; Blasutig, Ivan; Srivastava, Sudhir; Frazier, Marsha L.; Sen, Subrata; Hollingsworth, Michael A.; Rinaudo, Jo Ann; Killary, Ann M.; Brand, Randall E.

2015-01-01

The validation of candidate biomarkers often is hampered by the lack of a reliable means of assessing and comparing performance. We present here a reference set of serum and plasma samples to facilitate the validation of biomarkers for resectable pancreatic cancer. The reference set includes a large cohort of stage I-II pancreatic cancer patients, recruited from 5 different institutions, and relevant control groups. We characterized the performance of the current best serological biomarker for pancreatic cancer, CA 19–9, using plasma samples from the reference set to provide a benchmark for future biomarker studies and to further our knowledge of CA 19–9 in early-stage pancreatic cancer and the control groups. CA 19–9 distinguished pancreatic cancers from the healthy and chronic pancreatitis groups with an average sensitivity and specificity of 70–74%, similar to previous studies using all stages of pancreatic cancer. Chronic pancreatitis patients did not show CA 19–9 elevations, but patients with benign biliary obstruction had elevations nearly as high as the cancer patients. We gained additional information about the biomarker by comparing two distinct assays. The two CA 9–9 assays agreed well in overall performance but diverged in measurements of individual samples, potentially due to subtle differences in antibody specificity as revealed by glycan array analysis. Thus, the reference set promises be a valuable resource for biomarker validation and comparison, and the CA 19–9 data presented here will be useful for benchmarking and for exploring relationships to CA 19–9. PMID:26431551

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics.

PubMed

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana; Hu, Shen

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients' saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects ( p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity.

Validation of Protein Markers for Lung Cancer Using CARET Sera and Proteomics Techniques — EDRN Public Portal

Cancer.gov

1.1 To validate the finding from pilot studies with CARET sera of autoantibodies to annexins I and II and PGP9.5 as potential biomarkers for lung cancers before the clinical diagnosis, evaluating sensitivity and specificity by time before diagnosis, treatment arm, gender, histologic type, and smoking status. 1.2 To determine whether a pattern of occurrence of autoantibodies in lung cancer sera may be diagnostic of lung cancer that is not dependent on the occurrence of any particular autoantibody. 1.3 To compare the findings for individual biomarker candidates and combinations of biomarker candidates in participants who were current smokers versus former smokers.

Integrating multiple ‘omics’ analyses identifies serological protein biomarkers for preeclampsia

PubMed Central

2013-01-01

Background Preeclampsia (PE) is a pregnancy-related vascular disorder which is the leading cause of maternal morbidity and mortality. We sought to identify novel serological protein markers to diagnose PE with a multi-’omics’ based discovery approach. Methods Seven previous placental expression studies were combined for a multiplex analysis, and in parallel, two-dimensional gel electrophoresis was performed to compare serum proteomes in PE and control subjects. The combined biomarker candidates were validated with available ELISA assays using gestational age-matched PE (n=32) and control (n=32) samples. With the validated biomarkers, a genetic algorithm was then used to construct and optimize biomarker panels in PE assessment. Results In addition to the previously identified biomarkers, the angiogenic and antiangiogenic factors (soluble fms-like tyrosine kinase (sFlt-1) and placental growth factor (PIGF)), we found 3 up-regulated and 6 down-regulated biomakers in PE sera. Two optimal biomarker panels were developed for early and late onset PE assessment, respectively. Conclusions Both early and late onset PE diagnostic panels, constructed with our PE biomarkers, were superior over sFlt-1/PIGF ratio in PE discrimination. The functional significance of these PE biomarkers and their associated pathways were analyzed which may provide new insights into the pathogenesis of PE. PMID:24195779

Biomarkers and Surrogate Endpoints: Lessons Learned From Glaucoma

PubMed Central

Medeiros, Felipe A.

2017-01-01

With the recent progress in imaging technologies for assessment of structural damage in glaucoma, a debate has emerged on whether these measurements can be used as valid surrogate endpoints in clinical trials evaluating new therapies for the disease. A discussion of surrogates should be grounded on knowledge acquired from their use in other areas of medicine as well as regulatory requirements. This article reviews the conditions for valid surrogacy in the context of glaucoma clinical trials and critically evaluates the role of biomarkers such as IOP and imaging measurements as potential surrogates for clinically relevant outcomes. Valid surrogate endpoints must be able to predict a clinically relevant endpoint, such as loss of vision or decrease in quality of life. In addition, the effect of a proposed treatment on the surrogate must capture the effect of the treatment on the clinically relevant endpoint. Despite its widespread use in clinical trials, no proper validation of IOP as a surrogate endpoint has yet been conducted for any class of IOP-lowering treatments. Although strong evidence has accumulated about imaging measurements as predictors of relevant functional outcomes in glaucoma, there is still insufficient evidence to support their use as valid surrogate endpoints. However, imaging biomarkers could potentially be used as part of composite endpoints in glaucoma trials, overcoming weaknesses of the use of structural or functional endpoints in isolation. Efforts should be taken to properly design and conduct studies that can provide proper validation of potential biomarkers in glaucoma clinical trials. PMID:28475699

Biomarkers and Surrogate Endpoints: Lessons Learned From Glaucoma.

PubMed

Medeiros, Felipe A

2017-05-01

With the recent progress in imaging technologies for assessment of structural damage in glaucoma, a debate has emerged on whether these measurements can be used as valid surrogate endpoints in clinical trials evaluating new therapies for the disease. A discussion of surrogates should be grounded on knowledge acquired from their use in other areas of medicine as well as regulatory requirements. This article reviews the conditions for valid surrogacy in the context of glaucoma clinical trials and critically evaluates the role of biomarkers such as IOP and imaging measurements as potential surrogates for clinically relevant outcomes. Valid surrogate endpoints must be able to predict a clinically relevant endpoint, such as loss of vision or decrease in quality of life. In addition, the effect of a proposed treatment on the surrogate must capture the effect of the treatment on the clinically relevant endpoint. Despite its widespread use in clinical trials, no proper validation of IOP as a surrogate endpoint has yet been conducted for any class of IOP-lowering treatments. Although strong evidence has accumulated about imaging measurements as predictors of relevant functional outcomes in glaucoma, there is still insufficient evidence to support their use as valid surrogate endpoints. However, imaging biomarkers could potentially be used as part of composite endpoints in glaucoma trials, overcoming weaknesses of the use of structural or functional endpoints in isolation. Efforts should be taken to properly design and conduct studies that can provide proper validation of potential biomarkers in glaucoma clinical trials.

Emerging proteomics biomarkers and prostate cancer burden in Africa

PubMed Central

Adeola, Henry A.; Blackburn, Jonathan M.; Rebbeck, Timothy R.; Zerbini, Luiz F.

2017-01-01

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers. PMID:28388542

Emerging proteomics biomarkers and prostate cancer burden in Africa.

PubMed

Adeola, Henry A; Blackburn, Jonathan M; Rebbeck, Timothy R; Zerbini, Luiz F

2017-06-06

Various biomarkers have emerged via high throughput omics-based approaches for use in diagnosis, treatment, and monitoring of prostate cancer. Many of these have yet to be demonstrated as having value in routine clinical practice. Moreover, there is a dearth of information on validation of these emerging prostate biomarkers within African cohorts, despite the huge burden and aggressiveness of prostate cancer in men of African descent. This review focusses of the global landmark achievements in prostate cancer proteomics biomarker discovery and the potential for clinical implementation of these biomarkers in Africa. Biomarker validation processes at the preclinical, translational and clinical research level are discussed here, as are the challenges and prospects for the evaluation and use of novel proteomic prostate cancer biomarkers.

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

Biomarkers in Breast Cancer – An Update

PubMed Central

Schmidt, M.; Fasching, P. A.; Beckmann, M. W.; Kölbl, H.

2012-01-01

The therapy of choice for breast cancer patients requiring adjuvant chemo- or radiotherapy is increasingly guided by the principle of weighing the individual effectiveness of the therapy against the associated side effects. This has only been made possible by the discovery and validation of modern biomarkers. In the last decades and in the last few years some biomarkers have been integrated in clinical practice and a number have been included in modern study concepts. The importance of biomarkers lies not merely in their prognostic value indicating the future course of disease but also in their use to predict patient response to therapy. Due to the many subgroups, mathematical models and computer-assisted analysis are increasingly being used to assess the prognostic information obtained from established clinical and histopathological factors. In addition to describing some recent computer programmes this overview will focus on established molecular markers which have already been extensively validated in clinical practice and on new molecular markers identified by genome-wide studies. PMID:26640290

Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease.

PubMed

Lindholm, Daniel; Lindbäck, Johan; Armstrong, Paul W; Budaj, Andrzej; Cannon, Christopher P; Granger, Christopher B; Hagström, Emil; Held, Claes; Koenig, Wolfgang; Östlund, Ollie; Stewart, Ralph A H; Soffer, Joseph; White, Harvey D; de Winter, Robbert J; Steg, Philippe Gabriel; Siegbahn, Agneta; Kleber, Marcus E; Dressel, Alexander; Grammer, Tanja B; März, Winfried; Wallentin, Lars

2017-08-15

Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903). Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Drug designs fulfilling the requirements of clinical trials aiming at personalizing medicine

PubMed Central

Mandrekar, Sumithra J.; Sargent, Daniel J.

2014-01-01

In the current era of stratified medicine and biomarker-driven therapies, the focus has shifted from predictions based on the traditional anatomic staging systems to guide the choice of treatment for an individual patient to an integrated approach using the genetic makeup of the tumor and the genotype of the patient. The clinical trial designs utilized in the developmental pathway for biomarkers and biomarker-directed therapies from discovery to clinical practice are rapidly evolving. While several issues need careful consideration, two critical issues that surround the validation of biomarkers are the choice of the clinical trial design (which is based on the strength of the preliminary evidence and marker prevalence), and biomarker assay related issues surrounding the marker assessment methods such as the reliability and reproducibility of the assay. In this review, we focus on trial designs aiming at personalized medicine in the context of early phase trials for initial marker validation, as well as in the context of larger definitive trials. Designs for biomarker validation are broadly classified as retrospective (i.e., using data from previously well-conducted randomized controlled trials (RCTs) versus prospective (enrichment, all-comers, hybrid or adaptive). We believe that the systematic evaluation and implementation of these design strategies are essential to accelerate the clinical validation of biomarker guided therapy. PMID:25414851

Impact of cerebro-spinal fluid biomarkers of Alzheimer's disease in clinical practice: a multicentric study.

PubMed

Mouton-Liger, François; Wallon, David; Troussière, Anne-Cécile; Yatimi, Rachida; Dumurgier, Julien; Magnin, Eloi; de la Sayette, Vincent; Duron, Emannuelle; Philippi, Nathalie; Beaufils, Emilie; Gabelle, Audrey; Croisile, Bernard; Robert, Philippe; Pasquier, Florence; Hannequin, Didier; Hugon, Jacques; Paquet, Claire

2014-01-01

CSF biomarkers of Alzheimer's disease are well validated in clinical research; however, their pragmatic utility in daily practice is still unappreciated. These biomarkers are used in routine practice according to Health Authority Recommendations. In 604 consecutive patients explored for cognitive disorders, questionnaires were prospectively proposed and filled. Before and after CSF biomarker results, clinicians provided a diagnosis and an estimate of their diagnostic confidence. Analysis has compared the frequency of diagnosis before and after CSF biomarker results using the net reclassification improvement (NRI) method. We have evaluated external validity comparing with data of French Bank National of AD (BNA). A total of 561 patients [Alzheimer's disease (AD), n = 253; non-AD, n = 308] were included (mean age, 68.6 years; women, 52 %). Clinically suspected diagnosis and CSF results were concordant in 65.2 % of cases. When clinical hypothesis and biological results were discordant, a reclassification occurred in favour of CSF biomarkers results in 76.9 %. The NRI was 39.5 %. In addition, the results show a statistically significant improvement in clinician confidence for their diagnosis. In comparison with BNA data, patients were younger and more frequently diagnosed with AD. Clinicians tend to heavily rely on the CSF AD biomarkers results and are more confident in their diagnoses using CSF AD biomarkers. Thus, these biomarkers appear as a key tool in clinical practice.

Proteomics as a Tool for Biomarker Discovery

PubMed Central

Kohn, Elise C.; Azad, Nilofer; Annunziata, Christina; Dhamoon, Amit S.; Whiteley, Gordon

2007-01-01

Novel technologies are now being advanced for the purpose of identification and validation of new disease biomarkers. A reliable and useful clinical biomarker must a) come from a readily attainable source, such as blood or urine, b) have sufficient sensitivity to correctly identify affected individuals, c) have sufficient specificity to avoid incorrect labeling of unaffected persons, and d) result in a notable benefit for the patient through intervention, such as survival or life quality improvement. Despite these critical descriptors, the few available FDA-approved biomarkers for cancer do not completely fit this definition and their benefits are limited to a small number of cancers. Ovarian cancer exemplifies the need for a diagnostic biomarker of early stage disease. Symptoms are present but not specific to the disease, delaying diagnosis until an advanced and generally incurable stage in over 70% of affected women. As such, diagnostic intervention in the form of oopherectomy can be performed in the appropriate at-risk population if identified such as with a new accurate, sensitive, and specific biomarker. If early stage disease is identified, the requirement for survival and life quality improvement will be met. One of the new technologies applied to biomarker discovery is tour-de-force analysis of serum peptides and proteins. Optimization of mass spectrometry techniques coupled with advanced bioinformatics approaches has yielded informative biomarker signatures discriminating presence of cancer from unaffected in multiple studies from different groups. Validation and randomized outcome studies are needed to determine the true value of these new biomarkers in early diagnosis, and improved survival and quality of life. PMID:18057524

Role of metabolism and viruses in aflatoxin-induced liver cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Groopman, John D.; Kensler, Thomas W.

The use of biomarkers in molecular epidemiology studies for identifying stages in the progression of development of the health effects of environmental agents has the potential for providing important information for critical regulatory, clinical and public health problems. Investigations of aflatoxins probably represent one of the most extensive data sets in the field and this work may serve as a template for future studies of other environmental agents. The aflatoxins are naturally occurring mycotoxins found on foods such as corn, peanuts, various other nuts and cottonseed and they have been demonstrated to be carcinogenic in many experimental models. As amore » result of nearly 30 years of study, experimental data and epidemiological studies in human populations, aflatoxin B{sub 1} was classified as carcinogenic to humans by the International Agency for Research on Cancer. The long-term goal of the research described herein is the application of biomarkers to the development of preventative interventions for use in human populations at high-risk for cancer. Several of the aflatoxin-specific biomarkers have been validated in epidemiological studies and are now being used as intermediate biomarkers in prevention studies. The development of these aflatoxin biomarkers has been based upon the knowledge of the biochemistry and toxicology of aflatoxins gleaned from both experimental and human studies. These biomarkers have subsequently been utilized in experimental models to provide data on the modulation of these markers under different situations of disease risk. This systematic approach provides encouragement for preventive interventions and should serve as a template for the development, validation and application of other chemical-specific biomarkers to cancer or other chronic diseases.« less

Standard Specimen Reference Set: Lung — EDRN Public Portal

Cancer.gov

The NCI/EDRN/SPORE Lung Cancer Biomarkers Group (LCBG) began its activities back in November 2004 and developed clear objectives and strategies on how to begin validating a series of candidate biomarkers for the early detection of lung cancer. The initial goal of the LCBG is to develop the requisite sample resources to validate serum/plasma biomarkers for the early diagnosis of lung cancer. Researchers may use these resources and process for continued biomarker refinement but this is not the primary activity of the LCBG.

Derivation and validation of a two-biomarker panel for diagnosis of ARDS in patients with severe traumatic injuries

PubMed Central

Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S

2017-01-01

Background Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Methods Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Results Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). Discussion A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Level of evidence Diagnostic study, level II. PMID:29766112

Derivation and validation of a two-biomarker panel for diagnosis of ARDS in patients with severe traumatic injuries.

PubMed

Ware, Lorraine B; Zhao, Zhiguo; Koyama, Tatsuki; Brown, Ryan M; Semler, Matthew W; Janz, David R; May, Addison K; Fremont, Richard D; Matthay, Michael A; Cohen, Mitchell J; Calfee, Carolyn S

2017-01-01

Acute respiratory distress syndrome (ARDS) is common after severe traumatic injuries but is underdiagnosed and undertreated. We hypothesized that a panel of plasma biomarkers could be used to diagnose ARDS in severe trauma. To test this hypothesis, we derived and validated a biomarker panel in three independent cohorts and compared the diagnostic performance to clinician recognition of ARDS. Eleven plasma biomarkers of inflammation, lung epithelial and endothelial injury were measured in a derivation cohort of 439 severe trauma patients. ARDS status was analyzed by two-investigator consensus, and cases were required to meet Berlin criteria on intensive care unit (ICU) day 1. Controls were subjects without ARDS during the first 4 days of study enrollment. A multivariable logistic regression model was used to generate probabilities for ARDS. A reduced model with the top two performing markers was then tested in two independent validation cohorts. To assess clinical diagnosis of ARDS, medical records in the derivation cohort were systematically searched for documentation of ARDS diagnosis made by a clinical provider. Among 11 biomarkers, the combination of the endothelial injury marker angiopoietin-2 (Ang-2) and the lung epithelial injury marker receptor for advanced glycation endproducts (RAGE) provided good discrimination for ARDS in the derivation cohort (area under the curve (AUC)=0.74 (95% CI 0.67 to 0.80). In the validation cohorts, the AUCs for this model were 0.70 (0.61 to 0.77) and 0.78 (0.71 to 0.84). In contrast, provider assessment demonstrated poor diagnostic accuracy for ARDS, with AUC of 0.55 (0.51 to 0.60). A two-biomarker panel consisting of Ang-2 and RAGE performed well across multiple patient cohorts and outperformed clinical providers for diagnosing ARDS in severe trauma. Clinical application of this model could improve both diagnosis and treatment of ARDS in patients with severe trauma. Diagnostic study, level II.

Electrophysiological biomarkers of epileptogenicity after traumatic brain injury.

PubMed

Perucca, Piero; Smith, Gregory; Santana-Gomez, Cesar; Bragin, Anatol; Staba, Richard

2018-06-05

Post-traumatic epilepsy is the architype of acquired epilepsies, wherein a brain insult initiates an epileptogenic process culminating in an unprovoked seizure after weeks, months or years. Identifying biomarkers of such process is a prerequisite for developing and implementing targeted therapies aimed at preventing the development of epilepsy. Currently, there are no validated electrophysiological biomarkers of post-traumatic epileptogenesis. Experimental EEG studies using the lateral fluid percussion injury model have identified three candidate biomarkers of post-traumatic epileptogenesis: pathological high-frequency oscillations (HFOs, 80-300 Hz); repetitive HFOs and spikes (rHFOSs); and reduction in sleep spindle duration and dominant frequency at the transition from stage III to rapid eye movement sleep. EEG studies in humans have yielded conflicting data; recent evidence suggests that epileptiform abnormalities detected acutely after traumatic brain injury carry a significantly increased risk of subsequent epilepsy. Well-designed studies are required to validate these promising findings, and ultimately establish whether there are post-traumatic electrophysiological features which can guide the development of 'antiepileptogenic' therapies. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

Ebadi, Maryam; Mazurak, Vera C

2015-01-01

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

Validation of biomarkers to predict response to immunotherapy in cancer: Volume I - pre-analytical and analytical validation.

PubMed

Masucci, Giuseppe V; Cesano, Alessandra; Hawtin, Rachael; Janetzki, Sylvia; Zhang, Jenny; Kirsch, Ilan; Dobbin, Kevin K; Alvarez, John; Robbins, Paul B; Selvan, Senthamil R; Streicher, Howard Z; Butterfield, Lisa H; Thurin, Magdalena

2016-01-01

Immunotherapies have emerged as one of the most promising approaches to treat patients with cancer. Recently, there have been many clinical successes using checkpoint receptor blockade, including T cell inhibitory receptors such as cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and programmed cell death-1 (PD-1). Despite demonstrated successes in a variety of malignancies, responses only typically occur in a minority of patients in any given histology. Additionally, treatment is associated with inflammatory toxicity and high cost. Therefore, determining which patients would derive clinical benefit from immunotherapy is a compelling clinical question. Although numerous candidate biomarkers have been described, there are currently three FDA-approved assays based on PD-1 ligand expression (PD-L1) that have been clinically validated to identify patients who are more likely to benefit from a single-agent anti-PD-1/PD-L1 therapy. Because of the complexity of the immune response and tumor biology, it is unlikely that a single biomarker will be sufficient to predict clinical outcomes in response to immune-targeted therapy. Rather, the integration of multiple tumor and immune response parameters, such as protein expression, genomics, and transcriptomics, may be necessary for accurate prediction of clinical benefit. Before a candidate biomarker and/or new technology can be used in a clinical setting, several steps are necessary to demonstrate its clinical validity. Although regulatory guidelines provide general roadmaps for the validation process, their applicability to biomarkers in the cancer immunotherapy field is somewhat limited. Thus, Working Group 1 (WG1) of the Society for Immunotherapy of Cancer (SITC) Immune Biomarkers Task Force convened to address this need. In this two volume series, we discuss pre-analytical and analytical (Volume I) as well as clinical and regulatory (Volume II) aspects of the validation process as applied to predictive biomarkers for cancer immunotherapy. To illustrate the requirements for validation, we discuss examples of biomarker assays that have shown preliminary evidence of an association with clinical benefit from immunotherapeutic interventions. The scope includes only those assays and technologies that have established a certain level of validation for clinical use (fit-for-purpose). Recommendations to meet challenges and strategies to guide the choice of analytical and clinical validation design for specific assays are also provided.

Reverse-translational biomarker validation of Abnormal Repetitive Behaviors in mice: an illustration of the 4P's modeling approach.

PubMed

Garner, Joseph P; Thogerson, Collette M; Dufour, Brett D; Würbel, Hanno; Murray, James D; Mench, Joy A

2011-06-01

The NIMH's new strategic plan, with its emphasis on the "4P's" (Prediction, Pre-emption, Personalization, and Populations) and biomarker-based medicine requires a radical shift in animal modeling methodology. In particular 4P's models will be non-determinant (i.e. disease severity will depend on secondary environmental and genetic factors); and validated by reverse-translation of animal homologues to human biomarkers. A powerful consequence of the biomarker approach is that different closely related disorders have a unique fingerprint of biomarkers. Animals can be validated as a highly specific model of a single disorder by matching this 'fingerprint'; or as a model of a symptom seen in multiple disorders by matching common biomarkers. Here we illustrate this approach with two Abnormal Repetitive Behaviors (ARBs) in mice: stereotypies and barbering (hair pulling). We developed animal versions of the neuropsychological biomarkers that distinguish human ARBs, and tested the fingerprint of the different mouse ARBs. As predicted, the two mouse ARBs were associated with different biomarkers. Both barbering and stereotypy could be discounted as models of OCD (even though they are widely used as such), due to the absence of limbic biomarkers which are characteristic of OCD and hence are necessary for a valid model. Conversely barbering matched the fingerprint of trichotillomania (i.e. selective deficits in set-shifting), suggesting it may be a highly specific model of this disorder. In contrast stereotypies were correlated only with a biomarker (deficits in response shifting) correlated with stereotypies in multiple disorders, suggesting that animal stereotypies model stereotypies in multiple disorders. Copyright © 2011 Elsevier B.V. All rights reserved.

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges.

PubMed

Root, Alex; Allen, Peter; Tempst, Paul; Yu, Kenneth

2018-03-07

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary cooperation within the PDAC community is poised to confront it.

Di-22:6-bis(monoacylglycerol)phosphate: A clinical biomarker of drug-induced phospholipidosis for drug development and safety assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Nanjun; Tengstrand, Elizabeth A.; Chourb, Lisa

The inability to routinely monitor drug-induced phospholipidosis (DIPL) presents a challenge in pharmaceutical drug development and in the clinic. Several nonclinical studies have shown di-docosahexaenoyl (22:6) bis(monoacylglycerol) phosphate (di-22:6-BMP) to be a reliable biomarker of tissue DIPL that can be monitored in the plasma/serum and urine. The aim of this study was to show the relevance of di-22:6-BMP as a DIPL biomarker for drug development and safety assessment in humans. DIPL shares many similarities with the inherited lysosomal storage disorder Niemann–Pick type C (NPC) disease. DIPL and NPC result in similar changes in lysosomal function and cholesterol status that leadmore » to the accumulation of multi-lamellar bodies (myeloid bodies) in cells and tissues. To validate di-22:6-BMP as a biomarker of DIPL for clinical studies, NPC patients and healthy donors were classified by receiver operator curve analysis based on urinary di-22:6-BMP concentrations. By showing 96.7-specificity and 100-sensitivity to identify NPC disease, di-22:6-BMP can be used to assess DIPL in human studies. The mean concentration of di-22:6-BMP in the urine of NPC patients was 51.4-fold (p ≤ 0.05) above the healthy baseline range. Additionally, baseline levels of di-22:6-BMP were assessed in healthy non-medicated laboratory animals (rats, mice, dogs, and monkeys) and human subjects to define normal reference ranges for nonclinical/clinical studies. The baseline ranges of di-22:6-BMP in the plasma, serum, and urine of humans and laboratory animals were species dependent. The results of this study support the role of di-22:6-BMP as a biomarker of DIPL for pharmaceutical drug development and health care settings. - Highlights: • A reliable biomarker of drug-induced phospholipidosis (DIPL) is needed for humans. • Di-22:6-BMP is specific/sensitive for DIPL in animals as published in literatures. • The di-22:6-BMP biomarker can be validated for humans via NPC patients. • DIPL shares morphologic/mechanistic similarities with Niemann–Pick type C disease. • Di-22:6-BMP is an effective DIPL biomarker in humans via NPC patient validation.« less

Development and validation of a prognostic model using blood biomarker information for prediction of survival of non-small-cell lung cancer patients treated with combined chemotherapy and radiation or radiotherapy alone (NCT00181519, NCT00573040, and NCT00572325).

PubMed

Dehing-Oberije, Cary; Aerts, Hugo; Yu, Shipeng; De Ruysscher, Dirk; Menheere, Paul; Hilvo, Mika; van der Weide, Hiska; Rao, Bharat; Lambin, Philippe

2011-10-01

Currently, prediction of survival for non-small-cell lung cancer patients treated with (chemo)radiotherapy is mainly based on clinical factors. The hypothesis of this prospective study was that blood biomarkers related to hypoxia, inflammation, and tumor load would have an added prognostic value for predicting survival. Clinical data and blood samples were collected prospectively (NCT00181519, NCT00573040, and NCT00572325) from 106 inoperable non-small-cell lung cancer patients (Stages I-IIIB), treated with curative intent with radiotherapy alone or combined with chemotherapy. Blood biomarkers, including lactate dehydrogenase, C-reactive protein, osteopontin, carbonic anhydrase IX, interleukin (IL) 6, IL-8, carcinoembryonic antigen (CEA), and cytokeratin fragment 21-1, were measured. A multivariate model, built on a large patient population (N = 322) and externally validated, was used as a baseline model. An extended model was created by selecting additional biomarkers. The model's performance was expressed as the area under the curve (AUC) of the receiver operating characteristic and assessed by use of leave-one-out cross validation as well as a validation cohort (n = 52). The baseline model consisted of gender, World Health Organization performance status, forced expiratory volume, number of positive lymph node stations, and gross tumor volume and yielded an AUC of 0.72. The extended model included two additional blood biomarkers (CEA and IL-6) and resulted in a leave-one-out AUC of 0.81. The performance of the extended model was significantly better than the clinical model (p = 0.004). The AUC on the validation cohort was 0.66 and 0.76, respectively. The performance of the prognostic model for survival improved markedly by adding two blood biomarkers: CEA and IL-6. Copyright © 2011 Elsevier Inc. All rights reserved.

Clinical trial designs for testing biomarker-based personalized therapies

PubMed Central

Lai, Tze Leung; Lavori, Philip W; Shih, Mei-Chiung I; Sikic, Branimir I

2014-01-01

Background Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations. Methods We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature. Results Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power. Limitations The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to ‘standard of care’, such as physician’s choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to ‘standard of care’. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties. Conclusion Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies. PMID:22397801

Reliability and Validity of Food Frequency Questionnaire and Nutrient Biomarkers in Elders With and Without Mild Cognitive Impairment

PubMed Central

Bowman, Gene L.; Shannon, Jackilen; Ho, Emily; Traber, Maret G.; Frei, Balz; Oken, Barry S.; Kaye, Jeffery A.; Quinn, Joseph F.

2010-01-01

Introduction There is great interest in nutritional strategies for the prevention of age-related cognitive decline, yet the best methods for nutritional assessment in populations at risk for dementia are still evolving. Our study objective was to test the reliability and validity of two common nutritional assessments (plasma nutrient biomarkers and Food Frequency Questionnaire) in people at risk for dementia. Methods Thirty-eight elders, half with amnestic -Mild Cognitive Impairment and half with intact cognition were recruited. Nutritional assessments were collected together at baseline and again at 1 month. Intraclass and Pearson correlation coefficients quantified reliability and validity. Results Twenty-six nutrients were examined and reliability was very good or better for 77% (20/26, ICC ≥ .75) of the plasma nutrient biomarkers and for 88% of the FFQ estimates. Twelve of the plasma nutrient estimates were as reliable as the commonly measured plasma cholesterol (ICC=.92). FFQ and plasma long-chain fatty acids (docosahexaenoic acid, r =.39, eicosapentaenoic acid, r = .39) and carotenoids (α-carotene, r =.49; lutein + zeaxanthin, r = .48; β-carotene, r = .43; β-cryptoxanthin, r = .41) were correlated, but no other FFQ estimates correlated with respective nutrient biomarkers. Correlations between FFQ and plasma fatty acids and carotenoids were significantly stronger after removing subjects with MCI. Conclusion The reliability and validity of plasma and FFQ nutrient estimates vary according to the nutrient of interest. Memory deficit attenuates FFQ estimate validity and inflates FFQ estimate reliability. Many plasma nutrient biomarkers have very good reliability over 1-month regardless of memory state. This method can circumvent sources of error seen in other less direct methods of nutritional assessment. PMID:20856100

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

PubMed

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G; Treviño, Victor

2013-01-01

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

SurvExpress: An Online Biomarker Validation Tool and Database for Cancer Gene Expression Data Using Survival Analysis

PubMed Central

Aguirre-Gamboa, Raul; Gomez-Rueda, Hugo; Martínez-Ledesma, Emmanuel; Martínez-Torteya, Antonio; Chacolla-Huaringa, Rafael; Rodriguez-Barrientos, Alberto; Tamez-Peña, José G.; Treviño, Victor

2013-01-01

Validation of multi-gene biomarkers for clinical outcomes is one of the most important issues for cancer prognosis. An important source of information for virtual validation is the high number of available cancer datasets. Nevertheless, assessing the prognostic performance of a gene expression signature along datasets is a difficult task for Biologists and Physicians and also time-consuming for Statisticians and Bioinformaticians. Therefore, to facilitate performance comparisons and validations of survival biomarkers for cancer outcomes, we developed SurvExpress, a cancer-wide gene expression database with clinical outcomes and a web-based tool that provides survival analysis and risk assessment of cancer datasets. The main input of SurvExpress is only the biomarker gene list. We generated a cancer database collecting more than 20,000 samples and 130 datasets with censored clinical information covering tumors over 20 tissues. We implemented a web interface to perform biomarker validation and comparisons in this database, where a multivariate survival analysis can be accomplished in about one minute. We show the utility and simplicity of SurvExpress in two biomarker applications for breast and lung cancer. Compared to other tools, SurvExpress is the largest, most versatile, and quickest free tool available. SurvExpress web can be accessed in http://bioinformatica.mty.itesm.mx/SurvExpress (a tutorial is included). The website was implemented in JSP, JavaScript, MySQL, and R. PMID:24066126

Evaluation of pathogen-specific biomarkers for the diagnosis of tuberculosis in white-tailed deer (Odocoileus virginianus)

USDA-ARS?s Scientific Manuscript database

Objective - To develop a noninvasive biomarker based Mycobacterium bovis specific detection system to track infection in domestic and wild animals. Design – Experimental longitudinal study for discovery and cross sectional design for validation Animals - Yearling white-tailed deer fawns (n=8) were ...

A Multiplexed Serum Biomarker Immunoassay Panel Discriminates Clinical Lung Cancer Patients from High-Risk Individuals Found to be Cancer-Free by CT Screening

PubMed Central

Bigbee, William L.; Gopalakrishnan, Vanathi; Weissfeld, Joel L.; Wilson, David O.; Dacic, Sanja; Lokshin, Anna E.; Siegfried, Jill M.

2012-01-01

Introduction Clinical decision-making in the setting of CT screening could benefit from accessible biomarkers that help predict the level of lung cancer risk in high-risk individuals with indeterminate pulmonary nodules. Methods To identify candidate serum biomarkers, we measured 70 cancer-related proteins by Luminex xMAP® multiplexed immunoassays in a training set of sera from 56 patients with biopsy-proven primary non small cell lung cancer and 56 age-, sex- and smoking-matched CT-screened controls. Results We identified a panel of 10 serum biomarkers – prolactin, transthyretin, thrombospondin-1, E-selectin, C-C motif chemokine 5, macrophage migration inhibitory factor, plasminogen activator inhibitor, receptor tyrosine-protein kinase, Cyfra 21.1, and serum amyloid A – that distinguished lung cancer from controls with an estimated balanced accuracy (average of sensitivity and specificity) of 76.0%±3.8% from 20-fold internal cross-validation. We then iteratively evaluated this model in independent test and verification case/control studies confirming the initial classification performance of the panel. The classification performance of the 10-biomarker panel was also analytically validated using ELISAs in a second independent case/control population further validating the robustness of the panel. Conclusions The performance of this 10-biomarker panel based model was 77.1% sensitivity/76.2% specificity in cross-validation in the expanded training set, 73.3% sensitivity/93.3% specificity (balanced accuracy 83.3%) in the blinded verification set with the best discriminative performance in Stage I/II cases: 85% sensitivity (balanced accuracy 89.2%). Importantly, the rate of misclassification of CT-screened controls was not different in most control subgroups with or without airflow obstruction or emphysema or pulmonary nodules. These biomarkers have potential to aid in the early detection of lung cancer and more accurate interpretation of indeterminate pulmonary nodules detected by screening CT. PMID:22425918

MRM for the verification of cancer biomarker proteins: recent applications to human plasma and serum.

PubMed

Chambers, Andrew G; Percy, Andrew J; Simon, Romain; Borchers, Christoph H

2014-04-01

Accurate cancer biomarkers are needed for early detection, disease classification, prediction of therapeutic response and monitoring treatment. While there appears to be no shortage of candidate biomarker proteins, a major bottleneck in the biomarker pipeline continues to be their verification by enzyme linked immunosorbent assays. Multiple reaction monitoring (MRM), also known as selected reaction monitoring, is a targeted mass spectrometry approach to protein quantitation and is emerging to bridge the gap between biomarker discovery and clinical validation. Highly multiplexed MRM assays are readily configured and enable simultaneous verification of large numbers of candidates facilitating the development of biomarker panels which can increase specificity. This review focuses on recent applications of MRM to the analysis of plasma and serum from cancer patients for biomarker verification. The current status of this approach is discussed along with future directions for targeted mass spectrometry in clinical biomarker validation.

Potential protein biomarkers for burning mouth syndrome discovered by quantitative proteomics

PubMed Central

Ji, Eoon Hye; Diep, Cynthia; Liu, Tong; Li, Hong; Merrill, Robert; Messadi, Diana

2017-01-01

Burning mouth syndrome (BMS) is a chronic pain disorder characterized by severe burning sensation in normal looking oral mucosa. Diagnosis of BMS remains to be a challenge to oral healthcare professionals because the method for definite diagnosis is still uncertain. In this study, a quantitative saliva proteomic analysis was performed in order to identify target proteins in BMS patients’ saliva that may be used as biomarkers for simple, non-invasive detection of the disease. By using isobaric tags for relative and absolute quantitation labeling and liquid chromatography-tandem mass spectrometry to quantify 1130 saliva proteins between BMS patients and healthy control subjects, we found that 50 proteins were significantly changed in the BMS patients when compared to the healthy control subjects (p ≤ 0.05, 39 up-regulated and 11 down-regulated). Four candidates, alpha-enolase, interleukin-18 (IL-18), kallikrein-13 (KLK13), and cathepsin G, were selected for further validation. Based on enzyme-linked immunosorbent assay measurements, three potential biomarkers, alpha-enolase, IL-18, and KLK13, were successfully validated. The fold changes for alpha-enolase, IL-18, and KLK13 were determined as 3.6, 2.9, and 2.2 (burning mouth syndrome vs. control), and corresponding receiver operating characteristic values were determined as 0.78, 0.83, and 0.68, respectively. Our findings indicate that testing of the identified protein biomarkers in saliva might be a valuable clinical tool for BMS detection. Further validation studies of the identified biomarkers or additional candidate biomarkers are needed to achieve a multi-marker prediction model for improved detection of BMS with high sensitivity and specificity. PMID:28326926

Detection of an endogenous urinary biomarker associated with CYP2D6 activity using global metabolomics.

PubMed

Tay-Sontheimer, Jessica; Shireman, Laura M; Beyer, Richard P; Senn, Taurence; Witten, Daniela; Pearce, Robin E; Gaedigk, Andrea; Gana Fomban, Cletus L; Lutz, Justin D; Isoherranen, Nina; Thummel, Kenneth E; Fiehn, Oliver; Leeder, J Steven; Lin, Yvonne S

2014-12-01

We sought to discover endogenous urinary biomarkers of human CYP2D6 activity. Healthy pediatric subjects (n = 189) were phenotyped using dextromethorphan and randomized for candidate biomarker selection and validation. Global urinary metabolomics was performed using liquid chromatography quadrupole time-of-flight mass spectrometry. Candidate biomarkers were tested in adults receiving fluoxetine, a CYP2D6 inhibitor. A biomarker, M1 (m/z 444.3102) was correlated with CYP2D6 activity in both the pediatric training and validation sets. Poor metabolizers had undetectable levels of M1, whereas it was present in subjects with other phenotypes. In adult subjects, a 9.56-fold decrease in M1 abundance was observed during CYP2D6 inhibition. Identification and validation of M1 may provide a noninvasive means of CYP2D6 phenotyping.

Effects of dietary restriction on adipose mass and biomarkers of healthy aging in human.

PubMed

Lettieri-Barbato, Daniele; Giovannetti, Esmeralda; Aquilano, Katia

2016-11-29

In developing countries the rise of obesity and obesity-related metabolic disorders, such as cardiovascular diseases and type 2 diabetes, reflects the changes in lifestyle habits and wrong dietary choices. Dietary restriction (DR) regimens have been shown to extend health span and lifespan in many animal models including primates. Identifying biomarkers predictive of clinical benefits of treatment is one of the primary goals of precision medicine. To monitor the clinical outcomes of DR interventions in humans, several biomarkers are commonly adopted. However, a validated link between the behaviors of such biomarkers and DR effects is lacking at present time. Through a systematic analysis of human intervention studies, we evaluated the effect size of DR (i.e. calorie restriction, very low calorie diet, intermittent fasting, alternate day fasting) on health-related biomarkers. We found that DR is effective in reducing total and visceral adipose mass and improving inflammatory cytokines profile and adiponectin/leptin ratio. By analysing the levels of canonical biomarkers of healthy aging, we also validated the changes of insulin, IGF-1 and IGFBP-1,2 to monitor DR effects. Collectively, we developed a useful platform to evaluate the human responses to dietary regimens low in calories.

Time-dependent classification accuracy curve under marker-dependent sampling.

PubMed

Zhu, Zhaoyin; Wang, Xiaofei; Saha-Chaudhuri, Paramita; Kosinski, Andrzej S; George, Stephen L

2016-07-01

Evaluating the classification accuracy of a candidate biomarker signaling the onset of disease or disease status is essential for medical decision making. A good biomarker would accurately identify the patients who are likely to progress or die at a particular time in the future or who are in urgent need for active treatments. To assess the performance of a candidate biomarker, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) are commonly used. In many cases, the standard simple random sampling (SRS) design used for biomarker validation studies is costly and inefficient. In order to improve the efficiency and reduce the cost of biomarker validation, marker-dependent sampling (MDS) may be used. In a MDS design, the selection of patients to assess true survival time is dependent on the result of a biomarker assay. In this article, we introduce a nonparametric estimator for time-dependent AUC under a MDS design. The consistency and the asymptotic normality of the proposed estimator is established. Simulation shows the unbiasedness of the proposed estimator and a significant efficiency gain of the MDS design over the SRS design. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Oxidative stress-related biomarkers in essential hypertension and ischemia-reperfusion myocardial damage.

PubMed

Rodrigo, Ramón; Libuy, Matías; Feliú, Felipe; Hasson, Daniel

2013-01-01

Cardiovascular diseases are a leading cause of mortality and morbidity worldwide, with hypertension being a major risk factor. Numerous studies support the contribution of reactive oxygen and nitrogen species in the pathogenesis of hypertension, as well as other pathologies associated with ischemia/reperfusion. However, the validation of oxidative stress-related biomarkers in these settings is still lacking and novel association of these biomarkers and other biomarkers such as endothelial progenitor cells, endothelial microparticles, and ischemia modified albumin, is just emerging. Oxidative stress has been suggested as a pathogenic factor and therapeutic target in early stages of essential hypertension. Systolic and diastolic blood pressure correlated positively with plasma F2-isoprostane levels and negatively with total antioxidant capacity of plasma in hypertensive and normotensive patients. Cardiac surgery with extracorporeal circulation causes an ischemia/reperfusion event associated with increased lipid peroxidation and protein carbonylation, two biomarkers associated with oxidative damage of cardiac tissue. An enhancement of the antioxidant defense system should contribute to ameliorating functional and structural abnormalities derived from this metabolic impairment. However, data have to be validated with the analysis of the appropriate oxidative stress and/or nitrosative stress biomarkers.

Angiopoietin-1, Angiopoietin-2 and Bicarbonate as Diagnostic Biomarkers in Children with Severe Sepsis

PubMed Central

Wang, Kun; Bhandari, Vineet; Giuliano, John S.; O′Hern, Corey S.; Shattuck, Mark D.; Kirby, Michael

2014-01-01

Severe pediatric sepsis continues to be associated with high mortality rates in children. Thus, an important area of biomedical research is to identify biomarkers that can classify sepsis severity and outcomes. The complex and heterogeneous nature of sepsis makes the prospect of the classification of sepsis severity using a single biomarker less likely. Instead, we employ machine learning techniques to validate the use of a multiple biomarkers scoring system to determine the severity of sepsis in critically ill children. The study was based on clinical data and plasma samples provided by a tertiary care center's Pediatric Intensive Care Unit (PICU) from a group of 45 patients with varying sepsis severity at the time of admission. Canonical Correlation Analysis with the Forward Selection and Random Forests methods identified a particular set of biomarkers that included Angiopoietin-1 (Ang-1), Angiopoietin-2 (Ang-2), and Bicarbonate (HCO) as having the strongest correlations with sepsis severity. The robustness and effectiveness of these biomarkers for classifying sepsis severity were validated by constructing a linear Support Vector Machine diagnostic classifier. We also show that the concentrations of Ang-1, Ang-2, and HCO enable predictions of the time dependence of sepsis severity in children. PMID:25255212

An exploration into study design for biomarker identification: issues and recommendations.

PubMed

Hall, Jacqueline A; Brown, Robert; Paul, Jim

2007-01-01

Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.

A metabolomics approach to the identification of biomarkers of sugar-sweetened beverage intake.

PubMed

Gibbons, Helena; McNulty, Breige A; Nugent, Anne P; Walton, Janette; Flynn, Albert; Gibney, Michael J; Brennan, Lorraine

2015-03-01

The association between sugar-sweetened beverages (SSBs) and health risks remains controversial. To clarify proposed links, reliable and accurate dietary assessment methods of food intakes are essential. The aim of this present work was to use a metabolomics approach to identify a panel of urinary biomarkers indicative of SSB consumption from a national food consumption survey and subsequently validate this panel in an acute intervention study. Heat map analysis was performed to identify correlations between ¹H nuclear magnetic resonance (NMR) spectral regions and SSB intakes in participants of the National Adult Nutrition Survey (n = 565). Metabolites were identified and receiver operating characteristic (ROC) analysis was performed to assess sensitivity and specificity of biomarkers. The panel of biomarkers was validated in an acute study (n = 10). A fasting first-void urine sample and postprandial samples (2, 4, 6 h) were collected after SSB consumption. After NMR spectroscopic profiling of the urine samples, multivariate data analysis was applied. A panel of 4 biomarkers-formate, citrulline, taurine, and isocitrate-were identified as markers of SSB intake. This panel of biomarkers had an area under the curve of 0.8 for ROC analysis and a sensitivity and specificity of 0.7 and 0.8, respectively. All 4 biomarkers were identified in the SSB sample. After acute consumption of an SSB drink, all 4 metabolites increased in the urine. The present metabolomics-based strategy proved to be successful in the identification of SSB biomarkers. Future work will ascertain how to translate this panel of markers for use in nutrition epidemiology. © 2015 American Society for Nutrition.

Proteoglycan 4 is a diagnostic biomarker for COPD.

PubMed

Lee, Kang-Yun; Chuang, Hsiao-Chi; Chen, Tzu-Tao; Liu, Wen-Te; Su, Chien-Ling; Feng, Po-Hao; Chiang, Ling-Ling; Bien, Mauo-Ying; Ho, Shu-Chuan

2015-01-01

The measurement of C-reactive protein (CRP) to confirm the stability of COPD has been reported. However, CRP is a systemic inflammatory biomarker that is related to many other diseases. The objective of this study is to discover a diagnostic biomarker for COPD. Sixty-one subjects with COPD and 15 healthy controls (10 healthy non-smokers and 5 smokers) were recruited for a 1-year follow-up study. Data regarding the 1-year acute exacerbation frequency and changes in lung function were collected. CRP and the identified biomarkers were assessed in the validation COPD cohort patients and healthy subjects. Receiver operating characteristic values of CRP and the identified biomarkers were determined. A validation COPD cohort was used to reexamine the identified biomarker. Correlation of the biomarker with 1-year lung function decline was determined. Proteoglycan 4 (PRG4) was identified as a biomarker in COPD. The serum concentrations of PRG4 in COPD Global initiative for chronic Obstructive Lung Disease (GOLD) stages 1+2 and 3+4 were 10.29 ng/mL and 13.20 ng/mL, respectively; 4.99 ng/mL for healthy controls (P<0.05); and 4.49 ng/mL for healthy smokers (P<0.05). PRG4 was more sensitive and specific than CRP for confirming COPD severity and acute exacerbation frequency. There was no correlation between CRP and PRG4 levels, and PRG4 was negatively correlated with the 1-year change in predicted forced vital capacity percent (R (2)=0.91, P=0.013). PRG4 may be a biomarker for identification of severity in COPD. It was related to the 1-year forced vital capacity decline in COPD patients.

Group Sequential Testing of the Predictive Accuracy of a Continuous Biomarker with Unknown Prevalence

PubMed Central

Koopmeiners, Joseph S.; Feng, Ziding

2015-01-01

Group sequential testing procedures have been proposed as an approach to conserving resources in biomarker validation studies. Previously, Koopmeiners and Feng (2011) derived the asymptotic properties of the sequential empirical positive predictive value (PPV) and negative predictive value curves, which summarize the predictive accuracy of a continuous marker, under case-control sampling. A limitation of their approach is that the prevalence can not be estimated from a case-control study and must be assumed known. In this manuscript, we consider group sequential testing of the predictive accuracy of a continuous biomarker with unknown prevalence. First, we develop asymptotic theory for the sequential empirical PPV and NPV curves when the prevalence must be estimated, rather than assumed known in a case-control study. We then discuss how our results can be combined with standard group sequential methods to develop group sequential testing procedures and bias-adjusted estimators for the PPV and NPV curve. The small sample properties of the proposed group sequential testing procedures and estimators are evaluated by simulation and we illustrate our approach in the context of a study to validate a novel biomarker for prostate cancer. PMID:26537180

The novel biomarker-based ABC (age, biomarkers, clinical history)-bleeding risk score for patients with atrial fibrillation: a derivation and validation study.

PubMed

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Siegbahn, Agneta; Yusuf, Salim; Granger, Christopher B; Wallentin, Lars

2016-06-04

The benefit of oral anticoagulation in atrial fibrillation is based on a balance between reduction in ischaemic stroke and increase in major bleeding. We aimed to develop and validate a new biomarker-based risk score to improve the prognostication of major bleeding in patients with atrial fibrillation. We developed and internally validated a new biomarker-based risk score for major bleeding in 14,537 patients with atrial fibrillation randomised to apixaban versus warfarin in the ARISTOTLE trial and externally validated it in 8468 patients with atrial fibrillation randomised to dabigatran versus warfarin in the RE-LY trial. Plasma samples for determination of candidate biomarker concentrations were obtained at randomisation. Major bleeding events were centrally adjudicated. The predictive values of biomarkers and clinical variables were assessed with Cox regression models. The most important variables were included in the score with weights proportional to the model coefficients. The ARISTOTLE and RE-LY trials are registered with ClinicalTrials.gov, numbers NCT00412984 and NCT00262600, respectively. The most important predictors for major bleeding were the concentrations of the biomarkers growth differentiation factor-15 (GDF-15), high-sensitivity cardiac troponin T (cTnT-hs) and haemoglobin, age, and previous bleeding. The ABC-bleeding score (age, biomarkers [GDF-15, cTnT-hs, and haemoglobin], and clinical history [previous bleeding]) score yielded a higher c-index than the conventional HAS-BLED and the newer ORBIT scores for major bleeding in both the derivation cohort (0·68 [95% CI 0·66-0·70] vs 0·61 [0·59-0·63] vs 0·65 [0·62-0·67], respectively; ABC-bleeding vs HAS-BLED p<0·0001 and ABC-bleeding vs ORBIT p=0·0008). ABC-bleeding score also yielded a higher c-index score in the the external validation cohort (0·71 [95% CI 0·68-0·73] vs 0·62 [0·59-0·64] for HAS-BLED vs 0·68 [0·65-0·70] for ORBIT; ABC-bleeding vs HAS-BLED p<0·0001 and ABC-bleeding vs ORBIT p=0·0016). A modified ABC-bleeding score using alternative biomarkers (haematocrit, cTnI-hs, cystatin C, or creatinine clearance) also outperformed the HAS-BLED and ORBIT scores. The ABC-bleeding score, using age, history of bleeding, and three biomarkers (haemoglobin, cTn-hs, and GDF-15 or cystatin C/CKD-EPI) was internally and externally validated and calibrated in large cohorts of patients with atrial fibrillation receiving anticoagulation therapy. The ABC-bleeding score performed better than HAS-BLED and ORBIT scores and should be useful as decision support on anticoagulation treatment in patients with atrial fibrillation. BMS, Pfizer, Boehringer Ingelheim, Roche Diagnostics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pancreatic Reference Set Application: Ivan Blasutig-University of Toronto (2014) — EDRN Public Portal

Cancer.gov

The primary objective of this study is to independently validate a panel of serum biomarkers for the early detection of pancreatic ductal adenocarcinoma (PDAC). The biomarkers were identified in various discovery studies performed in our laboratory1-6. We hypothesize that our candidate biomarkers can be used as a panel that will perform better than CA19.9 alone for the early detection of PDAC. Such a panel has the potential to lead to improved patient outcomes by enabling patients to receive treatment as early as possible.

GLNE 003: Preliminary Validation of Biomarkers Predictive of Barrett’s Esophagus Progression to Dysplasia and Adenocarcinoma — EDRN Public Portal

Cancer.gov

   Recognizing that novel potential biomarkers are continually being identified and will need to be validated in a rapid, efficient, and scientifically rigorous manner, the NCI has made an enormous commitment to the development of a network that will facilitate biomarker development and validation in multiple organ sites. As part of the National Cancer Institute-funded Early Detection Research Network (EDRN), the Great Lakes-New England Clinical Epidemiological Center (GLNE CEC) proposes a research program that provides the structure for validating and discovering potential surrogate endpoint biomarkers (“biomarkers”). Although examples of such biomarkers are currently in clinical use (i.e. CEA, CA-125), there are limitations to all of them. Our consortium focuses specifically on gastrointestinal neoplasia.    There are three goals for this phase of the proposed research. 1. Establish the feasibility of measuring the biomarkers in a multi-center clinical trial. 2. Estimate the variance of the biomarkers in cohorts defined by sex, race, age and histologic diagnosis (non-Barrett’s controls, Barrett’s intestinal metaplasia, Barrett’s intestinal dysplasia [low and high-grade] and adenocarcinoma). 3. Determine if the distributions of the biomarkers differ significantly among patients with different histologic diagnoses.    In this protocol, biological samples will consist of serum, plasma, urine, and biopsies from Barrett’s esophagus (metaplasia, low and high-grade dysplasia) patients, from patients with esophageal adenocarcinoma, and from non-Barrett’s controls. Samples will be assayed for villin, p53, Hsp27, cyclooxygenase-2, and Cyclin D1. Samples will also be used for two biomarker discovery projects, one exploring genetic expression using genomic microarrays and a second using two-dimensional gene arrays to discover and characterize amplified proteins associated with esophageal carcinogenesis. Fifty subjects will

Potentials of single-cell biology in identification and validation of disease biomarkers.

PubMed

Niu, Furong; Wang, Diane C; Lu, Jiapei; Wu, Wei; Wang, Xiangdong

2016-09-01

Single-cell biology is considered a new approach to identify and validate disease-specific biomarkers. However, the concern raised by clinicians is how to apply single-cell measurements for clinical practice, translate the message of single-cell systems biology into clinical phenotype or explain alterations of single-cell gene sequencing and function in patient response to therapies. This study is to address the importance and necessity of single-cell gene sequencing in the identification and development of disease-specific biomarkers, the definition and significance of single-cell biology and single-cell systems biology in the understanding of single-cell full picture, the development and establishment of whole-cell models in the validation of targeted biological function and the figure and meaning of single-molecule imaging in single cell to trace intra-single-cell molecule expression, signal, interaction and location. We headline the important role of single-cell biology in the discovery and development of disease-specific biomarkers with a special emphasis on understanding single-cell biological functions, e.g. mechanical phenotypes, single-cell biology, heterogeneity and organization of genome function. We have reason to believe that such multi-dimensional, multi-layer, multi-crossing and stereoscopic single-cell biology definitely benefits the discovery and development of disease-specific biomarkers. © 2016 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Inter-individual variation in expression: a missing link in biomarker biology?

PubMed

Little, Peter F R; Williams, Rohan B H; Wilkins, Marc R

2009-01-01

The past decade has seen an explosion of variation data demonstrating that diversity of both protein-coding sequences and of regulatory elements of protein-coding genes is common and of functional importance. In this article, we argue that genetic diversity can no longer be ignored in studies of human biology, even research projects without explicit genetic experimental design, and that this knowledge can, and must, inform research. By way of illustration, we focus on the potential role of genetic data in case-control studies to identify and validate cancer protein biomarkers. We argue that a consideration of genetics, in conjunction with proteomic biomarker discovery projects, should improve the proportion of biomarkers that can accurately classify patients.

Utility of the Department of Defense Serum Repository in Assessing Deployment Exposure.

PubMed

Lushniak, Boris; Mallon, Col Timothy M; Gaydos, Joel C; Smith, David J

2016-08-01

This paper describes why the research project was conducted in terms of demonstrating the utility of the Department of Defense Serum Repository in addressing deployment environmental exposures. The history deployment exposure surveillance was reviewed and the rationale for developing validated biomarkers that were detected in sera in postdeployment samples and compared with nondeployed controls was described. The goal was to find validated biomarkers that are associated with both exposures and health outcomes. The articles in this supplement described novel serum biomarkers that were found to be associated with deployment exposures and weakly associated with some health outcomes. Future research must continue to validate the use of serum biomarkers when operational contingencies prevent the gold standard collection of real-time breathing zone samples in deployed service members.

Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment.

PubMed

Levey, D F; Niculescu, E M; Le-Niculescu, H; Dainton, H L; Phalen, P L; Ladd, T B; Weber, H; Belanger, E; Graham, D L; Khan, F N; Vanipenta, N P; Stage, E C; Ballew, A; Yard, M; Gelbart, T; Shekhar, A; Schork, N J; Kurian, S M; Sandusky, G E; Salomon, D R; Niculescu, A B

2016-06-01

Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We then showed how the clinical information apps combined with the 50 validated biomarkers into a broad predictor (UP-Suicide), our apriori primary end point, predicts suicidality in women. UP-Suicide had a receiver-operating characteristic (ROC) area under the curve (AUC) of 82% for predicting SI and an AUC of 78% for predicting future hospitalizations for suicidality. Some of the individual components of the UP-Suicide showed even better results. SASS had an AUC of 81% for predicting SI, CFI-S had an AUC of 84% and the combination of the two apps had an AUC of 87%. The top biomarker from our sequential discovery, prioritization and validation steps, BCL2, predicted future hospitalizations due to suicidality with an AUC of 89%, and the panel of 50 validated biomarkers (BioM-50) predicted future hospitalizations due to suicidality with an AUC of 94%. The best overall single blood biomarker for predictions was PIK3C3 with an AUC of 65% for SI and an AUC of 90% for future hospitalizations. Finally, we sought to understand the biology of the biomarkers. BCL2 and GSK3B, the top CFG scoring validated biomarkers, as well as PIK3C3, have anti-apoptotic and neurotrophic effects, are decreased in expression in suicidality and are known targets of the anti-suicidal mood stabilizer drug lithium, which increases their expression and/or activity. Circadian clock genes were overrepresented among the top markers. Notably, PER1, increased in expression in suicidality, had an AUC of 84% for predicting future hospitalizations, and CSNK1A1, decreased in expression, had an AUC of 96% for predicting future hospitalizations. Circadian clock abnormalities are related to mood disorder, and sleep abnormalities have been implicated in suicide. Docosahexaenoic acid signaling was one of the top biological pathways overrepresented in validated biomarkers, which is of interest given the potential therapeutic and prophylactic benefits of omega-3 fatty acids. Some of the top biomarkers from the current work in women showed co-directionality of change in expression with our previous work in men, whereas others had changes in opposite directions, underlying the issue of biological context and differences in suicidality between the two genders. With this study, we begin to shed much needed light in the area of female suicidality, identify useful objective predictors and help understand gender commonalities and differences. During the conduct of the study, one participant committed suicide. In retrospect, when the analyses were completed, her UP-Suicide risk prediction score was at the 100 percentile of all participants tested.

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

PubMed

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

2015-04-01

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

Leveraging Biospecimen Resources for Discovery or Validation of Markers for Early Cancer Detection

PubMed Central

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

2015-01-01

Validation of early detection cancer biomarkers has proven to be disappointing when initial promising claims have often not been reproducible in diagnostic samples or did not extend to prediagnostic samples. The previously reported lack of rigorous internal validity (systematic differences between compared groups) and external validity (lack of generalizability beyond compared groups) may be effectively addressed by utilizing blood specimens and data collected within well-conducted cohort studies. Cohort studies with prediagnostic specimens (eg, blood specimens collected prior to development of clinical symptoms) and clinical data have recently been used to assess the validity of some early detection biomarkers. With this background, the Division of Cancer Control and Population Sciences (DCCPS) and the Division of Cancer Prevention (DCP) of the National Cancer Institute (NCI) held a joint workshop in August 2013. The goal was to advance early detection cancer research by considering how the infrastructure of cohort studies that already exist or are being developed might be leveraged to include appropriate blood specimens, including prediagnostic specimens, ideally collected at periodic intervals, along with clinical data about symptom status and cancer diagnosis. Three overarching recommendations emerged from the discussions: 1) facilitate sharing of existing specimens and data, 2) encourage collaboration among scientists developing biomarkers and those conducting observational cohort studies or managing healthcare systems with cohorts followed over time, and 3) conduct pilot projects that identify and address key logistic and feasibility issues regarding how appropriate specimens and clinical data might be collected at reasonable effort and cost within existing or future cohorts. PMID:25688116

Urinary Sugars--A Biomarker of Total Sugars Intake.

PubMed

Tasevska, Natasha

2015-07-15

Measurement error in self-reported sugars intake may explain the lack of consistency in the epidemiologic evidence on the association between sugars and disease risk. This review describes the development and applications of a biomarker of sugars intake, informs its future use and recommends directions for future research. Recently, 24 h urinary sucrose and fructose were suggested as a predictive biomarker for total sugars intake, based on findings from three highly controlled feeding studies conducted in the United Kingdom. From this work, a calibration equation for the biomarker that provides an unbiased measure of sugars intake was generated that has since been used in two US-based studies with free-living individuals to assess measurement error in dietary self-reports and to develop regression calibration equations that could be used in future diet-disease analyses. Further applications of the biomarker include its use as a surrogate measure of intake in diet-disease association studies. Although this biomarker has great potential and exhibits favorable characteristics, available data come from a few controlled studies with limited sample sizes conducted in the UK. Larger feeding studies conducted in different populations are needed to further explore biomarker characteristics and stability of its biases, compare its performance, and generate a unique, or population-specific biomarker calibration equations to be applied in future studies. A validated sugars biomarker is critical for informed interpretation of sugars-disease association studies.

Urinary Sugars—A Biomarker of Total Sugars Intake

PubMed Central

Tasevska, Natasha

2015-01-01

Measurement error in self-reported sugars intake may explain the lack of consistency in the epidemiologic evidence on the association between sugars and disease risk. This review describes the development and applications of a biomarker of sugars intake, informs its future use and recommends directions for future research. Recently, 24 h urinary sucrose and fructose were suggested as a predictive biomarker for total sugars intake, based on findings from three highly controlled feeding studies conducted in the United Kingdom. From this work, a calibration equation for the biomarker that provides an unbiased measure of sugars intake was generated that has since been used in two US-based studies with free-living individuals to assess measurement error in dietary self-reports and to develop regression calibration equations that could be used in future diet-disease analyses. Further applications of the biomarker include its use as a surrogate measure of intake in diet-disease association studies. Although this biomarker has great potential and exhibits favorable characteristics, available data come from a few controlled studies with limited sample sizes conducted in the UK. Larger feeding studies conducted in different populations are needed to further explore biomarker characteristics and stability of its biases, compare its performance, and generate a unique, or population-specific biomarker calibration equations to be applied in future studies. A validated sugars biomarker is critical for informed interpretation of sugars-disease association studies. PMID:26184307

Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review

PubMed Central

Antoniou, Miranta; Jorgensen, Andrea L; Kolamunnage-Dona, Ruwanthi

2016-01-01

Background Personalized medicine is a growing area of research which aims to tailor the treatment given to a patient according to one or more personal characteristics. These characteristics can be demographic such as age or gender, or biological such as a genetic or other biomarker. Prior to utilizing a patient’s biomarker information in clinical practice, robust testing in terms of analytical validity, clinical validity and clinical utility is necessary. A number of clinical trial designs have been proposed for testing a biomarker’s clinical utility, including Phase II and Phase III clinical trials which aim to test the effectiveness of a biomarker-guided approach to treatment; these designs can be broadly classified into adaptive and non-adaptive. While adaptive designs allow planned modifications based on accumulating information during a trial, non-adaptive designs are typically simpler but less flexible. Methods and Findings We have undertaken a comprehensive review of biomarker-guided adaptive trial designs proposed in the past decade. We have identified eight distinct biomarker-guided adaptive designs and nine variations from 107 studies. Substantial variability has been observed in terms of how trial designs are described and particularly in the terminology used by different authors. We have graphically displayed the current biomarker-guided adaptive trial designs and summarised the characteristics of each design. Conclusions Our in-depth overview provides future researchers with clarity in definition, methodology and terminology for biomarker-guided adaptive trial designs. PMID:26910238

Alzheimer's Disease Normative Cerebrospinal Fluid Biomarkers Validated in PET Amyloid-β Characterized Subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study.

PubMed

Li, Qiao-Xin; Villemagne, Victor L; Doecke, James D; Rembach, Alan; Sarros, Shannon; Varghese, Shiji; McGlade, Amelia; Laughton, Katrina M; Pertile, Kelly K; Fowler, Christopher J; Rumble, Rebecca L; Trounson, Brett O; Taddei, Kevin; Rainey-Smith, Stephanie R; Laws, Simon M; Robertson, Joanne S; Evered, Lisbeth A; Silbert, Brendan; Ellis, Kathryn A; Rowe, Christopher C; Macaulay, S Lance; Darby, David; Martins, Ralph N; Ames, David; Masters, Colin L; Collins, Steven

2015-01-01

The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD). The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands. Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology. CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity. CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.

Saturated fatty acids as possible important metabolites for epithelial ovarian cancer based on the free and esterified fatty acid profiles determined by GC-MS analysis.

PubMed

Yin, Rui; Yang, Tongshu; Su, Hui; Ying, Li; Liu, Liyan; Sun, Changhao

2016-09-26

The aims were to investigate the serum free fatty acid (FFA) and esterified fatty acid (EFA) profiles and to identify biomarkers that can be used to identify patients with epithelial ovarian cancer (EOC) based on the metabolomics approach. We applied a targeted gas chromatography-mass spectrometry metabolomics approach to serum samples from 40 EOC patients and 35 healthy controls for achieving the FFA and EFA profiles. These metabolite profiles were processed using multivariate analysis to obtain potential biomarkers. And then, some independent samples were chosen to validate these potential biomarkers. There were higher saturated fatty acids and lower unsaturated fatty acids in EOC patients when compared with the healthy controls. EFA (C16:0), EFA (C18:0) and FFA (C16:0) were identified as potential biomarkers that distinguished EOC from the healthy controls. The areas under the curve from the EFA (C16:0), EFA (C18:0) and FFA (C16:0) in validated study were 0.745, 0.701, 0.682, respectively. Our study provides useful information to bridge the gaps in our understanding to the fatty acids metabolic alterations associated with EOC, and this study has demonstrated saturated fatty acid biomarkers might be helpful for the detection and characterization of EOC patients.

Resonance Raman Spectroscopic Evaluation of Skin Carotenoids as a Biomarker of Carotenoid Status for Human Studies

PubMed Central

Mayne, Susan T.; Cartmel, Brenda; Scarmo, Stephanie; Jahns, Lisa; Ermakov, Igor V.; Gellermann, Werner

2013-01-01

Resonance Raman Spectroscopy (RRS) is a non-invasive method that has been developed to assess carotenoid status in human tissues including human skin in vivo. Skin carotenoid status has been suggested as a promising biomarker for human studies. This manuscript describes research done relevant to the development of this biomarker, including its reproducibility, validity, feasibility for use in field settings, and factors that affect the biomarker such as diet, smoking, and adiposity. Recent studies have evaluated the response of the biomarker to controlled carotenoid interventions, both supplement-based and dietary [e.g., provision of a high-carotenoid fruit and vegetable (F/V)-enriched diet], demonstrating consistent response to intervention. The totality of evidence supports the use of skin carotenoid status as an objective biomarker of F/V intake, although in the cross-sectional setting, diet explains only some of the variation in this biomarker. However, this limitation is also a strength in that skin carotenoids may effectively serve as an integrated biomarker of health, with higher status reflecting greater F/V intake, lack of smoking, and lack of adiposity. Thus, this biomarker holds promise as both a health biomarker and an objective indicator of F/V intake, supporting its further development and utilization for medical and public health purposes. PMID:23823930

Adaptation of a Biomarker-Based Sepsis Mortality Risk Stratification Tool for Pediatric Acute Respiratory Distress Syndrome.

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly. Prospective observational cohort study. University affiliated PICU. Mechanically ventilated children with acute respiratory distress syndrome. Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements. In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics. A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow.

PubMed

Kulkarni, Shilpa; Koller, Antonius; Mani, Kartik M; Wen, Ruofeng; Alfieri, Alan; Saha, Subhrajit; Wang, Jian; Patel, Purvi; Bandeira, Nuno; Guha, Chandan; Chen, Emily I

2016-11-01

Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24 and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Urinary and Serum Exosome Biomarkers for Radiation Exposure Using a Data Dependent Acquisition and SWATH-MS Combined Workflow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kulkarni, Shilpa; Koller, Antonius; Proteomics Shared Resource, Herbert Irving Comprehensive Cancer Center, New York, New York

Purpose: Early and accurate assessment of radiation injury by radiation-responsive biomarkers is critical for triage and early intervention. Biofluids such as urine and serum are convenient for such analysis. Recent research has also suggested that exosomes are a reliable source of biomarkers in disease progression. In the present study, we analyzed total urine proteome and exosomes isolated from urine or serum for potential biomarkers of acute and persistent radiation injury in mice exposed to lethal whole body irradiation (WBI). Methods and Materials: For feasibility studies, the mice were irradiated at 10.4 Gy WBI, and urine and serum samples were collected 24more » and 72 hours after irradiation. Exosomes were isolated and analyzed using liquid chromatography mass spectrometry/mass spectrometry-based workflow for radiation exposure signatures. A data dependent acquisition and SWATH-MS combined workflow approach was used to identify significantly exosome biomarkers indicative of acute or persistent radiation-induced responses. For the validation studies, mice were exposed to 3, 6, 8, or 10 Gy WBI, and samples were analyzed for comparison. Results: A comparison between total urine proteomics and urine exosome proteomics demonstrated that exosome proteomic analysis was superior in identifying radiation signatures. Feasibility studies identified 23 biomarkers from urine and 24 biomarkers from serum exosomes after WBI. Urinary exosome signatures identified different physiological parameters than the ones obtained in serum exosomes. Exosome signatures from urine indicated injury to the liver, gastrointestinal, and genitourinary tracts. In contrast, serum showed vascular injuries and acute inflammation in response to radiation. Selected urinary exosomal biomarkers also showed changes at lower radiation doses in validation studies. Conclusions: Exosome proteomics revealed radiation- and time-dependent protein signatures after WBI. A total of 47 differentially secreted proteins were identified in urinary and serum exosomes. Together, these data showed the feasibility of defining biomarkers that could elucidate tissue-associated and systemic response caused by high-dose ionizing radiation. This is the first report using an exosome proteomics approach to identify radiation signatures.« less

Metabolomics, Nutrition, and Potential Biomarkers of Food Quality, Intake, and Health Status.

PubMed

Sébédio, Jean-Louis

Diet, dietary patterns, and other environmental factors such as exposure to toxins are playing an important role in the prevention/development of many diseases, like obesity, type 2 diabetes, and consequently on the health status of individuals. A major challenge nowadays is to identify novel biomarkers to detect as early as possible metabolic dysfunction and to predict evolution of health status in order to refine nutritional advices to specific population groups. Omics technologies such as genomics, transcriptomics, proteomics, and metabolomics coupled with statistical and bioinformatics tools have already shown great potential in this research field even if so far only few biomarkers have been validated. For the past two decades, important analytical techniques have been developed to detect as many metabolites as possible in human biofluids such as urine, blood, and saliva. In the field of food science and nutrition, many studies have been carried out for food authenticity, quality, and safety, as well as for food processing. Furthermore, metabolomic investigations have been carried out to discover new early biomarkers of metabolic dysfunction and predictive biomarkers of developing pathologies (obesity, metabolic syndrome, type-2 diabetes, etc.). Great emphasis is also placed in the development of methodologies to identify and validate biomarkers of nutrients exposure. © 2017 Elsevier Inc. All rights reserved.

Prediction of breast cancer risk with volatile biomarkers in breath.

PubMed

Phillips, Michael; Cataneo, Renee N; Cruz-Ramos, Jose Alfonso; Huston, Jan; Ornelas, Omar; Pappas, Nadine; Pathak, Sonali

2018-03-23

Human breath contains volatile organic compounds (VOCs) that are biomarkers of breast cancer. We investigated the positive and negative predictive values (PPV and NPV) of breath VOC biomarkers as indicators of breast cancer risk. We employed ultra-clean breath collection balloons to collect breath samples from 54 women with biopsy-proven breast cancer and 124 cancer-free controls. Breath VOCs were analyzed with gas chromatography (GC) combined with either mass spectrometry (GC MS) or surface acoustic wave detection (GC SAW). Chromatograms were randomly assigned to a training set or a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set. In the unsplit dataset, the predictive algorithms generated discriminant function (DF) values that varied with sensitivity, specificity, PPV and NPV. Using GC MS, test accuracy = 90% (area under curve of receiver operating characteristic in unsplit dataset) and cross-validated accuracy = 77%. Using GC SAW, test accuracy = 86% and cross-validated accuracy = 74%. With both assays, a low DF value was associated with a low risk of breast cancer (NPV > 99.9%). A high DF value was associated with a high risk of breast cancer and PPV rising to 100%. Analysis of breath VOC samples collected with ultra-clean balloons detected biomarkers that accurately predicted risk of breast cancer.

Oral Biofluid Biomarker Research: Current Status and Emerging Frontiers

PubMed Central

Wang, Austin; Wang, Chris P.; Tu, Michael; Wong, David T.W.

2016-01-01

Salivary diagnostics is a rapidly advancing field that offers clinicians and patients the potential of rapid, noninvasive diagnostics with excellent accuracy. In order for the complete realization of the potential of saliva, however, extensive profiling of constituents must be conducted and diagnostic biomarkers must be thoroughly validated. This article briefly overviews the process of conducting a study of salivary biomarkers in a patient cohort and highlights the studies that have been conducted on different classes of molecules in the saliva. Emerging frontiers in salivary diagnostics research that may significantly advance the field will also be highlighted. PMID:27999326

Biomarkers for equine joint injury and osteoarthritis.

PubMed

McIlwraith, C Wayne; Kawcak, Christopher E; Frisbie, David D; Little, Christopher B; Clegg, Peter D; Peffers, Mandy J; Karsdal, Morten A; Ekman, Stina; Laverty, Sheila; Slayden, Richard A; Sandell, Linda J; Lohmander, L S; Kraus, Virginia B

2018-03-01

We report the results of a symposium aimed at identifying validated biomarkers that can be used to complement clinical observations for diagnosis and prognosis of joint injury leading to equine osteoarthritis (OA). Biomarkers might also predict pre-fracture change that could lead to catastrophic bone failure in equine athletes. The workshop was attended by leading scientists in the fields of equine and human musculoskeletal biomarkers to enable cross-disciplinary exchange and improve knowledge in both. Detailed proceedings with strategic planning was written, added to, edited and referenced to develop this manuscript. The most recent information from work in equine and human osteoarthritic biomarkers was accumulated, including the use of personalized healthcare to stratify OA phenotypes, transcriptome analysis of anterior cruciate ligament (ACL) and meniscal injuries in the human knee. The spectrum of "wet" biomarker assays that are antibody based that have achieved usefulness in both humans and horses, imaging biomarkers and the role they can play in equine and human OA was discussed. Prediction of musculoskeletal injury in the horse remains a challenge, and the potential usefulness of spectroscopy, metabolomics, proteomics, and development of biobanks to classify biomarkers in different stages of equine and human OA were reviewed. The participants concluded that new information and studies in equine musculoskeletal biomarkers have potential translational value for humans and vice versa. OA is equally important in humans and horses, and the welfare issues associated with catastrophic musculoskeletal injury in horses add further emphasis to the need for good validated biomarkers in the horse. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:823-831, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

[Biological markers in epidemiology: concepts, applications, perspectives (part I)].

PubMed

Hoffmann, W; Latza, U; Ahrens, W; Greiser, K H; Kroke, A; Nieters, A; Schulze, M B; Steiner, M; Terschüren, C; Wjst, M

2002-02-01

The inclusion of biomarkers in epidemiological research provides new possibilities for exposure assessment and the study of early structural or functional changes and pre-clinical stages of diseases. At the same time issues of validity, reliability, and quality control as well as logistics require special attention. Usually epidemiological studies become more expensive with regard to time and cost. Interdisciplinary collaboration between epidemiology, basic research, and laboratory research is crucial. A prerequisite for this collaboration are agreements on definitions, methods and procedures. The definition of "biomarker" and a description of previous uses of biomarkers in epidemiological studies are presented in the first part of this paper. The second part addresses genetic markers and markers of individual sensitivity and susceptibility. We will end with a discussion about the possible future of biomarkers in epidemiology.

Unraveling the molecular repertoire of tears as a source of biomarkers: beyond ocular diseases.

PubMed

Pieragostino, Damiana; D'Alessandro, Michele; di Ioia, Maria; Di Ilio, Carmine; Sacchetta, Paolo; Del Boccio, Piero

2015-02-01

Proteomics and metabolomics investigations of body fluids present several challenges for biomarker discovery of several diseases. The search for biomarkers is actually conducted in different body fluids, even if the ideal biomarker can be found in an easily accessible biological fluid, because, if validated, the biomarker could be sought in the healthy population. In this regard, tears could be considered an optimum material obtained by noninvasive procedures. In the past years, the scientific community has become more interested in the study of tears for the research of new biomarkers not only for ocular diseases. In this review, we provide a discussion on the current state of biomarkers research in tears and their relevance for clinical practice, and report the main results of clinical proteomics studies on systemic and eye diseases. We summarize the main methods for tear samples analyses and report recent advances in "omics" platforms for tears investigations. Moreover, we want to take stock of the emerging field of metabolomics and lipidomics as a new and integrated approach to study protein-metabolites interplay for biomarkers research, where tears represent a still unexplored and attractive field. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and validation of a LC-MS/MS assay for quantitation of plasma citrulline for application to animal models of the acute radiation syndrome across multiple species.

PubMed

Jones, Jace W; Tudor, Gregory; Bennett, Alexander; Farese, Ann M; Moroni, Maria; Booth, Catherine; MacVittie, Thomas J; Kane, Maureen A

2014-07-01

The potential risk of a radiological catastrophe highlights the need for identifying and validating potential biomarkers that accurately predict radiation-induced organ damage. A key target organ that is acutely sensitive to the effects of irradiation is the gastrointestinal (GI) tract, referred to as the GI acute radiation syndrome (GI-ARS). Recently, citrulline has been identified as a potential circulating biomarker for radiation-induced GI damage. Prior to biologically validating citrulline as a biomarker for radiation-induced GI injury, there is the important task of developing and validating a quantitation assay for citrulline detection within the radiation animal models used for biomarker validation. Herein, we describe the analytical development and validation of citrulline detection using a liquid chromatography tandem mass spectrometry assay that incorporates stable-label isotope internal standards. Analytical validation for specificity, linearity, lower limit of quantitation, accuracy, intra- and interday precision, extraction recovery, matrix effects, and stability was performed under sample collection and storage conditions according to the Guidance for Industry, Bioanalytical Methods Validation issued by the US Food and Drug Administration. In addition, the method was biologically validated using plasma from well-characterized mouse, minipig, and nonhuman primate GI-ARS models. The results demonstrated that circulating citrulline can be confidently quantified from plasma. Additionally, circulating citrulline displayed a time-dependent response for radiological doses covering GI-ARS across multiple species.

Validation of a δ2Hn-alkane-δ18Ohemicellulose based paleohygrometer: Implications from a climate chamber experiment

NASA Astrophysics Data System (ADS)

Hepp, Johannes; Kathrin Schäfer, Imke; Tuthorn, Mario; Wüthrich, Lorenz; Zech, Jana; Glaser, Bruno; Juchelka, Dieter; Rozanski, Kazimierz; Zech, Roland; Mayr, Christoph; Zech, Michael

2017-04-01

Leaf wax-derived biomarkers, e.g. long chain n-alkanes and fatty acids, and their hydrogen isotopic composition are proved to be of a value in paleoclimatology/-hydrology research. However, the alteration of the isotopic signal as a result of the often unknown amount of leaf water enrichment challenges a direct reconstruction of the isotopic composition of paleoprecipitation. The coupling of ^2H/^1H results of leaf wax-derived biomarkers with 18O/16O results of hemicellulose-derived sugars has the potential to overcome this limitation and additionally allows reconstructing relative air humidity (RH) (Zech et al., 2013). This approach was recently validated by Tuthorn et al. (2015) by applying it to topsoil samples along a climate transect in Argentina. Accordingly, the biomarker-derived RH values correlate significantly with modern actual RH values from the respective study sites, showing the potential of the established 'paleohygrometer' approach. However, a climate chamber validation study to answer open questions regarding this approach, e.g. how robust biosynthetic fractionation factors are, is still missing. Here we present coupled δ2Hn-alkane-δ18Ohemicellulose results obtained for leaf material from a climate chamber experiment, in which Eucalyptus globulus, Vicia faba and Brassica oleracea were grown under controlled conditions (Mayr, 2003). First, the 2H and 18O enrichment of leaf water strongly reflects actual RH values of the climate chambers. Second, the biomarker-based reconstructed RH values correlate well with the actual RH values of the respective climate chamber, validating the proposed 'paleohygrometer' approach. And third, the calculated fractionation factors between the investigated leaf biomarkers (n-C29 and n-C31 for alkanes; arabinose and xylose for hemicellulose) and leaf water are close to the expected once reviewed from the literature (+27\\permil for hemicellulose; -155\\permil for n-alkanes). Nevertheless, minor dependencies of these biomarker fractionation factors from temperature and relative humidity of the climate chamber, as well as from the measured transpiration rate of the plants are evident from the data. As an outlook, the proposed coupled δ2Hn-alkane-δ18Ohemicellulose approach allows (i) more robust δ2H/δ18Oprecipitation reconstructions and (ii) paleohygrometry studies in future paleoclimate research. References Mayr, C., 2003. Möglichkeiten der Klimarekonstruktion im Holozän mit δ13C- und δ2H-Werten von Baum-Jahrringen auf der Basis von Klimakammerversuchen und Rezentstudien. Ludwig-Maximilians-Universität München. Tuthorn, M., Zech, R., Ruppenthal, M., Oelmann, Y., Kahmen, A., del Valle, H.F., Eglinton, T., Rozanski, K., Zech, M., 2015. Coupling δ2H and δ18O biomarker results yields information on relative humidity and isotopic composition of precipitation - a climate transect validation study. Biogeosciences 12, 3913-3924. Zech, M., Tuthorn, M., Detsch, F., Rozanski, K., Zech, R., Zöller, L., Zech, W., Glaser, B., 2013. A 220 ka terrestrial δ18O and deuterium excess biomarker record from an eolian permafrost paleosol sequence, NE-Siberia. Chemical Geology.

Application of proteomics in the discovery of candidate protein biomarkers in a Diabetes Autoantibody Standardization Program (DASP) sample subset

PubMed Central

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

2009-01-01

Novel biomarkers of type 1 diabetes must be identified and validated in initial, exploratory studies before they can be assessed in proficiency evaluations. Currently, untargeted “-omics” approaches are under-utilized in profiling studies of clinical samples. This report describes the evaluation of capillary liquid chromatography (LC) coupled with mass spectrometry (MS) in a pilot proteomic analysis of human plasma and serum from a subset of control and type 1 diabetic individuals enrolled in the Diabetes Autoantibody Standardization Program with the goal of identifying candidate biomarkers of type 1 diabetes. Initial high-resolution capillary LC-MS/MS experiments were performed to augment an existing plasma peptide database, while subsequent LC-FTICR studies identified quantitative differences in the abundance of plasma proteins. Analysis of LC-FTICR proteomic data identified five candidate protein biomarkers of type 1 diabetes. Alpha-2-glycoprotein 1 (zinc), corticosteroid-binding globulin, and lumican were 2-fold up-regulated in type 1 diabetic samples relative to control samples, whereas clusterin and serotransferrin were 2-fold up-regulated in control samples relative to type 1 diabetic samples. Observed perturbations in the levels of all five proteins are consistent with the metabolic aberrations found in type 1 diabetes. While the discovery of these candidate protein biomarkers of type 1 diabetes is encouraging, follow up studies are required for validation in a larger population of individuals and for determination of laboratory-defined sensitivity and specificity values using blinded samples. PMID:18092746

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

PubMed

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

2008-02-01

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

Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury

PubMed Central

2013-01-01

Introduction Acute kidney injury (AKI) can evolve quickly and clinical measures of function often fail to detect AKI at a time when interventions are likely to provide benefit. Identifying early markers of kidney damage has been difficult due to the complex nature of human AKI, in which multiple etiologies exist. The objective of this study was to identify and validate novel biomarkers of AKI. Methods We performed two multicenter observational studies in critically ill patients at risk for AKI - discovery and validation. The top two markers from discovery were validated in a second study (Sapphire) and compared to a number of previously described biomarkers. In the discovery phase, we enrolled 522 adults in three distinct cohorts including patients with sepsis, shock, major surgery, and trauma and examined over 300 markers. In the Sapphire validation study, we enrolled 744 adult subjects with critical illness and without evidence of AKI at enrollment; the final analysis cohort was a heterogeneous sample of 728 critically ill patients. The primary endpoint was moderate to severe AKI (KDIGO stage 2 to 3) within 12 hours of sample collection. Results Moderate to severe AKI occurred in 14% of Sapphire subjects. The two top biomarkers from discovery were validated. Urine insulin-like growth factor-binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases-2 (TIMP-2), both inducers of G1 cell cycle arrest, a key mechanism implicated in AKI, together demonstrated an AUC of 0.80 (0.76 and 0.79 alone). Urine [TIMP-2]·[IGFBP7] was significantly superior to all previously described markers of AKI (P <0.002), none of which achieved an AUC >0.72. Furthermore, [TIMP-2]·[IGFBP7] significantly improved risk stratification when added to a nine-variable clinical model when analyzed using Cox proportional hazards model, generalized estimating equation, integrated discrimination improvement or net reclassification improvement. Finally, in sensitivity analyses [TIMP-2]·[IGFBP7] remained significant and superior to all other markers regardless of changes in reference creatinine method. Conclusions Two novel markers for AKI have been identified and validated in independent multicenter cohorts. Both markers are superior to existing markers, provide additional information over clinical variables and add mechanistic insight into AKI. Trial registration ClinicalTrials.gov number NCT01209169. PMID:23388612

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study.

PubMed

Larkin, S E T; Johnston, H E; Jackson, T R; Jamieson, D G; Roumeliotis, T I; Mockridge, C I; Michael, A; Manousopoulou, A; Papachristou, E K; Brown, M D; Clarke, N W; Pandha, H; Aukim-Hastie, C L; Cragg, M S; Garbis, S D; Townsend, P A

2016-10-25

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease. We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa. We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6. Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Derivation and Validation of a Biomarker-Based Clinical Algorithm to Rule Out Sepsis From Noninfectious Systemic Inflammatory Response Syndrome at Emergency Department Admission: A Multicenter Prospective Study.

PubMed

Mearelli, Filippo; Fiotti, Nicola; Giansante, Carlo; Casarsa, Chiara; Orso, Daniele; De Helmersen, Marco; Altamura, Nicola; Ruscio, Maurizio; Castello, Luigi Mario; Colonetti, Efrem; Marino, Rossella; Barbati, Giulia; Bregnocchi, Andrea; Ronco, Claudio; Lupia, Enrico; Montrucchio, Giuseppe; Muiesan, Maria Lorenza; Di Somma, Salvatore; Avanzi, Gian Carlo; Biolo, Gianni

2018-05-07

To derive and validate a predictive algorithm integrating a nomogram-based prediction of the pretest probability of infection with a panel of serum biomarkers, which could robustly differentiate sepsis/septic shock from noninfectious systemic inflammatory response syndrome. Multicenter prospective study. At emergency department admission in five University hospitals. Nine-hundred forty-seven adults in inception cohort and 185 adults in validation cohort. None. A nomogram, including age, Sequential Organ Failure Assessment score, recent antimicrobial therapy, hyperthermia, leukocytosis, and high C-reactive protein values, was built in order to take data from 716 infected patients and 120 patients with noninfectious systemic inflammatory response syndrome to predict pretest probability of infection. Then, the best combination of procalcitonin, soluble phospholypase A2 group IIA, presepsin, soluble interleukin-2 receptor α, and soluble triggering receptor expressed on myeloid cell-1 was applied in order to categorize patients as "likely" or "unlikely" to be infected. The predictive algorithm required only procalcitonin backed up with soluble phospholypase A2 group IIA determined in 29% of the patients to rule out sepsis/septic shock with a negative predictive value of 93%. In a validation cohort of 158 patients, predictive algorithm reached 100% of negative predictive value requiring biomarker measurements in 18% of the population. We have developed and validated a high-performing, reproducible, and parsimonious algorithm to assist emergency department physicians in distinguishing sepsis/septic shock from noninfectious systemic inflammatory response syndrome.

Harnessing pain heterogeneity and RNA transcriptome to identify blood–based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model

PubMed Central

Grace, Peter M.; Hurley, Daniel; Barratt, Daniel T.; Tsykin, Anna; Watkins, Linda R.; Rolan, Paul E.; Hutchinson, Mark R.

2017-01-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. PMID:22697386

First-void urine: A potential biomarker source for triage of high-risk human papillomavirus infected women.

PubMed

Van Keer, Severien; Pattyn, Jade; Tjalma, Wiebren A A; Van Ostade, Xaveer; Ieven, Margareta; Van Damme, Pierre; Vorsters, Alex

2017-09-01

Great interest has been directed towards the use of first-void urine as a liquid biopsy for high-risk human papillomavirus DNA testing. Despite the high correlations established between urinary and cervical infections, human papillomavirus testing is unable to distinguish between productive and transforming high-risk infections that have the tendency to progress to cervical cancer. Thus far, investigations have been primarily confined to the identification of biomarkers for triage of high-risk human papillomavirus-positive women in cervicovaginal specimens and tissue biopsies. This paper reviews urinary biomarkers for cervical cancer and triage of high-risk human papillomavirus infections and elaborates on the opportunities and challenges that have emerged regarding the use of first-void urine as a liquid biopsy for the analysis of both morphological- (conventional cytology and novel immunohistochemical techniques) and molecular-based (HPV16/18 genotyping, host/viral gene methylation, RNA, and proteins) biomarkers. A literature search was performed in PubMed and Web of Science for studies investigating the use of urine as a biomarker source for cervical cancer screening. Five studies were identified reporting on biomarkers that are still in preclinical exploratory or clinical assay development phases and on assessments of non-invasive (urine) samples. Although large-scale validation studies are still needed, we conclude that methylation of both host and viral genes in urine has been proven feasible for use as a molecular cervical cancer triage and screening biomarker in phase two studies. This is especially promising and underscores our hypothesis that human papillomavirus DNA and candidate human and viral biomarkers are washed away with the initial, first-void urine, together with exfoliated cells, debris and impurities that line the urethra opening. Similar to the limitations of self-collected cervicovaginal samples, first-void urine will likely not fulfil the high-quality cellularity standards required for morphological biomarkers. Molecular biomarkers will likely overcome this issue to yield high-throughput, objective, and reproducible results. When using proper sampling, transport, storage, preanalytical biomarker concentration techniques, and clinically validated assays, first-void urine is expected to be a valuable source of molecular biomarkers for cervical cancer screening. Furthermore, as first-void urine can be easily and non-invasively collected, it is a highly preferred technique among women and offers the ability to test both primary high-risk human papillomavirus and biomarkers in the same sample. In addition, the use of first-void urine confers opportunities to reduce loss-to follow-up and non-adherence to screening subjects. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

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

PubMed Central

May, Felicity E B; Westley, Bruce R

2015-01-01

The stratification of breast cancer patients for endocrine therapies by oestrogen or progesterone receptor expression is effective but imperfect. The present study aims were to validate microarray studies that demonstrate TFF3 regulation by oestrogen and its association with oestrogen receptors in breast cancer, to evaluate TFF3 as a biomarker of endocrine response, and to investigate TFF3 function. Microarray data were validated by quantitative RT-PCR and northern and western transfer analyses. TFF3 was induced by oestrogen, and its induction was inhibited by antioestrogens, tamoxifen, 4-hydroxytamoxifen and fulvestrant in oestrogen-responsive breast cancer cells. The expression of TFF3 mRNA was associated with oestrogen receptor mRNA in breast tumours (Pearson's coefficient=0.762, P=0.000). Monoclonal antibodies raised against the TFF3 protein detected TFF3 by immunohistochemistry in oesophageal submucosal glands, intestinal goblet and neuroendocrine cells, Barrett's metaplasia and intestinal metaplasia. TFF3 protein expression was associated with oestrogen receptor, progesterone receptor and TFF1 expression in malignant breast cells. TFF3 is a specific and sensitive predictive biomarker of response to endocrine therapy, degree of response and duration of response in unstratified metastatic breast cancer patients (P=0.000, P=0.002 and P=0.002 respectively). Multivariate binary logistic regression analysis demonstrated that TFF3 is an independent biomarker of endocrine response and degree of response, and this was confirmed in a validation cohort. TFF3 stimulated migration and invasion of breast cancer cells. In conclusion, TFF3 expression is associated with response to endocrine therapy, and outperforms oestrogen receptor, progesterone receptor and TFF1 as an independent biomarker, possibly because it mediates the malign effects of oestrogen on invasion and metastasis. PMID:25900183

DEVELOPMENT OF URINARY METABOLITE BIOMARKERS TO ASSESS POPULATION EXPOSURE TO PM2.5 FROM VARIOUS COMBUSTION SOURCES

EPA Science Inventory

A primary goal of our research is to validate the use of urinary biomarkers to apportion the sources of human exposure to PM2.5. Organic source tracers have been used in source apportionment studies of ambient PM2.5 to distinguish a range of combustion sources. Both gas and par...

The past and the future of Alzheimer's disease CSF biomarkers-a journey toward validated biochemical tests covering the whole spectrum of molecular events.

PubMed

Blennow, Kaj; Zetterberg, Henrik

2015-01-01

This paper gives a short review on cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD), from early developments to high-precision validated assays on fully automated lab analyzers. We also discuss developments on novel biomarkers, such as synaptic proteins and Aβ oligomers. Our vision for the future is that assaying a set of biomarkers in a single CSF tube can monitor the whole spectrum of AD molecular pathogenic events. CSF biomarkers will have a central position not only for clinical diagnosis, but also for the understanding of the sequence of molecular events in the pathogenic process underlying AD and as tools to monitor the effects of novel drug candidates targeting these different mechanisms.

The Road Ahead to Cure Alzheimer’s Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations

PubMed Central

Cavedo, E.; Lista, S.; Khachaturian, Z.; Aisen, P.; Amouyel, P.; Herholz, K.; Jack, C.R.; Sperling, R.; Cummings, J.; Blennow, K.; O’Bryant, S.; Frisoni, G.B.; Khachaturian, A.; Kivipelto, M.; Klunk, W.; Broich, K.; Andrieu, S.; de Schotten, M. Thiebaut; Mangin, J.-F.; Lammertsma, A.A.; Johnson, K.; Teipel, S.; Drzezga, A.; Bokde, A.; Colliot, O.; Bakardjian, H.; Zetterberg, H.; Dubois, B.; Vellas, B.; Schneider, L.S.; Hampel, H.

2015-01-01

Alzheimer’s disease (AD) is a slowly progressing non-linear dynamic brain disease in which pathophysiological abnormalities, detectable in vivo by biological markers, precede overt clinical symptoms by many years to decades. Use of these biomarkers for the detection of early and preclinical AD has become of central importance following publication of two international expert working group’s revised criteria for the diagnosis of AD dementia, mild cognitive impairment (MCI) due to AD, prodromal AD and preclinical AD. As a consequence of matured research evidence six AD biomarkers are sufficiently validated and partly qualified to be incorporated into operationalized clinical diagnostic criteria and use in primary and secondary prevention trials. These biomarkers fall into two molecular categories: biomarkers of amyloid-beta (Aβ) deposition and plaque formation as well as of tau-protein related hyperphosphorylation and neurodegeneration. Three of the six gold-standard (“core feasible) biomarkers are neuroimaging measures and three are cerebrospinal fluid (CSF) analytes. CSF Aβ1-42 (Aβ1-42), also expressed as Aβ1-42 : Aβ1-40 ratio, T-tau, and P-tau Thr181 & Thr231 proteins have proven diagnostic accuracy and risk enhancement in prodromal MCI and AD dementia. Conversely, having all three biomarkers in the normal range rules out AD. Intermediate conditions require further patient follow-up. Magnetic resonance imaging (MRI) at increasing field strength and resolution allows detecting the evolution of distinct types of structural and functional abnormality pattern throughout early to late AD stages. Anatomical or volumetric MRI is the most widely used technique and provides local and global measures of atrophy. The revised diagnostic criteria for “prodromal AD” and “mild cognitive impairment due to AD” include hippocampal atrophy (as the fourth validated biomarker), which is considered an indicator of regional neuronal injury. Advanced image analysis techniques generate automatic and reproducible measures both in regions of interest, such as the hippocampus and in an exploratory fashion, observer and hypothesis-indedendent, throughout the entire brain. Evolving modalities such as diffusion-tensor imaging (DTI) and advanced tractography as well as resting-state functional MRI provide useful additionally useful measures indicating the degree of fiber tract and neural network disintegration (structural, effective and functional connectivity) that may substantially contribute to early detection and the mapping of progression. These modalities require further standardization and validation. The use of molecular in vivo amyloid imaging agents (the fifth validated biomarker), such as the Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) (as the sixth validated biomarker) support the detection of early AD pathological processes and associated neurodegeneration. How to use, interpret, and disclose biomarker results drives the need for optimized standardization. Multimodal AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping fashion. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. AD biomarkers can be combined to increase accuracy or risk. A list of genetic risk factors is increasingly included in secondary prevention trials to stratify and select individuals at genetic risk of AD. Although most of these biomarker candidates are not yet qualified and approved by regulatory authorities for their intended use in drug trials, they are nonetheless applied in ongoing clinical studies for the following functions: (i) inclusion/exclusion criteria, (ii) patient stratification, (iii) evaluation of treatment effect, (iv) drug target engagement, and (v) safety. Moreover, novel promising hypothesis-driven, as well as exploratory biochemical, genetic, electrophysiological, and neuroimaging markers for use in clinical trials are being developed. The current state-of-the-art and future perspectives on both biological and neuroimaging derived biomarker discovery and development as well as the intended application in prevention trials is outlined in the present publication. PMID:26478889

Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens

PubMed Central

Huang, Shan-Han; Tung, Chun-Wei

2017-01-01

The assessment of non-genotoxic hepatocarcinogens (NGHCs) is currently relying on two-year rodent bioassays. Toxicogenomics biomarkers provide a potential alternative method for the prioritization of NGHCs that could be useful for risk assessment. However, previous studies using inconsistently classified chemicals as the training set and a single microarray dataset concluded no consensus biomarkers. In this study, 4 consensus biomarkers of A2m, Ca3, Cxcl1, and Cyp8b1 were identified from four large-scale microarray datasets of the one-day single maximum tolerated dose and a large set of chemicals without inconsistent classifications. Machine learning techniques were subsequently applied to develop prediction models for NGHCs. The final bagging decision tree models were constructed with an average AUC performance of 0.803 for an independent test. A set of 16 chemicals with controversial classifications were reclassified according to the consensus biomarkers. The developed prediction models and identified consensus biomarkers are expected to be potential alternative methods for prioritization of NGHCs for further experimental validation. PMID:28117354

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

Cancer.gov

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

Recommendations for adaptation and validation of commercial kits for biomarker quantification in drug development.

PubMed

Khan, Masood U; Bowsher, Ronald R; Cameron, Mark; Devanarayan, Viswanath; Keller, Steve; King, Lindsay; Lee, Jean; Morimoto, Alyssa; Rhyne, Paul; Stephen, Laurie; Wu, Yuling; Wyant, Timothy; Lachno, D Richard

2015-01-01

Increasingly, commercial immunoassay kits are used to support drug discovery and development. Longitudinally consistent kit performance is crucial, but the degree to which kits and reagents are characterized by manufacturers is not standardized, nor are the approaches by users to adapt them and evaluate their performance through validation prior to use. These factors can negatively impact data quality. This paper offers a systematic approach to assessment, method adaptation and validation of commercial immunoassay kits for quantification of biomarkers in drug development, expanding upon previous publications and guidance. These recommendations aim to standardize and harmonize user practices, contributing to reliable biomarker data from commercial immunoassays, thus, enabling properly informed decisions during drug development.

Toenail as a biomarker of heavy metal exposure via drinking water: a systematic review.

PubMed

Ab Razak, Nurul Hafiza; Praveena, Sarva Mangala; Hashim, Zailina

2015-01-01

Toenail is metabolic end product of the skin, which can provide information about heavy metal accumulation in human cells. Slow growth rates of toenail can represent heavy metal exposure from 2 to 12 months before the clipping. The toenail is a non-invasive biomarker that is easy to collect and store and is stable over time. In this systematic review, the suitability of toenail as a long-term biomarker was reviewed, along with the analysis and validation of toenail and confounders to heavy metal. This systematic review has included 30 articles chosen from a total of 132 articles searched from online electronic databases like Pubmed, Proquest, Science Direct, and SCOPUS. Keywords used in the search included "toenail", "biomarker", "heavy metal", and "drinking water". Heavy metal in toenail can be accurately analyzed using an ICP-MS instrument. The validation of toenail heavy metal concentration data is very crucial; however, the Certified Reference Material (CRM) for toenail is still unavailable. Usually, CRM for hair is used in toenail studies. Confounders that have major effects on heavy metal accumulation in toenail are dietary intake of food and supplement, smoking habit, and overall health condition. This review has identified the advantages and limitations of using toenail as a biomarker for long-term exposure, which can help future researchers design a study on heavy metal exposure using toenail.

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

PubMed

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

2015-11-01

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

Biomarkers associated with obstructive sleep apnea: A scoping review

PubMed Central

De Luca Canto, Graziela; Pachêco-Pereira, Camila; Aydinoz, Secil; Major, Paul W.; Flores-Mir, Carlos; Gozal, David

2014-01-01

Summary The overall validity of biomarkers in the diagnosis of obstructive sleep apnea (OSA) remains unclear. We conducted a scoping review to provide assessments of biomarkers characteristics in the context of obstructive sleep apnea (OSA) and to identify gaps in the literature. A scoping review of studies in humans without age restriction that evaluated the potential diagnostic value of biological markers (blood, exhaled breath condensate, salivary, and urinary) in the OSA diagnosis was undertaken. Retained articles were those focused on the identification of biomarkers in subjects with OSA, the latter being confirmed with a full overnight or home-based polysomnography (PSG). Search strategies for six different databases were developed. The methodology of selected studies was classified using an adaptation of the evidence quality criteria from the American Academy of Pediatrics. Additionally the biomarkers were classified according to their potential clinical application. We identified 572 relevant studies, of which 117 met the inclusion criteria. Eighty-two studies were conducted in adults, 34 studies involved children, and one study had a sample composed of both adults and children. Most of the studies evaluated blood biomarkers. Potential diagnostic biomarkers were found in 9 pediatric studies and in 58 adults studies. Only 9 studies that reported sensitivity and specificity, which varied substantially from 43% to 100%, and from 45% to 100%, respectively. Thus, studies in adults have focused on the investigation of IL-6, TNF-α and hsCRP. There was not a specific biomarker that was tested by a majority of authors in pediatric studies, and combinatorial urine biomarker approaches have shown preliminary promising results. In adults IL-6 and IL-10 seem to have a favorable potential to become a good biomarker to identify OSA. PMID:25645128

The druggable genome and support for target identification and validation in drug development.

PubMed

Finan, Chris; Gaulton, Anna; Kruger, Felix A; Lumbers, R Thomas; Shah, Tina; Engmann, Jorgen; Galver, Luana; Kelley, Ryan; Karlsson, Anneli; Santos, Rita; Overington, John P; Hingorani, Aroon D; Casas, Juan P

2017-03-29

Target identification (determining the correct drug targets for a disease) and target validation (demonstrating an effect of target perturbation on disease biomarkers and disease end points) are important steps in drug development. Clinically relevant associations of variants in genes encoding drug targets model the effect of modifying the same targets pharmacologically. To delineate drug development (including repurposing) opportunities arising from this paradigm, we connected complex disease- and biomarker-associated loci from genome-wide association studies to an updated set of genes encoding druggable human proteins, to agents with bioactivity against these targets, and, where there were licensed drugs, to clinical indications. We used this set of genes to inform the design of a new genotyping array, which will enable association studies of druggable genes for drug target selection and validation in human disease. Copyright © 2017, American Association for the Advancement of Science.

Circulating tumor cells: clinical validity and utility.

PubMed

Cabel, Luc; Proudhon, Charlotte; Gortais, Hugo; Loirat, Delphine; Coussy, Florence; Pierga, Jean-Yves; Bidard, François-Clément

2017-06-01

Circulating tumor cells (CTCs) are rare tumor cells and have been investigated as diagnostic, prognostic and predictive biomarkers in many types of cancer. Although CTCs are not currently used in clinical practice, CTC studies have accumulated a high level of clinical validity, especially in breast, lung, prostate and colorectal cancers. In this review, we present an overview of the current clinical validity of CTCs in metastatic and non-metastatic disease, and the main concepts and studies investigating the clinical utility of CTCs. In particular, this review will focus on breast, lung, colorectal and prostate cancer. Three major topics concerning the clinical utility of CTC are discussed-(1) treatment based on CTCs used as liquid biopsy, (2) treatment based on CTC count or CTC variations, and (3) treatment based on CTC biomarker expression. A summary of published or ongoing phase II and III trials is also presented.

Translating pharmacodynamic biomarkers from bench to bedside: analytical validation and fit-for-purpose studies to qualify multiplex immunofluorescent assays for use on clinical core biopsy specimens.

PubMed

Marrero, Allison; Lawrence, Scott; Wilsker, Deborah; Voth, Andrea Regier; Kinders, Robert J

2016-08-01

Multiplex pharmacodynamic (PD) assays have the potential to increase sensitivity of biomarker-based reporting for new targeted agents, as well as revealing significantly more information about target and pathway activation than single-biomarker PD assays. Stringent methodology is required to ensure reliable and reproducible results. Common to all PD assays is the importance of reagent validation, assay and instrument calibration, and the determination of suitable response calibrators; however, multiplex assays, particularly those performed on paraffin specimens from tissue blocks, bring format-specific challenges adding a layer of complexity to assay development. We discuss existing multiplex approaches and the development of a multiplex immunofluorescence assay measuring DNA damage and DNA repair enzymes in response to anti-cancer therapeutics and describe how our novel method addresses known issues. Copyright © 2016 Elsevier Inc. All rights reserved.

High-throughput deep screening and identification of four peripheral leucocyte microRNAs as novel potential combination biomarkers for preeclampsia

PubMed Central

Wang, Yonghong; Yang, Xukui; Yang, Yuanyuan; Wang, Wenjun; Zhao, Meiling; Liu, Huiqiang; Li, Dongyan; Hao, Min

2016-01-01

Objective: To identify the specific microRNA (miRNA) biomarkers of preeclampsia (PE), the miRNA profiles analysis were performed. Study Design: The blood samples were obtained from five PE patients and five normal healthy pregnant women. The small RNA profiles were analyzed to identify miRNA expression levels and find out miRNAs that may associate with PE. The quantitative reverse transcriptase–PCR (qRT-PCR) assay was used to validate differentially expressed peripheral leucocyte miRNAs in a new cohort. Result: The data analysis showed that 10 peripheral leucocyte miRNAs were significantly differently expressed in severe PE patients. Four differently expressed miRNAs were successfully validated using qRT-PCR method. Conclusion: We successfully constructed a model with high accuracy to predict PE. A combination of four peripheral leucocyte miRNAs has great potential to serve as diagnostic biomarkers of PE. PMID:26675000

Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

PubMed

Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

2016-03-01

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. © 2016 EAN.

Novel Biomarkers of Abdominal Aortic Aneurysm Disease: Identifying Gaps and Dispelling Misperceptions

PubMed Central

Moris, Demetrios; Avgerinos, Efthymios; Makris, Marinos; Bakoyiannis, Chris; Pikoulis, Emmanuel; Georgopoulos, Sotirios

2014-01-01

Abdominal aortic aneurysm (AAA) is a prevalent and potentially life-threatening disease. Early detection by screening programs and subsequent surveillance has been shown to be effective at reducing the risk of mortality due to aneurysm rupture. The aim of this review is to summarize the developments in the literature concerning the latest biomarkers (from 2008 to date) and their potential screening and therapeutic values. Our search included human studies in English and found numerous novel biomarkers under research, which were categorized in 6 groups. Most of these studies are either experimental or hampered by their low numbers of patients. We concluded that currently no specific laboratory markers allow screeing for the disease and monitoring its progression or the results of treatment. Further studies and studies in larger patient groups are required in order to validate biomarkers as cost-effective tools in the AAA disease. PMID:24967416

Identification and Validation of Potential New Biomarkers for Prostate Cancer Diagnosis and Prognosis Using 2D-DIGE and MS

PubMed Central

Geisler, Cordelia; Gaisa, Nadine T.; Pfister, David; Fuessel, Susanne; Kristiansen, Glen; Braunschweig, Till; Gostek, Sonja; Beine, Birte; Diehl, Hanna C.; Jackson, Angela M.; Borchers, Christoph H.; Heidenreich, Axel; Meyer, Helmut E.; Knüchel, Ruth; Henkel, Corinna

2015-01-01

This study was designed to identify and validate potential new biomarkers for prostate cancer and to distinguish patients with and without biochemical relapse. Prostate tissue samples analyzed by 2D-DIGE (two-dimensional difference in gel electrophoresis) and mass spectrometry (MS) revealed downregulation of secernin-1 (P < 0.044) in prostate cancer, while vinculin showed significant upregulation (P < 0.001). Secernin-1 overexpression in prostate tissue was validated using Western blot and immunohistochemistry while vinculin expression was validated using immunohistochemistry. These findings indicate that secernin-1 and vinculin are potential new tissue biomarkers for prostate cancer diagnosis and prognosis, respectively. For validation, protein levels in urine were also examined by Western blot analysis. Urinary vinculin levels in prostate cancer patients were significantly higher than in urine from nontumor patients (P = 0.006). Using multiple reaction monitoring-MS (MRM-MS) analysis, prostatic acid phosphatase (PAP) showed significant higher levels in the urine of prostate cancer patients compared to controls (P = 0.012), while galectin-3 showed significant lower levels in the urine of prostate cancer patients with biochemical relapse, compared to those without relapse (P = 0.017). Three proteins were successfully differentiated between patients with and without prostate cancer and patients with and without relapse by using MRM. Thus, this technique shows promise for implementation as a noninvasive clinical diagnostic technique. PMID:25667921

Improving the quality of biomarker discovery research: the right samples and enough of them.

PubMed

Pepe, Margaret S; Li, Christopher I; Feng, Ziding

2015-06-01

Biomarker discovery research has yielded few biomarkers that validate for clinical use. A contributing factor may be poor study designs. The goal in discovery research is to identify a subset of potentially useful markers from a large set of candidates assayed on case and control samples. We recommend the PRoBE design for selecting samples. We propose sample size calculations that require specifying: (i) a definition for biomarker performance; (ii) the proportion of useful markers the study should identify (Discovery Power); and (iii) the tolerable number of useless markers amongst those identified (False Leads Expected, FLE). We apply the methodology to a study of 9,000 candidate biomarkers for risk of colon cancer recurrence where a useful biomarker has positive predictive value ≥ 30%. We find that 40 patients with recurrence and 160 without recurrence suffice to filter out 98% of useless markers (2% FLE) while identifying 95% of useful biomarkers (95% Discovery Power). Alternative methods for sample size calculation required more assumptions. Biomarker discovery research should utilize quality biospecimen repositories and include sample sizes that enable markers meeting prespecified performance characteristics for well-defined clinical applications to be identified. The scientific rigor of discovery research should be improved. ©2015 American Association for Cancer Research.

Mass spectrometry for biomarker development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Chaochao; Liu, Tao; Baker, Erin Shammel

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.

Effects of Exercise on Select Biomarkers and Associated Outcomes in Chronic Pain Conditions: Systematic Review.

PubMed

Kawi, Jennifer; Lukkahatai, Nada; Inouye, Jillian; Thomason, Diane; Connelly, Kirsten

2016-03-01

Chronic pain is highly prevalent. Current management is challenged by lack of validated objective measures like biological markers. Clinical pain studies employing exercise interventions have evaluated biomarkers; however, it is unclear how exercise impacts biomarkers involved in pain pathways and whether these markers are associated with relevant pain-related outcomes. This systematic review evaluates data from clinical studies employing exercise interventions in chronic musculoskeletal nonmalignant pain conditions in which biomarkers in pain pathways were measured. Published research studies from several databases were examined using the Jadad Scale for assessing the quality of clinical studies. Twelve research studies were reviewed. Jadad scores ranged from 5 to 11 out of 13 points. Inflammatory markers were most commonly measured followed by neurotransmitter-related genes and metabolite-detecting genes. After exercise interventions, changes in biomarkers involved in neurotransmission and inflammation suggest a hypoalgesic exercise effect. Significant biomarker associations were found with pain intensity, fatigue, depression, anxiety, and quality of life. However, there were varying methodologies in the studies reviewed. It remains a question whether biomarkers can be used as objective measures for risk assessment, diagnosis, or evaluation or as surrogate endpoints in chronic pain. Adequate sample sizes, optimal exercise dose determination, study replications, and longitudinal research studies with consistent methodologies are warranted. Regardless, the potential translational value of biomarkers in chronic pain is evident. Advancing nursing research in biomarkers is vital for moving the nursing discipline and clinical chronic pain practice forward. Developing a biobehavioral perspective in chronic pain is also necessary for comprehensive management. © The Author(s) 2015.

Dietary biomarkers: advances, limitations and future directions

PubMed Central

2012-01-01

The subjective nature of self-reported dietary intake assessment methods presents numerous challenges to obtaining accurate dietary intake and nutritional status. This limitation can be overcome by the use of dietary biomarkers, which are able to objectively assess dietary consumption (or exposure) without the bias of self-reported dietary intake errors. The need for dietary biomarkers was addressed by the Institute of Medicine, who recognized the lack of nutritional biomarkers as a knowledge gap requiring future research. The purpose of this article is to review existing literature on currently available dietary biomarkers, including novel biomarkers of specific foods and dietary components, and assess the validity, reliability and sensitivity of the markers. This review revealed several biomarkers in need of additional validation research; research is also needed to produce sensitive, specific, cost-effective and noninvasive dietary biomarkers. The emerging field of metabolomics may help to advance the development of food/nutrient biomarkers, yet advances in food metabolome databases are needed. The availability of biomarkers that estimate intake of specific foods and dietary components could greatly enhance nutritional research targeting compliance to national recommendations as well as direct associations with disease outcomes. More research is necessary to refine existing biomarkers by accounting for confounding factors, to establish new indicators of specific food intake, and to develop techniques that are cost-effective, noninvasive, rapid and accurate measures of nutritional status. PMID:23237668

Skin carotenoids as biomarker for vegetable and fruit intake: Validation of the reflection-spectroscopy based “Veggie Meter”

USDA-ARS?s Scientific Manuscript database

Skin is a relatively stable storage medium for carotenoids; non-invasive optical measurements of carotenoids in this tissue via Resonance Raman spectroscopy (RRS) serve as a non-invasive biomarker for fruit and vegetable (F/V) intake. The RRS method has been validated with HPLC-based measurements of...

Biomarkers for Severity of Spinal Cord Injury in the Cerebrospinal Fluid of Rats

PubMed Central

Lubieniecka, Joanna M.; Streijger, Femke; Lee, Jae H. T.; Stoynov, Nikolay; Liu, Jie; Mottus, Randy; Pfeifer, Tom; Kwon, Brian K.; Coorssen, Jens R.; Foster, Leonard J.; Grigliatti, Thomas A.; Tetzlaff, Wolfram

2011-01-01

One of the major challenges in management of spinal cord injury (SCI) is that the assessment of injury severity is often imprecise. Identification of reliable, easily quantifiable biomarkers that delineate the severity of the initial injury and that have prognostic value for the degree of functional recovery would significantly aid the clinician in the choice of potential treatments. To find such biomarkers we performed quantitative liquid chromatography-mass spectrometry (LC-MS/MS) analyses of cerebrospinal fluid (CSF) collected from rats 24 h after either a moderate or severe SCI. We identified a panel of 42 putative biomarkers of SCI, 10 of which represent potential biomarkers of SCI severity. Three of the candidate biomarkers, Ywhaz, Itih4, and Gpx3 were also validated by Western blot in a biological replicate of the injury. The putative biomarkers identified in this study may potentially be a valuable tool in the assessment of the extent of spinal cord damage. PMID:21559420

BiomarCaRE: rationale and design of the European BiomarCaRE project including 300,000 participants from 13 European countries.

PubMed

Zeller, Tanja; Hughes, Maria; Tuovinen, Tarja; Schillert, Arne; Conrads-Frank, Annette; Ruijter, Hester den; Schnabel, Renate B; Kee, Frank; Salomaa, Veikko; Siebert, Uwe; Thorand, Barbara; Ziegler, Andreas; Breek, Heico; Pasterkamp, Gerard; Kuulasmaa, Kari; Koenig, Wolfgang; Blankenberg, Stefan

2014-10-01

Biomarkers are considered as tools to enhance cardiovascular risk estimation. However, the value of biomarkers on risk estimation beyond European risk scores, their comparative impact among different European regions and their role towards personalised medicine remains uncertain. Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE) is an European collaborative research project with the primary objective to assess the value of established and emerging biomarkers for cardiovascular risk prediction. BiomarCaRE integrates clinical and epidemiological biomarker research and commercial enterprises throughout Europe to combine innovation in biomarker discovery for cardiovascular disease prediction with consecutive validation of biomarker effectiveness in large, well-defined primary and secondary prevention cohorts including over 300,000 participants from 13 European countries. Results from this study will contribute to improved cardiovascular risk prediction across different European populations. The present publication describes the rationale and design of the BiomarCaRE project.

Urinary Excretion of Sodium, Nitrogen, and Sugar Amounts Are Valid Biomarkers of Dietary Sodium, Protein, and High Sugar Intake in Nonobese Adolescents.

PubMed

Moore, Lori B; Liu, Sarah V; Halliday, Tanya M; Neilson, Andrew P; Hedrick, Valisa E; Davy, Brenda M

2017-12-01

Background: Objective indicators of dietary intake (e.g., biomarkers) are needed to overcome the limitations of self-reported dietary intake assessment methods in adolescents. To our knowledge, no controlled feeding studies to date have evaluated the validity of urinary sodium, nitrogen, or sugar excretion as dietary biomarkers in adolescents. Objective: This investigation aimed to evaluate the validity of urinary sodium, nitrogen, and total sugars (TS) excretion as biomarkers for sodium, protein, and added sugars (AS) intake in nonobese adolescents. Methods: In a crossover controlled feeding study design, 33 adolescents [12-18 y of age, 47 ± 25th percentile (mean ± SD) of body mass index (BMI; in kg/m 2 ) for age] consumed 5% AS [low added sugars (LAS)] and 25% AS [high added sugars (HAS)] isocaloric, macronutrient-matched (55% carbohydrate, 30% fat, and 15% protein) diets for 7 d each, in a randomly assigned order, with a 4-wk washout period between diets. On the final 2 d of each diet period, 24-h urine samples were collected. Thirty-two adolescents completed all measurements (97% retention). Results: Urinary sodium was not different from the expected 90% recovery (mean ± SD: 88% ± 18%, P = 0.50). Urinary nitrogen was correlated with protein intake ( r = 0.69, P < 0.001), although it was below the 80% expected recovery (62% ± 7%, P < 0.001). Urinary TS values were correlated with AS intake during the HAS diet ( r = 0.77, P < 0.001) and had a higher R 2 value of 0.28 than did AS intake ( R 2 = 0.36). TS excretion differed between LAS (0.226 ± 0.09 mg/d) and HAS (0.365 ± 0.16 mg/d) feeding periods ( P < 0.001). Conclusions: Urinary sodium appears to be a valid biomarker for sodium intake in nonobese adolescents. Urinary nitrogen is associated with protein intake, but nitrogen excretion rates were less than previously reported for adults, possibly owing to adolescent growth rates. TS excretion reflects AS at 25% AS intake and was responsive to the change in AS intake. Thus, urinary biomarkers are promising objective indicators of dietary intake in adolescents, although larger-scale feeding trials are needed to confirm these findings. This trial was registered at clinicaltrials.gov as NCT02455388. © 2017 American Society for Nutrition.

Biomarkers in Sports and Exercise: Tracking Health, Performance, and Recovery in Athletes.

PubMed

Lee, Elaine C; Fragala, Maren S; Kavouras, Stavros A; Queen, Robin M; Pryor, John Luke; Casa, Douglas J

2017-10-01

Biomarker discovery and validation is a critical aim of the medical and scientific community. Research into exercise and diet-related biomarkers aims to improve health, performance, and recovery in military personnel, athletes, and lay persons. Exercise physiology research has identified individual biomarkers for assessing health, performance, and recovery during exercise training. However, there are few recommendations for biomarker panels for tracking changes in individuals participating in physical activity and exercise training programs. Our approach was to review the current literature and recommend a collection of validated biomarkers in key categories of health, performance, and recovery that could be used for this purpose. We determined that a comprehensive performance set of biomarkers should include key markers of (a) nutrition and metabolic health, (b) hydration status, (c) muscle status, (d) endurance performance, (e) injury status and risk, and (f) inflammation. Our review will help coaches, clinical sport professionals, researchers, and athletes better understand how to comprehensively monitor physiologic changes, as they design training cycles that elicit maximal improvements in performance while minimizing overtraining and injury risk.

Qualification of imaging biomarkers for oncology drug development.

PubMed

Waterton, John C; Pylkkanen, Liisa

2012-03-01

Although many imaging biomarkers have been described for cancer research, few are sufficiently robust, reliable and well-characterised to be used as routine tools in clinical cancer research. In particular, biomarkers which show that investigational therapies have reduced tumour cell proliferation, or induced necrotic or apoptotic cell death are not commonly used to support decision-making in drug development, even though such pharmacodynamic effects are common goals of many classes of investigational drugs. Moreover we lack well-qualified biomarkers of propensity to metastasise. The qualification and technical validation of imaging biomarkers poses unique challenges not always encountered when validating biospecimen biomarkers. These include standardisation of acquisition and analysis, imaging-pathology correlation, cross-sectional clinical-biomarker correlations and correlation with outcome. Such work is ideally suited to precompetitive research and public-private partnerships, and this has been recognised within the Innovative Medicines Initiative (IMI), a Joint Undertaking between the European Union and the European Federation of Pharmaceutical Industries and Associations, which has initiated projects in the areas of drug safety, drug efficacy, knowledge management and training. Copyright © 2011 Elsevier Ltd. All rights reserved.

Harnessing pain heterogeneity and RNA transcriptome to identify blood-based pain biomarkers: a novel correlational study design and bioinformatics approach in a graded chronic constriction injury model.

PubMed

Grace, Peter M; Hurley, Daniel; Barratt, Daniel T; Tsykin, Anna; Watkins, Linda R; Rolan, Paul E; Hutchinson, Mark R

2012-09-01

A quantitative, peripherally accessible biomarker for neuropathic pain has great potential to improve clinical outcomes. Based on the premise that peripheral and central immunity contribute to neuropathic pain mechanisms, we hypothesized that biomarkers could be identified from the whole blood of adult male rats, by integrating graded chronic constriction injury (CCI), ipsilateral lumbar dorsal quadrant (iLDQ) and whole blood transcriptomes, and pathway analysis with pain behavior. Correlational bioinformatics identified a range of putative biomarker genes for allodynia intensity, many encoding for proteins with a recognized role in immune/nociceptive mechanisms. A selection of these genes was validated in a separate replication study. Pathway analysis of the iLDQ transcriptome identified Fcγ and Fcε signaling pathways, among others. This study is the first to employ the whole blood transcriptome to identify pain biomarker panels. The novel correlational bioinformatics, developed here, selected such putative biomarkers based on a correlation with pain behavior and formation of signaling pathways with iLDQ genes. Future studies may demonstrate the predictive ability of these biomarker genes across other models and additional variables. © 2012 The Authors. Journal of Neurochemistry © 2012 International Society for Neurochemistry.

A Roadmap for the Development and Validation of ERP Biomarkers in Schizophrenia Research

PubMed Central

Luck, Steven J.; Mathalon, Daniel H.; O'Donnell, Brian F.; Hämäläinen, Matti S.; Spencer, Kevin M.; Javitt, Daniel C.; Uhlhaas, Peter J.

2010-01-01

New efforts to develop treatments for cognitive dysfunction in mental illnesses would benefit enormously from biomarkers that provide sensitive and reliable measures of the neural events underlying cognition. Here we evaluate the promise of event-related potentials (ERPs) as biomarkers of cognitive dysfunction in schizophrenia. We conclude that ERPs have several desirable properties: (a) they provide a direct measure of electrical activity during neurotransmission; (b) their high temporal resolutions makes it possible to measure neural synchrony and oscillations; (c) they are relatively inexpensive and convenient to record; (d) animal models are readily available for several ERP components; (e) decades of research has established the sensitivity and reliability of ERP measures in psychiatric illnesses; and (f) feasibility of large N (>500) multi-site studies has been demonstrated for key measures. Consequently, ERPs may be useful for identifying endophenotypes and defining treatment targets, for evaluating new compounds in animals and in humans, and for identifying individuals who are good candidates for early interventions or for specific treatments. However, several challenges must be overcome before ERPs gain widespread use as biomarkers in schizophrenia research, and we make several recommendations for the research that is necessary to develop and validate ERP-based biomarkers that can have a real impact on treatment development. PMID:21111401

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

PubMed

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

2015-11-01

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

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

PubMed

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

2016-11-30

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

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

Tolerance Signatures in Transplant Recipients

PubMed Central

Newell, Kenneth A.; Turka, Laurence A.

2015-01-01

Purpose of review The intent of this review is to describe biomarkers that predict or identify individuals who exhibit tolerance to a transplanted organ. The identification of tolerance biomarkers would spare some individuals the toxicity of immunosuppressive agents, enhance the safety of studies to induce tolerance, and provide insights into mechanisms of tolerance that may aid in designing new regimens. Recent findings Studies of tolerant kidney transplant recipients have revealed an association with B cells. More recent studies have suggested that these B cells may be less mature than from those in nontolerant recipients, and specially suited to suppress alloimmune responses. Biomarkers in tolerant liver transplant patients appear to be distinct from those associated renal tolerance. Most reports have identified an association with NK and/or γδ T cells rather than B cells. Recent data indicate biomarkers associated with iron homeostasis within the transplanted liver more accurately predict the tolerant state than do biomarkers expressed in the blood, suggesting that the renal allograft itself, which is infrequently sampled, would be informative. Summary Given the encouraging progress in identifying tolerance biomarkers, it will be important to validate these markers in larger studies of transplant recipients undergoing prospective minimization or withdrawal of immunosuppression. PMID:26107969

Current status and recommendations for biomarkers and biobanking in neurofibromatosis.

PubMed

Hanemann, C Oliver; Blakeley, Jaishri O; Nunes, Fabio P; Robertson, Kent; Stemmer-Rachamimov, Anat; Mautner, Victor; Kurtz, Andreas; Ferguson, Michael; Widemann, Brigitte C; Evans, D Gareth; Ferner, Rosalie; Carroll, Steven L; Korf, Bruce; Wolkenstein, Pierre; Knight, Pamela; Plotkin, Scott R

2016-08-16

Clinically validated biomarkers for neurofibromatosis 1 (NF1), neurofibromatosis 2 (NF2), and schwannomatosis (SWN) have not been identified to date. The biomarker working group's goals are to (1) define biomarker needs in NF1, NF2, and SWN; (2) summarize existing data on biomarkers in NF1, NF2, and SWN; (3) outline recommendations for sample collection and biomarker development; and (4) standardize sample collection and methodology protocols where possible to promote comparison between studies by publishing standard operating procedures (SOPs). The biomarker group reviewed published data on biomarkers in NF1, NF2, and SWN and on biobanking efforts outside these diseases via literature search, defined the need for biomarkers in NF, and developed recommendations in a series of consensus meetings. We describe existing biomarkers in NF and report consensus recommendations for SOP and a minimal clinical dataset to accompany samples derived from patients with NF1, NF2, and SWN in decentralized biobanks. These recommendations are intended to provide clinicians and researchers with a common set of guidelines to collect and store biospecimens and for establishment of biobanks for NF1, NF2, and SWN. © 2016 American Academy of Neurology.

Current status and recommendations for biomarkers and biobanking in neurofibromatosis

PubMed Central

Blakeley, Jaishri O.; Nunes, Fabio P.; Robertson, Kent; Stemmer-Rachamimov, Anat; Mautner, Victor; Kurtz, Andreas; Ferguson, Michael; Widemann, Brigitte C.; Evans, D. Gareth; Ferner, Rosalie; Carroll, Steven L.; Korf, Bruce; Wolkenstein, Pierre; Knight, Pamela; Plotkin, Scott R.

2016-01-01

Objective: Clinically validated biomarkers for neurofibromatosis 1 (NF1), neurofibromatosis 2 (NF2), and schwannomatosis (SWN) have not been identified to date. The biomarker working group's goals are to (1) define biomarker needs in NF1, NF2, and SWN; (2) summarize existing data on biomarkers in NF1, NF2, and SWN; (3) outline recommendations for sample collection and biomarker development; and (4) standardize sample collection and methodology protocols where possible to promote comparison between studies by publishing standard operating procedures (SOPs). Methods: The biomarker group reviewed published data on biomarkers in NF1, NF2, and SWN and on biobanking efforts outside these diseases via literature search, defined the need for biomarkers in NF, and developed recommendations in a series of consensus meetings. Results: We describe existing biomarkers in NF and report consensus recommendations for SOP and a minimal clinical dataset to accompany samples derived from patients with NF1, NF2, and SWN in decentralized biobanks. Conclusions: These recommendations are intended to provide clinicians and researchers with a common set of guidelines to collect and store biospecimens and for establishment of biobanks for NF1, NF2, and SWN. PMID:27527649

Criteria of validity for animal models of psychiatric disorders: focus on anxiety disorders and depression

PubMed Central

2011-01-01

Animal models of psychiatric disorders are usually discussed with regard to three criteria first elaborated by Willner; face, predictive and construct validity. Here, we draw the history of these concepts and then try to redraw and refine these criteria, using the framework of the diathesis model of depression that has been proposed by several authors. We thus propose a set of five major criteria (with sub-categories for some of them); homological validity (including species validity and strain validity), pathogenic validity (including ontopathogenic validity and triggering validity), mechanistic validity, face validity (including ethological and biomarker validity) and predictive validity (including induction and remission validity). Homological validity requires that an adequate species and strain be chosen: considering species validity, primates will be considered to have a higher score than drosophila, and considering strains, a high stress reactivity in a strain scores higher than a low stress reactivity in another strain. Pathological validity corresponds to the fact that, in order to shape pathological characteristics, the organism has been manipulated both during the developmental period (for example, maternal separation: ontopathogenic validity) and during adulthood (for example, stress: triggering validity). Mechanistic validity corresponds to the fact that the cognitive (for example, cognitive bias) or biological mechanisms (such as dysfunction of the hormonal stress axis regulation) underlying the disorder are identical in both humans and animals. Face validity corresponds to the observable behavioral (ethological validity) or biological (biomarker validity) outcomes: for example anhedonic behavior (ethological validity) or elevated corticosterone (biomarker validity). Finally, predictive validity corresponds to the identity of the relationship between the triggering factor and the outcome (induction validity) and between the effects of the treatments on the two organisms (remission validity). The relevance of this framework is then discussed regarding various animal models of depression. PMID:22738250

Adaptation of commercial biomarker kits and proposal for 'drug development kits' to support bioanalysis: call for action.

PubMed

Islam, Rafiqul; Kar, Sumit; Islam, Clarinda; Farmen, Raymond

2018-06-01

There has been an increased use of commercial kits for biomarker measurement, commensurate with the increased demand for biomarkers in drug development. However, in most cases these kits do not meet the quality attributes for use in regulated environment. The process for adaptation of these kits can be frustrating, time consuming and resource intensive. In addition, a lack of harmonized guidance for the validation of biomarker poses a significant challenge in the adaptation of kits in a regulated environment. The purpose of this perspective is to propose a tiered approach to commercial drug development kits with clearly defined quality attributes and to demonstrate how these kits can be adapted to perform analytical validation in a regulated environment.

Inflammatory mediators as biomarkers in brain disorders.

PubMed

Nuzzo, Domenico; Picone, Pasquale; Caruana, Luca; Vasto, Sonya; Barera, Annalisa; Caruso, Calogero; Di Carlo, Marta

2014-06-01

Neurodegenerative diseases such as Alzheimer, Parkinson, amyotrophic lateral sclerosis, and Huntington are incurable and debilitating conditions that result in progressive death of the neurons. The definite diagnosis of a neurodegenerative disorder is disadvantaged by the difficulty in obtaining biopsies and thereby to validate the clinical diagnosis with pathological results. Biomarkers are valuable indicators for detecting different phases of a disease such as prevention, early onset, treatment, progression, and monitoring the effect of pharmacological responses to a therapeutic intervention. Inflammation occurs in neurodegenerative diseases, and identification and validation of molecules involved in this process could be a strategy for finding new biomarkers. The ideal inflammatory biomarker needs to be easily measurable, must be reproducible, not subject to wide variation in the population, and unaffected by external factors. Our review summarizes the most important inflammation biomarkers currently available, whose specificity could be utilized for identifying and monitoring distinctive phases of different neurodegenerative diseases.

Development and validation of empirical indices to assess the insulinemic potential of diet and lifestyle

PubMed Central

Tabung, Fred K.; Wang, Weike; Fung, Teresa T.; Hu, Frank B.; Smith-Warner, Stephanie A.; Chavarro, Jorge E.; Fuchs, Charles S.; Willett, Walter C.; Giovannucci, Edward L.

2017-01-01

The glycemic and insulin indices assess postprandial glycemic and insulin response to foods respectively, which may not reflect the long-term effects of diet on insulin response. We developed and evaluated the validity of four empirical indices to assess the insulinemic potential of usual diets and lifestyles, using dietary, lifestyle and biomarker data from the Nurses’ Health Study (NHS, n=5,812 for hyperinsulinemia, n=3,929 for insulin resistance). The four indices were: the empirical dietary index for hyperinsulinemia (EDIH) and empirical lifestyle index for hyperinsulinemia (ELIH); empirical dietary index for insulin resistance (EDIR) and empirical lifestyle index for insulin resistance (ELIR). We entered 39 food frequency questionnaire-derived food groups in stepwise linear regression models and defined indices as the patterns most predictive of fasting plasma C-peptide, for the hyperinsulinemia pathway (EDIH and ELIH); and of the triglyceride/high density lipoprotein-cholesterol (TG/HDL) ratio, for the insulin resistance pathway (EDIR and ELIR). We evaluated the validity of indices in two independent samples from NHS-II and Health Professionals Follow-up Study (HPFS) using multivariable-adjusted linear regression analyses to calculate relative concentrations of biomarkers. EDIH is comprised of 18 food groups; 13 were positively associated with C-peptide, five inversely. EDIR is comprised of 18 food groups; ten were positively associated with TG/HDL and eight inversely. Lifestyle indices had fewer dietary components, and included BMI and physical activity as components. In the validation samples, all indices significantly predicted biomarker concentrations, e.g., the relative concentrations (95%CI) of the corresponding biomarkers comparing extreme index quintiles in HPFS were: EDIH, 1.29(1.22, 1.37); ELIH, 1.78(1.68, 1.88); EDIR, 1.44(1.34, 1.55); ELIR, 2.03(1.89, 2.19); all P-trend<0.0001. The robust associations of these novel hypothesis-driven indices with insulin response biomarker concentrations suggests their usefulness in assessing the ability of whole diets and lifestyles to stimulate and/or sustain insulin secretion. PMID:27821188

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 might be added to the list of known entities applicable in immunotherapy trials. The need for a systematic approach to biomarker discovery that takes advantage of powerful high-throughput technologies was recognized; it was clear from the current state of the science that immunotherapy is still in a discovery phase and only a few of the current biomarkers warrant extensive validation. It was, finally, clear that, while current technologies have almost limitless potential, inadequate study design, limited standardization and cross-validation among laboratories and suboptimal comparability of data remain major road blocks. The institution of an interactive consortium for high throughput molecular monitoring of clinical trials with voluntary participation might provide cost-effective solutions. PMID:19534815

The Biomarker Knowledge System Informatics Pilot Project Supplement To The Biomarker Development Laboratory at Moffitt (Bedlam) — EDRN Public Portal

Cancer.gov

The Biomarker Knowledge System Informatics Pilot Project goal will develop network interfaces among databases that contain information about existing clinical populations and biospecimens and data relating to those specimens that are important in biomarker assay validation. This protocol comprises one of two that will comprise the Moffitt participation in the Biomarker Knowledge System Informatics Pilot Project. THIS PROTOCOL (58) is the Sput-Epi Database.

Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis.

PubMed

Bos, L D; Schouten, L R; van Vught, L A; Wiewel, M A; Ong, D S Y; Cremer, O; Artigas, A; Martin-Loeches, I; Hoogendijk, A J; van der Poll, T; Horn, J; Juffermans, N; Calfee, C S; Schultz, M J

2017-10-01

We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Two phenotypes were identified in 454 patients, which we named 'uninflamed' (N=218) and 'reactive' (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The 'reactive phenotype' was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31). Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A new biomarker panel in bronchoalveolar lavage for an improved lung cancer diagnosis.

PubMed

Uribarri, María; Hormaeche, Itsaso; Zalacain, Rafael; Lopez-Vivanco, Guillermo; Martinez, Antonio; Nagore, Daniel; Ruiz-Argüello, M Begoña

2014-10-01

The enormous biological complexity and high mortality rate of lung cancer highlights the need for new global approaches for the discovery of reliable early diagnostic biomarkers. The study of bronchoalveolar lavage samples by proteomic techniques could identify new lung cancer biomarkers and may provide promising noninvasive diagnostic tools able to enhance the sensitivity of current methods. First, an observational prospective study was designed to assess protein expression differences in bronchoalveolar lavages from patients with (n = 139) and without (n = 49) lung cancer, using two-dimensional gel electrophoresis and subsequent protein identification by mass spectrometry. Second, validation of candidate biomarkers was performed by bead-based immunoassays with a different patient cohort (204 patients, 48 controls). Thirty-two differentially expressed proteins were identified in bronchoalveolar lavages, 10 of which were confirmed by immunoassays. The expression levels of APOA1, CO4A, CRP, GSTP1, and SAMP led to a lung cancer diagnostic panel that reached 95% sensitivity and 81% specificity, and the quantification of STMN1 and GSTP1 proteins allowed the two main lung cancer subtypes to be discriminated with 90% sensitivity and 57% specificity. Bronchoalveolar lavage represents a promising noninvasive source of lung cancer specific protein biomarkers with high diagnostic accuracy. Measurement of APOA1, CO4A, CRP, GSTP1, SAMP, and STMN1 in this fluid may be a useful tool for lung cancer diagnosis, although a further validation in a larger clinical set is required for early stages.

Blood Sampling and Preparation Procedures for Proteomic Biomarker Studies of Psychiatric Disorders.

PubMed

Guest, Paul C; Rahmoune, Hassan

2017-01-01

A major challenge in proteomic biomarker discovery and validation for psychiatric diseases is the inherent biological complexity underlying these conditions. There are also many technical issues which hinder this process such as the lack of standardization in sampling, processing and storage of bio-samples in preclinical and clinical settings. This chapter describes a reproducible procedure for sampling blood serum and plasma that is specifically designed for maximizing data quality output in two-dimensional gel electrophoresis, multiplex immunoassay and mass spectrometry profiling studies.

The Potential Utility of Urinary Biomarkers for Risk Prediction in Combat Casualties: A Prospective Observational Cohort Study

DTIC Science & Technology

2015-06-16

are associated with poor outcomes, including death and the need for renal replacement therapy. Methods : We conducted a prospective, observational study...penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 16 JUN 2015...2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE The Potential Utility of Urinary Biomarkers for Risk Prediction in Combat

Minimally-invasive biomarker studies in eosinophilic esophagitis: a systematic review.

PubMed

Hines, Brittany T; Rank, Matthew A; Wright, Benjamin L; Marks, Lisa A; Hagan, John B; Straumann, Alex; Greenhawt, Matthew; Dellon, Evan S

2018-05-10

Eosinophilic esophagitis (EoE) is a chronic, inflammatory disease of the esophagus which currently requires repeated endoscopic biopsies for diagnosis and monitoring as no reliable non-invasive markers have been identified. To identify promising minimally-invasive EoE biomarkers and remaining gaps in biomarker validation. We performed a systematic review of EMBASE, Ovid Medline, PubMed, and Web of Science from inception to June 6, 2017. Studies were included if subjects met the 2007 consensus criteria for EoE diagnosis, a minimally-invasive biomarker was assessed, and the study included at least 1 control for comparison. The search identified 2094 studies, with 234 reviewed at full text level, and 49 included in the analysis (20 adult, 19 pediatric, 7 pediatric and adult, and 3 not stated). The majority (26 of 49) were published after 2014. Thirty-five studies included normal controls, 9 analyzed atopic controls, and 29 compared samples from subjects with active and inactive EoE. Minimally-invasive biomarkers were obtained from peripheral blood (n=41 studies), sponge/string samples (3), oral/throat swab secretions (2), breath condensate (2), stool (2), and urine (2). The most commonly reported biomarkers were peripheral blood eosinophils (16), blood and string eosinophil granule proteins (14), and eosinophil surface or intracellular markers (12). EoE biomarkers distinguished active EoE from normal controls in 23 studies, atopic controls in 2 studies, and inactive EoE controls in 20 studies. Several promising minimally-invasive biomarkers for EoE have emerged; however, few are able to differentiate EoE from other atopic diseases. Copyright © 2018. Published by Elsevier Inc.

Leveraging molecular datasets for biomarker-based clinical trial design in glioblastoma.

PubMed

Tanguturi, Shyam K; Trippa, Lorenzo; Ramkissoon, Shakti H; Pelton, Kristine; Knoff, David; Sandak, David; Lindeman, Neal I; Ligon, Azra H; Beroukhim, Rameen; Parmigiani, Giovanni; Wen, Patrick Y; Ligon, Keith L; Alexander, Brian M

2017-07-01

Biomarkers can improve clinical trial efficiency, but designing and interpreting biomarker-driven trials require knowledge of relationships among biomarkers, clinical covariates, and endpoints. We investigated these relationships across genomic subgroups of glioblastoma (GBM) within our institution (DF/BWCC), validated results in The Cancer Genome Atlas (TCGA), and demonstrated potential impacts on clinical trial design and interpretation. We identified genotyped patients at DF/BWCC, and clinical associations across 4 common GBM genomic biomarker groups were compared along with overall survival (OS), progression-free survival (PFS), and survival post-progression (SPP). Significant associations were validated in TCGA. Biomarker-based clinical trials were simulated using various assumptions. Epidermal growth factor receptor (EGFR)(+) and p53(-) subgroups were more likely isocitrate dehydrogenase (IDH) wild-type. Phosphatidylinositol-3 kinase (PI3K)(+) patients were older, and patients with O6-DNA methylguanine-methyltransferase (MGMT)-promoter methylation were more often female. OS, PFS, and SPP were all longer for IDH mutant and MGMT methylated patients, but there was no independent prognostic value for other genomic subgroups. PI3K(+) patients had shorter PFS among IDH wild-type tumors, however, and no DF/BWCC long-term survivors were either EGFR(+) (0% vs 7%, P = .014) or p53(-) (0% vs 10%, P = .005). The degree of biomarker overlap impacted the efficiency of Bayesian-adaptive clinical trials, while PFS and OS distribution variation had less impact. Biomarker frequency was proportionally associated with sample size in all designs. We identified several associations between GBM genomic subgroups and clinical or molecular prognostic covariates and validated known prognostic factors in all survival periods. These results are important for biomarker-based trial design and interpretation of biomarker-only and nonrandomized trials. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

10th EDRN Scientific Workshop | Division of Cancer Prevention

Cancer.gov

This year's event entitled, "Cancer Biomarkers in Precision Medicine" will include both lectures and panel debates. The topics of the workshop include discussions on standards and regulatory science, novel technologies for precision detection, imaging, clinical and validation science, alliances and consortia on biomarkers, non-profit foundations support for biomarkers. Agenda

Horizon 2020 SME-Instrument topic: clinical research for the validation of biomarkers and/or diagnostic medical devices.

PubMed

Sanne, Jean-Luc

2018-06-21

The European Commission released €130 million over 2014, 2015 and 2017 under the EU Framework Program for Research and Innovation, Horizon 2020, to support innovative small and medium-sized enterprises in the diagnostic area. The call topic focused on 'Clinical research for the validation of biomarkers and/or diagnostic medical devices'. It attracted 1194 applicants from all over Europe. The quality of the proposals was high and a large proportion of them were eligible for funding. In the majority, proposals were about in vitro diagnostics and tackled both clinical validation of new biomarkers and device optimization. The proposals dealt with various advanced technologies. One third of the proposers gave priority to the new and promising field of personalized medicine.

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE PAGES

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; ...

2013-01-01

Background . The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective . To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods . The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expertmore » knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results . The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions . Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

PubMed Central

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Varnum, Susan M.; Brown, Joseph N.; Riensche, Roderick M.; Adkins, Joshua N.; Jacobs, Jon M.; Hoidal, John R.; Scholand, Mary Beth; Pounds, Joel G.; Blackburn, Michael R.; Rodland, Karin D.; McDermott, Jason E.

2013-01-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integrated into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification. PMID:24223463

A Semiautomated Framework for Integrating Expert Knowledge into Disease Marker Identification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jing; Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.

2013-10-01

Background. The availability of large complex data sets generated by high throughput technologies has enabled the recent proliferation of disease biomarker studies. However, a recurring problem in deriving biological information from large data sets is how to best incorporate expert knowledge into the biomarker selection process. Objective. To develop a generalizable framework that can incorporate expert knowledge into data-driven processes in a semiautomated way while providing a metric for optimization in a biomarker selection scheme. Methods. The framework was implemented as a pipeline consisting of five components for the identification of signatures from integrated clustering (ISIC). Expert knowledge was integratedmore » into the biomarker identification process using the combination of two distinct approaches; a distance-based clustering approach and an expert knowledge-driven functional selection. Results. The utility of the developed framework ISIC was demonstrated on proteomics data from a study of chronic obstructive pulmonary disease (COPD). Biomarker candidates were identified in a mouse model using ISIC and validated in a study of a human cohort. Conclusions. Expert knowledge can be introduced into a biomarker discovery process in different ways to enhance the robustness of selected marker candidates. Developing strategies for extracting orthogonal and robust features from large data sets increases the chances of success in biomarker identification.« less

Metabolomics as a tool in the identification of dietary biomarkers.

PubMed

Gibbons, Helena; Brennan, Lorraine

2017-02-01

Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

Biomarkers in Prodromal Parkinson Disease: a Qualitative Review.

PubMed

Cooper, Christine A; Chahine, Lama M

2016-11-01

Over the past several years, the concept of prodromal Parkinson disease (PD) has been increasingly recognized. This term refers to individuals who do not fulfill motor diagnostic criteria for PD, but who have clinical, genetic, or biomarker characteristics suggesting risk of developing PD in the future. Clinical diagnosis of prodromal PD has low specificity, prompting the need for objective biomarkers with higher specificity. In this qualitative review, we discuss objectively defined putative biomarkers for PD and prodromal PD. We searched Pubmed and Embase for articles pertaining to objective biomarkers for PD and their application in prodromal cohorts. Articles were selected based on relevance and methodology. Objective biomarkers of demonstrated utility in prodromal PD include ligand-based imaging and transcranial sonography. Development of serum, cerebrospinal fluid, and tissue-based biomarkers is underway, but their application in prodromal PD has yet to meaningfully occur. Combining objective biomarkers with clinical or genetic prodromal features increases the sensitivity and specificity for identifying prodromal PD. Several objective biomarkers for prodromal PD show promise but require further study, including their application to and validation in prodromal cohorts followed longitudinally. Accurate identification of prodromal PD will likely require a multimodal approach. (JINS, 2016, 22, 956-967).

Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

PubMed

Magdalinou, N K; Noyce, A J; Pinto, R; Lindstrom, E; Holmén-Larsson, J; Holtta, M; Blennow, K; Morris, H R; Skillbäck, T; Warner, T T; Lees, A J; Pike, I; Ward, M; Zetterberg, H; Gobom, J

2017-04-01

Neurodegenerative parkinsonian syndromes have significant clinical and pathological overlap, making early diagnosis difficult. Cerebrospinal fluid (CSF) biomarkers may aid the differentiation of these disorders, but other than α-synuclein and neurofilament light chain protein, which have limited diagnostic power, specific protein biomarkers remain elusive. To study disease mechanisms and identify possible CSF diagnostic biomarkers through discovery proteomics, which discriminate parkinsonian syndromes from healthy controls. CSF was collected consecutively from 134 participants; Parkinson's disease (n = 26), atypical parkinsonian syndromes (n = 78, including progressive supranuclear palsy (n = 36), multiple system atrophy (n = 28), corticobasal syndrome (n = 14)), and elderly healthy controls (n = 30). Participants were divided into a discovery and a validation set for analysis. The samples were subjected to tryptic digestion, followed by liquid chromatography-mass spectrometry analysis for identification and relative quantification by isobaric labelling. Candidate protein biomarkers were identified based on the relative abundances of the identified tryptic peptides. Their predictive performance was evaluated by analysis of the validation set. 79 tryptic peptides, derived from 26 proteins were found to differ significantly between atypical parkinsonism patients and controls. They included acute phase/inflammatory markers and neuronal/synaptic markers, which were respectively increased or decreased in atypical parkinsonism, while their levels in PD subjects were intermediate between controls and atypical parkinsonism. Using an unbiased proteomic approach, proteins were identified that were able to differentiate atypical parkinsonian syndrome patients from healthy controls. Our study indicates that markers that may reflect neuronal function and/or plasticity, such as the amyloid precursor protein, and inflammatory markers may hold future promise as candidate biomarkers in parkinsonism. Copyright © 2017. Published by Elsevier Ltd.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

PubMed Central

Hervé, Mylène; Bergon, Aurélie; Le Guisquet, Anne-Marie; Leman, Samuel; Consoloni, Julia-Lou; Fernandez-Nunez, Nicolas; Lefebvre, Marie-Noëlle; El-Hage, Wissam; Belzeaux, Raoul; Belzung, Catherine; Ibrahim, El Chérif

2017-01-01

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD. PMID:28848385

Implications of the Institute of Medicine Report: Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease.

PubMed

Wagner, J A; Ball, J R

2015-07-01

The Institute of Medicine (IOM) released a groundbreaking 2010 report, Evaluation of Biomarkers and Surrogate Endpoints in Chronic Disease. Key recommendations included a harmonized scientific process and a general framework for biomarker evaluation with three interrelated steps: (1) Analytical validation -- is the biomarker measurement accurate? (2) Qualification -- is the biomarker associated with the clinical endpoint of concern? (3) Utilization -- what is the specific context of the proposed use? © 2015 American Society for Clinical Pharmacology and Therapeutics.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodland, Karin D.

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].

Circulating exosomal miR-27a and miR-130a act as novel diagnostic and prognostic biomarkers of colorectal cancer.

PubMed

Wang, Shukui; Liu, Xiangxiang; Pan, Bei; Sun, Li; Chen, Xiaoxiang; Zeng, Kaixuan; Hu, Xiuxiu; Xu, Tao; Xu, Mu

2018-05-08

Colorectal cancer (CRC) is one of the most common cancers worldwide usually with poor prognosis due to the advanced stage when diagnosed. This study aimed to investigate whether specific circulating exosomal miRNAs could act as biomarkers for early diagnosis of CRC. A total of 369 peripheral blood samples were included in this study. In the discovery phase, circulating exosomal miR-27a and miR-130a were selected after synthetical analysis of two GEO datasets and TCGA database. The differential expression and diagnostic utility of miR-27a and miR-130a panel were validated using quantitative reverse-transcriptase PCR (qRT-PCR) and Receiver operating characteristic (ROC) curve analysis in subsequent training phase, validation phase and external validation phase. The prognosis of circulating exosomal miR-27a and miR-130a were investigated using the Kaplan-Meier method. The expression of exosomal miR-27a and miR-130a in plasma significantly increased in CRC. The area under ROC curves (AUCs) of miR-27a (miR-130a) were 0.773 (0.742) in the training phase, 0.82 (0.787) in the validation phase, and 0.746 (0.697) in the external validation phase. The combination of two miRNAs presented higher diagnostic utility for CRC (AUCs = 0.846, 0.898 and 0.801 for the training, validation, and external validation phases, respectively). CRC patients with high expression of circulating exosomal miR-27a or miR-130a underwent poorer prognosis. We identified a circulating exosomal miRNAs panel for the detection of CRC. The exosomal miR-27a and miR-130a panel in plasma may act as a non-invasive biomarker for early detection and predicting prognosis of CRC. Copyright ©2018, American Association for Cancer Research.

Diagnostic accuracy of pulmonary host inflammatory mediators in the exclusion of ventilator-acquired pneumonia

PubMed Central

Hellyer, Thomas P; Conway Morris, Andrew; McAuley, Daniel F; Walsh, Timothy S; Anderson, Niall H; Singh, Suveer; Dark, Paul; Roy, Alistair I; Baudouin, Simon V; Wright, Stephen E; Perkins, Gavin D; Kefala, Kallirroi; Jeffels, Melinda; McMullan, Ronan; O'Kane, Cecilia M; Spencer, Craig; Laha, Shondipon; Robin, Nicole; Gossain, Savita; Gould, Kate; Ruchaud-Sparagano, Marie-Hélène; Scott, Jonathan; Browne, Emma M; MacFarlane, James G; Wiscombe, Sarah; Widdrington, John D; Dimmick, Ian; Laurenson, Ian F; Nauwelaers, Frans; Simpson, A John

2015-01-01

Background Excessive use of empirical antibiotics is common in critically ill patients. Rapid biomarker-based exclusion of infection may improve antibiotic stewardship in ventilator-acquired pneumonia (VAP). However, successful validation of the usefulness of potential markers in this setting is exceptionally rare. Objectives We sought to validate the capacity for specific host inflammatory mediators to exclude pneumonia in patients with suspected VAP. Methods A prospective, multicentre, validation study of patients with suspected VAP was conducted in 12 intensive care units. VAP was confirmed following bronchoscopy by culture of a potential pathogen in bronchoalveolar lavage fluid (BALF) at >104 colony forming units per millilitre (cfu/mL). Interleukin-1 beta (IL-1β), IL-8, matrix metalloproteinase-8 (MMP-8), MMP-9 and human neutrophil elastase (HNE) were quantified in BALF. Diagnostic utility was determined for biomarkers individually and in combination. Results Paired BALF culture and biomarker results were available for 150 patients. 53 patients (35%) had VAP and 97 (65%) patients formed the non-VAP group. All biomarkers were significantly higher in the VAP group (p<0.001). The area under the receiver operator characteristic curve for IL-1β was 0.81; IL-8, 0.74; MMP-8, 0.76; MMP-9, 0.79 and HNE, 0.78. A combination of IL-1β and IL-8, at the optimal cut-point, excluded VAP with a sensitivity of 100%, a specificity of 44.3% and a post-test probability of 0% (95% CI 0% to 9.2%). Conclusions Low BALF IL-1β in combination with IL-8 confidently excludes VAP and could form a rapid biomarker-based rule-out test, with the potential to improve antibiotic stewardship. PMID:25298325

Multiomics Data Triangulation for Asthma Candidate Biomarkers and Precision Medicine.

PubMed

Pecak, Matija; Korošec, Peter; Kunej, Tanja

2018-06-01

Asthma is a common complex disorder and has been subject to intensive omics research for disease susceptibility and therapeutic innovation. Candidate biomarkers of asthma and its precision treatment demand that they stand the test of multiomics data triangulation before they can be prioritized for clinical applications. We classified the biomarkers of asthma after a search of the literature and based on whether or not a given biomarker candidate is reported in multiple omics platforms and methodologies, using PubMed and Web of Science, we identified omics studies of asthma conducted on diverse platforms using keywords, such as asthma, genomics, metabolomics, and epigenomics. We extracted data about asthma candidate biomarkers from 73 articles and developed a catalog of 190 potential asthma biomarkers (167 human, 23 animal data), comprising DNA loci, transcripts, proteins, metabolites, epimutations, and noncoding RNAs. The data were sorted according to 13 omics types: genomics, epigenomics, transcriptomics, proteomics, interactomics, metabolomics, ncRNAomics, glycomics, lipidomics, environmental omics, pharmacogenomics, phenomics, and integrative omics. Importantly, we found that 10 candidate biomarkers were apparent in at least two or more omics levels, thus promising potential for further biomarker research and development and precision medicine applications. This multiomics catalog reported herein for the first time contributes to future decision-making on prioritization of biomarkers and validation efforts for precision medicine in asthma. The findings may also facilitate meta-analyses and integrative omics studies in the future.

New markers of dietary added sugar intake.

PubMed

Davy, Brenda; Jahren, Hope

2016-07-01

Added sugar consumption is associated with adverse health outcomes, including weight gain and cardio-metabolic disease, yet the reliance on self-reported methods to determine added sugar intake continues to be a significant research limitation. The purpose of this review is to summarize recent advances in the development of two potential predictive biomarkers of added sugar intake: δC and urinary sugar excretion. The results of numerous cross-sectional investigations have indicated modest associations of the δC sugar biomarker measured in a variety of sample types (e.g., fingerstick blood, serum, red blood cells, and hair) with self-reported added sugar and sugar-sweetened beverage intake, and δC values have been reported to change over time with changes in reported sugar-sweetened beverage intake. Results from large-scale trials have suggested modest associations of urinary sugar excretion with reported sugar intake, and a dose-response relation has been demonstrated between urinary sugar excretion and actual sugar intake. Valid markers of sugar intake are urgently needed to more definitively determine the health consequences of added sugar intake. Adequately powered controlled feeding studies are needed to validate and compare these two biomarkers of sugar intake, and to determine what individual characteristics and conditions impact biomarker results.

Prioritization of Biomarker Targets in Human Umbilical Cord Blood: Identification of Proteins in Infant Blood Serving as Validated Biomarkers in Adults

PubMed Central

Hansmeier, Nicole; Chao, Tzu-Chiao; Goldman, Lynn R.; Witter, Frank R.

2012-01-01

Background: Early diagnosis represents one of the best lines of defense in the fight against a wide array of human diseases. Umbilical cord blood (UCB) is one of the first easily available diagnostic biofluids and can inform about the health status of newborns. However, compared with adult blood, its diagnostic potential remains largely untapped. Objectives: Our goal was to accelerate biomarker research on UCB by exploring its detectable protein content and providing a priority list of potential biomarkers based on known proteins involved in disease pathways. Methods: We explored cord blood serum proteins by profiling a UCB pool of 12 neonates with different backgrounds using a combination of isoelectric focusing and liquid chromatography coupled with matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) and by comparing results with information contained in metabolic and disease databases available for adult blood. Results: A total of 1,210 UCB proteins were identified with a protein-level false discovery rate of ~ 5% as estimated by naïve target-decoy and MAYU approaches, signifying a 6-fold increase in the number of UCB proteins described to date. Identified proteins correspond to 138 different metabolic and disease pathways and provide a platform of mechanistically linked biomarker candidates for tracking disruptions in cellular processes. Moreover, among the identified proteins, 38 were found to be approved biomarkers for adult blood. Conclusions: The results of this study advance current knowledge of the human cord blood serum proteome. They showcase the potential of UCB as a diagnostic medium for assessing infant health by detection and identification of candidate biomarkers for known disease pathways using a global, nontargeted approach. These biomarkers may inform about mechanisms of exposure–disease relationships. Furthermore, biomarkers approved by the U.S. Food and Drug Administration for screening in adult blood were detected in UCB and represent high-priority targets for immediate validation. PMID:22538116

Prioritization of biomarker targets in human umbilical cord blood: identification of proteins in infant blood serving as validated biomarkers in adults.

PubMed

Hansmeier, Nicole; Chao, Tzu-Chiao; Goldman, Lynn R; Witter, Frank R; Halden, Rolf U

2012-05-01

Early diagnosis represents one of the best lines of defense in the fight against a wide array of human diseases. Umbilical cord blood (UCB) is one of the first easily available diagnostic biofluids and can inform about the health status of newborns. However, compared with adult blood, its diagnostic potential remains largely untapped. Our goal was to accelerate biomarker research on UCB by exploring its detectable protein content and providing a priority list of potential biomarkers based on known proteins involved in disease pathways. We explored cord blood serum proteins by profiling a UCB pool of 12 neonates with different backgrounds using a combination of isoelectric focusing and liquid chromatography coupled with matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS) and by comparing results with information contained in metabolic and disease databases available for adult blood. A total of 1,210 UCB proteins were identified with a protein-level false discovery rate of ~ 5% as estimated by naïve target-decoy and MAYU approaches, signifying a 6-fold increase in the number of UCB proteins described to date. Identified proteins correspond to 138 different metabolic and disease pathways and provide a platform of mechanistically linked biomarker candidates for tracking disruptions in cellular processes. Moreover, among the identified proteins, 38 were found to be approved biomarkers for adult blood. The results of this study advance current knowledge of the human cord blood serum proteome. They showcase the potential of UCB as a diagnostic medium for assessing infant health by detection and identification of candidate biomarkers for known disease pathways using a global, nontargeted approach. These biomarkers may inform about mechanisms of exposure-disease relationships. Furthermore, biomarkers approved by the U.S. Food and Drug Administration for screening in adult blood were detected in UCB and represent high-priority targets for immediate validation.

CSF inflammatory biomarkers responsive to treatment in progressive multiple sclerosis capture residual inflammation associated with axonal damage.

PubMed

Romme Christensen, Jeppe; Komori, Mika; von Essen, Marina Rode; Ratzer, Rikke; Börnsen, Lars; Bielekova, Bibi; Sellebjerg, Finn

2018-05-01

Development of treatments for progressive multiple sclerosis (MS) is challenged by the lack of sensitive and treatment-responsive biomarkers of intrathecal inflammation. To validate the responsiveness of cerebrospinal fluid (CSF) inflammatory biomarkers to treatment with natalizumab and methylprednisolone in progressive MS and to examine the relationship between CSF inflammatory and tissue damage biomarkers. CSF samples from two open-label phase II trials of natalizumab and methylprednisolone in primary and secondary progressive MS. CSF concentrations of 20 inflammatory biomarkers and CSF biomarkers of axonal damage (neurofilament light chain (NFL)) and demyelination were analysed using electrochemiluminescent assay and enzyme-linked immunosorbent assay (ELISA). In all, 17 natalizumab- and 23 methylprednisolone-treated patients had paired CSF samples. CSF sCD27 displayed superior standardised response means and highly significant decreases during both natalizumab and methylprednisolone treatment; however, post-treatment levels remained above healthy donor reference levels. Correlation analyses of CSF inflammatory biomarkers and NFL before, during and after treatment demonstrated that CSF sCD27 consistently correlates with NFL. These findings validate CSF sCD27 as a responsive and sensitive biomarker of intrathecal inflammation in progressive MS, capturing residual inflammation after treatment. Importantly, CSF sCD27 correlates with NFL, consistent with residual inflammation after anti-inflammatory treatment being associated with axonal damage.

Biomarkers in Sports and Exercise: Tracking Health, Performance, and Recovery in Athletes

PubMed Central

Fragala, Maren S.; Kavouras, Stavros A.; Queen, Robin M.; Pryor, John Luke; Casa, Douglas J.

2017-01-01

Abstract Lee, EC, Fragala, MS, Kavouras, SA, Queen, RM, Pryor, JL, and Casa, DJ. Biomarkers in sports and exercise: tracking health, performance, and recovery in athletes. J Strength Cond Res 31(10): 2920–2937, 2017—Biomarker discovery and validation is a critical aim of the medical and scientific community. Research into exercise and diet-related biomarkers aims to improve health, performance, and recovery in military personnel, athletes, and lay persons. Exercise physiology research has identified individual biomarkers for assessing health, performance, and recovery during exercise training. However, there are few recommendations for biomarker panels for tracking changes in individuals participating in physical activity and exercise training programs. Our approach was to review the current literature and recommend a collection of validated biomarkers in key categories of health, performance, and recovery that could be used for this purpose. We determined that a comprehensive performance set of biomarkers should include key markers of (a) nutrition and metabolic health, (b) hydration status, (c) muscle status, (d) endurance performance, (e) injury status and risk, and (f) inflammation. Our review will help coaches, clinical sport professionals, researchers, and athletes better understand how to comprehensively monitor physiologic changes, as they design training cycles that elicit maximal improvements in performance while minimizing overtraining and injury risk. PMID:28737585

Use of ProteinChip technology for identifying biomarkers of parasitic diseases: the example of porcine cysticercosis (Taenia solium).

PubMed

Deckers, N; Dorny, P; Kanobana, K; Vercruysse, J; Gonzalez, A E; Ward, B; Ndao, M

2008-12-01

Taenia solium cysticercosis is a significant public health problem in endemic countries. The current serodiagnostic techniques are not able to differentiate between infections with viable cysts and infections with degenerated cysts. The objectives of this study were to identify specific novel biomarkers of these different disease stages in the serum of experimentally infected pigs using ProteinChip technology (Bio-Rad) and to validate these biomarkers by analyzing serum samples from naturally infected pigs. In the experimental sample set 30 discriminating biomarkers (p<0.05) were found, 13 specific for the viable phenotype, 9 specific for the degenerated phenotype and 8 specific for the infected phenotype (either viable or degenerated cysts). Only 3 of these biomarkers were also significant in the field samples; however, the peak profiles were not consistent among the two sample sets. Five biomarkers discovered in the sera from experimentally infected pigs were identified as clusterin, lecithin-cholesterol acyltransferase, vitronectin, haptoglobin and apolipoprotein A-I.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Analysis of human plasma proteins: a focus on sample collection and separation using free-flow electrophoresis.

PubMed

Nissum, Mikkel; Foucher, Aude L

2008-08-01

Due to ease of accessibility, plasma has become the sample of choice for proteomics studies directed towards biomarker discovery intended for use in diagnostics, prognostics and even in theranostics. The result of these extensive efforts is a long list of potential biomarkers, very few of which have led to clinical utility. Why have so many potential biomarkers failed validation? Herein, we address certain issues encountered, which complicate biomarker discovery efforts originating from plasma. The advantages of stabilizing the sample at collection by the addition of protease inhibitors are discussed. The principles of free-flow electrophoresis (FFE) separation are provided together with examples applying to various studies. Finally, particular attention is given to plasma or serum analysis using multidimensional separation strategies into which the FFE is incorporated. The advantages of using FFE separation in these workflows are discussed.

Discovery of Colorectal Cancer Biomarker Candidates by Membrane Proteomic Analysis and Subsequent Verification using Selected Reaction Monitoring (SRM) and Tissue Microarray (TMA) Analysis*

PubMed Central

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-01-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. PMID:24687888

Discovery of colorectal cancer biomarker candidates by membrane proteomic analysis and subsequent verification using selected reaction monitoring (SRM) and tissue microarray (TMA) analysis.

PubMed

Kume, Hideaki; Muraoka, Satoshi; Kuga, Takahisa; Adachi, Jun; Narumi, Ryohei; Watanabe, Shio; Kuwano, Masayoshi; Kodera, Yoshio; Matsushita, Kazuyuki; Fukuoka, Junya; Masuda, Takeshi; Ishihama, Yasushi; Matsubara, Hisahiro; Nomura, Fumio; Tomonaga, Takeshi

2014-06-01

Recent advances in quantitative proteomic technology have enabled the large-scale validation of biomarkers. We here performed a quantitative proteomic analysis of membrane fractions from colorectal cancer tissue to discover biomarker candidates, and then extensively validated the candidate proteins identified. A total of 5566 proteins were identified in six tissue samples, each of which was obtained from polyps and cancer with and without metastasis. GO cellular component analysis predicted that 3087 of these proteins were membrane proteins, whereas TMHMM algorithm predicted that 1567 proteins had a transmembrane domain. Differences were observed in the expression of 159 membrane proteins and 55 extracellular proteins between polyps and cancer without metastasis, while the expression of 32 membrane proteins and 17 extracellular proteins differed between cancer with and without metastasis. A total of 105 of these biomarker candidates were quantitated using selected (or multiple) reaction monitoring (SRM/MRM) with stable synthetic isotope-labeled peptides as an internal control. The results obtained revealed differences in the expression of 69 of these proteins, and this was subsequently verified in an independent set of patient samples (polyps (n = 10), cancer without metastasis (n = 10), cancer with metastasis (n = 10)). Significant differences were observed in the expression of 44 of these proteins, including ITGA5, GPRC5A, PDGFRB, and TFRC, which have already been shown to be overexpressed in colorectal cancer, as well as proteins with unknown function, such as C8orf55. The expression of C8orf55 was also shown to be high not only in colorectal cancer, but also in several cancer tissues using a multicancer tissue microarray, which included 1150 cores from 14 cancer tissues. This is the largest verification study of biomarker candidate membrane proteins to date; our methods for biomarker discovery and subsequent validation using SRM/MRM will contribute to the identification of useful biomarker candidates for various cancers. Data are available via ProteomeXchange with identifier PXD000851. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

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

PubMed

Kraus, Virginia B

2018-06-01

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

Bioindicators of contaminant exposure and effect in aquatic and terrestrial monitoring

USGS Publications Warehouse

Melancon, Mark J.; Hoffman, David J.; Rattner, Barnett A.; Burton, G. Allen; Cairns, John

2003-01-01

Bioindicators of contaminant exposure presently used in environmental monitoring arc discussed. Some have been extensively field-validated and arc already in routine application. Included are (1) inhibition of brain or blood cholinesterase by anticholinesterase pesticides, (2) induction of hepatic microsomal cytochromes P450 by chemicals such as PAHs and PCBs, (3) reproductive problems such as terata and eggshell thinning, and (4) aberrations of hemoglobin synthesis, including the effects of lead and of certain chlorinated hydrocarbons. Many studies on DNA damage and of histopathological effects, particularly in the form of tumors, have already been completed. There are presently numerous other opportunities for field validation. Bile metabolites of contaminants in fish reveal exposure to contaminants that might otherwise be difficult to detect or quantify. Bile analysis is beginning to be extended to species other than fishes. Assessment of oxidative damage and immune competence appear to be valuable biomarkers. needing only additional field validation for wider use. The use of metallothioneins as biomarkers depends on the development of convenient, inexpensive methodology that provides information not available from measurements of metal ions. The use of stress proteins as biomarkers depends on development of convenient, inexpensive methodology and field validation. Gene arrays and proteomics hold promise as bioindicators for contaminant exposure or effect, particularly because of the large amount of data that could be generated, but they still need extensive development and testing.

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer

PubMed Central

Yoon, Ho Il; Kwon, Oh-Ran; Kang, Kyung Nam; Shin, Yong Sung; Shin, Ho Sang; Yeon, Eun Hee; Kwon, Keon Young; Hwang, Ilseon; Jeon, Yoon Kyung; Kim, Yongdai; Kim, Chul Woo

2016-01-01

Background Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer. Methods We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer. Results In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results. Conclusions Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer. PMID:27722145

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.

PubMed

Yoon, Ho Il; Kwon, Oh-Ran; Kang, Kyung Nam; Shin, Yong Sung; Shin, Ho Sang; Yeon, Eun Hee; Kwon, Keon Young; Hwang, Ilseon; Jeon, Yoon Kyung; Kim, Yongdai; Kim, Chul Woo

2016-09-01

Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer. We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer. In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results. Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.

Amniotic fluid: the use of high-dimensional biology to understand fetal well-being.

PubMed

Kamath-Rayne, Beena D; Smith, Heather C; Muglia, Louis J; Morrow, Ardythe L

2014-01-01

Our aim was to review the use of high-dimensional biology techniques, specifically transcriptomics, proteomics, and metabolomics, in amniotic fluid to elucidate the mechanisms behind preterm birth or assessment of fetal development. We performed a comprehensive MEDLINE literature search on the use of transcriptomic, proteomic, and metabolomic technologies for amniotic fluid analysis. All abstracts were reviewed for pertinence to preterm birth or fetal maturation in human subjects. Nineteen articles qualified for inclusion. Most articles described the discovery of biomarker candidates, but few larger, multicenter replication or validation studies have been done. We conclude that the use of high-dimensional systems biology techniques to analyze amniotic fluid has significant potential to elucidate the mechanisms of preterm birth and fetal maturation. However, further multicenter collaborative efforts are needed to replicate and validate candidate biomarkers before they can become useful tools for clinical practice. Ideally, amniotic fluid biomarkers should be translated to a noninvasive test performed in maternal serum or urine.

Overlap of proteomics biomarkers between women with pre-eclampsia and PCOS: a systematic review and biomarker database integration

PubMed Central

Khan, Gulafshana Hafeez; Galazis, Nicolas; Docheva, Nikolina; Layfield, Robert; Atiomo, William

2015-01-01

STUDY QUESTION Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). SUMMARY ANSWER Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. WHAT IS KNOWN ALREADY Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. STUDY DESIGN, SIZE, DURATION A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. MAIN RESULTS AND THE ROLE OF CHANCE Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. LIMITATIONS, REASONS FOR CAUTION The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. WIDER IMPLICATIONS OF THE FINDINGS This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. If validated, these biomarkers could provide a useful framework for the knowledge infrastructure in this area. To accomplish this goal, a well co-ordinated multidisciplinary collaboration of clinicians, basic scientists and mathematicians is vital. STUDY FUNDING/COMPETING INTEREST(S) No financial support was obtained for this project. There are no conflicts of interest. PMID:25351721

Cross-Disciplinary Biomarkers Research: Lessons Learned by the CKD Biomarkers Consortium.

PubMed

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; Nelson, Robert G

2015-05-07

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. Copyright © 2015 by the American Society of Nephrology.

Bladder Cancer-associated Protein, a Potential Prognostic Biomarker in Human Bladder Cancer*

PubMed Central

Moreira, José M. A.; Ohlsson, Gita; Gromov, Pavel; Simon, Ronald; Sauter, Guido; Celis, Julio E.; Gromova, Irina

2010-01-01

It is becoming increasingly clear that no single marker will have the sensitivity and specificity necessary to be used on its own for diagnosis/prognosis of tumors. Interpatient and intratumor heterogeneity provides overwhelming odds against the existence of such an ideal marker. With this in mind, our laboratory has been applying a long term systematic approach to identify multiple biomarkers that can be used for clinical purposes. As a result of these studies, we have identified and reported several candidate biomarker proteins that are deregulated in bladder cancer. Following the conceptual biomarker development phases proposed by the Early Detection Research Network, we have taken some of the most promising candidate proteins into postdiscovery validation studies, and here we report on the characterization of one such biomarker, the bladder cancer-associated protein (BLCAP), formerly termed Bc10. To characterize BLCAP protein expression and cellular localization patterns in benign bladder urothelium and urothelial carcinomas (UCs), we used two independent sets of samples from different patient cohorts: a reference set consisting of 120 bladder specimens (formalin-fixed as well as frozen biopsies) and a validation set consisting of 2,108 retrospectively collected UCs with long term clinical follow-up. We could categorize the UCs examined into four groups based on levels of expression and subcellular localization of BLCAP protein and showed that loss of BLCAP expression is associated with tumor progression. The results indicated that increased expression of this protein confers an adverse patient outcome, suggesting that categorization of staining patterns for this protein may have prognostic value. Finally, we applied a combinatorial two-marker discriminator using BLCAP and adipocyte-type fatty acid-binding protein, another UC biomarker previously reported by us, and found that the combination of the two markers correlated more closely with grade and/or stage of disease than the individual markers. The implications of these results in biomarker discovery are discussed. PMID:19783793

MicroRNAs in urine are not biomarkers of multiple myeloma.

PubMed

Sedlaříková, Lenka; Bešše, Lenka; Novosadová, Soňa; Kubaczková, Veronika; Radová, Lenka; Staník, Michal; Krejčí, Marta; Hájek, Roman; Ševčíková, Sabina

2015-09-23

In this study, we aimed to identify microRNA from urine of multiple myeloma patients that could serve as a biomarker for the disease. Analysis of urine samples was performed using Serum/Plasma Focus PCR MicroRNA Panel (Exiqon) and verified using individual TaqMan miRNA assays for qPCR. We found 20 deregulated microRNA (p < 0.05); for further validation, we chose 8 of them. Nevertheless, only differences in expression levels of miR-22-3p remained close to statistical significance. Our preliminary results did not confirm urine microRNA as a potential biomarker for multiple myeloma.

Evaluation of a Serum Lung Cancer Biomarker Panel.

PubMed

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

2018-01-01

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

Evaluation of a Serum Lung Cancer Biomarker Panel

PubMed Central

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

2018-01-01

Background: A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. Methods: The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. Results: The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. Conclusions: This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results. PMID:29371783

Capsaicinoids, Chloropicrin and Sulfur Mustard: Possibilities for Exposure Biomarkers

PubMed Central

Pesonen, Maija; Vähäkangas, Kirsi; Halme, Mia; Vanninen, Paula; Seulanto, Heikki; Hemmilä, Matti; Pasanen, Markku; Kuitunen, Tapio

2010-01-01

Incapacitating and irritating agents produce temporary disability persisting for hours to days after the exposure. One can be exposed to these agents occupationally in industrial or other working environments. Also general public can be exposed in special circumstances, like industrial accidents or riots. Incapacitating and irritating agents discussed in this review are chloropicrin and capsaicinoids. In addition, we include sulfur mustard, which is an old chemical warfare agent and known to cause severe long-lasting injuries or even death. Chloropicrin that was used as a warfare agent in the World War I is currently used mainly as a pesticide. Capsaicinoids, components of hot pepper plants, are used by police and other law enforcement personnel as riot control agents. Toxicity of these chemicals is associated particularly with the respiratory tract, eyes, and skin. Their acute effects are relatively well known but the knowledge of putative long-term effects is almost non-existent. Also, mechanisms of effects at cellular level are not fully understood. There is a need for further research to get better idea of health risks, particularly of long-term and low-level exposures to these chemicals. For this, exposure biomarkers are essential. Validated exposure biomarkers for capsaicinoids, chloropicrin, and sulfur mustard do not exist so far. Metabolites and macromolecular adducts have been suggested biomarkers for sulfur mustard and these can already be measured qualitatively, but quantitative biomarkers await further development and validation. The purpose of this review is, based on the existing mechanistic and toxicokinetic information, to shed light on the possibilities for developing biomarkers for exposure biomonitoring of these compounds. It is also of interest to find ideas for early effect biomarkers considering the need for studies on subchronic and chronic toxicity. PMID:21833179

Myocardial Injury Is Distinguished from Stable Angina by a Set of Candidate Plasma Biomarkers Identified Using iTRAQ/MRM-Based Approach.

PubMed

Cheow, Esther Sok Hwee; Cheng, Woo Chin; Yap, Terence; Dutta, Bamaprasad; Lee, Chuen Neng; Kleijn, Dominique P V de; Sorokin, Vitaly; Sze, Siu Kwan

2018-01-05

The lack of precise biomarkers that identify patients at risk for myocardial injury and stable angina delays administration of optimal therapy. Hence, the search for noninvasive biomarkers that could accurately stratify patients with impending heart attack, from patients with stable coronary artery disease (CAD), is urgently needed in the clinic. Herein, we performed comparative quantitative proteomics on whole plasma sampled from patients with stable angina (NMI), acute myocardial infarction (MI), and healthy control subjects (Ctrl). We detected a total of 371 proteins with high confidence (FDR < 1%, p < 0.05) including 53 preliminary biomarkers that displayed ≥2-fold modulated expression in patients with CAD (27 associated with atherosclerotic stable angina, 26 with myocardial injury). In the verification phase, we used label-free LC-MRM-MS-based targeted method to verify the preliminary biomarkers in pooled plasma, excluded peptides that were poorly distinguished from background, and performed further validation of the remaining candidates in 49 individual plasma samples. Using this approach, we identified a final panel of eight novel candidate biomarkers that were significantly modulated in CAD (p < 0.05) including proteins associated with atherosclerotic stable angina that were implicated in endothelial dysfunction (F10 and MST1), proteins associated with myocardial injury reportedly involved in plaque destabilization (SERPINA3, CPN2, LUM), and in tissue protection/repair mechanisms (ORM2, ACTG1, NAGLU). Taken together, our data showed that candidate biomarkers with potential diagnostic values can be successfully detected in nondepleted human plasma using an iTRAQ/MRM-based discovery-validation approach and demonstrated the plausible clinical utility of the proposed panel in discriminating atherosclerotic stable angina from myocardial injury in the studied cohort.

Urinary Proteomic Biomarkers for Diagnosis and Risk Stratification of Autosomal Dominant Polycystic Kidney Disease: A Multicentric Study

PubMed Central

Kistler, Andreas D.; Serra, Andreas L.; Siwy, Justyna; Poster, Diane; Krauer, Fabienne; Torres, Vicente E.; Mrug, Michal; Grantham, Jared J.; Bae, Kyongtae T.; Bost, James E.; Mullen, William; Wüthrich, Rudolf P.; Mischak, Harald; Chapman, Arlene B.

2013-01-01

Treatment options for autosomal dominant polycystic kidney disease (ADPKD) will likely become available in the near future, hence reliable diagnostic and prognostic biomarkers for the disease are strongly needed. Here, we aimed to define urinary proteomic patterns in ADPKD patients, which aid diagnosis and risk stratification. By capillary electrophoresis online coupled to mass spectrometry (CE-MS), we compared the urinary peptidome of 41 ADPKD patients to 189 healthy controls and identified 657 peptides with significantly altered excretion, of which 209 could be sequenced using tandem mass spectrometry. A support-vector-machine based diagnostic biomarker model based on the 142 most consistent peptide markers achieved a diagnostic sensitivity of 84.5% and specificity of 94.2% in an independent validation cohort, consisting of 251 ADPKD patients from five different centers and 86 healthy controls. The proteomic alterations in ADPKD included, but were not limited to markers previously associated with acute kidney injury (AKI). The diagnostic biomarker model was highly specific for ADPKD when tested in a cohort consisting of 481 patients with a variety of renal and extrarenal diseases, including AKI. Similar to ultrasound, sensitivity and specificity of the diagnostic score depended on patient age and genotype. We were furthermore able to identify biomarkers for disease severity and progression. A proteomic severity score was developed to predict height adjusted total kidney volume (htTKV) based on proteomic analysis of 134 ADPKD patients and showed a correlation of r = 0.415 (p<0.0001) with htTKV in an independent validation cohort consisting of 158 ADPKD patients. In conclusion, the performance of peptidomic biomarker scores is superior to any other biochemical markers of ADPKD and the proteomic biomarker patterns are a promising tool for prognostic evaluation of ADPKD. PMID:23326375

Biomarkers in pancreatic adenocarcinoma: current perspectives.

PubMed

Swords, Douglas S; Firpo, Matthew A; Scaife, Courtney L; Mulvihill, Sean J

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of 7.7%. Most patients are diagnosed at an advanced stage not amenable to potentially curative resection. A substantial portion of this review is dedicated to reviewing the current literature on carbohydrate antigen (CA 19-9), which is currently the only guideline-recommended biomarker for PDAC. It provides valuable prognostic information, can predict resectability, and is useful in decision making about neoadjuvant therapy. We also discuss carcinoembryonic antigen (CEA), CA 125, serum biomarker panels, circulating tumor cells, and cell-free nucleic acids. Although many biomarkers have now been studied in relation to PDAC, significant work still needs to be done to validate their usefulness in the early detection of PDAC and management of patients with PDAC.

Biomarkers in pancreatic adenocarcinoma: current perspectives

PubMed Central

Swords, Douglas S; Firpo, Matthew A; Scaife, Courtney L; Mulvihill, Sean J

2016-01-01

Pancreatic ductal adenocarcinoma (PDAC) has a poor prognosis, with a 5-year survival rate of 7.7%. Most patients are diagnosed at an advanced stage not amenable to potentially curative resection. A substantial portion of this review is dedicated to reviewing the current literature on carbohydrate antigen (CA 19-9), which is currently the only guideline-recommended biomarker for PDAC. It provides valuable prognostic information, can predict resectability, and is useful in decision making about neoadjuvant therapy. We also discuss carcinoembryonic antigen (CEA), CA 125, serum biomarker panels, circulating tumor cells, and cell-free nucleic acids. Although many biomarkers have now been studied in relation to PDAC, significant work still needs to be done to validate their usefulness in the early detection of PDAC and management of patients with PDAC. PMID:28003762

Feasibility of event-related potential (ERP) biomarker use to study effects of mother's voice exposure on speech sound differentiation of preterm infants.

PubMed

D Chorna, Olena; L Hamm, Ellyn; Shrivastava, Hemang; Maitre, Nathalie L

2018-01-01

Atypical maturation of auditory neural processing contributes to preterm-born infants' language delays. Event-related potential (ERP) measurement of speech-sound differentiation might fill a gap in treatment-response biomarkers to auditory interventions. We evaluated whether these markers could measure treatment effects in a quasi-randomized prospective study. Hospitalized preterm infants in passive or active, suck-contingent mother's voice exposure groups were not different at baseline. Post-intervention, the active group had greater increases in/du/-/gu/differentiation in left frontal and temporal regions. Infants with brain injury had lower baseline/ba/-/ga/and/du/-/gu/differentiation than those without. ERP provides valid discriminative, responsive, and predictive biomarkers of infant speech-sound differentiation.

Toward reliable biomarker signatures in the age of liquid biopsies - how to standardize the small RNA-Seq workflow

PubMed Central

Buschmann, Dominik; Haberberger, Anna; Kirchner, Benedikt; Spornraft, Melanie; Riedmaier, Irmgard; Schelling, Gustav; Pfaffl, Michael W.

2016-01-01

Small RNA-Seq has emerged as a powerful tool in transcriptomics, gene expression profiling and biomarker discovery. Sequencing cell-free nucleic acids, particularly microRNA (miRNA), from liquid biopsies additionally provides exciting possibilities for molecular diagnostics, and might help establish disease-specific biomarker signatures. The complexity of the small RNA-Seq workflow, however, bears challenges and biases that researchers need to be aware of in order to generate high-quality data. Rigorous standardization and extensive validation are required to guarantee reliability, reproducibility and comparability of research findings. Hypotheses based on flawed experimental conditions can be inconsistent and even misleading. Comparable to the well-established MIQE guidelines for qPCR experiments, this work aims at establishing guidelines for experimental design and pre-analytical sample processing, standardization of library preparation and sequencing reactions, as well as facilitating data analysis. We highlight bottlenecks in small RNA-Seq experiments, point out the importance of stringent quality control and validation, and provide a primer for differential expression analysis and biomarker discovery. Following our recommendations will encourage better sequencing practice, increase experimental transparency and lead to more reproducible small RNA-Seq results. This will ultimately enhance the validity of biomarker signatures, and allow reliable and robust clinical predictions. PMID:27317696

Bio-markers: traceability in food safety issues.

PubMed

Raspor, Peter

2005-01-01

Research and practice are focusing on development, validation and harmonization of technologies and methodologies to ensure complete traceability process throughout the food chain. The main goals are: scale-up, implementation and validation of methods in whole food chains, assurance of authenticity, validity of labelling and application of HACCP (hazard analysis and critical control point) to the entire food chain. The current review is to sum the scientific and technological basis for ensuring complete traceability. Tracing and tracking (traceability) of foods are complex processes due to the (bio)markers, technical solutions and different circumstances in different technologies which produces various foods (processed, semi-processed, or raw). Since the food is produced for human or animal consumption we need suitable markers to be stable and traceable all along the production chain. Specific biomarkers can have a function in technology and in nutrition. Such approach would make this development faster and more comprehensive and would make possible that food effect could be monitored with same set of biomarkers in consumer. This would help to develop and implement food safety standards that would be based on real physiological function of particular food component.

High-Throughput Quantitation of Proline Betaine in Foods and Suitability as a Valid Biomarker for Citrus Consumption.

PubMed

Lang, Roman; Lang, Tatjana; Bader, Matthias; Beusch, Anja; Schlagbauer, Verena; Hofmann, Thomas

2017-03-01

Proline betaine has been proposed as a candidate dietary biomarker for citrus intake. To validate its suitability as a dietary biomarker and to gain insight into the range of this per-methylated amino acid in foods and beverages, a quick and accurate stable isotope dilution assay was developed for quantitative high-throughput HILIC-MS/MS screening of proline betaine in foods and urine after solvent-mediated matrix precipitation. Quantitative analysis of a variety of foods confirmed substantial amounts of proline betaine in citrus juices (140-1100 mg/L) and revealed high abundance in tubers of the vegetable Stachys affinis, also known as Chinese artichocke (∼700 mg/kg). Seafood including clams, shrimp, and lobster contained limited amounts (1-95 mg/kg), whereas only traces were detected in fish, cuttlefish, fresh meat, dairy products, fresh vegetable (<3 mg/kg), coffee, tea, beer, and wine (<7 mg/L). The human excretion profiles of proline betaine in urine were comparable when common portions of orange juice or fried Stachys tubers were consumed. Neither mussels nor beer provided enough proline betaine to detect significant differences between morning urine samples collected before and after consumption. As Stachys is a rather rare vegetable and not part of peoples' daily diet, the data reported here will help to monitor the subject's compliance in future nutritional human studies on citrus products or the exclusion of citrus products in the wash-out phase of an intervention study. Moreover, proline betaine measurement can contribute to the establishment of a toolbox of valid dietary biomarkers reflecting wider aspects of diet to assess metabolic profiles as measures of dietary exposure and indicators of dietary patterns, dietary changes, or effectiveness of dietary interventions.

Novel biomarker-based model for the prediction of sorafenib response and overall survival in advanced hepatocellular carcinoma: a prospective cohort study.

PubMed

Kim, Hwi Young; Lee, Dong Hyeon; Lee, Jeong-Hoon; Cho, Young Youn; Cho, Eun Ju; Yu, Su Jong; Kim, Yoon Jun; Yoon, Jung-Hwan

2018-03-20

Prediction of the outcome of sorafenib therapy using biomarkers is an unmet clinical need in patients with advanced hepatocellular carcinoma (HCC). The aim was to develop and validate a biomarker-based model for predicting sorafenib response and overall survival (OS). This prospective cohort study included 124 consecutive HCC patients (44 with disease control, 80 with progression) with Child-Pugh class A liver function, who received sorafenib. Potential serum biomarkers (namely, hepatocyte growth factor [HGF], fibroblast growth factor [FGF], vascular endothelial growth factor receptor-1, CD117, and angiopoietin-2) were tested. After identifying independent predictors of tumor response, a risk scoring system for predicting OS was developed and 3-fold internal validation was conducted. A risk scoring system was developed with six covariates: etiology, platelet count, Barcelona Clinic Liver Cancer stage, protein induced by vitamin K absence-II, HGF, and FGF. When patients were stratified into low-risk (score ≤ 5), intermediate-risk (score 6), and high-risk (score ≥ 7) groups, the model provided good discriminant functions on tumor response (concordance [c]-index, 0.884) and 12-month survival (area under the curve [AUC], 0.825). The median OS was 19.0, 11.2, and 6.1 months in the low-, intermediate-, and high-risk group, respectively (P < 0.001). In internal validation, the model maintained good discriminant functions on tumor response (c-index, 0.825) and 12-month survival (AUC, 0.803), and good calibration functions (all P > 0.05 between expected and observed values). This new model including serum FGF and HGF showed good performance in predicting the response to sorafenib and survival in patients with advanced HCC.

First attempt to validate the gSG6-P1 salivary peptide as an immuno-epidemiological tool for evaluating human exposure to Anopheles funestus bites.

PubMed

Poinsignon, Anne; Samb, Badara; Doucoure, Souleymane; Drame, Papa-Makhtar; Sarr, Jean Biram; Sow, Cheikh; Cornelie, Sylvie; Maiga, Sophie; Thiam, Cheikh; Rogerie, François; Guindo, Sohidou; Hermann, Emmanuel; Simondon, François; Dia, Ibrahima; Riveau, Gilles; Konate, Lassana; Remoue, Franck

2010-10-01

The development of a biomarker of exposure based on the evaluation of the human antibody response specific to Anopheles salivary proteins seems promising in improving malaria control. The IgG response specific to the gSG6-P1 peptide has already been validated as a biomarker of An. gambiae exposure. This study represents a first attempt to validate the gSG6-P1 peptide as an epidemiological tool evaluating exposure to An. funestus bites, the second main malaria vector in sub-Saharan Africa. A multi-disciplinary survey was performed in a Senegalese village where An. funestus represents the principal anopheline species. The IgG antibody level specific to gSG6-P1 was evaluated and compared in the same children before, at the peak and after the rainy season. Two-thirds of the children developed a specific IgG response to gSG6-P1 during the study period and--more interestingly--before the rainy season, when An. funestus was the only anopheline species reported. The specific IgG response increased during the An. funestus exposure season, and a positive association between the IgG level and the level of exposure to An. funestus bites was observed. The results suggest that the evaluation of the IgG response specific to gSG6-P1 in children could also represent a biomarker of exposure to An. funestus bites. The availability of such a biomarker evaluating the exposure to both main Plasmodium falciparum vectors in Africa could be particularly relevant as a direct criterion for the evaluation of the efficacy of vector control strategies. © 2010 Blackwell Publishing Ltd.

Clinical performance validation of PITX2 DNA methylation as prognostic biomarker in patients with head and neck squamous cell carcinoma.

PubMed

Sailer, Verena; Gevensleben, Heidrun; Dietrich, Joern; Goltz, Diane; Kristiansen, Glen; Bootz, Friedrich; Dietrich, Dimo

2017-01-01

Despite advances in combined modality therapy, outcomes in head and neck squamous cell cancer (HNSCC) remain dismal with five-year overall survival rates of less than 50%. Prognostic biomarkers are urgently needed to identify patients with a high risk of death after initial curative treatment. Methylation status of the paired-like homeodomain transcription factor 2 (PITX2) has recently emerged as a powerful prognostic biomarker in various cancers. In the present study, the clinical performance of PITX2 methylation was validated in a HNSCC cohort by means of an independent analytical platform (Infinium HumanMethylation450 BeadChip, Illumina, Inc.). A total of 528 HNSCC patients from The Cancer Genome Atlas (TCGA) were included in the study. Death was defined as primary endpoint. PITX2 methylation was correlated with overall survival and clinicopathological parameters. PITX2 methylation was significantly associated with sex, tumor site, p16 status, and grade. In univariate Cox proportional hazards analysis, PITX2 hypermethylation analyzed as continuous and dichotomized variable was significantly associated with prolonged overall survival of HNSCC patients (continuous: hazard ratio (HR) = 0.19 [95%CI: 0.04-0.88], p = 0.034; dichotomized: HR = 0.52 [95%CI: 0.33-0.84], p = 0.007). In multivariate Cox analysis including established clinicopathological parameters, PITX2 promoter methylation was confirmed as prognostic factor (HR = 0.28 [95%CI: 0.09-0.84], p = 0.023). Using an independent analytical platform, PITX2 methylation was validated as a prognostic biomarker in HNSCC patients, identifying patients that potentially benefit from intensified surveillance and/or administration of adjuvant/neodjuvant treatment, i.e. immunotherapy.

Biomarkers for Early Detection of Clinically Relvant Prostate Cancer: A Multi-Institutional Validation Trial - Genomic Health, Inc. — EDRN Public Portal

Cancer.gov

Validate a panel of tissue-based biomarkers to determine the presence of or progression to clinically relevant prostate cancer at the time of diagnosis. Utilize a novel, biopsy based multi-gene quantitative RT-PCR assay developed by Genomic Health, Oncotype DX Prostate Cancer Assay, which discriminates aggressive from indolent cancer on multivariate modeling of PCa patients.

Prognostic biomarkers in osteoarthritis

PubMed Central

Attur, Mukundan; Krasnokutsky-Samuels, Svetlana; Samuels, Jonathan; Abramson, Steven B.

2013-01-01

Purpose of review Identification of patients at risk for incident disease or disease progression in osteoarthritis remains challenging, as radiography is an insensitive reflection of molecular changes that presage cartilage and bone abnormalities. Thus there is a widely appreciated need for biochemical and imaging biomarkers. We describe recent developments with such biomarkers to identify osteoarthritis patients who are at risk for disease progression. Recent findings The biochemical markers currently under evaluation include anabolic, catabolic, and inflammatory molecules representing diverse biological pathways. A few promising cartilage and bone degradation and synthesis biomarkers are in various stages of development, awaiting further validation in larger populations. A number of studies have shown elevated expression levels of inflammatory biomarkers, both locally (synovial fluid) and systemically (serum and plasma). These chemical biomarkers are under evaluation in combination with imaging biomarkers to predict early onset and the burden of disease. Summary Prognostic biomarkers may be used in clinical knee osteoarthritis to identify subgroups in whom the disease progresses at different rates. This could facilitate our understanding of the pathogenesis and allow us to differentiate phenotypes within a heterogeneous knee osteoarthritis population. Ultimately, such findings may help facilitate the development of disease-modifying osteoarthritis drugs (DMOADs). PMID:23169101

Quantitative body fluid proteomics in medicine - A focus on minimal invasiveness.

PubMed

Csősz, Éva; Kalló, Gergő; Márkus, Bernadett; Deák, Eszter; Csutak, Adrienne; Tőzsér, József

2017-02-05

Identification of new biomarkers specific for various pathological conditions is an important field in medical sciences. Body fluids have emerging potential in biomarker studies especially those which are continuously available and can be collected by non-invasive means. Changes in the protein composition of body fluids such as tears, saliva, sweat, etc. may provide information on both local and systemic conditions of medical relevance. In this review, our aim is to discuss the quantitative proteomics techniques used in biomarker studies, and to present advances in quantitative body fluid proteomics of non-invasively collectable body fluids with relevance to biomarker identification. The advantages and limitations of the widely used quantitative proteomics techniques are also presented. Based on the reviewed literature, we suggest an ideal pipeline for body fluid analyses aiming at biomarkers discoveries: starting from identification of biomarker candidates by shotgun quantitative proteomics or protein arrays, through verification of potential biomarkers by targeted mass spectrometry, to the antibody-based validation of biomarkers. The importance of body fluids as a rich source of biomarkers is discussed. Quantitative proteomics is a challenging part of proteomics applications. The body fluids collected by non-invasive means have high relevance in medicine; they are good sources for biomarkers used in establishing the diagnosis, follow up of disease progression and predicting high risk groups. The review presents the most widely used quantitative proteomics techniques in body fluid analysis and lists the potential biomarkers identified in tears, saliva, sweat, nasal mucus and urine for local and systemic diseases. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed Central

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

2014-01-01

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

Clinical protein science developments for patient monitoring in hospital central laboratories.

PubMed

Malm, Johan; Marko-Varga, György

2016-12-01

Patient care relies heavily on standardized tests performed in hospital laboratories, typically including clinical chemistry, pathology and microbiology. With the introduction of personalized medicine tremendous efforts have been made to identify new biomarkers of disease with various omics technologies, often including mass spectrometry. In order to validate new biomarkers and perform clinical studies high quality biobank samples are of key importance. In this editorial different aspects of mass spectrometry in future personalized medicine are discussed.

Validation of housekeeping genes as internal controls for studying biomarkers of endocrine-disrupting chemicals in disk abalone by real-time PCR.

PubMed

Wan, Qiang; Whang, Ilson; Choi, Cheol Young; Lee, Jae-Seong; Lee, Jehee

2011-04-01

Our experiments were designed to identify suitable housekeeping genes (HKGs) in disk abalone as internal controls to quantify biomarker expression following endocrine disrupting chemicals (EDCs). Relative expression levels of twelve candidate HKGs were examined by real-time reverse transcription PCR (qRT-PCR) in gill and hepatopancreas of abalone following a 7-day challenge with either tributyltin chloride (TBT) or 17β-estradiol (E2). The expression levels of several conventional HKGs, such as 18s rRNA, glyceraldehyde-3-phosphate dehydrogenase and β-actin, were significantly altered by the challenges, indicating that they might not be suitable internal controls. Instead, the geNorm analysis pinpointed ribosomal protein L-5/ elongation factor 1 and ribosomal protein L-5/ succinate dehydrogenase as the most stable HKGs under TBT and E2 challenges, respectively. Moreover, these three HKGs also showed the highest stabilities overall amongst different tissues, genders and EDC challenges. The expression of a biomarker gene, cytochrome P450 4B (CYP4), was also investigated and exhibited a significant increase after the challenges. Importantly, when unsuitable HKGs were used for normalization, the influence of two EDCs on CYP4 expression was imprecisely overestimated or underestimated, which strongly emphasized the importance of selecting appropriately validated HKGs as internal controls in biomarker studies. Copyright © 2010 Elsevier Inc. All rights reserved.

Extracellular matrix specific protein fingerprints measured in serum can separate pancreatic cancer patients from healthy controls

PubMed Central

2013-01-01

Background Pancreatic cancer (PC) is an aggressive disease with an urgent need for biomarkers. Hallmarks of PC include increased collagen deposition (desmoplasia) and increased matrix metalloproteinase (MMP) activity. The aim of this study was to investigate whether protein fingerprints of specific MMP-generated collagen fragments differentiate PC patients from healthy controls when measured in serum. Methods The levels of biomarkers reflecting MMP-mediated degradation of type I (C1M), type III (C3M) and type IV (C4M, C4M12a1) collagen were assessed in serum samples from PC patients (n = 15) and healthy controls (n = 33) using well-characterized and validated competitive ELISAs. Results The MMP-generated collagen fragments were significantly elevated in serum from PC patients as compared to controls. The diagnostic power of C1M, C3M, C4M and C4M12 were ≥83% (p < 0.001) and when combining all biomarkers 99% (p < 0.0001). Conclusions A panel of serum biomarkers reflecting altered MMP-mediated collagen turnover is able to differentiate PC patients from healthy controls. These markers may increase the understanding of mode of action of the disease and, if validated in larger clinical studies, provide an improved and additional tool in the PC setting. PMID:24261855

Detection of gastric cancer-associated microRNAs on microRNA microarray comparing pre- and post-operative plasma

PubMed Central

Konishi, H; Ichikawa, D; Komatsu, S; Shiozaki, A; Tsujiura, M; Takeshita, H; Morimura, R; Nagata, H; Arita, T; Kawaguchi, T; Hirashima, S; Fujiwara, H; Okamoto, K; Otsuji, E

2012-01-01

Background: Recently, it was reported that plasma microRNAs (miRNAs) are low-invasive useful biomarkers for cancer. We attempted to isolate gastric cancer (GC)-associated miRNAs comparing pre- and post-operative paired plasma, thereby excluding the possible effects of individual variability. Methods: This study was divided into four steps: (1) microarray analysis comparing pre- and post-operative plasma; (2) validation of candidate miRNAs by quantitative RT–PCR; (3) validation study of selected miRNAs using paired plasma; and (4) comparison of the levels of selected miRNAs in plasma between healthy controls and patients. Results: From the results of microarray analysis, nine candidate miRNAs the levels of which were markedly decreased in post-operative plasma were selected for further studies. After confirmation of their post-operative marked reduction, two candidate miRNAs, miR-451 and miR-486, were selected as plasma biomarkers, considering the abundance in plasma, and marked decrease in post-operative samples. In validation, the two miRNAs were found to decrease in post-operative plasma in 90 and 93% of patients (both P<0.01). In comparison with healthy controls, the levels of both miRNAs were found to be significantly higher in patients, and the area under the curve values were high at 0.96 and 0.92. Conclusion: Plasma miR-451 and miR-486 could be useful blood-based biomarkers for screening GC. PMID:22262318

Blood-Bourne MicroRNA Biomarker Evaluation in Attention-Deficit/Hyperactivity Disorder of Han Chinese Individuals: An Exploratory Study.

PubMed

Wang, Liang-Jen; Li, Sung-Chou; Lee, Min-Jing; Chou, Miao-Chun; Chou, Wen-Jiun; Lee, Sheng-Yu; Hsu, Chih-Wei; Huang, Lien-Hung; Kuo, Ho-Chang

2018-01-01

Background: Attention-deficit/hyperactivity disorder (ADHD) is a highly genetic neurodevelopmental disorder, and its dysregulation of gene expression involves microRNAs (miRNAs). The purpose of this study was to identify potential miRNAs biomarkers and then use these biomarkers to establish a diagnostic panel for ADHD. Design and methods: RNA samples from white blood cells (WBCs) of five ADHD patients and five healthy controls were combined to create one pooled patient library and one control library. We identified 20 candidate miRNAs with the next-generation sequencing (NGS) technique (Illumina). Blood samples were then collected from a Training Set (68 patients and 54 controls) and a Testing Set (20 patients and 20 controls) to identify the expression profiles of these miRNAs with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used receiver operating characteristic (ROC) curves and the area under the curve (AUC) to evaluate both the specificity and sensitivity of the probability score yielded by the support vector machine (SVM) model. Results: We identified 13 miRNAs as potential ADHD biomarkers. The ΔCt values of these miRNAs in the Training Set were integrated to create a biomarker model using the SVM algorithm, which demonstrated good validity in differentiating ADHD patients from control subjects (sensitivity: 86.8%, specificity: 88.9%, AUC: 0.94, p < 0.001). The results of the blind testing showed that 85% of the subjects in the Testing Set were correctly classified using the SVM model alignment (AUC: 0.91, p < 0.001). The discriminative validity is not influenced by patients' age or gender, indicating both the robustness and the reliability of the SVM classification model. Conclusion: As measured in peripheral blood, miRNA-based biomarkers can aid in the differentiation of ADHD in clinical settings. Additional studies are needed in the future to clarify the ADHD-associated gene functions and biological mechanisms modulated by miRNAs.

Global analysis of serum microRNAs as potential biomarkers for lung adenocarcinoma.

PubMed

Rani, Sweta; Gately, Kathy; Crown, John; O'Byrne, Ken; O'Driscoll, Lorraine

2013-12-01

Early diagnosis and the ability to predict the most relevant treatment option for individuals is essential to improve clinical outcomes for non-small cell lung cancer (NSCLC) patients. Adenocarcinoma (ADC), a subtype of NSCLC, is the single biggest cancer killer and therefore an urgent need to identify minimally invasive biomarkers to enable early diagnosis. Recent studies, by ourselves and others, indicate that circulating miRNAs have potential as biomarkers. Here we applied global profiling approaches in serum from patients with ADC of the lung to explore if miRNAs have potential as diagnostic biomarkers. This study involved RNA isolation from 80 sera specimens including those from ADC patients (equal numbers of stages 1, 2, 3, and 4) and age- and gender-matched controls (n = 40 each). Six hundred and sixty-seven miRNAs were co-analyzed in these specimens using TaqMan low density arrays and qPCR validation using individual miRNAs. Overall, approximately 390 and 370 miRNAs were detected in ADC and control sera, respectively. A group of 6 miRNAs, miR-30c-1* (AUC = 0.74; P<0.002), miR-616* (AUC = 0.71; P = 0.001), miR-146b-3p (AUC = 0.82; P<0.0001), miR-566 (AUC = 0.80; P<0.0001), miR-550 (AUC = 0.72; P = 0.0006), and miR-939 (AUC = 0.82; P<0.0001) was found to be present at substantially higher levels in ADC compared with control sera. Conversely, miR-339-5p and miR-656 were detected at substantially lower levels in ADC sera (co-analysis resulting in AUC = 0.6; P = 0.02). Differences in miRNA profile identified support circulating miRNAs having potential as diagnostic biomarkers for ADC. More extensive studies of ADC and control serum specimens are warranted to independently validate the potential clinical relevance of these miRNAs as minimally invasive biomarkers for ADC.

Comparative analysis of novel autoantibody isotypes against citrullinated-inter-alpha-trypsin inhibitor heavy chain 3 (ITIH3)(542-556) peptide in serum from Taiwanese females with rheumatoid arthritis, primary Sjögren's syndrome and secondary Sjögren's syndrome in rheumatoid arthritis.

PubMed

Liao, Chen-Chung; Chou, Pei-Lun; Cheng, Chao-Wen; Chang, Yu-Sheng; Chi, Wei-Ming; Tsai, Kai-Leun; Chen, Wei-Jung; Kung, Ting-Shuan; Tai, Chih-Chun; Lee, Kuan-Wei; Chen, You-Chia; Lin, Ching-Yu

2016-06-01

The purpose of this study was to discover and validate inter-alpha-trypsin inhibitor heavy chain H3 (ITIH3) as novel biomarkers, and evaluate autoantibody isotypes against an unmodified and citrullinated ITIH3(542-556) peptide among Taiwanese female patients with rheumatoid arthritis (RA), primary Sjögren's syndrome (pSS), secondary Sjögren's syndrome in rheumatoid arthritis (RA-sSS), and healthy controls (HCs). We used concanavalin A (Con A) affinity chromatography, 1-D SDS-PAGE, and label-free nano-LC-MS/MS to screen biomarker candidates (serum-derived Con A-captured proteins) and then identify PTMs of validated biomarkers (serum proteins) using pooled serum from 7 RA-sSS female patients and 7 age-matched HCs (the discovery set). Furthermore, the protein level and autoantibody isotype analyses were further validated against individual serum from 18 HCs, 18 RA, 18 pSS, and 18 RA-sSS patients (the validation set). Con A-bound ITIH3 was identified and validated as the only differentially expressed protein, which was elevated. Additionally, 2 novel PTMs in ITIH3 were identified and included citrullination at arginine-(546) and arginine-(556), and hexosamine at tryptophan-(558). Further, concentrations of anti-citrullinatd-ITIH3(542-556) peptide autoantibodies significantly increased in patients with RA, pSS, and RA-sSS compared to HCs. Especially, autoantibody IgM against the citrullinated-ITIH3(542-556) peptide showed better diagnostic performance in discriminating both RA versus pSS and pSS versus RA-sSS. By using comparative proteomic analysis of serum samples, the current study discovered and validates differentially expressed Con A-bound ITIH3 as a potential biomarker for secondary Sjögren's syndrome (SS) in rheumatoid arthritis (RA) patients and healthy controls (HCs). Besides, hexosamine and citrullination on ITIH3 were further identified. Through analyzing autoantibody isotypes against the citrullinated ITIH3 peptide, patients with RA, primary SS, and RA-secondary SS, and HCs can be further discriminated. The current strategy can be applied for identifying potential diagnostic and pathologic markers for autoimmune diseases. Copyright © 2016. Published by Elsevier B.V.

Colorectal cancer biomarkers: To be or not to be? Cautionary tales from a road well travelled

PubMed Central

Fung, Kim YC; Nice, Edouard; Priebe, Ilka; Belobrajdic, Damien; Phatak, Aloke; Purins, Leanne; Tabor, Bruce; Pompeia, Celine; Lockett, Trevor; Adams, Timothy E; Burgess, Antony; Cosgrove, Leah

2014-01-01

Colorectal cancer (CRC) is the second most common cause of cancer-related death worldwide and places a major economic burden on the global health care system. The time frame for development from premalignant to malignant disease typically spans 10-15 years, and this latent period provides an ideal opportunity for early detection and intervention to improve patient outcomes. Currently, early diagnosis of CRC is hampered by a lack of suitable non-invasive biomarkers that are clinically or economically acceptable for population-based screening. New blood-based protein biomarkers for early detection of CRC are therefore urgently required. The success of clinical biomarker discovery and validation studies is critically dependent on understanding and adjusting for potential experimental, analytical, and biological factors that can interfere with the robust interpretation of results. In this review we outline some important considerations for research groups undertaking biomarker research with exemplars from our studies. Implementation of experimental strategies to minimise the potential effects of these problems will facilitate the identification of panels of biomarkers with the sensitivity and specificity required for the development of successful tests for the early detection and surveillance of CRC. PMID:24574763

Fluid Biomarkers of Traumatic Brain Injury and Intended Context of Use

PubMed Central

Bogoslovsky, Tanya; Gill, Jessica; Jeromin, Andreas; Davis, Cora; Diaz-Arrastia, Ramon

2016-01-01

Traumatic brain injury (TBI) is one of the leading causes of death and disability around the world. The lack of validated biomarkers for TBI is a major impediment to developing effective therapies and improving clinical practice, as well as stimulating much work in this area. In this review, we focus on different settings of TBI management where blood or cerebrospinal fluid (CSF) biomarkers could be utilized for predicting clinically-relevant consequences and guiding management decisions. Requirements that the biomarker must fulfill differ based on the intended context of use (CoU). Specifically, we focus on fluid biomarkers in order to: (1) identify patients who may require acute neuroimaging (cranial computerized tomography (CT) or magnetic resonance imaging (MRI); (2) select patients at risk for secondary brain injury processes; (3) aid in counseling patients about their symptoms at discharge; (4) identify patients at risk for developing postconcussive syndrome (PCS), posttraumatic epilepsy (PTE) or chronic traumatic encephalopathy (CTE); (5) predict outcomes with respect to poor or good recovery; (6) inform counseling as to return to work (RTW) or to play. Despite significant advances already made from biomarker-based studies of TBI, there is an immediate need for further large-scale studies focused on identifying and innovating sensitive and reliable TBI biomarkers. These studies should be designed with the intended CoU in mind. PMID:27763536

Validation of Mismatch Negativity and P3a for Use in Multi-Site Studies of Schizophrenia: Characterization of Demographic, Clinical, Cognitive, and Functional Correlates in COGS-2

PubMed Central

Light, Gregory A.; Swerdlow, Neal R.; Thomas, Michael L.; Calkins, Monica E.; Green, Michael F.; Greenwood, Tiffany A.; Gur, Raquel E.; Gur, Ruben C.; Lazzeroni, Laura C.; Nuechterlein, Keith H.; Pela, Marlena; Radant, Allen D.; Seidman, Larry J.; Sharp, Richard F.; Siever, Larry J.; Silverman, Jeremy M.; Sprock, Joyce; Stone, William S.; Sugar, Catherine A.; Tsuang, Debby W.; Tsuang, Ming T.; Braff, David L.; Turetsky, Bruce I.

2014-01-01

Mismatch negativity (MMN) and P3a are auditory event-related potential (ERP) components that show robust deficits in schizophrenia (SZ) patients and exhibit qualities of endophenotypes, including substantial heritability, test-retest reliability, and trait-like stability. These measures also fulfill criteria for use as cognition and function-linked biomarkers in outcome studies, but have not yet been validated for use in large-scale multi-site clinical studies. This study tested the feasibility of adding MMN and P3a to the ongoing Consortium on the Genetics of Schizophrenia (COGS) study. The extent to which demographic, clinical, cognitive, and functional characteristics contribute to variability in MMN and P3a amplitudes was also examined. Participants (HCS n=824, SZ n=966) underwent testing at 5 geographically distributed COGS laboratories. Valid ERP data was obtained from 91% of HCS and 91% of SZ patients. Highly significant MMN (d=0.96) and P3a (d=0.93) amplitude reductions were observed in SZ patients, comparable in magnitude to those observed in single-lab studies with no appreciable differences across laboratories. Demographic characteristics accounted for 26% and 18% of the variance in MMN and P3a amplitudes, respectively. Significant relationships were observed among demographically-adjusted MMN and P3a measures and medication status as well as several clinical, cognitive, and functional characteristics of the SZ patients. This study demonstrates that MMN and P3a ERP biomarkers can be feasibly used in multi-site clinical studies. As with many clinical tests of brain function, demographic factors contribute to MMN and P3a amplitudes and should be carefully considered in future biomarker-informed clinical studies. PMID:25449710

Validation of mismatch negativity and P3a for use in multi-site studies of schizophrenia: characterization of demographic, clinical, cognitive, and functional correlates in COGS-2.

PubMed

Light, Gregory A; Swerdlow, Neal R; Thomas, Michael L; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Pela, Marlena; Radant, Allen D; Seidman, Larry J; Sharp, Richard F; Siever, Larry J; Silverman, Jeremy M; Sprock, Joyce; Stone, William S; Sugar, Catherine A; Tsuang, Debby W; Tsuang, Ming T; Braff, David L; Turetsky, Bruce I

2015-04-01

Mismatch negativity (MMN) and P3a are auditory event-related potential (ERP) components that show robust deficits in schizophrenia (SZ) patients and exhibit qualities of endophenotypes, including substantial heritability, test-retest reliability, and trait-like stability. These measures also fulfill criteria for use as cognition and function-linked biomarkers in outcome studies, but have not yet been validated for use in large-scale multi-site clinical studies. This study tested the feasibility of adding MMN and P3a to the ongoing Consortium on the Genetics of Schizophrenia (COGS) study. The extent to which demographic, clinical, cognitive, and functional characteristics contribute to variability in MMN and P3a amplitudes was also examined. Participants (HCS n=824, SZ n=966) underwent testing at 5 geographically distributed COGS laboratories. Valid ERP recordings were obtained from 91% of HCS and 91% of SZ patients. Highly significant MMN (d=0.96) and P3a (d=0.93) amplitude reductions were observed in SZ patients, comparable in magnitude to those observed in single-lab studies with no appreciable differences across laboratories. Demographic characteristics accounted for 26% and 18% of the variance in MMN and P3a amplitudes, respectively. Significant relationships were observed among demographically-adjusted MMN and P3a measures and medication status as well as several clinical, cognitive, and functional characteristics of the SZ patients. This study demonstrates that MMN and P3a ERP biomarkers can be feasibly used in multi-site clinical studies. As with many clinical tests of brain function, demographic factors contribute to MMN and P3a amplitudes and should be carefully considered in future biomarker-informed clinical studies. Published by Elsevier B.V.

Biomarkers in cancer screening: a public health perspective.

PubMed

Srivastava, Sudhir; Gopal-Srivastava, Rashmi

2002-08-01

The last three decades have witnessed a rapid advancement and diffusion of technology in health services. Technological innovations have given health service providers the means to diagnose and treat an increasing number of illnesses, including cancer. In this effort, research on biomarkers for cancer detection and risk assessment has taken a center stage in our effort to reduce cancer deaths. For the first time, scientists have the technologies to decipher and understand these biomarkers and to apply them to earlier cancer detection. By identifying people at high risk of developing cancer, it would be possible to develop intervention efforts on prevention rather than treatment. Once fully developed and validated, then the regular clinical use of biomarkers in early detection and risk assessment will meet nationally recognized health care needs: detection of cancer at its earliest stage. The dramatic rise in health care costs in the past three decades is partly related to the proliferation of new technologies. More recent analysis indicates that technological change, such as new procedures, products and capabilities, is the primary explanation of the historical increase in expenditure. Biomarkers are the new entrants in this competing environment. Biomarkers are considered as a competing, halfway or add-on technology. Technology such as laboratory tests of biomarkers will cost less compared with computed tomography (CT) scans and other radiographs. However, biomarkers for earlier detection and risk assessment have not achieved the level of confidence required for clinical applications. This paper discusses some issues related to biomarker development, validation and quality assurance. Some data on the trends of diagnostic technologies, proteomics and genomics are presented and discussed in terms of the market share. Eventually, the use of biomarkers in health care could reduce cost by providing noninvasive, sensitive and reliable assays at a fraction of the cost of definitive technology, such as CT scan. The National Cancer Institute's Early Detection Research Network (EDRN) has begun an innovative, investigator-initiated project to improve methods for detecting the biomarkers of cancer cells. The EDRN is a consortium of more than 32 institutions to link discovery of biomarkers to the next steps in the process of developing early detection tests. These discoveries will lead to early clinical validation of tests with improved accuracy and reliability.

Relative validity and reproducibility of a quantitative FFQ for assessing nutrient intakes of vegetarians in Taiwan.

PubMed

Chiu, Tina H T; Huang, Hui-Ya; Chen, Kuan-Ju; Wu, Yu-R U; Chiu, Jason P C; Li, Yi-Hwei; Chiu, Brian C-H; Lin, Chin-Lon; Lin, Ming-Nan

2014-07-01

To assess the relative validity and reproducibility of the quantitative FFQ used in the Tzu Chi Health Study (TCHS). The reproducibility was evaluated by comparing the baseline FFQ with the 2-year follow-up FFQ. The validity was evaluated by comparing the baseline FFQ with 3 d dietary records and biomarkers (serum folate and vitamin B12). Median comparison, cross-classification and Spearman correlation with and without energy adjustment and deattenuation for day-to-day variation were assessed. TCHS is a prospective cohort containing a high proportion of true vegetarians and part-time vegetarians (regularly consuming a vegetarian diet without completely avoiding meat). Subsets of 103, seventy-eight and 1528 TCHS participants were included in the reproducibility, dietary record-validity and biomarker-validity studies, respectively. Correlations assessing the reproducibility for repeat administrations of the FFQ were in the range of 0·46-0·65 for macronutrients and 0·35-0·67 for micronutrients; the average same quartile agreement was 40%. The correlation between FFQ and biomarkers was 0·41 for both vitamin B12 and folate. Moderate to good correlations between the baseline FFQ and dietary records were found for energy, protein, carbohydrate, saturated and monounsaturated fat, fibre, vitamin C, vitamin A, K, Ca, Mg, P, Fe and Zn (average crude correlation: 0·47 (range: 0·37-0·66); average energy-adjusted correlation: 0·43 (range: 0·38-0·55); average energy-adjusted deattenuated correlation: 0·50 (range: 0·44-0·66)) with same quartile agreement rate of 39% (range: 35-45%), while misclassification to the extreme quartile was rare (average: 4% (range: 0-6%)). The FFQ is a reliable and valid tool to rank relative intake of major nutrients for TCHS participants.

Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.

PubMed

Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

2013-01-01

The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases.

Knowledge-Based Identification of Soluble Biomarkers: Hepatic Fibrosis in NAFLD as an Example

PubMed Central

Page, Sandra; Birerdinc, Aybike; Estep, Michael; Stepanova, Maria; Afendy, Arian; Petricoin, Emanuel; Younossi, Zobair; Chandhoke, Vikas; Baranova, Ancha

2013-01-01

The discovery of biomarkers is often performed using high-throughput proteomics-based platforms and is limited to the molecules recognized by a given set of purified and validated antigens or antibodies. Knowledge-based, or systems biology, approaches that involve the analysis of integrated data, predominantly molecular pathways and networks may infer quantitative changes in the levels of biomolecules not included by the given assay from the levels of the analytes profiled. In this study we attempted to use a knowledge-based approach to predict biomarkers reflecting the changes in underlying protein phosphorylation events using Nonalcoholic Fatty Liver Disease (NAFLD) as a model. Two soluble biomarkers, CCL-2 and FasL, were inferred in silico as relevant to NAFLD pathogenesis. Predictive performance of these biomarkers was studied using serum samples collected from patients with histologically proven NAFLD. Serum levels of both molecules, in combination with clinical and demographic data, were predictive of hepatic fibrosis in a cohort of NAFLD patients. Our study suggests that (1) NASH-specific disruption of the kinase-driven signaling cascades in visceral adipose tissue lead to detectable changes in the levels of soluble molecules released into the bloodstream, and (2) biomarkers discovered in silico could contribute to predictive models for non-malignant chronic diseases. PMID:23405244

A Novel Grading Biomarker for the Prediction of Conversion From Mild Cognitive Impairment to Alzheimer's Disease.

PubMed

Tong, Tong; Gao, Qinquan; Guerrero, Ricardo; Ledig, Christian; Chen, Liang; Rueckert, Daniel; Initiative, Alzheimer's Disease Neuroimaging

2017-01-01

Identifying mild cognitive impairment (MCI) subjects who will progress to Alzheimer's disease (AD) is not only crucial in clinical practice, but also has a significant potential to enrich clinical trials. The purpose of this study is to develop an effective biomarker for an accurate prediction of MCI-to-AD conversion from magnetic resonance images. We propose a novel grading biomarker for the prediction of MCI-to-AD conversion. First, we comprehensively study the effects of several important factors on the performance in the prediction task including registration accuracy, age correction, feature selection, and the selection of training data. Based on the studies of these factors, a grading biomarker is then calculated for each MCI subject using sparse representation techniques. Finally, the grading biomarker is combined with age and cognitive measures to provide a more accurate prediction of MCI-to-AD conversion. Using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, the proposed global grading biomarker achieved an area under the receiver operating characteristic curve (AUC) in the range of 79-81% for the prediction of MCI-to-AD conversion within three years in tenfold cross validations. The classification AUC further increases to 84-92% when age and cognitive measures are combined with the proposed grading biomarker. The obtained accuracy of the proposed biomarker benefits from the contributions of different factors: a tradeoff registration level to align images to the template space, the removal of the normal aging effect, selection of discriminative voxels, the calculation of the grading biomarker using AD and normal control groups, and the integration of sparse representation technique and the combination of cognitive measures. The evaluation on the ADNI dataset shows the efficacy of the proposed biomarker and demonstrates a significant contribution in accurate prediction of MCI-to-AD conversion.

Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers.

PubMed

Xu, Jing; Chen, Yanhua; Zhang, Ruiping; Song, Yongmei; Cao, Jianzhong; Bi, Nan; Wang, Jingbo; He, Jiuming; Bai, Jinfa; Dong, Lijia; Wang, Luhua; Zhan, Qimin; Abliz, Zeper

2013-05-01

Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)(1) analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated over the treatment course. The results suggest that these biomarkers may be useful in diagnosis, as well as in monitoring therapeutic responses and predicting outcomes of the ESCC.

Alzheimer’s Disease and Environmental Exposure to Lead: The Epidemiologic Evidence and Potential Role of Epigenetics

PubMed Central

Bakulski, Kelly M.; Rozek, Laura S.; Dolinoy, Dana C.; Paulson, Henry L.; Hu, Howard

2013-01-01

Several lines of evidence indicate that the etiology of late-onset Alzheimer’s disease (LOAD) is complex, with significant contributions from both genes and environmental factors. Recent research suggests the importance of epigenetic mechanisms in defining the relationship between environmental exposures and LOAD. In epidemiologic studies of adults, cumulative lifetime lead (Pb) exposure has been associated with accelerated declines in cognition. In addition, research in animal models suggests a causal association between Pb exposure during early life, epigenetics, and LOAD. There are multiple challenges to human epidemiologic research evaluating the relationship between epigenetics, LOAD, and Pb exposure. Epidemiologic studies are not well-suited to accommodate the long latency period between exposures during early life and onset of Alzheimer’s disease. There is also a lack of validated circulating epigenetics biomarkers and retrospective biomarkers of Pb exposure. Members of our research group have shown bone Pb is an accurate measurement of historical Pb exposure in adults, offering an avenue for future epidemiologic studies. However, this would not address the risk of LOAD attributable to early-life Pb exposures. Future studies that use a cohort design to measure both Pb exposure and validated epigenetic biomarkers of LOAD will be useful to clarify this important relationship. PMID:22272628

Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a Subcohort from the PREDIMED study.

PubMed

Madrid-Gambin, Francisco; Llorach, Rafael; Vázquez-Fresno, Rosa; Urpi-Sarda, Mireia; Almanza-Aguilera, Enrique; Garcia-Aloy, Mar; Estruch, Ramon; Corella, Dolores; Andres-Lacueva, Cristina

2017-04-07

Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils, and beans), spot urine samples from a subcohort from the PREDIMED study were stratified using a validated food frequency questionnaire. Urine samples of nonpulse consumers (≤4 g/day of pulse intake) and habitual pulse consumers (≥25 g/day of pulse intake) were analyzed using a 1 H nuclear magnetic resonance (NMR) metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine, and 3-methylhistidine. This model was evaluated by a receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to reported pulse exposure highlighted new candidates for biomarkers of pulse consumption and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings.

Disease Heterogeneity and Immune Biomarkers in Preclinical Mouse Models of Ovarian Carcinogenesis

DTIC Science & Technology

2011-08-01

with either endometriosis , ovarian cancer or endometriosis progressing to ovarian cancer. Aim 3. To validate in human specimens the disease...biomarkers identified (in aim 2) in mice with endometriosis and ovarian tumors. BODY We present below our progress (year 1) according to the tasks and... endometriosis , ovarian cancer or endometriosis progressing to ovarian cancer. The work on this aim has been initiated. We have already validated the in vivo

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed Central

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-01-01

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-09-28

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

Improved multimodal biomarkers for Alzheimer's disease and mild cognitive impairment diagnosis: data from ADNI

NASA Astrophysics Data System (ADS)

Martinez-Torteya, Antonio; Treviño-Alvarado, Víctor; Tamez-Peña, José

2013-02-01

The accurate diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) confers many clinical research and patient care benefits. Studies have shown that multimodal biomarkers provide better diagnosis accuracy of AD and MCI than unimodal biomarkers, but their construction has been based on traditional statistical approaches. The objective of this work was the creation of accurate AD and MCI diagnostic multimodal biomarkers using advanced bioinformatics tools. The biomarkers were created by exploring multimodal combinations of features using machine learning techniques. Data was obtained from the ADNI database. The baseline information (e.g. MRI analyses, PET analyses and laboratory essays) from AD, MCI and healthy control (HC) subjects with available diagnosis up to June 2012 was mined for case/controls candidates. The data mining yielded 47 HC, 83 MCI and 43 AD subjects for biomarker creation. Each subject was characterized by at least 980 ADNI features. A genetic algorithm feature selection strategy was used to obtain compact and accurate cross-validated nearest centroid biomarkers. The biomarkers achieved training classification accuracies of 0.983, 0.871 and 0.917 for HC vs. AD, HC vs. MCI and MCI vs. AD respectively. The constructed biomarkers were relatively compact: from 5 to 11 features. Those multimodal biomarkers included several widely accepted univariate biomarkers and novel image and biochemical features. Multimodal biomarkers constructed from previously and non-previously AD associated features showed improved diagnostic performance when compared to those based solely on previously AD associated features.

Automated assessment of imaging biomarkers for the PanCan lung cancer risk prediction model with validation on NLST data

NASA Astrophysics Data System (ADS)

Wiemker, Rafael; Sevenster, Merlijn; MacMahon, Heber; Li, Feng; Dalal, Sandeep; Tahmasebi, Amir; Klinder, Tobias

2017-03-01

The imaging biomarkers EmphysemaPresence and NoduleSpiculation are crucial inputs for most models aiming to predict the risk of indeterminate pulmonary nodules detected at CT screening. To increase reproducibility and to accelerate screening workflow it is desirable to assess these biomarkers automatically. Validation on NLST images indicates that standard histogram measures are not sufficient to assess EmphysemaPresence in screenees. However, automatic scoring of bulla-resembling low attenuation areas can achieve agreement with experts with close to 80% sensitivity and specificity. NoduleSpiculation can be automatically assessed with similar accuracy. We find a dedicated spiculi tracing score to slightly outperform generic combinations of texture features with classifiers.

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

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

PubMed

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

2017-02-22

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

Quantitative Analysis of Tissue Samples by Combining iTRAQ Isobaric Labeling with Selected/Multiple Reaction Monitoring (SRM/MRM).

PubMed

Narumi, Ryohei; Tomonaga, Takeshi

2016-01-01

Mass spectrometry-based phosphoproteomics is an indispensible technique used in the discovery and quantification of phosphorylation events on proteins in biological samples. The application of this technique to tissue samples is especially useful for the discovery of biomarkers as well as biological studies. We herein describe the application of a large-scale phosphoproteome analysis and SRM/MRM-based quantitation to develop a strategy for the systematic discovery and validation of biomarkers using tissue samples.

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

PubMed Central

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

2014-01-01

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

Developing a national strategy to prevent dementia: Leon Thal Symposium 2009.

PubMed

Khachaturian, Zaven S; Barnes, Deborah; Einstein, Richard; Johnson, Sterling; Lee, Virginia; Roses, Allen; Sager, Mark A; Shankle, William R; Snyder, Peter J; Petersen, Ronald C; Schellenberg, Gerard; Trojanowski, John; Aisen, Paul; Albert, Marilyn S; Breitner, John C S; Buckholtz, Neil; Carrillo, Maria; Ferris, Steven; Greenberg, Barry D; Grundman, Michael; Khachaturian, Ara S; Kuller, Lewis H; Lopez, Oscar L; Maruff, Paul; Mohs, Richard C; Morrison-Bogorad, Marcelle; Phelps, Creighton; Reiman, Eric; Sabbagh, Marwan; Sano, Mary; Schneider, Lon S; Siemers, Eric; Tariot, Pierre; Touchon, Jacques; Vellas, Bruno; Bain, Lisa J

2010-03-01

Among the major impediments to the design of clinical trials for the prevention of Alzheimer's disease (AD), the most critical is the lack of validated biomarkers, assessment tools, and algorithms that would facilitate identification of asymptomatic individuals with elevated risk who might be recruited as study volunteers. Thus, the Leon Thal Symposium 2009 (LTS'09), on October 27-28, 2009 in Las Vegas, Nevada, was convened to explore strategies to surmount the barriers in designing a multisite, comparative study to evaluate and validate various approaches for detecting and selecting asymptomatic people at risk for cognitive disorders/dementia. The deliberations of LTS'09 included presentations and reviews of different approaches (algorithms, biomarkers, or measures) for identifying asymptomatic individuals at elevated risk for AD who would be candidates for longitudinal or prevention studies. The key nested recommendations of LTS'09 included: (1) establishment of a National Database for Longitudinal Studies as a shared research core resource; (2) launch of a large collaborative study that will compare multiple screening approaches and biomarkers to determine the best method for identifying asymptomatic people at risk for AD; (3) initiation of a Global Database that extends the concept of the National Database for Longitudinal Studies for longitudinal studies beyond the United States; and (4) development of an educational campaign that will address public misconceptions about AD and promote healthy brain aging. 2010. Published by Elsevier Inc.

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

NASA Astrophysics Data System (ADS)

Lou, Sha; Balluff, Benjamin; Cleven, Arjen H. G.; Bovée, Judith V. M. G.; McDonnell, Liam A.

2017-02-01

Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival ( m/z 180.9436 and 241.0118) and metastasis-free survival ( m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine.

Epistemology, Ethics, and Progress in Precision Medicine.

PubMed

Hey, Spencer Phillips; Barsanti-Innes, Brianna

2016-01-01

The emerging paradigm of precision medicine strives to leverage the tools of molecular biology to prospectively tailor treatments to the individual patient. Fundamental to the success of this movement is the discovery and validation of "predictive biomarkers," which are properties of a patient's biological specimens that can be assayed in advance of therapy to inform the treatment decision. Unfortunately, research into biomarkers and diagnostics for precision medicine has fallen well short of expectations. In this essay, we examine the portfolio of research activities into the excision repair cross complement group 1 (ERCC1) gene as a predictive biomarker for precision lung cancer therapy as a case study in elucidating the epistemological and ethical obstacles to developing new precision medicines.

New Markers of Dietary Added Sugar Intake

PubMed Central

Davy, Brenda; Jahren, Hope

2016-01-01

Purpose of review Added sugar (AS) consumption is associated with adverse health outcomes including weight gain and cardio-metabolic disease, yet the reliance on self-reported methods to determine AS intake continues to be a significant research limitation. The purpose of this review is to summarize recent advances in the development of two potential predictive biomarkers of added sugar intake: δ13C and urinary sugar excretion. Recent findings The results of numerous cross-sectional investigations have indicated modest associations of the δ13C sugar biomarker measured in a variety of sample types (e.g., fingerstick blood, serum, red blood cells, hair) with self-reported AS and sugar-sweetened beverage (SSB) intake, and δ13C values have been reported to change over time with changes in reported SSB intake. Results from large-scale trials have suggested modest associations of urinary sugar excretion with reported sugar intake, and a dose-response relation has been demonstrated between urinary sugar excretion and actual sugar intake. Summary Valid markers of sugar intake are urgently needed to more definitively determine the health consequences of AS intake. Adequately-powered controlled feeding studies are needed to validate and compare these two biomarkers of sugar intake, and to determine what individual characteristics and conditions impact biomarker results. PMID:27137898

Biomarkers and mortality after transient ischemic attack and minor ischemic stroke: population-based study.

PubMed

Greisenegger, Stefan; Segal, Helen C; Burgess, Annette I; Poole, Debbie L; Mehta, Ziyah; Rothwell, Peter M

2015-03-01

Premature death after transient ischemic attack or stroke is more often because of heart disease or cancer than stroke. Previous studies found blood biomarkers not usefully predictive of nonfatal stroke but possibly of all-cause death. This association might be explained by potentially treatable occult cardiac disease or cancer. We therefore aimed to validate the association of a panel of biomarkers with all-cause death, particularly cardiac death and cancer death, despite the absence of associations with risk of nonfatal vascular events. Fifteen biomarkers were measured in 929 consecutive patients in a population-based study (Oxford Vascular Study), recruited from 2002 and followed up to 2013. Associations were determined by Cox regression. Model discrimination was assessed by c-statistic and the integrated discrimination improvement. During 5560 patient-years of follow-up, none of the biomarkers predicted risk of nonfatal vascular events. However, soluble tumor necrosis factor α receptor-1, von Willebrand factor, heart-type fatty-acid-binding protein, and N-terminal pro-B-type natriuretic peptide were independently predictive of all-cause death (n=361; adjusted hazard ratio per SD, 95% confidence interval: heart-type fatty-acid-binding protein: 1.31, 1.12-1.56, P=0.002; N-terminal pro-B-type natriuretic peptide: 1.34, 1.11-1.62, P=0.002; soluble tumor necrosis factor α receptor-1: 1.45, 1.26-1.66, P=0.02; von Willebrand factor: 1.19, 1.04-1.36, P=0.01). The independent contribution of the four biomarkers taken together added prognostic information and improved model discrimination (integrated discrimination improvement=0.028, P=0.0001). N-terminal pro-B-type natriuretic peptide was most predictive of vascular death (adjusted hazard ratio=1.80, 95% confidence interval, 1.34-2.41, P<0.0001), whereas heart-type fatty-acid-binding protein predicted cancer deaths (1.64, 1.26-2.12, P=0.0002). Associations were strongest in patients without known prior cardiac disease or cancer. Several biomarkers predicted death of any cause after transient ischemic attack and minor stroke. N-terminal pro-B-type natriuretic peptide and heart-type fatty-acid-binding protein might improve patient selection for additional screening for occult cardiac disease or cancer, respectively. However, our results require validation in future studies. © 2015 American Heart Association, Inc.

Biomarkers in patients treated with BCG: an update.

PubMed

Klap, Julia; Schmid, Marianne; Loughlin, Kevin R

2014-08-01

Bacillus Calmette-Guerin (BCG) instillations are the recommended treatment for non-muscle invasive bladder cancer but high recurrence and progression rates remain after treatment. Despite patients risk stratification, BCG effectiveness remains unpredictable. A close, invasive and expensive follow up is mandatory. To improve or even replace this heavy surveillance in this high risk population, validated biomarkers were developed. To identify the useful tools for the urologist in monitoring bladder cancer patients, we reviewed the literature focusing on plasma and urinary biomarkers of BCG-therapy outcome. Articles dated from 1988 to 2013 including specific keywords (urinary bladder neoplasm, biological markers, intravesical administration, recurrence) were examined and relevant papers were selected. Before treatment initiation, genetic polymorphisms of multiple agents (cytokines, matrix-metalloproteinases) were found to become very useful to tailor therapy and monitoring. Those biomarkers belong to personalized medicine which is a topic of great interest today, but still need to be validated in cohorts from different ethnicities. During instillations, cytokines (IL-2, IL-8, IL-6/IL-10) were reported to be reliable to determine treatment response and efficacy. Further studies are needed to confirm results and standardize thresholds. After treatment, UroVysion, the FDA-approved fluorescence in situ hybridization (FISH), appeared to be the most robust marker of all the clinical parameters reviewed; but is not yet validated for BCG-treated patients. No recommendations for everyday practice can be established today, but a combination of several markers and clinicopathological characteristics may be the future. As bladder cancer diagnosis and management are evolving, practicing urologists should be aware of and utilize bladder cancer markers in clinical practice.

Biomarkers in mood disorders research: developing new and improved therapeutics

PubMed Central

Niciu, Mark J.; Mathews, Daniel C.; Ionescu, Dawn F.; Richards, Erica M.; Furey, Maura L.; Yuan, Peixiong; Nugent, Allison C.; Henter, Ioline D.; Machado-Vieira, Rodrigo; Zarate, Carlos A.

2015-01-01

Background Recently, surrogate neurobiological biomarkers that correlate with target engagement and therapeutic response have been developed and tested in early phase studies of mood disorders. Objective The identification of biomarkers could help develop personalized psychiatric treatments that may impact public health. Methods These biomarkers, which are associated with clinical response post-treatment, can be directly validated using multimodal approaches including genetic tools, proteomics/metabolomics, peripheral measures, neuroimaging, biostatistical predictors, and clinical predictors. Results To date, early phase biomarker studies have sought to identify measures that can serve as “biosignatures”, or biological patterns of clinical response. These studies have also sought to identify clinical predictors and surrogate outcomes associated with pathophysiological domains consistently described in the National Institute of Mental Health’s (NIMH) new Research Domain Criteria (RDoC). Using the N-methyl-D-aspartate (NMDA) antagonist ketamine as an example, we identified changes in several domains (clinical, cognitive, and neurophysiological) that predicted ketamine’s rapid and sustained antidepressant effects in individuals with treatment-resistant major depressive disorder (MDD) or bipolar depression. Discussion These approaches may ultimately provide clues into the neurobiology of psychiatric disorders and may have enormous impact Backon the development of novel therapeutics. PMID:26082563

Peri-Implant Crevicular Fluid Analysis, Enzymes and Biomarkers: a Systemetic Review

PubMed Central

Dursun, Erhan

2016-01-01

ABSTRACT Objectives To review the current understanding of the biomarkers and enzymes associated with different forms peri-implant diseases and how their level changes influence the pathogenesis of the inflammatory diseases around dental implants. Material and Methods An electronic search in two different databases was performed including MEDLINE (PubMed) and EMBASE between 1996 to 2016. Human studies analyse peri-implant crevicular fluid (PICF) biomarker and enzyme levels of implants having peri-implant mucositis and peri-implantitis published in English language, were evaluated. A systematic review was performed to assess which biomarkers and enzymes in PICF were used to identify the inflammatory conditions around dental implants. Results Fifty-one articles were identified of which 41 were further evaluated and included in the analysis. Due to significant heterogeneity between included studies, a meta-analysis could not be performed. Instead, a systematic descriptive review was performed. Conclusions Biomarkers and enzymes in peri-implant crevicular fluid have shown promising results in differentiating from peri-implant disease condition to health. However, due to inconsistent results and acquiring much evidence from cross-sectional studies, additional evidence supported by randomized-controlled trials is needed to validate the links reported. PMID:27833734

The combination of decoy receptor 3 and soluble triggering receptor expressed on myeloid cells-1 for the diagnosis of nosocomial bacterial meningitis.

PubMed

Liu, Yong-Juan; Shao, Li-Hua; Zhang, Jian; Fu, Shan-Ji; Wang, Gang; Chen, Feng-Zhe; Zheng, Feng; Ma, Rui-Ping; Liu, Hai-Hong; Dong, Xiao-Meng; Ma, Li-Xian

2015-03-23

Early diagnosis and appropriate antibiotic treatment can significantly reduce mortality of nosocomial bacterial meningitis. However, it is a challenge for clinicians to make an accurate and rapid diagnosis of bacterial meningitis. This study aimed at determining whether combined biomarkers can provide a useful tool for the diagnosis of bacterial meningitis. A retrospective study was carried out. Cerebrospinal fluid (CSF) levels of decoy receptor 3 (DcR3) and soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) were detected by enzyme-linked immunosorbent assay (ELISA). The patients with bacterial meningitis had significantly elevated levels of the above mentioned biomarkers. The two biomarkers were all risk factors with bacterial meningitis. The biomarkers were constructed into a "bioscore". The discriminative performance of the bioscore was better than that of each biomarker, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.842 (95% confidence intervals (CI) 0.770-0.914; p< 0.001). Combined measurement of CSF DcR3 and sTREM-1 concentrations improved the prediction of nosocomial bacterial meningitis. The combined strategy is of interest and the validation of that improvement needs further studies.

Systematic review of clinical studies examining biomarkers of brain injury in athletes after sports-related concussion.

PubMed

Papa, Linda; Ramia, Michelle M; Edwards, Damyan; Johnson, Brian D; Slobounov, Semyon M

2015-05-15

The aim of this study was to systematically review clinical studies examining biofluid biomarkers of brain injury for concussion in athletes. Data sources included PubMed, MEDLINE, and the Cochrane Database from 1966 to October 2013. Studies were included if they recruited athletes participating in organized sports who experienced concussion or head injury during a sports-related activity and had brain injury biomarkers measured. Acceptable research designs included experimental, observational, and case-control studies. Review articles, opinion papers, and editorials were excluded. After title and abstract screening of potential articles, full texts were independently reviewed to identify articles that met inclusion criteria. A composite evidentiary table was then constructed and documented the study title, design, population, methods, sample size, outcome measures, and results. The search identified 52 publications, of which 13 were selected and critically reviewed. All of the included studies were prospective and were published either in or after the year 2000. Sports included boxing (six studies), soccer (five studies), running/jogging (two studies), hockey (one study), basketball (one study), cycling (one study), and swimming (one study). The majority of studies (92%) had fewer than 100 patients. Three studies (23%) evaluated biomarkers in cerebrospinal fluid (CSF), one in both serum and CSF, and 10 (77%) in serum exclusively. There were 11 different biomarkers assessed, including S100β, glial fibrillary acidic protein, neuron-specific enolase, tau, neurofilament light protein, amyloid beta, brain-derived neurotrophic factor, creatine kinase and heart-type fatty acid binding protein, prolactin, cortisol, and albumin. A handful of biomarkers showed a correlation with number of hits to the head (soccer), acceleration/deceleration forces (jumps, collisions, and falls), postconcussive symptoms, trauma to the body versus the head, and dynamics of different sports. Although there are no validated biomarkers for concussion as yet, there is potential for biomarkers to provide diagnostic, prognostic, and monitoring information postinjury. They could also be combined with neuroimaging to assess injury evolution and recovery.

Systematic Review of Clinical Studies Examining Biomarkers of Brain Injury in Athletes after Sports-Related Concussion

PubMed Central

Ramia, Michelle M.; Edwards, Damyan; Johnson, Brian D.; Slobounov, Semyon M.

2015-01-01

Abstract The aim of this study was to systematically review clinical studies examining biofluid biomarkers of brain injury for concussion in athletes. Data sources included PubMed®, MEDLINE®, and the Cochrane Database from 1966 to October 2013. Studies were included if they recruited athletes participating in organized sports who experienced concussion or head injury during a sports-related activity and had brain injury biomarkers measured. Acceptable research designs included experimental, observational, and case-control studies. Review articles, opinion papers, and editorials were excluded. After title and abstract screening of potential articles, full texts were independently reviewed to identify articles that met inclusion criteria. A composite evidentiary table was then constructed and documented the study title, design, population, methods, sample size, outcome measures, and results. The search identified 52 publications, of which 13 were selected and critically reviewed. All of the included studies were prospective and were published either in or after the year 2000. Sports included boxing (six studies), soccer (five studies), running/jogging (two studies), hockey (one study), basketball (one study), cycling (one study), and swimming (one study). The majority of studies (92%) had fewer than 100 patients. Three studies (23%) evaluated biomarkers in cerebrospinal fluid (CSF), one in both serum and CSF, and 10 (77%) in serum exclusively. There were 11 different biomarkers assessed, including S100β, glial fibrillary acidic protein, neuron-specific enolase, tau, neurofilament light protein, amyloid beta, brain-derived neurotrophic factor, creatine kinase and heart-type fatty acid binding protein, prolactin, cortisol, and albumin. A handful of biomarkers showed a correlation with number of hits to the head (soccer), acceleration/deceleration forces (jumps, collisions, and falls), postconcussive symptoms, trauma to the body versus the head, and dynamics of different sports. Although there are no validated biomarkers for concussion as yet, there is potential for biomarkers to provide diagnostic, prognostic, and monitoring information postinjury. They could also be combined with neuroimaging to assess injury evolution and recovery. PMID:25254425

Metabolic products as biomarkers

USGS Publications Warehouse

Melancon, M.J.; Alscher, R.; Benson, W.; Kruzynski, G.; Lee, R.F.; Sikka, H.C.; Spies, R.B.; Huggett, Robert J.; Kimerle, Richard A.; Mehrle, Paul M.=; Bergman, Harold L.

1992-01-01

Ideally, endogenous biomarkers would indicate both exposure and environmental effects of toxic chemicals; however, such comprehensive biochemical and physiological indices are currently being developed and, at the present time, are unavailable for use in environmental monitoring programs. Continued work is required to validate the use of biochemical and physiological stress indices as useful components of monitoring programs. Of the compounds discussed only phytochelatins and porphyrins are currently in biomarkers in a useful state; however, glutathione,metallothioneins, stress ethylene, and polyamines are promising as biomarkers in environmental monitoring.

Identifying FGA peptides as nasopharyngeal carcinoma-associated biomarkers by magnetic beads.

PubMed

Tao, Ya-Lan; Li, Yan; Gao, Jin; Liu, Zhi-Gang; Tu, Zi-Wei; Li, Guo; Xu, Bing-Qing; Niu, Dao-Li; Jiang, Chang-Bin; Yi, Wei; Li, Zhi-Qiang; Li, Jing; Wang, Yi-Ming; Cheng, Zhi-Bin; Liu, Qiao-Dan; Bai, Li; Zhang, Chun; Zhang, Jing-Yu; Zeng, Mu-Sheng; Xia, Yun-Fei

2012-07-01

Early diagnosis and treatment is known to improve prognosis for nasopharyngeal carcinoma (NPC). The study determined the specific peptide profiles by comparing the serum differences between NPC patients and healthy controls, and provided the basis for the diagnostic model and identification of specific biomarkers of NPC. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) can be used to detect the molecular mass of peptides. Mass spectra of peptides were generated after extracting and purification of 40 NPC samples in the training set, 21 in the single center validation set and 99 in the multicenter validation set using weak cationic-exchanger magnetic beads. The spectra were analyzed statistically using FlexAnalysis™ and ClinProt™ bioinformatics software. The four most significant peaks were selected out to train a genetic algorithm model to diagnose NPC. The diagnostic sensitivity and specificity were 100% and 100% in the training set, 90.5% and 88.9% in the single center validation set, 91.9% and 83.3% in the multicenter validation set, and the false positive rate (FPR) and false negative rate (FNR) were obviously lower in the NPC group (FPR, 16.7%; FNR, 8.1%) than in the other cancer group (FPR, 39%; FNR, 61%), respectively. So, the diagnostic model including four peptides can be suitable for NPC but not for other cancers. FGA peptide fragments identified may serve as tumor-associated biomarkers for NPC. Copyright © 2012 Wiley Periodicals, Inc.

Biomarkers of exposure to new and emerging tobacco delivery products.

PubMed

Schick, Suzaynn F; Blount, Benjamin C; Jacob, Peyton; Saliba, Najat A; Bernert, John T; El Hellani, Ahmad; Jatlow, Peter; Pappas, R Steven; Wang, Lanqing; Foulds, Jonathan; Ghosh, Arunava; Hecht, Stephen S; Gomez, John C; Martin, Jessica R; Mesaros, Clementina; Srivastava, Sanjay; St Helen, Gideon; Tarran, Robert; Lorkiewicz, Pawel K; Blair, Ian A; Kimmel, Heather L; Doerschuk, Claire M; Benowitz, Neal L; Bhatnagar, Aruni

2017-09-01

Accurate and reliable measurements of exposure to tobacco products are essential for identifying and confirming patterns of tobacco product use and for assessing their potential biological effects in both human populations and experimental systems. Due to the introduction of new tobacco-derived products and the development of novel ways to modify and use conventional tobacco products, precise and specific assessments of exposure to tobacco are now more important than ever. Biomarkers that were developed and validated to measure exposure to cigarettes are being evaluated to assess their use for measuring exposure to these new products. Here, we review current methods for measuring exposure to new and emerging tobacco products, such as electronic cigarettes, little cigars, water pipes, and cigarillos. Rigorously validated biomarkers specific to these new products have not yet been identified. Here, we discuss the strengths and limitations of current approaches, including whether they provide reliable exposure estimates for new and emerging products. We provide specific guidance for choosing practical and economical biomarkers for different study designs and experimental conditions. Our goal is to help both new and experienced investigators measure exposure to tobacco products accurately and avoid common experimental errors. With the identification of the capacity gaps in biomarker research on new and emerging tobacco products, we hope to provide researchers, policymakers, and funding agencies with a clear action plan for conducting and promoting research on the patterns of use and health effects of these products.

Assessment of beverage intake and hydration status.

PubMed

Nissensohn, Mariela; López-Ufano, Marisa; Castro-Quezada, Itandehui; Serra-Majem, Lluis

2015-02-26

Water is the main constituent of the human body. It is involved in practically all its functions. It is particularly important for thermoregulation and in the physical and cognitive performance. Water balance reflects water intake and loss. Intake of water is done mainly through consumption of drinking water and beverages (70 to 80%) plus water containing foods (20 to 30%). Water loss is mainly due to excretion of water in urine, faeces and sweat. The interest in the type and quantity of beverage consumption is not new, and numerous approaches have been used to assess beverage intake, but the validity of these approaches has not been well established. There is no standardized questionnaire developed as a research tool for the evaluation of water intake in the general population. Sometimes, the information comes from different sources or from different methodological characteristics which raises problems of the comparability. In the European Union, current epidemiological studies that focus exclusively on beverage intake are scarce. Biomarkers of intake are able to objectively assess dietary intake/status without the bias of self-reported dietary intake errors and also overcome the problem of intra-individual diet variability. Furthermore, some methods of measuring dietary intake used biomarkers to validate the data it collects. Biological markers may offer advantages and be able to improve the estimates of dietary intake assessment, which impact into the statistical power of the study. There is a surprising paucity of studies that systematically examine the correlation of beverages intake and hydration biomarker in different populations. A pilot investigation was developed to evaluate the comparative validity and reliability of newly developed interactive multimedia (IMM) versions compared to validated paper-administered (PP) versions of the Hedrick et al. beverage questionnaire. The study showed that the IMM appears to be a valid and reliable measure to assess habitual beverage intake. Similar study was developed in China, but in this case, the use of Smartphone technology was employed for beverage assessment. The methodology for measuring beverage intake in population studies remains controversial. There are few validated and reproducible studies, so there is still lacking an ideal method (ie, short, easy to administer, inexpensive and accurate) in this regard. Clearly, this is an area of scientific interest that is still in development and seems to be very promising for improving health research. Copyright AULA MEDICA EDICIONES 2015. Published by AULA MEDICA. All rights reserved.

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

PubMed

Verma, Mukesh

2015-01-01

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

Foods contributing to vitamin B6, folate, and vitamin B12 intakes and biomarkers status in European adolescents: The HELENA study.

PubMed

Iglesia, Iris; Mouratidou, Theodora; González-Gross, Marcela; Huybrechts, Inge; Breidenassel, Christina; Santabárbara, Javier; Díaz, Ligia-Esperanza; Hällström, Lena; De Henauw, Stefaan; Gottrand, Frédéric; Kafatos, Anthony; Widhalm, Kurt; Manios, Yannis; Molnar, Denes; Stehle, Peter; Moreno, Luis A

2017-06-01

To examine the association between food groups consumption and vitamin B 6 , folate and B 12 intakes and biomarkers in adolescents. In total 2189 individuals participating in the cross-sectional Healthy Lifestyle in Europe by Nutrition in Adolescence study met the eligibility criteria for analysis of dietary intakes (46 % males) and 632 for biomarker analysis (47 % males). Food intakes were assessed by two non-consecutive 24-h recalls. Biomarkers were measured by chromatography and immunoassay. Food groups which best discriminated participants in the extreme tertiles of the distribution of vitamins were identified by discriminant analyses. Food groups with standardised canonical coefficients higher or equal to 0.3 were selected as valid discriminators of vitamins intake and biomarkers extreme tertiles. Linear mixed model elucidated the association between food groups and vitamins intakes and biomarkers. Vitamin B 6 intakes and biomarkers were best discriminated by meat (males and females), margarine and mixed origin lipids only in males and breakfast cereals (females). Breakfast cereals (males), and fruits, margarine and mixed origin lipids, vegetables excluding potatoes, breakfast cereals, and soups/bouillon (females) determined the most folate intakes and biomarkers. Considering vitamin B 12 intakes and biomarkers, meat, and white and butter milk (males and females), snacks (males), and dairy products (females) best discriminated individual in the extremes of the distribution. Fewer associations were obtained with mixed model for biomarkers than for vitamins intakes with food groups. Whereas B-vitamin intakes were associated with their food sources, biomarkers did with overall food consumption. Low-nutrient-density foods may compromise adolescents' vitamin status.

Blood biomarkers for brain injury: What are we measuring?

PubMed Central

Kawata, Keisuke; Liu, Charles Y.; Merkel, Steven F.; Ramirez, Servio H.; Tierney, Ryan T.; Langford, Dianne

2016-01-01

Accurate diagnosis for mild traumatic brain injury (mTBI) remains challenging, as prognosis and return-to-play/work decisions are based largely on patient reports. Numerous investigations have identified and characterized cellular factors in the blood as potential biomarkers for TBI, in the hope that these factors may be used to gauge the severity of brain injury. None of these potential biomarkers have advanced to use in the clinical setting. Some of the most extensively studied blood biomarkers for TBI include S100β, neuron-specific enolase, glial fibrillary acidic protein, and Tau. Understanding the biological function of each of these factors may be imperative to achieve progress in the field. We address the basic question: what are we measuring? This review will discuss blood biomarkers in terms of cellular origin, normal and pathological function, and possible reasons for increased blood levels. Considerations in the selection, evaluation, and validation of potential biomarkers will also be addressed, along with mechanisms that allow brain-derived proteins to enter the bloodstream after TBI. Lastly, we will highlight perspectives and implications for repetitive neurotrauma in the field of blood biomarkers for brain injury. PMID:27181909

Accurate Quantification of Cardiovascular Biomarkers in Serum Using Protein Standard Absolute Quantification (PSAQ™) and Selected Reaction Monitoring*

PubMed Central

Huillet, Céline; Adrait, Annie; Lebert, Dorothée; Picard, Guillaume; Trauchessec, Mathieu; Louwagie, Mathilde; Dupuis, Alain; Hittinger, Luc; Ghaleh, Bijan; Le Corvoisier, Philippe; Jaquinod, Michel; Garin, Jérôme; Bruley, Christophe; Brun, Virginie

2012-01-01

Development of new biomarkers needs to be significantly accelerated to improve diagnostic, prognostic, and toxicity monitoring as well as therapeutic follow-up. Biomarker evaluation is the main bottleneck in this development process. Selected Reaction Monitoring (SRM) combined with stable isotope dilution has emerged as a promising option to speed this step, particularly because of its multiplexing capacities. However, analytical variabilities because of upstream sample handling or incomplete trypsin digestion still need to be resolved. In 2007, we developed the PSAQ™ method (Protein Standard Absolute Quantification), which uses full-length isotope-labeled protein standards to quantify target proteins. In the present study we used clinically validated cardiovascular biomarkers (LDH-B, CKMB, myoglobin, and troponin I) to demonstrate that the combination of PSAQ and SRM (PSAQ-SRM) allows highly accurate biomarker quantification in serum samples. A multiplex PSAQ-SRM assay was used to quantify these biomarkers in clinical samples from myocardial infarction patients. Good correlation between PSAQ-SRM and ELISA assay results was found and demonstrated the consistency between these analytical approaches. Thus, PSAQ-SRM has the capacity to improve both accuracy and reproducibility in protein analysis. This will be a major contribution to efficient biomarker development strategies. PMID:22080464

A lung cancer risk classifier comprising genome maintenance genes measured in normal bronchial epithelial cells.

PubMed

Yeo, Jiyoun; Crawford, Erin L; Zhang, Xiaolu; Khuder, Sadik; Chen, Tian; Levin, Albert; Blomquist, Thomas M; Willey, James C

2017-05-02

Annual low dose CT (LDCT) screening of individuals at high demographic risk reduces lung cancer mortality by more than 20%. However, subjects selected for screening based on demographic criteria typically have less than a 10% lifetime risk for lung cancer. Thus, there is need for a biomarker that better stratifies subjects for LDCT screening. Toward this goal, we previously reported a lung cancer risk test (LCRT) biomarker comprising 14 genome-maintenance (GM) pathway genes measured in normal bronchial epithelial cells (NBEC) that accurately classified cancer (CA) from non-cancer (NC) subjects. The primary goal of the studies reported here was to optimize the LCRT biomarker for high specificity and ease of clinical implementation. Targeted competitive multiplex PCR amplicon libraries were prepared for next generation sequencing (NGS) analysis of transcript abundance at 68 sites among 33 GM target genes in NBEC specimens collected from a retrospective cohort of 120 subjects, including 61 CA cases and 59 NC controls. Genes were selected for analysis based on contribution to the previously reported LCRT biomarker and/or prior evidence for association with lung cancer risk. Linear discriminant analysis was used to identify the most accurate classifier suitable to stratify subjects for screening. After cross-validation, a model comprising expression values from 12 genes (CDKN1A, E2F1, ERCC1, ERCC4, ERCC5, GPX1, GSTP1, KEAP1, RB1, TP53, TP63, and XRCC1) and demographic factors age, gender, and pack-years smoking, had Receiver Operator Characteristic area under the curve (ROC AUC) of 0.975 (95% CI: 0.96-0.99). The overall classification accuracy was 93% (95% CI 88%-98%) with sensitivity 93.1%, specificity 92.9%, positive predictive value 93.1% and negative predictive value 93%. The ROC AUC for this classifier was significantly better (p < 0.0001) than the best model comprising demographic features alone. The LCRT biomarker reported here displayed high accuracy and ease of implementation on a high throughput, quality-controlled targeted NGS platform. As such, it is optimized for clinical validation in specimens from the ongoing LCRT blinded prospective cohort study. Following validation, the biomarker is expected to have clinical utility by better stratifying subjects for annual lung cancer screening compared to current demographic criteria alone.

Validation of Biomarkers for Prostate Cancer Prognosis

DTIC Science & Technology

2013-10-01

prostate cancer research community for testing candidate biomarkers. Groups using the resource include Dr. Jeremy Squire, Dr. Gustavo Ayala, and Dr...Ferrari, Javier Hernandez , Antonio Hurtado-Coll, Kyle Kuchinsky, Janet Liew, Rosario Mendez-Meza, Elizabeth Smith, Imelda Tenggarra, Xiaotun Zhang

Genomic analysis of hepatoblastoma identifies distinct molecular and prognostic subgroups.

PubMed

Sumazin, Pavel; Chen, Yidong; Treviño, Lisa R; Sarabia, Stephen F; Hampton, Oliver A; Patel, Kayuri; Mistretta, Toni-Ann; Zorman, Barry; Thompson, Patrick; Heczey, Andras; Comerford, Sarah; Wheeler, David A; Chintagumpala, Murali; Meyers, Rebecka; Rakheja, Dinesh; Finegold, Milton J; Tomlinson, Gail; Parsons, D Williams; López-Terrada, Dolores

2017-01-01

Despite being the most common liver cancer in children, hepatoblastoma (HB) is a rare neoplasm. Consequently, few pretreatment tumors have been molecularly profiled, and there are no validated prognostic or therapeutic biomarkers for HB patients. We report on the first large-scale effort to profile pretreatment HBs at diagnosis. Our analysis of 88 clinically annotated HBs revealed three risk-stratifying molecular subtypes that are characterized by differential activation of hepatic progenitor cell markers and metabolic pathways: high-risk tumors were characterized by up-regulated nuclear factor, erythroid 2-like 2 activity; high lin-28 homolog B, high mobility group AT-hook 2, spalt-like transcription factor 4, and alpha-fetoprotein expression; and high coordinated expression of oncofetal proteins and stem-cell markers, while low-risk tumors had low lin-28 homolog B and lethal-7 expression and high hepatic nuclear factor 1 alpha activity. Analysis of immunohistochemical assays using antibodies targeting these genes in a prospective study of 35 HBs suggested that these candidate biomarkers have the potential to improve risk stratification and guide treatment decisions for HB patients at diagnosis; our results pave the way for clinical collaborative studies to validate candidate biomarkers and test their potential to improve outcome for HB patients. (Hepatology 2017;65:104-121). © 2016 by the American Association for the Study of Liver Diseases.

Proteomic study of benign and malignant pleural effusion.

PubMed

Li, Hongqing; Tang, Zhonghao; Zhu, Huili; Ge, Haiyan; Cui, Shilei; Jiang, Weiping

2016-06-01

Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion. This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model. We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker. A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion. This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

Identification of head and neck squamous cell carcinoma biomarker candidates through proteomic analysis of cancer cell secretome.

PubMed

Marimuthu, Arivusudar; Chavan, Sandip; Sathe, Gajanan; Sahasrabuddhe, Nandini A; Srikanth, Srinivas M; Renuse, Santosh; Ahmad, Sartaj; Radhakrishnan, Aneesha; Barbhuiya, Mustafa A; Kumar, Rekha V; Harsha, H C; Sidransky, David; Califano, Joseph; Pandey, Akhilesh; Chatterjee, Aditi

2013-11-01

Protein biomarker discovery for early detection of head and neck squamous cell carcinoma (HNSCC) is a crucial unmet need to improve patient outcomes. Mass spectrometry-based proteomics has emerged as a promising tool for identification of biomarkers in different cancer types. Proteins secreted from cancer cells can serve as potential biomarkers for early diagnosis. In the current study, we have used isobaric tag for relative and absolute quantitation (iTRAQ) labeling methodology coupled with high resolution mass spectrometry to identify and quantitate secreted proteins from a panel of head and neck carcinoma cell lines. In all, we identified 2,472 proteins, of which 225 proteins were secreted at higher or lower abundance in HNSCC-derived cell lines. Of these, 148 were present in higher abundance and 77 were present in lower abundance in the cancer-cell derived secretome. We detected a higher abundance of some previously known markers for HNSCC including insulin like growth factor binding protein 3, IGFBP3 (11-fold) and opioid growth factor receptor, OGFR (10-fold) demonstrating the validity of our approach. We also identified several novel secreted proteins in HNSCC including olfactomedin-4, OLFM4 (12-fold) and hepatocyte growth factor activator, HGFA (5-fold). IHC-based validation was conducted in HNSCC using tissue microarrays which revealed overexpression of IGFBP3 and OLFM4 in 70% and 75% of the tested cases, respectively. Our study illustrates quantitative proteomics of secretome as a robust approach for identification of potential HNSCC biomarkers. This article is part of a Special Issue entitled: An Updated Secretome. Copyright © 2013 Elsevier B.V. All rights reserved.

Periostin and CA242 as potential diagnostic serum biomarkers complementing CA19.9 in detecting pancreatic cancer.

PubMed

Dong, Dong; Jia, Li; Zhang, Lufang; Ma, Na; Zhang, Aimin; Zhou, Yunli; Ren, Li

2018-06-26

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant tumor with few biomarkers to guide treatment options. Carbohydrate antigen 19.9 (CA19.9), the mainly used biomarker for PDAC, is not sensitive and specific enough for the detection of the disease. This study was aimed to evaluate serum periostin (POSTN) and CA242 as potential diagnostic biomarkers complementing CA19.9 in detecting pancreatic cancer. Blood samples were from 362 participants, including 213 patients with different stages of PDAC, 75 patients with benign pancreatic disease and 74 healthy individuals. All samples were randomly divided into training set and validation set. CA19.9, CA242, POSTN, as well as carcinoembryonic antigen (CEA), were measured by ELISA or automated immunoassay. The receiver operating curve (ROC) analysis revealed that the performances of CA19.9 in the validation group were improved by the marker panel composed of CA19.9, POSTN and CA242, to discriminate early-stage PDAC not only from healthy controls (AUC CA 19.9 = 0.94 vs. AUC CA 19.9 + POSTN + CA 242 = 0.98, P < 0.05) but also from benign conditions (AUC CA 19.9 = 0.87 vs. AUC CA 19.9 + POSTN + CA 242 = 0.90, P < 0.05). In addition, POSTN retained significant diagnostic capabilities to distinguish PDAC CA19.9-negative from healthy controls (AUC POSTN = 0.87) as well as from benign conditions (AUC POSTN = 0.84) in the whole set. This study suggested that POSTN and CA242 are potential diagnostic serum biomarkers complementing CA19.9 in detecting early pancreatic cancer. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

ANMCO/ELAS/SIBioC Consensus Document: biomarkers in heart failure

PubMed Central

Gulizia, Michele Massimo; Clerico, Aldo; Di Tano, Giuseppe; Emdin, Michele; Feola, Mauro; Iacoviello, Massimo; Latini, Roberto; Mortara, Andrea; Valle, Roberto; Misuraca, Gianfranco; Passino, Claudio; Masson, Serge; Aimo, Alberto; Ciaccio, Marcello; Migliardi, Marco

2017-01-01

Abstract Biomarkers have dramatically impacted the way heart failure (HF) patients are evaluated and managed. A biomarker is a characteristic that is objectively measured and evaluated as an indicator of normal biological or pathogenic processes, or pharmacological responses to a therapeutic intervention. Natriuretic peptides [B-type natriuretic peptide (BNP) and N-terminal proBNP] are the gold standard biomarkers in determining the diagnosis and prognosis of HF, and a natriuretic peptide-guided HF management looks promising. In the last few years, an array of additional biomarkers has emerged, each reflecting different pathophysiological processes in the development and progression of HF: myocardial insult, inflammation, fibrosis, and remodelling, but their role in the clinical care of the patient is still partially defined and more studies are needed before to be well validated. Moreover, several new biomarkers have the potential to identify patients with early renal dysfunction and appear to have promise to help the management cardio-renal syndrome. With different biomarkers reflecting HF presence, the various pathways involved in its progression, as well as identifying unique treatment options for HF management, a closer cardiologist-laboratory link, with a multi-biomarker approach to the HF patient, is not far ahead, allowing the unique opportunity for specifically tailoring care to the individual pathological phenotype. PMID:28751838

Neutrophil Gelatinase Associated Lipocalin (NGAL) - a biomarker of renal dysfunction in patients with liver cirrhosis: Do we have enough proof?

PubMed

Firu, S G; Streba, C T; Firu, D; Tache, D E; Rogoveanu, I

2015-01-01

Renal dysfunction has a serious impact on the natural evolution of liver cirrhosis. Treatment and prognosis may be improved if an early diagnosis could be established, and specific therapeutic interventions would be applied. Although RIFLE and AKIN classifications have been successfully implemented in the clinical practice of Nephrology and Intensive Care Units, these did not provide major improvements in patients with liver cirrhosis. In the last decade, various biomarkers of kidney injury have been assessed, and Neutrophil Gelatinase-Associated Lipocalin (NGAL) is one of the most promising and most studied novel biomarker. To offer a brief evaluation on current data on the utility of this biomarker in patients with liver cirrhosis. We have searched through current literature and analyzed all significant full text articles on this topic. NGAL and other new kidney injury molecules may be useful in patients with liver cirrhosis, particularly in identifying structural kidney dysfunction, but larger validation studies to confirm this observation are needed.

Functional Imaging Biomarkers: Potential to Guide an Individualised Approach to Radiotherapy.

PubMed

Prestwich, R J D; Vaidyanathan, S; Scarsbrook, A F

2015-10-01

The identification of robust prognostic and predictive biomarkers would transform the ability to implement an individualised approach to radiotherapy. In this regard, there has been a surge of interest in the use of functional imaging to assess key underlying biological processes within tumours and their response to therapy. Importantly, functional imaging biomarkers hold the potential to evaluate tumour heterogeneity/biology both spatially and temporally. An ever-increasing range of functional imaging techniques is now available primarily involving positron emission tomography and magnetic resonance imaging. Small-scale studies across multiple tumour types have consistently been able to correlate changes in functional imaging parameters during radiotherapy with disease outcomes. Considerable challenges remain before the implementation of functional imaging biomarkers into routine clinical practice, including the inherent temporal variability of biological processes within tumours, reproducibility of imaging, determination of optimal imaging technique/combinations, timing during treatment and design of appropriate validation studies. Copyright © 2015 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Guidelines for the standardization of preanalytic variables for blood-based biomarker studies in Alzheimer’s disease research

PubMed Central

Gupta, Veer; Henriksen, Kim; Edwards, Melissa; Jeromin, Andreas; Lista, Simone; Bazenet, Chantal; Soares, Holly; Lovestone, Simon; Hampel, Harald; Montine, Thomas; Blennow, Kaj; Foroud, Tatiana; Carrillo, Maria; Graff-Radford, Neill; Laske, Christoph; Breteler, Monique; Shaw, Leslie; Trojanowski, John Q.; Schupf, Nicole; Rissman, Robert A.; Fagan, Anne M.; Oberoi, Pankaj; Umek, Robert; Weiner, Michael W.; Grammas, Paula; Posner, Holly; Martins, Ralph

2015-01-01

The lack of readily available biomarkers is a significant hindrance towards progressing to effective therapeutic and preventative strategies for Alzheimer’s disease (AD). Blood-based biomarkers have potential to overcome access and cost barriers and greatly facilitate advanced neuroimaging and cerebrospinal fluid biomarker approaches. Despite the fact that preanalytical processing is the largest source of variability in laboratory testing, there are no currently available standardized preanalytical guidelines. The current international working group provides the initial starting point for such guidelines for standardized operating procedures (SOPs). It is anticipated that these guidelines will be updated as additional research findings become available. The statement provides (1) a synopsis of selected preanalytical methods utilized in many international AD cohort studies, (2) initial draft guidelines/SOPs for preanalytical methods, and (3) a list of required methodological information and protocols to be made available for publications in the field in order to foster cross-validation across cohorts and laboratories. PMID:25282381

The current status of clinical proteomics and the use of MRM and MRM(3) for biomarker validation.

PubMed

Lemoine, Jérôme; Fortin, Tanguy; Salvador, Arnaud; Jaffuel, Aurore; Charrier, Jean-Philippe; Choquet-Kastylevsky, Geneviève

2012-05-01

The transfer of biomarkers from the discovery field to clinical use is still, despite progress, on a road filled with pitfalls. Since the emergence of proteomics, thousands of putative biomarkers have been published, often with overlapping diagnostic capacities. The strengthening of the robustness of discovery technologies, particularly in mass spectrometry, has been followed by intense discussions on establishing well-defined evaluation procedures for the identified targets to ultimately allow the clinical validation and then the clinical use of some of these biomarkers. Some of the obstacles to the evaluation process have been the lack of the availability of quick and easy-to-develop, easy-to-use, robust, specific and sensitive alternative quantitative methods when immunoaffinity-based tests are unavailable. Multiple reaction monitoring (MRM; also called selected reaction monitoring) is currently proving its capabilities as a complementary or alternative technique to ELISA for large biomarker panel evaluation. Here, we present how MRM(3) can overcome the lack of specificity and sensitivity often encountered by MRM when tracking minor proteins diluted by complex biological matrices.

Clinical applications of the functional connectome

PubMed Central

Castellanos, F. Xavier; Di Martino, Adriana; Craddock, R. Cameron; Mehta, Ashesh D.; Milham, Michael P.

2013-01-01

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis. PMID:23631991

THE MECHANISMS OF ENDOCRINE DISRUPTORS IN LABORATORY MICE

EPA Science Inventory

Overall, these studies are designed to confirm and validate the biomarkers determined in the CCCEH human studies of BPA and PAH exposure and to determine the hypothesized link between epigenetic changes in blood with those determined in brain and adipose tissue to determine th...

Comparative differential proteomic analysis of minimal change disease and focal segmental glomerulosclerosis.

PubMed

Pérez, Vanessa; López, Dolores; Boixadera, Ester; Ibernón, Meritxell; Espinal, Anna; Bonet, Josep; Romero, Ramón

2017-02-03

Minimal change disease (MCD) and primary focal segmental glomerulosclerosis (FSGS) are glomerular diseases characterized by nephrotic syndrome. Their diagnosis requires a renal biopsy, but it is an invasive procedure with potential complications. In a small biopsy sample, where only normal glomeruli are observed, FSGS cannot be differentiated from MCD. The correct diagnosis is crucial to an effective treatment, as MCD is normally responsive to steroid therapy, whereas FSGS is usually resistant. The purpose of our study was to discover and validate novel early urinary biomarkers capable to differentiate between MCD and FSGS. Forty-nine patients biopsy-diagnosed of MCD and primary FSGS were randomly subdivided into a training set (10 MCD, 11 FSGS) and a validation set (14 MCD, 14 FSGS). The urinary proteome of the training set was analyzed by two-dimensional differential gel electrophoresis coupled with mass spectrometry. The proteins identified were quantified by enzyme-linked immunosorbent assay in urine samples from the validation set. Urinary concentration of alpha-1 antitrypsin, transferrin, histatin-3 and 39S ribosomal protein L17 was decreased and calretinin was increased in FSGS compared to MCD. These proteins were used to build a decision tree capable to predict patient's pathology. This preliminary study suggests a group of urinary proteins as possible non-invasive biomarkers with potential value in the differential diagnosis of MCD and FSGS. These biomarkers would reduce the number of misdiagnoses, avoiding unnecessary or inadequate treatments.

A characteristic biosignature for discrimination of gastric cancer from healthy population by high throughput GC-MS analysis

PubMed Central

Guo, Lei; Liu, Lei; Wen, Jingran; Xu, Lu; Yan, Min; Li, Zuofeng; Zhang, Xiaoyan; Nan, Peng; Jiang, Jinling; Ji, Jun; Zhang, Jianian; Cai, Wei; Zhuang, Huisheng; Wang, Yan; Zhu, Zhenggang; Yu, Yingyan

2016-01-01

Early diagnosis of gastric cancer is crucial to improve patient′ outcome. A good biomarker will function in early diagnosis for gastric cancer. In order to find practical and cost-effective biomarkers, we used gas chromatography combined mass spectrometer (GC-MS) to profile urinary metabolites on 293 urine samples. Ninety-four samples are taken as training set, others for validating study. Orthogonal partial least squares discriminant analysis (OPLS-DA), significance analysis of microarray (SAM) and Mann-Whitney U test are used for data analysis. The diagnostic value of urinary metabolites was evaluated by ROC curve. As results, Seventeen metabolites are significantly different between patients and healthy controls in training set. Among them, 14 metabolites show diagnostic value better than classic blood biomarkers by quantitative assay on validation set. Ten of them are amino acids and four are organic metabolites. Importantly, proline, p-cresol and 4-hydroxybenzoic acid disclose outcome-prediction value by means of survival analysis. Therefore, the examination of urinary metabolites is a promising noninvasive strategy for gastric cancer screening. PMID:27589838

Label-Free Biomarker Detection from Whole Blood

DTIC Science & Technology

2010-02-01

we overcome this limitation by using distinct components within the sensor to perform purification and detection. A microfluidic purification chip...nanosensors to purify biomarkers of interest. This microfluidic purification chip (MPC) captures cancer biomarkers from physiological solutions and, after...assay validation experiments (Fig. 2c). As shown in Fig. 1d, after a second valve switching step transfers MPC contents to the nanosen- sor chip, the

A novel diagnostic biomarker panel for obesity-related nonalcoholic steatohepatitis (NASH).

PubMed

Younossi, Zobair M; Jarrar, Mohammed; Nugent, Clare; Randhawa, Manpreet; Afendy, Mariam; Stepanova, Maria; Rafiq, Nila; Goodman, Zachary; Chandhoke, Vikas; Baranova, Ancha

2008-11-01

Within the spectrum of nonalcoholic fatty liver disease (NAFLD), only patients with nonalcoholic steatohepatitis (NASH) show convincing evidence for progression. To date, liver biopsy remains the gold standard for the diagnosis of NASH; however, liver biopsy is expensive and associated with a small risk, emphasizing the urgent need for noninvasive diagnostic biomarkers. Recent findings suggest a role for apoptosis and adipocytokines in the pathogenesis of NASH. The aim of this study was to develop a noninvasive diagnostic biomarker for NASH. The study included 101 patients with liver biopsies who were tested with enzyme-linked immunosorbent assay (ELISA)-based assays. Of these, 69 were included in the biomarker development set and 32 were included in the biomarker validation set. Clinical data and serum samples were collected at the time of biopsy. Fasting serum samples were assayed for adiponectin, resistin, insulin, glucose, TNF-alpha, IL-6, IL-8, cytokeratin CK-18 (M65 antigen), and caspase-cleaved CK-18 (M30 antigen). Data analysis revealed that the levels of M30 antigen (cleaved CK-18) predicted histological NASH with 70% sensitivity and 83.7% specificity and area under the curve (AUC) = 0.711, p < 10(-4), whereas the predictive value of the levels of intact CK-18 (M65) was higher (63.6% sensitivity and 89.4% specificity and AUC = 0.814, p < 10(-4)). Histological NASH could be predicted by a combination of Cleaved CK-18, a product of the subtraction of Cleaved CK-18 level from intact CK-18 level, serum adiponectin, and serum resistin with a sensitivity of 95.45% sensitivity, specificity of 70.21%, and AUC of 0.908 (p < 10(-4)). Blinded validation of this model confirmed its reliability for separating NASH from simple steatosis. Four ELISA-based tests were combined to form a simple diagnostic biomarker for NASH.

Host Biomarkers for Distinguishing Bacterial from Non-Bacterial Causes of Acute Febrile Illness: A Comprehensive Review

PubMed Central

Kapasi, Anokhi J.; Dittrich, Sabine; González, Iveth J.; Rodwell, Timothy C.

2016-01-01

Background In resource limited settings acute febrile illnesses are often treated empirically due to a lack of reliable, rapid point-of-care diagnostics. This contributes to the indiscriminate use of antimicrobial drugs and poor treatment outcomes. The aim of this comprehensive review was to summarize the diagnostic performance of host biomarkers capable of differentiating bacterial from non-bacterial infections to guide the use of antibiotics. Methods Online databases of published literature were searched from January 2010 through April 2015. English language studies that evaluated the performance of one or more host biomarker in differentiating bacterial from non-bacterial infection in patients were included. Key information extracted included author information, study methods, population, pathogens, clinical information, and biomarker performance data. Study quality was assessed using a combination of validated criteria from the QUADAS and Lijmer checklists. Biomarkers were categorized as hematologic factors, inflammatory molecules, cytokines, cell surface or metabolic markers, other host biomarkers, host transcripts, clinical biometrics, and combinations of markers. Findings Of the 193 citations identified, 59 studies that evaluated over 112 host biomarkers were selected. Most studies involved patient populations from high-income countries, while 19% involved populations from low- and middle-income countries. The most frequently evaluated host biomarkers were C-reactive protein (61%), white blood cell count (44%) and procalcitonin (34%). Study quality scores ranged from 23.1% to 92.3%. There were 9 high performance host biomarkers or combinations, with sensitivity and specificity of ≥85% or either sensitivity or specificity was reported to be 100%. Five host biomarkers were considered weak markers as they lacked statistically significant performance in discriminating between bacterial and non-bacterial infections. Discussion This manuscript provides a summary of host biomarkers to differentiate bacterial from non-bacterial infections in patients with acute febrile illness. Findings provide a basis for prioritizing efforts for further research, assay development and eventual commercialization of rapid point-of-care tests to guide use of antimicrobials. This review also highlights gaps in current knowledge that should be addressed to further improve management of febrile patients. PMID:27486746

Pollution biomarkers in the spiny lizard (Sceloporus spp.) from two suburban populations of Monterrey, Mexico.

PubMed

Aguilera, Carlos; del Pliego, Pamela González; Alfaro, Roberto Mendoza; Lazcano, David; Cruz, Julio

2012-11-01

Environmental pollution may severely impact reptile species in urbanized areas. The magnitude of the impact is analyzed in the present study using lizard tail tips for the quantitative evaluation of enzymatic biomarkers of pollution. Spiny lizards (Sceloporus serrifer and S. torquatus) were collected from two suburban localities in the Monterrey metropolitan area, Mexico: Chipinque Ecological Park, a natural protected area, and El Carmen Industrial Park (IP), a highly polluted site. Different enzymes were used as biomarkers including: acetylcholinesterase (AChE), butyrylcholinesterase (BChE), carboxylesterase (CaE), alkaline phosphatase (ALP), acid phosphatase (ACP), superoxide dismutase (SOD) and glutathione S-transferase (GST). The levels of AChE, BChE and ACP activity were not significantly different between localities. AChE and BChE, commonly used as biomarkers of neurotoxic polluting agents (e.g. organophosphate pesticides) do not appear to be affecting the populations from the study locations. In contrast, the levels of CaE, GST, ALP and SOD were significantly different between the localities. These biomarkers are regularly associated with oxidative stress and processes of detoxification, and generally indicate pollution caused by heavy metals or hydrocarbons, which are common in industrial sites. The data resulting from the analysis of these biomarkers indicate that these polluting agents are affecting the populations of Sceloporus in IP. The present work validates the possibility of conducting additional ecotoxicological studies using biomarkers in combination with a nondestructive sampling technique in species of spiny lizards that are abundant in many North America areas.

Urine Metabonomics Reveals Early Biomarkers in Diabetic Cognitive Dysfunction.

PubMed

Song, Lili; Zhuang, Pengwei; Lin, Mengya; Kang, Mingqin; Liu, Hongyue; Zhang, Yuping; Yang, Zhen; Chen, Yunlong; Zhang, Yanjun

2017-09-01

Recently, increasing attention has been paid to diabetic encephalopathy, which is a frequent diabetic complication and affects nearly 30% of diabetics. Because cognitive dysfunction from diabetic encephalopathy might develop into irreversible dementia, early diagnosis and detection of this disease is of great significance for its prevention and treatment. This study is to investigate the early specific metabolites biomarkers in urine prior to the onset of diabetic cognitive dysfunction (DCD) by using metabolomics technology. An ultra-high performance liquid-chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-Q/TOF-MS) platform was used to analyze the urine samples from diabetic mice that were associated with mild cognitive impairment (MCI) and nonassociated with MCI in the stage of diabetes (prior to the onset of DCD). We then screened and validated the early biomarkers using OPLS-DA model and support vector machine (SVM) method. Following multivariate statistical and integration analysis, we found that seven metabolites could be accepted as early biomarkers of DCD, and the SVM results showed that the prediction accuracy is as high as 91.66%. The identities of four biomarkers were determined by mass spectrometry. The identified biomarkers were largely involved in nicotinate and nicotinamide metabolism, glutathione metabolism, tryptophan metabolism, and sphingolipid metabolism. The present study first revealed reliable biomarkers for early diagnosis of DCD. It provides new insight and strategy for the early diagnosis and treatment of DCD.

Blood biomarker for Parkinson disease: peptoids

PubMed Central

Yazdani, Umar; Zaman, Sayed; Hynan, Linda S; Brown, L Steven; Dewey, Richard B; Karp, David; German, Dwight C

2016-01-01

Parkinson disease (PD) is the second most common neurodegenerative disease. Because dopaminergic neuronal loss begins years before motor symptoms appear, a biomarker for the early identification of the disease is critical for the study of putative neuroprotective therapies. Brain imaging of the nigrostriatal dopamine system has been used as a biomarker for early disease along with cerebrospinal fluid analysis of α-synuclein, but a less costly and relatively non-invasive biomarker would be optimal. We sought to identify an antibody biomarker in the blood of PD patients using a combinatorial peptoid library approach. We examined serum samples from 75 PD patients, 25 de novo PD patients, and 104 normal control subjects in the NINDS Parkinson’s Disease Biomarker Program. We identified a peptoid, PD2, which binds significantly higher levels of IgG3 antibody in PD versus control subjects (P<0.0001) and is 68% accurate in identifying PD. The PD2 peptoid is 84% accurate in identifying de novo PD. Also, IgG3 levels are significantly higher in PD versus control serum (P<0.001). Finally, PD2 levels are positively correlated with the United Parkinson’s Disease Rating Scale score (r=0.457, P<0001), a marker of disease severity. The PD2 peptoid may be useful for the early-stage identification of PD, and serve as an indicator of disease severity. Additional studies are needed to validate this PD biomarker. PMID:27812535

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis

PubMed Central

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography–tandem mass spectrometry (LC–MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets. PMID:28122020

Whole gene expression profile in blood reveals multiple pathways deregulation in R6/2 mouse model

PubMed Central

2013-01-01

Background Huntington Disease (HD) is a progressive neurological disorder, with pathological manifestations in brain areas and in periphery caused by the ubiquitous expression of mutant Huntingtin protein. Transcriptional dysregulation is considered a key molecular mechanism responsible of HD pathogenesis but, although numerous studies investigated mRNA alterations in HD, so far none evaluated a whole gene expression profile in blood of R6/2 mouse model. Findings To discover novel pathogenic mechanisms and potential peripheral biomarkers useful to monitor disease progression or drug efficacy, a microarray study was performed in blood of R6/2 at manifest stage and wild type littermate mice. This approach allowed to propose new peripheral molecular processes involved in HD and to suggest different panels of candidate biomarkers. Among the discovered deregulated processes, we focused on specific ones: complement and coagulation cascades, PPAR signaling, cardiac muscle contraction, and dilated cardiomyopathy pathways. Selected genes derived from these pathways were additionally investigated in other accessible tissues to validate these matrices as source of biomarkers, and in brain, to link central and peripheral disease manifestations. Conclusions Our findings validated the skeletal muscle as suitable source to investigate peripheral transcriptional alterations in HD and supported the hypothesis that immunological alteration may contribute to neurological degeneration. Moreover, the identification of altered signaling in mouse blood enforce R6/2 transgenic mouse as a powerful HD model while suggesting novel disease biomarkers for pre-clinical investigation. PMID:24252798

iTRAQ-Based Proteomics Reveals Novel Biomarkers for Idiopathic Pulmonary Fibrosis.

PubMed

Niu, Rui; Liu, Ying; Zhang, Ying; Zhang, Yuan; Wang, Hui; Wang, Yongbin; Wang, Wei; Li, Xiaohui

2017-01-01

Idiopathic pulmonary fibrosis (IPF) is a gradual lung disease with a survival of less than 5 years post-diagnosis for most patients. Poor molecular description of IPF has led to unsatisfactory interpretation of the pathogenesis of this disease, resulting in the lack of successful treatments. The objective of this study was to discover novel noninvasive biomarkers for the diagnosis of IPF. We employed a coupled isobaric tag for relative and absolute quantitation (iTRAQ)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach to examine protein expression in patients with IPF. A total of 97 differentially expressed proteins (38 upregulated proteins and 59 downregulated proteins) were identified in the serum of IPF patients. Using String software, a regulatory network containing 87 nodes and 244 edges was built, and the functional enrichment showed that differentially expressed proteins were predominantly involved in protein activation cascade, regulation of response to wounding and extracellular components. A set of three most significantly upregulated proteins (HBB, CRP and SERPINA1) and four most significantly downregulated proteins (APOA2, AHSG, KNG1 and AMBP) were selected for validation in an independent cohort of IPF and other lung diseases using ELISA test. The results confirmed the iTRAQ profiling results and AHSG, AMBP, CRP and KNG1 were found as specific IPF biomarkers. ROC analysis indicated the diagnosis potential of the validated biomarkers. The findings of this study will contribute in understanding the pathogenesis of IPF and facilitate the development of therapeutic targets.

PD-L1 promoter methylation is a prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients following radical prostatectomy.

PubMed

Gevensleben, Heidrun; Holmes, Emily Eva; Goltz, Diane; Dietrich, Jörn; Sailer, Verena; Ellinger, Jörg; Dietrich, Dimo; Kristiansen, Glen

2016-11-29

The rapid development of programmed death 1 (PD-1)/programmed death ligand 1 (PD-L1) inhibitors has generated an urgent need for biomarkers assisting the selection of patients eligible for therapy. The use of PD-L1 immunohistochemistry, which has been suggested as a predictive biomarker, however, is confounded by multiple unresolved issues. The aim of this study therefore was to quantify PD-L1 DNA methylation (mPD-L1) in prostate tissue samples and to evaluate its potential as a biomarker in prostate cancer (PCa). In the training cohort, normal tissue showed significantly lower levels of mPD-L1 compared to tumor tissue. High mPD-L1 in PCa was associated with biochemical recurrence (BCR) in univariate Cox proportional hazards (hazard ratio (HR)=2.60 [95%CI: 1.50-4.51], p=0.001) and Kaplan-Meier analyses (p<0.001). These results were corroborated in an independent validation cohort in univariate Cox (HR=1.24 [95%CI: 1.08-1.43], p=0.002) and Kaplan-Meier analyses (p=0.029). Although mPD-L1 and PD-L1 protein expression did not correlate in the validation cohort, both parameters added significant prognostic information in bivariate Cox analysis (HR=1.22 [95%CI: 1.05-1.42], p=0.008 for mPD-L1 and HR=2.58 [95%CI: 1.43-4.63], p=0.002 for PD-L1 protein expression). mPD-L1 was analyzed in a training cohort from The Cancer Genome Atlas (n=498) and was subsequently measured in an independent validation cohort (n=299) by quantitative methylation-specific real-time PCR. All patients had undergone radical prostatectomy. mPD-L1 is a promising biomarker for the risk stratification of PCa patients and might offer additional relevant prognostic information to the implemented clinical parameters, particularly in the setting of immune checkpoint inhibition.

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

Meta-Review of CSF Core Biomarkers in Alzheimer’s Disease: The State-of-the-Art after the New Revised Diagnostic Criteria

PubMed Central

Ferreira, Daniel; Perestelo-Pérez, Lilisbeth; Westman, Eric; Wahlund, Lars-Olof; Sarría, Antonio; Serrano-Aguilar, Pedro

2014-01-01

Background: Current research criteria for Alzheimer’s disease (AD) include cerebrospinal fluid (CSF) biomarkers into the diagnostic algorithm. However, spreading their use to the clinical routine is still questionable. Objective: To provide an updated, systematic and critical review on the diagnostic utility of the CSF core biomarkers for AD. Data sources: MEDLINE, PreMedline, EMBASE, PsycInfo, CINAHL, Cochrane Library, and CRD. Eligibility criteria: (1a) Systematic reviews with meta-analysis; (1b) Primary studies published after the new revised diagnostic criteria; (2) Evaluation of the diagnostic performance of at least one CSF core biomarker. Results: The diagnostic performance of CSF biomarkers is generally satisfactory. They are optimal for discriminating AD patients from healthy controls. Their combination may also be suitable for mild cognitive impairment (MCI) prognosis. However, CSF biomarkers fail to distinguish AD from other forms of dementia. Limitations: (1) Use of clinical diagnosis as standard instead of pathological postmortem confirmation; (2) variability of methodological aspects; (3) insufficiently long follow-up periods in MCI studies; and (4) lower diagnostic accuracy in primary care compared with memory clinics. Conclusion: Additional work needs to be done to validate the application of CSF core biomarkers as they are proposed in the new revised diagnostic criteria. The use of CSF core biomarkers in clinical routine is more likely if these limitations are overcome. Early diagnosis is going to be of utmost importance when effective pharmacological treatment will be available and the CSF core biomarkers can also be implemented in clinical trials for drug development. PMID:24715863

Urinary Tobacco Smoke Constituent Biomarkers for Assessing Risk of Lung Cancer

PubMed Central

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

2014-01-01

Tobacco constituent biomarkers are metabolites of specific compounds present in tobacco or tobacco smoke. Highly reliable analytical methods, based mainly on mass spectrometry, have been developed for quantitation of these biomarkers in both urine and blood specimens. There is substantial inter-individual variation in smoking-related lung cancer risk that is determined in part by individual variability in the uptake and metabolism of tobacco smoke carcinogens. Thus, by incorporating these biomarkers in epidemiological studies we can potentially obtain a more valid and precise measure of in vivo carcinogen dose than by using self-reported smoking history, ultimately improving the estimation of smoking-related lung cancer risk. Indeed, we have demonstrated this by using a prospective study design comparing biomarker levels in urine samples collected from smokers many years prior to their development of cancer, versus those in their smoking counterparts without a cancer diagnosis. The following urinary metabolites were associated with lung cancer risk, independent of smoking intensity and duration: cotinine plus its glucuronide, a biomarker of nicotine uptake; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol and its glucuronides (total NNAL), a biomarker of the tobacco carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK); and r-1-,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene (PheT), a biomarker of polycyclic aromatic hydrocarbons (PAH). These results provide several possible new directions for using tobacco smoke constituent biomarkers in lung cancer prevention, including improved lung cancer risk assessment, intermediate outcome determination in prevention trials and regulation of tobacco products. PMID:24408916

Automated Comprehensive Evaluation of mTBI Visual Dysfunction

DTIC Science & Technology

2016-10-01

of this study is to validate the Neuro-Ophthalmic Device (NODe) test battery that provides the highest sensitivity and specificity for the detection...that the tests within the NODe test battery can serve as objective biomarkers for acute mTBI. Two hundred acute mTBI (≤72 hrs post injury) and 200 age...post-mTBI-related vision problems. The purpose of this study is to validate the Neuro-Ophthalmic Device (NODe) test battery that provides the

Prediagnostic Serum Biomarkers as Early Detection Tools for Pancreatic Cancer in a Large Prospective Cohort Study

PubMed Central

Nolen, Brian M.; Brand, Randall E.; Prosser, Denise; Velikokhatnaya, Liudmila; Allen, Peter J.; Zeh, Herbert J.; Grizzle, William E.; Lomakin, Aleksey; Lokshin, Anna E.

2014-01-01

Background The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Methods Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Results The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively associated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected <1 and >1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Conclusions Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combinations offered advantage over CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis. However, the efficacy of biomarker-based tools remains limited at present. Several biomarkers demonstrated significant velocity related to time to diagnosis, an observation which may offer considerable potential for enhancements in early detection. PMID:24747429

The Potential Role of Sensory Testing, Skin Biopsy, and Functional Brain Imaging as Biomarkers in Chronic Pain Clinical Trials: IMMPACT Considerations.

PubMed

Smith, Shannon M; Dworkin, Robert H; Turk, Dennis C; Baron, Ralf; Polydefkis, Michael; Tracey, Irene; Borsook, David; Edwards, Robert R; Harris, Richard E; Wager, Tor D; Arendt-Nielsen, Lars; Burke, Laurie B; Carr, Daniel B; Chappell, Amy; Farrar, John T; Freeman, Roy; Gilron, Ian; Goli, Veeraindar; Haeussler, Juergen; Jensen, Troels; Katz, Nathaniel P; Kent, Jeffrey; Kopecky, Ernest A; Lee, David A; Maixner, William; Markman, John D; McArthur, Justin C; McDermott, Michael P; Parvathenani, Lav; Raja, Srinivasa N; Rappaport, Bob A; Rice, Andrew S C; Rowbotham, Michael C; Tobias, Jeffrey K; Wasan, Ajay D; Witter, James

2017-07-01

Valid and reliable biomarkers can play an important role in clinical trials as indicators of biological or pathogenic processes or as a signal of treatment response. Currently, there are no biomarkers for pain qualified by the U.S. Food and Drug Administration or the European Medicines Agency for use in clinical trials. This article summarizes an Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials meeting in which 3 potential biomarkers were discussed for use in the development of analgesic treatments: 1) sensory testing, 2) skin punch biopsy, and 3) brain imaging. The empirical evidence supporting the use of these tests is described within the context of the 4 categories of biomarkers: 1) diagnostic, 2) prognostic, 3) predictive, and 4) pharmacodynamic. Although sensory testing, skin punch biopsy, and brain imaging are promising tools for pain in clinical trials, additional evidence is needed to further support and standardize these tests for use as biomarkers in pain clinical trials. The applicability of sensory testing, skin biopsy, and brain imaging as diagnostic, prognostic, predictive, and pharmacodynamic biomarkers for use in analgesic treatment trials is considered. Evidence in support of their use and outlining problems is presented, as well as a call for further standardization and demonstrations of validity and reliability. Copyright © 2017 American Pain Society. All rights reserved.

A Proteomics View of the Molecular Mechanisms and Biomarkers of Glaucomatous Neurodegeneration

PubMed Central

Tezel, Gülgün

2013-01-01

Despite improving understanding of glaucoma, key molecular players of neurodegeneration that can be targeted for treatment of glaucoma, or molecular biomarkers that can be useful for clinical testing, remain unclear. Proteomics technology offers a powerful toolbox to accomplish these important goals of the glaucoma research and is increasingly being applied to identify molecular mechanisms and biomarkers of glaucoma. Recent studies of glaucoma using proteomics analysis techniques have resulted in the lists of differentially expressed proteins in human glaucoma and animal models. The global analysis of protein expression in glaucoma has been followed by cell-specific proteome analysis of retinal ganglion cells and astrocytes. The proteomics data have also guided targeted studies to identify post-translational modifications and protein-protein interactions during glaucomatous neurodegeneration. In addition, recent applications of proteomics have provided a number of potential biomarker candidates. Proteomics technology holds great promise to move glaucoma research forward toward new treatment strategies and biomarker discovery. By reviewing the major proteomics approaches and their applications in the field of glaucoma, this article highlights the power of proteomics in translational and clinical research related to glaucoma and also provides a framework for future research to functionally test the importance of specific molecular pathways and validate candidate biomarkers. PMID:23396249

Pregnant & Lactating Populations Research - NCS Dietary Assessment Literature Review

Cancer.gov

Identifying and studying additional biomarkers of energy and nutrient intake will advance validation efforts and lead to a better understanding of the biases and sources of measurement error in dietary assessment instruments in pregnant or lactating populations.

Development of a Multi-Biomarker Disease Activity Test for Rheumatoid Arthritis

PubMed Central

Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A.; Turner, Mary; Sutton, Chris; Smith, Dustin R.; Haney, Douglas J.; Chernoff, David; Hesterberg, Lyndal K.; Carulli, John P.; Taylor, Peter C.; Shadick, Nancy A.; Weinblatt, Michael E.; Curtis, Jeffrey R.

2013-01-01

Background Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. Objectives To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Methods Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. Results 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. Conclusion We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels. PMID:23585841

Development of a multi-biomarker disease activity test for rheumatoid arthritis.

PubMed

Centola, Michael; Cavet, Guy; Shen, Yijing; Ramanujan, Saroja; Knowlton, Nicholas; Swan, Kathryn A; Turner, Mary; Sutton, Chris; Smith, Dustin R; Haney, Douglas J; Chernoff, David; Hesterberg, Lyndal K; Carulli, John P; Taylor, Peter C; Shadick, Nancy A; Weinblatt, Michael E; Curtis, Jeffrey R

2013-01-01

Disease activity measurement is a key component of rheumatoid arthritis (RA) management. Biomarkers that capture the complex and heterogeneous biology of RA have the potential to complement clinical disease activity assessment. To develop a multi-biomarker disease activity (MBDA) test for rheumatoid arthritis. Candidate serum protein biomarkers were selected from extensive literature screens, bioinformatics databases, mRNA expression and protein microarray data. Quantitative assays were identified and optimized for measuring candidate biomarkers in RA patient sera. Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity (e.g. the Disease Activity Score 28-C-Reactive Protein [DAS28-CRP], a validated metric commonly used in clinical trials) and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity, assessed by correlation to DAS and area under the receiver operating characteristic curve for classification of low vs. moderate/high disease activity. The effect of comorbidities on the MBDA score was evaluated using linear models with adjustment for multiple hypothesis testing. 130 candidate biomarkers were tested in feasibility studies and 25 were selected for algorithm training. Multi-biomarker statistical models outperformed individual biomarkers at estimating disease activity. Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography. The final MBDA algorithm uses 12 biomarkers to generate an MBDA score between 1 and 100. No significant effects on the MBDA score were found for common comorbidities. We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels.

Derivation and Validation of a Serum Biomarker Panel to Identify Infants With Acute Intracranial Hemorrhage.

PubMed

Berger, Rachel Pardes; Pak, Brian J; Kolesnikova, Mariya D; Fromkin, Janet; Saladino, Richard; Herman, Bruce E; Pierce, Mary Clyde; Englert, David; Smith, Paul T; Kochanek, Patrick M

2017-06-05

Abusive head trauma is the leading cause of death from physical abuse. Missing the diagnosis of abusive head trauma, particularly in its mild form, is common and contributes to increased morbidity and mortality. Serum biomarkers may have potential as quantitative point-of-care screening tools to alert physicians to the possibility of intracranial hemorrhage. To identify and validate a set of biomarkers that could be the basis of a multivariable model to identify intracranial hemorrhage in well-appearing infants using the Ziplex System. Binary logistic regression was used to develop a multivariable model incorporating 3 serum biomarkers (matrix metallopeptidase-9, neuron-specific enolase, and vascular cellular adhesion molecule-1) and 1 clinical variable (total hemoglobin). The model was then prospectively validated. Multiplex biomarker measurements were performed using Flow-Thru microarray technology on the Ziplex System, which has potential as a point-of-care system. The model was tested at 3 pediatric emergency departments in level I pediatric trauma centers (Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Primary Children's Hospital, Salt Lake City, Utah; and Lurie Children's Hospital, Chicago, Illinois) among well-appearing infants who presented for care owing to symptoms that placed them at increased risk of abusive head trauma. The study took place from November 2006 to April 2014 at Children's Hospital of Pittsburgh, June 2010 to August 2013 at Primary Children's Hospital, and January 2011 to August 2013 at Lurie Children's Hospital. A mathematical model that can predict acute intracranial hemorrhage in infants at increased risk of abusive head trauma. The multivariable model, Biomarkers for Infant Brain Injury Score, was applied prospectively to 599 patients. The mean (SD) age was 4.7 (3.1) months. Fifty-two percent were boys, 78% were white, and 8% were Hispanic. At a cutoff of 0.182, the model was 89.3% sensitive (95% CI, 87.7-90.4) and 48.0% specific (95% CI, 47.3-48.9) for acute intracranial hemorrhage. Positive and negative predictive values were 21.3% and 95.6%, respectively. The model was neither sensitive nor specific for atraumatic brain abnormalities, isolated skull fractures, or chronic intracranial hemorrhage. The Biomarkers for Infant Brain Injury Score, a multivariable model using 3 serum biomarker concentrations and serum hemoglobin, can identify infants with acute intracranial hemorrhage. Accurate and timely identification of intracranial hemorrhage in infants without a history of trauma in whom trauma may not be part of the differential diagnosis has the potential to decrease morbidity and mortality from abusive head trauma.

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. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Expression of FOXP3, CD68, and CD20 at Diagnosis in the Microenvironment of Classical Hodgkin Lymphoma Is Predictive of Outcome

PubMed Central

Greaves, Paul; Clear, Andrew; Coutinho, Rita; Wilson, Andrew; Matthews, Janet; Owen, Andrew; Shanyinde, Milensu; Lister, T. Andrew; Calaminici, Maria; Gribben, John G.

2013-01-01

Purpose The immune microenvironment is key to the pathophysiology of classical Hodgkin lymphoma (CHL). Twenty percent of patients experience failure of their initial treatment, and others receive excessively toxic treatment. Prognostic scores and biomarkers have yet to influence outcomes significantly. Previous biomarker studies have been limited by the extent of tissue analyzed, statistical inconsistencies, and failure to validate findings. We aimed to overcome these limitations by validating recently identified microenvironment biomarkers (CD68, FOXP3, and CD20) in a new patient cohort with a greater extent of tissue and by using rigorous statistical methodology. Patients and Methods Diagnostic tissue from 122 patients with CHL was microarrayed and stained, and positive cells were counted across 10 to 20 high-powered fields per patient by using an automated system. Two statistical analyses were performed: a categorical analysis with test/validation set-defined cut points and Kaplan-Meier estimated outcome measures of 5-year overall survival (OS), disease-specific survival (DSS), and freedom from first-line treatment failure (FFTF) and an independent multivariate analysis of absolute uncategorized counts. Results Increased CD20 expression confers superior OS. Increased FOXP3 expression confers superior OS, and increased CD68 confers inferior FFTF and OS. FOXP3 varies independently of CD68 expression and retains significance when analyzed as a continuous variable in multivariate analysis. A simple score combining FOXP3 and CD68 discriminates three groups: FFTF 93%, 62%, and 47% (P < .001), DSS 93%, 82%, and 63% (P = .03), and OS 93%, 82%, and 59% (P = .002). Conclusion We have independently validated CD68, FOXP3, and CD20 as prognostic biomarkers in CHL, and we demonstrate, to the best of our knowledge for the first time, that combining FOXP3 and CD68 may further improve prognostic stratification. PMID:23045593

Hair Measurements of Cortisol, DHEA, and DHEA to Cortisol Ratio as Biomarkers of Chronic Stress among People Living with HIV in China: Known-Group Validation

PubMed Central

Li, Xiaoming; Zilioli, Samuele; Chen, Zheng; Deng, Huihua; Pan, Juxian

2017-01-01

Background Existing literature suggests that endocrine measures, including the steroid hormones of cortisol and Dehydroepiandrosterone (DHEA), as well as the DHEA to cortisol ratio in the human hair can be used as promising biomarkers of chronic stress among humans. However, data are limited regarding the validity of these measures as biomarkers of chronic stress among people living with HIV (PLWH), whose endocrine system or hypothalamic pituitary adrenal (HPA) axis may be affected by HIV infection and/or antiretroviral therapy (ART) medications. Method Using hair sample data and self-reported survey from 60 PLWH in China, we examined the validity of three endocrine measures among Chinese PLWH using a known-groups validation strategy. High-stress group (n = 30) and low-stress group (n = 30) of PLWH were recruited through individual assessment interviews by a local licensed psychologist. The endocrine measures in hair were extracted and assessed by LC-APCI-MS/MS method. Both bivariate and multivariate analyses were conducted to examine the associations between the endocrine measures and the stress level, and to investigate if the associations differ by ART status. Results The levels of endocrine measures among Chinese PLWH were consistent with existing studies among PLWH. Generally, this pilot study confirmed the association between endocrine measures and chronic stress. The high stress group showed higher level hair cortisol and lower DHEA to cortisol ratio. The higher stress group also reported higher scores of stressful life events, perceived stress, anxiety and depression. Hair cortisol level was positively related to anxiety; DHEA was negatively associated with stressful life events; and the DHEA to cortisol ratio was positively related to stressful life events and perceived stress. ART did not affect the associations between the endocrine measures and stress level. Conclusions Our findings suggest that hair cortisol and DHEA to cortisol ratio can be used as promising biomarkers of chronic stress among PLWH. Clarifying the role of steroid hormones in the psychoimmunology of PLWH may yield important implications for clinical practice and psychological intervention. PMID:28095431

Multiplexed LC-MS/MS analysis of horse plasma proteins to study doping in sport.

PubMed

Barton, Chris; Beck, Paul; Kay, Richard; Teale, Phil; Roberts, Jane

2009-06-01

The development of protein biomarkers for the indirect detection of doping in horse is a potential solution to doping threats such as gene and protein doping. A method for biomarker candidate discovery in horse plasma is presented using targeted analysis of proteotypic peptides from horse proteins. These peptides were first identified in a novel list of the abundant proteins in horse plasma. To monitor these peptides, an LC-MS/MS method using multiple reaction monitoring was developed to study the quantity of 49 proteins in horse plasma in a single run. The method was optimised and validated, and then applied to a population of race-horses to study protein variance within a population. The method was finally applied to longitudinal time courses of horse plasma collected after administration of an anabolic steroid to demonstrate utility for hypothesis-driven discovery of doping biomarker candidates.

Circulating microRNA Biomarkers as Liquid Biopsy for Cancer Patients: Pros and Cons of Current Assays

PubMed Central

Ono, Shigeshi; Lam, Stella; Nagahara, Makoto; Hoon, Dave S. B.

2015-01-01

An increasing number of studies have focused on circulating microRNAs (cmiRNA) in cancer patients’ blood for their potential as minimally-invasive biomarkers. Studies have reported the utility of assessing specific miRNAs in blood as diagnostic/prognostic biomarkers; however, the methodologies are not validated or standardized across laboratories. Unfortunately, there is often minimum limited overlap in techniques between results reported even in similar type studies on the same cancer. This hampers interpretation and reliability of cmiRNA as potential cancer biomarkers. Blood collection and processing, cmiRNA extractions, quality and quantity control of assays, defined patient population assessment, reproducibility, and reference standards all affect the cmiRNA assay results. To date, there is no reported definitive method to assess cmiRNAs. Therefore, appropriate and reliable methodologies are highly necessary in order for cmiRNAs to be used in regulated clinical diagnostic laboratories. In this review, we summarize the developments made over the past decade towards cmiRNA detection and discuss the pros and cons of the assays. PMID:26512704

Limitations of an ocular surface inflammatory biomarker in impression cytology specimens.

PubMed

Yafawi, Rolla; Ko, Mira; Sace, Frederick P; John-Baptiste, Annette

2013-03-01

A number of ocular conditions, such as dry eye, are associated with inflammation on the surface of the eye leading to irritation and ocular pain. Many drugs such as chemotherapeutics, beta blockers, angiotensin-converting enzymes and so forth also cause dry eye but currently there are no validated ocular surface biomarkers available. We evaluated sample stability, assay sensitivity, reproducibility and overall performance of impression cytology (IC) utilizing the cellular surface biomarker human leukocyte antigen DR-1 (HLA-DR) as an ocular surface inflammatory biomarker by flow cytometry in a fit-for-purpose validation study. Additionally, subjects classified as normal or having various degrees of dry eye were evaluated to determine if HLA-DR could demonstrate a clear separation between normal and dry eye samples. The assay demonstrated high dynamic range detecting a broad range of fluorescent intensities in healthy donors. Additionally, inter, intra and stability assay results demonstrated strong concordance and low variability. Overall CV% for both assays were less than 25% for all measured parameters. However, high variability was observed for donor samples assayed beyond day 10 post IC sample collection (4.2-110.8 CV%). HLA-DR expression demonstrated a progressive increase in patients with mild to severe levels of dry eye disease providing sufficient evidence it is sensitive enough to monitor inflammatory effects of dry eye when coupled with additional biomarkers and/or methodologies such as cytokine analysis or ICAM-1. This biomarker can be used to monitor ocular surface disorders in patients and to evaluate potential treatment options during drug development. Although our results demonstrate this methodology is reproducible for routine evaluation, limitations around sample integrity exist. The ocular cell surface inflammatory biomarker, HLA-DR coupled with impression cytology is a simple non-invasive robust, specific and reproducible assay that can be utilized to measure inflammatory infiltrates on the surface of the eye in IC samples less than 10-days old.

Evaluation of the 24-Hour Recall as a Reference Instrument for Calibrating Other Self-Report Instruments in Nutritional Cohort Studies: Evidence From the Validation Studies Pooling Project.

PubMed

Freedman, Laurence S; Commins, John M; Willett, Walter; Tinker, Lesley F; Spiegelman, Donna; Rhodes, Donna; Potischman, Nancy; Neuhouser, Marian L; Moshfegh, Alanna J; Kipnis, Victor; Baer, David J; Arab, Lenore; Prentice, Ross L; Subar, Amy F

2017-07-01

Calibrating dietary self-report instruments is recommended as a way to adjust for measurement error when estimating diet-disease associations. Because biomarkers available for calibration are limited, most investigators use self-reports (e.g., 24-hour recalls (24HRs)) as the reference instrument. We evaluated the performance of 24HRs as reference instruments for calibrating food frequency questionnaires (FFQs), using data from the Validation Studies Pooling Project, comprising 5 large validation studies using recovery biomarkers. Using 24HRs as reference instruments, we estimated attenuation factors, correlations with truth, and calibration equations for FFQ-reported intakes of energy and for protein, potassium, and sodium and their densities, and we compared them with values derived using biomarkers. Based on 24HRs, FFQ attenuation factors were substantially overestimated for energy and sodium intakes, less for protein and potassium, and minimally for nutrient densities. FFQ correlations with truth, based on 24HRs, were substantially overestimated for all dietary components. Calibration equations did not capture dependencies on body mass index. We also compared predicted bias in estimated relative risks adjusted using 24HRs as reference instruments with bias when making no adjustment. In disease models with energy and 1 or more nutrient intakes, predicted bias in estimated nutrient relative risks was reduced on average, but bias in the energy risk coefficient was unchanged. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The dynamics of Alzheimer's disease biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort.

PubMed

Caroli, A; Frisoni, G B

2010-08-01

The aim of this study was to investigate the dynamics of four of the most validated biomarkers for Alzheimer's disease (AD), cerebro-spinal fluid (CSF) Abeta 1-42, tau, hippocampal volume, and FDG-PET, in patients at different stage of AD. Two hundred twenty-nine cognitively healthy subjects, 154 mild cognitive impairment (MCI) patients converted to AD, and 193 (95 early and 98 late) AD patients were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. For each biomarker, individual values were Z-transformed and plotted against ADAS-cog scores, and sigmoid and linear fits were compared. For most biomarkers the sigmoid model fitted data significantly better than the linear model. Abeta 1-42 time course followed a steep curve, stabilizing early in the disease course. CSF tau and hippocampal volume changed later showing similar monotonous trends, reflecting disease progression. Hippocampal loss trend was steeper and occurred earlier in time in APOE epsilon4 carriers than in non-carriers. FDG-PET started changing early in time and likely followed a linear decline. In conclusion, this study provides the first evidence in favor of the dynamic biomarker model which has recently been proposed. 2010 Elsevier Inc. All rights reserved.

Circulating Long Noncoding RNAs as Potential Biomarkers of Sepsis: A Preliminary Study.

PubMed

Dai, Yu; Liang, Zhixin; Li, Yulin; Li, Chunsun; Chen, Liangan

2017-11-01

Long noncoding RNAs (lncRNAs) are becoming promising biomarker candidates in various diseases as assessed via sequencing technologies. Sepsis is a life-threatening disease without ideal biomarkers. The aim of this study was to investigate the expression profile of lncRNAs in the peripheral blood of sepsis patients and to find potential biomarkers of sepsis. A lncRNA expression profile was performed using peripheral blood from three sepsis patients and three healthy volunteers using microarray screening. The differentially expressed lncRNAs were validated by real-time quantitative polymerase chain reaction (qRT-PCR) in a further set of 22 sepsis patients and 22 healthy volunteers. Among 1316 differentially expressed lncRNAs, 771 were downregulated and 545 were upregulated. Results of the qRT-PCR were consistent with the microarray data. lncRNA ENST00000452391.1, uc001vji.1, and uc021zxw.1 were significantly differentially expressed between sepsis patients and healthy volunteers. Moreover, lncRNA ENST00000504301.1 and ENST00000452391.1 were significantly differentially expressed between sepsis survivors and nonsurvivors. The lncRNA expression profile in the peripheral blood of sepsis patients significantly differed from that of healthy volunteers. Circulating lncRNAs may be good candidates for sepsis biomarkers.

Combining large number of weak biomarkers based on AUC.

PubMed

Yan, Li; Tian, Lili; Liu, Song

2015-12-20

Combining multiple biomarkers to improve diagnosis and/or prognosis accuracy is a common practice in clinical medicine. Both parametric and non-parametric methods have been developed for finding the optimal linear combination of biomarkers to maximize the area under the receiver operating characteristic curve (AUC), primarily focusing on the setting with a small number of well-defined biomarkers. This problem becomes more challenging when the number of observations is not order of magnitude greater than the number of variables, especially when the involved biomarkers are relatively weak. Such settings are not uncommon in certain applied fields. The first aim of this paper is to empirically evaluate the performance of existing linear combination methods under such settings. The second aim is to propose a new combination method, namely, the pairwise approach, to maximize AUC. Our simulation studies demonstrated that the performance of several existing methods can become unsatisfactory as the number of markers becomes large, while the newly proposed pairwise method performs reasonably well. Furthermore, we apply all the combination methods to real datasets used for the development and validation of MammaPrint. The implication of our study for the design of optimal linear combination methods is discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Combining large number of weak biomarkers based on AUC

PubMed Central

Yan, Li; Tian, Lili; Liu, Song

2018-01-01

Combining multiple biomarkers to improve diagnosis and/or prognosis accuracy is a common practice in clinical medicine. Both parametric and non-parametric methods have been developed for finding the optimal linear combination of biomarkers to maximize the area under the receiver operating characteristic curve (AUC), primarily focusing on the setting with a small number of well-defined biomarkers. This problem becomes more challenging when the number of observations is not order of magnitude greater than the number of variables, especially when the involved biomarkers are relatively weak. Such settings are not uncommon in certain applied fields. The first aim of this paper is to empirically evaluate the performance of existing linear combination methods under such settings. The second aim is to propose a new combination method, namely, the pairwise approach, to maximize AUC. Our simulation studies demonstrated that the performance of several existing methods can become unsatisfactory as the number of markers becomes large, while the newly proposed pairwise method performs reasonably well. Furthermore, we apply all the combination methods to real datasets used for the development and validation of MammaPrint. The implication of our study for the design of optimal linear combination methods is discussed. PMID:26227901

Possible biomarkers modulating haloperidol efficacy and/or tolerability.

PubMed

Porcelli, Stefano; Crisafulli, Concetta; Calabrò, Marco; Serretti, Alessandro; Rujescu, Dan

2016-04-01

Haloperidol (HP) is widely used in the treatment of several forms of psychosis. Despite of its efficacy, HP use is a cause of concern for the elevated risk of adverse drug reactions. adverse drug reactions risk and HP efficacy greatly vary across subjects, indicating the involvement of several factors in HP mechanism of action. The use of biomarkers that could monitor or even predict HP treatment impact would be of extreme importance. We reviewed the elements that could potentially be used as peripheral biomarkers of HP effectiveness. Although a validated biomarker still does not exist, we underlined the several potential findings (e.g., about cytokines, HP metabolites and genotypic biomarkers) which could pave the way for future research on HP biomarkers.

A comparison of the prevalence of prenatal alcohol exposure obtained via maternal self-reports versus meconium testing: a systematic literature review and meta-analysis

PubMed Central

2014-01-01

Background Maternal self-reports, used for the detection of prenatal alcohol exposure (PAE), may lack validity, necessitating the use of an objective biomarker. The detection of fatty acid ethyl esters (products of non-oxidative ethanol metabolism) in meconium has been established as a novel biomarker of PAE. The purpose of the current study was to compare the prevalence of PAE as reported via maternal self-reports with the results of meconium testing, and to quantify the disparity between these two methods. Methods A systematic literature search for studies reporting on the prevalence of PAE, using maternal self-reports in combination with meconium testing, was conducted using multiple electronic bibliographic databases. Pooled prevalence estimates and 95% confidence intervals (CI) were calculated based on eight studies, using the Mantel-Haenszel method, assuming a random effects model. A random effects meta-regression was performed to test for a difference. Results The pooled prevalence of PAE as measured by meconium testing was 4.26 (95% CI: 1.34-13.57) times the pooled prevalence of PAE as measured by maternal self-reports. Large variations across the studies in regard to the difference between estimates obtained from maternal self-reports and those obtained from meconium testing were observed. Conclusions If maternal self-reports are the sole information source upon which health care professionals rely, a number of infants who were prenatally exposed to alcohol are not being recognized as such. However, further research is needed in order to validate existing biomarkers, as well as discover new biomarkers, for the detection of PAE. PMID:24708684

Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.

PubMed

Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta; Watzl, Bernhard; Bub, Achim; Miller, Edgar R; Castenmiller, Jacqueline J M; Pasman, Wilrike J; van Het Hof, Karin; Chopra, Mridula; Karlsen, Anette; Dragsted, Lars O; Winkels, Renate; Itsiopoulos, Catherine; Brazionis, Laima; O'Dea, Kerin; van Loo-Bouwman, Carolien A; Naber, Ton H J; van der Voet, Hilko; Boshuizen, Hendriek C

2015-05-14

Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258.0 g, the correlation between observed and predicted intake was 0.78 and the mean difference between observed and predicted intake was - 1.7 g (limits of agreement: - 466.3, 462.8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201.1 g, the correlation was 0.65 and the mean bias was 2.4 g (limits of agreement: -368.2, 373.0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake.

Gestational Obstructive Sleep Apnea: Biomarker Screening Models and Lack of Postpartum Resolution.

PubMed

Street, Linda M; Aschenbrenner, Carol A; Houle, Timothy T; Pinyan, Clark W; Eisenach, James C

2018-04-15

To measure prevalence and severity of third trimester obstructive sleep apnea and evaluate postpartum resolution. To assess a novel biomarker for screening for obstructive sleep apnea in pregnancy. This prospective observational study was performed at Wake Forest School of Medicine obstetrics clinics between April 2014 and December 2015. Fractional exhaled nitric oxide measurements and sleep studies were obtained and compared at 32 0/7 to 35 6/7 weeks gestation and postpartum. Exhaled nitric oxide and risk factors for the development of gestational sleep apnea were evaluated for predictive ability independently and in screening models. Of 76 women enrolled, 73 performed valid sleep studies in pregnancy and 65 had an additional valid study 6 to 15 weeks postpartum. Twenty-four women (37%) had gestational sleep apnea compared with 23 (35%) with postpartum sleep apnea ( P > .99). Eight of 11 women (73%) retested 6 to 8 months postpartum had persistent sleep apnea. Exhaled nitric oxide had moderate discrimination screening for sleep apnea in pregnancy (area under the receiver operating characteristic curve = 0.64). A model utilizing exhaled nitric oxide, pregnancy-specific screening, and Mallampati score improved ability to identify women at risk for gestational sleep apnea (sensitivity = 46%, specificity = 91% and likelihood ratio = 5.11, area under receiver operating characteristic curve = 0.75). Obstructive sleep apnea is common in the early postpartum period and often persisted at least 6 months. Exhaled nitric oxide as a sole biomarker to screen for sleep apnea in pregnancy has only modest discrimination. Combined with additional parameters sensitivity and specificity improved. Registry: ClinicalTrials.gov, Identifier: NCT02100943, Title: Exhaled Nitric Oxide as a Biomarker of Gestational Obstructive Sleep Apnea and Persistence Postpartum, URL: https://clinicaltrials.gov/ct2/show/NCT02100943. © 2018 American Academy of Sleep Medicine.

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation.

PubMed

Wu, Long; Peng, Chun-Wei; Hou, Jin-Xuan; Zhang, Yan-Hua; Chen, Chuang; Chen, Liang-Dong; Li, Yan

2010-02-24

To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.

MicroRNAs for Detection of Pancreatic Neoplasia

PubMed Central

Vila-Navarro, Elena; Vila-Casadesús, Maria; Moreira, Leticia; Duran-Sanchon, Saray; Sinha, Rupal; Ginés, Àngels; Fernández-Esparrach, Glòria; Miquel, Rosa; Cuatrecasas, Miriam; Castells, Antoni; Lozano, Juan José; Gironella, Meritxell

2017-01-01

Objective: The aim of our study was to analyze the miRNome of pancreatic ductal adenocarcinoma (PDAC) and its preneoplastic lesion intraductal papillary mucinous neoplasm (IPMN), to find new microRNA (miRNA)-based biomarkers for early detection of pancreatic neoplasia. Objective: Effective early detection methods for PDAC are needed. miRNAs are good biomarker candidates. Methods: Pancreatic tissues (n = 165) were obtained from patients with PDAC, IPMN, or from control individuals (C), from Hospital Clínic of Barcelona. Biomarker discovery was done using next-generation sequencing in a discovery set of 18 surgical samples (11 PDAC, 4 IPMN, 3 C). MiRNA validation was carried out by quantitative reverse transcriptase PCR in 2 different set of samples. Set 1—52 surgical samples (24 PDAC, 7 IPMN, 6 chronic pancreatitis, 15 C), and set 2—95 endoscopic ultrasound-guided fine-needle aspirations (60 PDAC, 9 IPMN, 26 C). Results: In all, 607 and 396 miRNAs were significantly deregulated in PDAC and IPMN versus C. Of them, 40 miRNAs commonly overexpressed in both PDAC and IPMN were selected for further validation. Among them, significant up-regulation of 31 and 30 miRNAs was confirmed by quantitative reverse transcriptase PCR in samples from set 1 and set 2, respectively. Conclusions: miRNome analysis shows that PDAC and IPMN have differential miRNA profiles with respect to C, with a large number of deregulated miRNAs shared by both neoplastic lesions. Indeed, we have identified and validated 30 miRNAs whose expression is significantly increased in PDAC and IPMN lesions. The feasibility of detecting these miRNAs in endoscopic ultrasound-guided fine-needle aspiration samples makes them good biomarker candidates for early detection of pancreatic cancer. PMID:27232245

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Computer Algorithm Comparisons

PubMed Central

2014-01-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. PMID:24919829

Searching for non-genetic molecular and imaging PTSD risk and resilience markers: Systematic review of literature and design of the German Armed Forces PTSD biomarker study.

PubMed

Schmidt, Ulrike; Willmund, Gerd-Dieter; Holsboer, Florian; Wotjak, Carsten T; Gallinat, Jürgen; Kowalski, Jens T; Zimmermann, Peter

2015-01-01

Biomarkers allowing the identification of individuals with an above average vulnerability or resilience for posttraumatic stress disorder (PTSD) would especially serve populations at high risk for trauma exposure like firefighters, police officers and combat soldiers. Aiming to identify the most promising putative PTSD vulnerability markers, we conducted the first systematic review on potential imaging and non-genetic molecular markers for PTSD risk and resilience. Following the PRISMA guidelines, we systematically screened the PubMed database for prospective longitudinal clinical studies and twin studies reporting on pre-trauma and post-trauma PTSD risk and resilience biomarkers. Using 25 different combinations of search terms, we retrieved 8151 articles of which we finally included and evaluated 9 imaging and 27 molecular studies. In addition, we briefly illustrate the design of the ongoing prospective German Armed Forces (Bundeswehr) PTSD biomarker study (Bw-BioPTSD) which not only aims to validate these previous findings but also to identify novel and clinically applicable molecular, psychological and imaging risk, resilience and disease markers for deployment-related psychopathology in a cohort of German soldiers who served in Afghanistan. Copyright © 2014 Elsevier Ltd. All rights reserved.

Characterization of renal biomarkers for use in clinical trials: biomarker evaluation in healthy volunteers

PubMed Central

Brott, David A; Adler, Scott H; Arani, Ramin; Lovick, Susan C; Pinches, Mark; Furlong, Stephen T

2014-01-01

Background Several preclinical urinary biomarkers have been qualified and accepted by the health authorities (US Food and Drug Administration, European Medicines Agency, and Pharmaceuticals and Medical Devices Agency) for detecting drug-induced kidney injury during preclinical toxicologic testing. Validated human assays for many of these biomarkers have become commercially available, and this study was designed to characterize some of the novel clinical renal biomarkers. The objective of this study was to evaluate clinical renal biomarkers in a typical Phase I healthy volunteer population to determine confidence intervals (pilot reference intervals), intersubject and intrasubject variability, effects of food intake, effect of sex, and vendor assay comparisons. Methods Spot urine samples from 20 male and 19 female healthy volunteers collected on multiple days were analyzed using single analyte and multiplex assays. The following analytes were measured: α-1-microglobulin, β-2-microglobulin, calbindin, clusterin, connective tissue growth factor, creatinine, cystatin C, glutathione S-transferase-α, kidney injury marker-1, microalbumin, N-acetyl-β-(D) glucosaminidase, neutrophil gelatinase-associated lipocalin, osteopontin, Tamm-Horsfall urinary glycoprotein, tissue inhibitor of metalloproteinase 1, trefoil factor 3, and vascular endothelial growth factor. Results Confidence intervals were determined from the single analyte and multiplex assays. Intersubject and intrasubject variability ranged from 38% to 299% and from 29% to 82% for biomarker concentration, and from 24% to 331% and from 10% to 67% for biomarker concentration normalized to creatinine, respectively. There was no major effect of food intake or sex. Single analyte and multiplex assays correlated with r2≥0.700 for five of six biomarkers when evaluating biomarker concentration, but for only two biomarkers when evaluating concentration normalized to creatinine. Conclusion Confidence intervals as well as intersubject and intrasubject variability were determined for novel clinical renal biomarkers/assays, which should be considered for evaluation in the next steps of the qualification process. PMID:24611000

Characterization of renal biomarkers for use in clinical trials: biomarker evaluation in healthy volunteers.

PubMed

Brott, David A; Adler, Scott H; Arani, Ramin; Lovick, Susan C; Pinches, Mark; Furlong, Stephen T

2014-01-01

Several preclinical urinary biomarkers have been qualified and accepted by the health authorities (US Food and Drug Administration, European Medicines Agency, and Pharmaceuticals and Medical Devices Agency) for detecting drug-induced kidney injury during preclinical toxicologic testing. Validated human assays for many of these biomarkers have become commercially available, and this study was designed to characterize some of the novel clinical renal biomarkers. The objective of this study was to evaluate clinical renal biomarkers in a typical Phase I healthy volunteer population to determine confidence intervals (pilot reference intervals), intersubject and intrasubject variability, effects of food intake, effect of sex, and vendor assay comparisons. Spot urine samples from 20 male and 19 female healthy volunteers collected on multiple days were analyzed using single analyte and multiplex assays. The following analytes were measured: α-1-microglobulin, β-2-microglobulin, calbindin, clusterin, connective tissue growth factor, creatinine, cystatin C, glutathione S-transferase-α, kidney injury marker-1, microalbumin, N-acetyl-β-(D) glucosaminidase, neutrophil gelatinase-associated lipocalin, osteopontin, Tamm-Horsfall urinary glycoprotein, tissue inhibitor of metalloproteinase 1, trefoil factor 3, and vascular endothelial growth factor. Confidence intervals were determined from the single analyte and multiplex assays. Intersubject and intrasubject variability ranged from 38% to 299% and from 29% to 82% for biomarker concentration, and from 24% to 331% and from 10% to 67% for biomarker concentration normalized to creatinine, respectively. There was no major effect of food intake or sex. Single analyte and multiplex assays correlated with r (2)≥0.700 for five of six biomarkers when evaluating biomarker concentration, but for only two biomarkers when evaluating concentration normalized to creatinine. Confidence intervals as well as intersubject and intrasubject variability were determined for novel clinical renal biomarkers/assays, which should be considered for evaluation in the next steps of the qualification process.

Biomarker discovery for colon cancer using a 761 gene RT-PCR assay.

PubMed

Clark-Langone, Kim M; Wu, Jenny Y; Sangli, Chithra; Chen, Angela; Snable, James L; Nguyen, Anhthu; Hackett, James R; Baker, Joffre; Yothers, Greg; Kim, Chungyeul; Cronin, Maureen T

2007-08-15

Reverse transcription PCR (RT-PCR) is widely recognized to be the gold standard method for quantifying gene expression. Studies using RT-PCR technology as a discovery tool have historically been limited to relatively small gene sets compared to other gene expression platforms such as microarrays. We have recently shown that TaqMan RT-PCR can be scaled up to profile expression for 192 genes in fixed paraffin-embedded (FPE) clinical study tumor specimens. This technology has also been used to develop and commercialize a widely used clinical test for breast cancer prognosis and prediction, the Onco typeDX assay. A similar need exists in colon cancer for a test that provides information on the likelihood of disease recurrence in colon cancer (prognosis) and the likelihood of tumor response to standard chemotherapy regimens (prediction). We have now scaled our RT-PCR assay to efficiently screen 761 biomarkers across hundreds of patient samples and applied this process to biomarker discovery in colon cancer. This screening strategy remains attractive due to the inherent advantages of maintaining platform consistency from discovery through clinical application. RNA was extracted from formalin fixed paraffin embedded (FPE) tissue, as old as 28 years, from 354 patients enrolled in NSABP C-01 and C-02 colon cancer studies. Multiplexed reverse transcription reactions were performed using a gene specific primer pool containing 761 unique primers. PCR was performed as independent TaqMan reactions for each candidate gene. Hierarchal clustering demonstrates that genes expected to co-express form obvious, distinct and in certain cases very tightly correlated clusters, validating the reliability of this technical approach to biomarker discovery. We have developed a high throughput, quantitatively precise multi-analyte gene expression platform for biomarker discovery that approaches low density DNA arrays in numbers of genes analyzed while maintaining the high specificity, sensitivity and reproducibility that are characteristics of RT-PCR. Biomarkers discovered using this approach can be transferred to a clinical reference laboratory setting without having to re-validate the assay on a second technology platform.

PITX3 promoter methylation is a prognostic biomarker for biochemical recurrence-free survival in prostate cancer patients after radical prostatectomy.

PubMed

Holmes, Emily Eva; Goltz, Diane; Sailer, Verena; Jung, Maria; Meller, Sebastian; Uhl, Barbara; Dietrich, Jörn; Röhler, Magda; Ellinger, Jörg; Kristiansen, Glen; Dietrich, Dimo

2016-01-01

Molecular biomarkers that might help to distinguish between more aggressive and clinically insignificant prostate cancers (PCa) are still urgently needed. Aberrant DNA methylation as a common molecular alteration in PCa seems to be a promising source for such biomarkers. In this study, PITX3 DNA methylation ( mPITX3 ) and its potential role as a prognostic biomarker were investigated. Furthermore, m PITX3 was analyzed in combination with the established PCa methylation biomarker PITX2 ( mPITX2 ). mPITX3 and mPITX2 were assessed by a quantitative real-time PCR and by means of the Infinium HumanMethylation450 BeadChip. BeadChip data were obtained from The Cancer Genome Atlas (TCGA) Research Network. DNA methylation differences between normal adjacent, benign hyperplastic, and carcinomatous prostate tissues were examined in the TCGA dataset as well as in prostatectomy specimens from the University Hospital Bonn. Retrospective analyses of biochemical recurrence (BCR) were conducted in a training cohort ( n  = 498) from the TCGA and an independent validation cohort ( n  = 300) from the University Hospital Bonn. All patients received radical prostatectomy. In PCa tissue, mPITX3 was increased significantly compared to normal and benign hyperplastic tissue. In univariate Cox proportional hazards analyses, mPITX3 showed a significant prognostic value for BCR (training cohort: hazard ratio (HR) = 1.83 (95 % CI 1.07-3.11), p  = 0.027; validation cohort: HR = 2.56 (95 % CI 1.44-4.54), p  = 0.001). A combined evaluation with PITX2 methylation further revealed that hypermethylation of a single PITX gene member (either PITX2 or PITX3 ) identifies an intermediate risk group. PITX3 DNA methylation alone and in combination with PITX2 is a promising biomarker for the risk stratification of PCa patients and adds relevant prognostic information to common clinically implemented parameters. Further studies are required to determine whether the results are transferable to a biopsy-based patient cohort. Trial registration: Patients for this unregistered study were enrolled retrospectively.

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

PubMed

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

2016-05-14

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.

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

Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis.

PubMed

Bühnemann, Claudia; Li, Simon; Yu, Haiyue; Branford White, Harriet; Schäfer, Karl L; Llombart-Bosch, Antonio; Machado, Isidro; Picci, Piero; Hogendoorn, Pancras C W; Athanasou, Nicholas A; Noble, J Alison; Hassan, A Bassim

2014-01-01

Driven by genomic somatic variation, tumour tissues are typically heterogeneous, yet unbiased quantitative methods are rarely used to analyse heterogeneity at the protein level. Motivated by this problem, we developed automated image segmentation of images of multiple biomarkers in Ewing sarcoma to generate distributions of biomarkers between and within tumour cells. We further integrate high dimensional data with patient clinical outcomes utilising random survival forest (RSF) machine learning. Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. Ki67, pS6, Foxo3a, EGR1, MAPK) localised relative to nuclear and cytoplasmic regions of each cell in order to generate image feature distributions. The image distribution features were analysed with RSF in relation to known overall patient survival from three separate cohorts (185 informative cases). Variation in pre-analytical processing resulted in elimination of a high number of non-informative images that had poor DAPI localisation or biomarker preservation (67 cases, 36%). The distribution of image features for biomarkers in the remaining high quality material (118 cases, 104 features per case) were analysed by RSF with feature selection, and performance assessed using internal cross-validation, rather than a separate validation cohort. A prognostic classifier for Ewing sarcoma with low cross-validation error rates (0.36) was comprised of multiple features, including the Ki67 proliferative marker and a sub-population of cells with low cytoplasmic/nuclear ratio of CD99. Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. Such an automated and integrated methodology has potential application in the identification of prognostic classifiers based on tumour cell heterogeneity.

Agenda: EDRN FDA Education Workshop — EDRN Public Portal

Cancer.gov

The purpose of this workshop was to open dialogue between FDA staff that provide oversight for review of in vitro diagnostic applications and EDRN scientists currently performing clinical validation studies on cancer biomarkers. Issues related to FDA review of diagnostic tests were presented by FDA personnel. Representatives from EDRN provided details on supporting data of their validation studies and the resources developed within EDRN to facilitate such research for FDA compliance. The agenda provided here provides links to the presentations by each speaker.

Role of the adverse outcome pathway framework in the validation of predictive biomarkers

EPA Science Inventory

Gene expression, enzyme activities, changes in endogenous metabolite or hormone titers, altered histology, etc. are widely used as biomarkers, but rarely, if ever, used for regulatory decision-making or to define management objectives. The disconnect between the measurements comm...

Novel Automated Blood Separations Validate Whole Cell Biomarkers

PubMed Central

Burger, Douglas E.; Wang, Limei; Ban, Liqin; Okubo, Yoshiaki; Kühtreiber, Willem M.; Leichliter, Ashley K.; Faustman, Denise L.

2011-01-01

Background Progress in clinical trials in infectious disease, autoimmunity, and cancer is stymied by a dearth of successful whole cell biomarkers for peripheral blood lymphocytes (PBLs). Successful biomarkers could help to track drug effects at early time points in clinical trials to prevent costly trial failures late in development. One major obstacle is the inaccuracy of Ficoll density centrifugation, the decades-old method of separating PBLs from the abundant red blood cells (RBCs) of fresh blood samples. Methods and Findings To replace the Ficoll method, we developed and studied a novel blood-based magnetic separation method. The magnetic method strikingly surpassed Ficoll in viability, purity and yield of PBLs. To reduce labor, we developed an automated platform and compared two magnet configurations for cell separations. These more accurate and labor-saving magnet configurations allowed the lymphocytes to be tested in bioassays for rare antigen-specific T cells. The automated method succeeded at identifying 79% of patients with the rare PBLs of interest as compared with Ficoll's uniform failure. We validated improved upfront blood processing and show accurate detection of rare antigen-specific lymphocytes. Conclusions Improving, automating and standardizing lymphocyte detections from whole blood may facilitate development of new cell-based biomarkers for human diseases. Improved upfront blood processes may lead to broad improvements in monitoring early trial outcome measurements in human clinical trials. PMID:21799852

Mortality risk prediction in COPD by a prognostic biomarker panel.

PubMed

Stolz, Daiana; Meyer, Anja; Rakic, Janko; Boeck, Lucas; Scherr, Andreas; Tamm, Michael

2014-12-01

Chronic obstructive pulmonary disease (COPD) is a complex disease with various phenotypes. The simultaneous determination of multiple biomarkers reflecting different pathobiological pathways could be useful in identifying individuals with an increased risk of death. We derived and validated a combination of three biomarkers (adrenomedullin, arginine vasopressin and atrial natriuretic peptide), assessed in plasma samples of 385 patients, to estimate mortality risk in stable COPD. Biomarkers were analysed in combination and defined as high or low. In the derivation cohort (n = 142), there were 73 deaths during the 5-year follow-up. Crude hazard ratios for mortality were 3.0 (95% CI 1.8-5.1) for one high biomarker, 4.8 (95% CI 2.4-9.5) for two biomarkers and 9.6 (95% CI 3.3-28.3) for three high biomarkers compared with no elevated biomarkers. In the validation cohort (n = 243), 87 individuals died. Corresponding hazard ratios were 1.9 (95% CI 1.1-3.3), 3.1 (95% CI 1.8-5.4) and 5.4 (95% CI 2.5-11.4). Multivariable adjustment for clinical variables as well as the BODE (body mass index, airflow obstruction, dyspnoea, exercise capacity) index and stratification by the Global Initiative for Chronic Obstructive Lung Disease stages provided consistent results. The addition of the panel of three biomarkers to the BODE index generated a net reclassification improvement of 57.9% (95% CI 21.7-92.4%) and 45.9% (95% CI 13.9-75.7%) at 3 and 5 years, respectively. Simultaneously elevated levels of adrenomedullin, arginine vasopressin and atrial natriuretic peptide are associated with increased risk of death in patients with stable COPD. ©ERS 2014.

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

Glial Biomarkers in Human Central Nervous System Disease

PubMed Central

Garden, Gwenn A.; Campbell, Brian M.

2017-01-01

There is a growing understanding that aberrant GLIA function is an underlying factor in psychiatric and neurological disorders. As drug discovery efforts begin to focus on glia-related targets, a key gap in knowledge includes the availability of validated biomarkers to help determine which patients suffer from dysfunction of glial cells or who may best respond by targeting glia-related drug mechanisms. Biomarkers are biological variables with a significant relationship to parameters of disease states and can be used as surrogate markers of disease pathology, progression, and/or responses to drug treatment. For example, imaging studies of the CNS enable localization and characterization of anatomical lesions without the need to isolate tissue for biopsy. Many biomarkers of disease pathology in the CNS involve assays of glial cell function and/or response to injury. Each major glia subtype (oligodendroglia, astroglia and microglia) are connected to a number of important and useful biomarkers. Here, we describe current and emerging glial based biomarker approaches for acute CNS injury and the major categories of chronic nervous system dysfunction including neurodegenerative, neuropsychiatric, neoplastic, and autoimmune disorders of the CNS. These descriptions are highlighted in the context of how biomarkers are employed to better understand the role of glia in human CNS disease and in the development of novel therapeutic treatments. PMID:27228454

Urothelial cancer of the upper urinary tract: emerging biomarkers and integrative models for risk stratification.

PubMed

Mathieu, Romain; Vartolomei, Mihai D; Mbeutcha, Aurélie; Karakiewicz, Pierre I; Briganti, Alberto; Roupret, Morgan; Shariat, Shahrokh F

2016-08-01

The aim of this review was to provide an overview of current biomarkers and risk stratification models in urothelial cancer of the upper urinary tract (UTUC). A non-systematic Medline/PubMed literature search was performed using the terms "biomarkers", "preoperative models", "postoperative models", "risk stratification", together with "upper tract urothelial carcinoma". Original articles published between January 2003 and August 2015 were included based on their clinical relevance. Additional references were collected by cross referencing the bibliography of the selected articles. Various promising predictive and prognostic biomarkers have been identified in UTUC thanks to the increasing knowledge of the different biological pathways involved in UTUC tumorigenesis. These biomarkers may help identify tumors with aggressive biology and worse outcomes. Current tools aim at predicting muscle invasive or non-organ confined disease, renal failure after radical nephroureterectomy and survival outcomes. These models are still mainly based on imaging and clinicopathological feature and none has integrated biomarkers. Risk stratification in UTUC is still suboptimal, especially in the preoperative setting due to current limitations in staging and grading. Identification of novel biomarkers and external validation of current prognostic models may help improve risk stratification to allow evidence-based counselling for kidney-sparing approaches, perioperative chemotherapy and/or risk-based surveillance. Despite growing understanding of the biology underlying UTUC, management of this disease remains difficult due to the lack of validated biomarkers and the limitations of current predictive and prognostic tools. Further efforts and collaborations are necessaryry to allow their integration in daily practice.

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

Screening and validation of serum protein biomarkers for early postmenopausal osteoporosis diagnosis.

PubMed

Wang, Long; Hu, Ya-Qian; Zhao, Zhuo-Jie; Zhang, Hong-Yang; Gao, Bo; Lu, Wei-Guang; Xu, Xiao-Long; Lin, Xi-Sheng; Wang, Jin-Peng; Jie, Qiang; Luo, Zhuo-Jing; Yang, Liu

2017-12-01

Postmenopausal osteoporosis is one of the most prominent worldwide public health problems and the morbidity is increasing with the aging population. It has been demonstrated that early diagnosis and intervention delay the disease progression and improve the outcome. Therefore, searching for biomarkers that are able to identify postmenopausal women at high risk for developing osteoporosis is an effective way to improve the quality of life of patients, and alleviate social and economic burdens. In the present study, a protein array was used to identify potential biomarkers. The bone mineral densities of 10 rats were dynamically measured in an ovariectomized model by micro‑computed tomography assessment, and the early stage of osteoporosis was defined. Through the protein array‑based screening, the expression levels of six serum protein biomarkers in ovariectomized rats were observed to alter at the initiation stage of the postmenopausal osteoporosis. Fractalkine, tissue inhibitor of metalloproteinases‑1 and monocyte chemotactic protein‑1 were finally demonstrated to be increased in the serum of eight enrolled postmenopausal osteoporosis patients using ELISA assay and were correlated with the severity of progressive bone loss. These biomarkers may be explored as potential early biomarkers to readily evaluate and diagnose postmenopausal osteoporosis in the clinic.

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

PubMed Central

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

2015-01-01

Background Breath volatile organic compounds (VOCs) have been reported as biomarkers of lung cancer, but it is not known if biomarkers identified in one group can identify disease in a separate independent cohort. Also, it is not known if combining breath biomarkers with chest CT has the potential to improve the sensitivity and specificity of lung cancer screening. Methods Model-building phase (unblinded): Breath VOCs were analyzed with gas chromatography mass spectrometry in 82 asymptomatic smokers having screening chest CT, 84 symptomatic high-risk subjects with a tissue diagnosis, 100 without a tissue diagnosis, and 35 healthy subjects. Multiple Monte Carlo simulations identified breath VOC mass ions with greater than random diagnostic accuracy for lung cancer, and these were combined in a multivariate predictive algorithm. Model-testing phase (blinded validation): We analyzed breath VOCs in an independent cohort of similar subjects (n = 70, 51, 75 and 19 respectively). The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening. Results Unblinded model-building phase. The algorithm identified lung cancer with sensitivity 74.0%, specificity 70.7% and C-statistic 0.78. Blinded model-testing phase: The algorithm identified lung cancer at Laboratory A with sensitivity 68.0%, specificity 68.4%, C-statistic 0.71; and at Laboratory B with sensitivity 70.1%, specificity 68.0%, C-statistic 0.70, with linear correlation between replicates (r = 0.88). In a projected outcome model, breath biomarkers increased the sensitivity, specificity, and positive and negative predictive values of chest CT for lung cancer when the tests were combined in series or parallel. Conclusions Breath VOC mass ion biomarkers identified lung cancer in a separate independent cohort, in a blinded replicated study. Combining breath biomarkers with chest CT could potentially improve the sensitivity and specificity of lung cancer screening. Trial Registration ClinicalTrials.gov NCT00639067 PMID:26698306

Identification of miRNA-103 in the Cellular Fraction of Human Peripheral Blood as a Potential Biomarker for Malignant Mesothelioma – A Pilot Study

PubMed Central

Weber, Daniel G.; Johnen, Georg; Bryk, Oleksandr; Jöckel, Karl-Heinz; Brüning, Thomas

2012-01-01

Background To date, no biomarkers with reasonable sensitivity and specificity for the early detection of malignant mesothelioma have been described. The use of microRNAs (miRNAs) as minimally-invasive biomarkers has opened new opportunities for the diagnosis of cancer, primarily because they exhibit tumor-specific expression profiles and have been commonly observed in blood of both cancer patients and healthy controls. The aim of this pilot study was to identify miRNAs in the cellular fraction of human peripheral blood as potential novel biomarkers for the detection of malignant mesothelioma. Methodology/Principal Findings Using oligonucleotide microarrays for biomarker identification the miRNA levels in the cellular fraction of human peripheral blood of mesothelioma patients and asbestos-exposed controls were analyzed. Using a threefold expression change in combination with a significance level of p<0.05, miR-103 was identified as a potential biomarker for malignant mesothelioma. Quantitative real-time PCR (qRT-PCR) was used for validation of miR-103 in 23 malignant mesothelioma patients, 17 asbestos-exposed controls, and 25 controls from the general population. For discrimination of mesothelioma patients from asbestos-exposed controls a sensitivity of 83% and a specificity of 71% were calculated, and for discrimination of mesothelioma patients from the general population a sensitivity of 78% and a specificity of 76%. Conclusions/Significance The results of this pilot study show that miR-103 is characterized by a promising sensitivity and specificity and might be a potential minimally-invasive biomarker for the diagnosis of mesothelioma. In addition, our results support the concept of using the cellular fraction of human blood for biomarker discovery. However, for early detection of malignant mesothelioma the feasibility of miR-103 alone or in combination with other biomarkers needs to be analyzed in a prospective study. PMID:22253921

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

PubMed

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

2017-03-15

Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection process; biomarkers were retained at p < 0.157 indicating improvement in the Akaike information criterion (AIC). Improvement in discrimination was assessed using the C-statistic for all biomarkers alone, and change in C-statistic from addition of biomarkers to preexisting absolute risk estimates. We used internal validation with bootstrapping (1000-fold) to adjust for over-fitting. Adiponectin, estrone, interleukin-1 receptor antagonist, tumor necrosis factor-alpha and triglycerides were selected into the model. After accounting for over-fitting, discrimination was improved by 2.0 percentage points when all evaluated biomarkers were included and 1.7 percentage points in the model including the selected biomarkers. Models including etiologic markers on independent pathways and genetic markers may further improve discrimination. © 2016 UICC.

IL-11 and CCL-1: Novel Protein Diagnostic Biomarkers of Lung Adenocarcinoma in Bronchoalveolar Lavage Fluid (BALF).

PubMed

Pastor, Maria Delores; Nogal, Ana; Molina-Pinelo, Sonia; Quintanal-Villalonga, Álvaro; Meléndez, Ricardo; Ferrer, I; Romero-Romero, Beatrice; De Miguel, Maria José; López-Campos, José Luis; Corral, Jesús; García-Carboner, Rocío; Carnero, Amancio; Paz-Ares, Luis

2016-12-01

Lung cancer (LC) and chronic obstructive pulmonary disease (COPD) are smoking-related diseases, with the presence of COPD itself increasing the risk for development of LC, probably owing to underlying inflammation. LC is typically detected at late stages of the disease and carries a poor prognosis. There is an unmet need for methods to facilitate the early detection of LC in high-risk subjects such as smokers. The expression of inflammatory proteins in bronchoalveolar lavage fluid (BALF) samples was studied by antibody arrays in a prospective cohort of 60 smokers of more than 30 pack-years divided into four groups (control, patients with LC, patients with COPD, and patients with LC plus COPD). Relevant biomarkers were validated by Western blot. Additional validation with enzyme-linked immunosorbent assay (ELISA) was carried out on two independent controlled cohorts of 139 patients (control, patients with LC, patients with COPD, and patients with LC plus COPD) and 160 patients (control and patients with LC of all histological types). A total of 16 differentially expressed proteins in samples from patients with LC, COPD, and LC plus COPD were identified by antibody arrays and validated by Western blot and ELISA. C-C motif chemokine ligand 1 (CCL-1) and interleukin-11 (IL)-11 were selectively expressed in samples from patients with adenocarcinoma with or without COPD (p < 0.005). These proteins exhibited a remarkable diagnostic performance for lung adenocarcinoma in an independent cohort of 139 patients. Receiver operating characteristic curves showed that the optimum diagnostic cutoff value for IL-11 was 42 pg/mL (area under the curve = 0.93 [95% confidence interval: 0.896-0.975], sensitivity 90%, specificity 86%), whereas for CCL-1 it was 39.5 pg/mL (0.83 [95% confidence interval: 0.749-0.902], sensitivity 83%, and specificity 74%). Further validation of the ELISA biomarkers at the aforementioned cutoffs was performed in an additional cohort of 160 patients (20 controls, 66 patients with LC, and 74 patients with LC plus COPD). There was a significant correlation between BALF levels of IL-11 and CCL-1 (r 2  = 0.76, p < 0.001), and the use of both biomarkers increased the diagnostic accuracy to 96.1% in the two validation cohorts. Appropriate diagnostic performance was observed for all subgroups regardless of stage at diagnosis, involvement of the bronchial tract, pack-years smoked, and number of cells in BALF. IL-11 and CCL-1 are highly specific biomarkers with great accuracy for the diagnosis of lung adenocarcinoma in BALF specimens. Further study of these proteins as markers for the early diagnosis and screening of plasma and other biological materials is warranted. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Linking biomarkers to reproductive success of caged fathead minnows in streams with increasing urbanization

USGS Publications Warehouse

Crago, J.; Corsi, S.R.; Weber, D.; Bannerman, R.; Klaper, R.

2011-01-01

Reproductive and oxidative stress biomarkers have been recommended as tools to assess the health of aquatic organisms. Though validated in the laboratory, there are few studies that tie a change in gene expression to adverse reproductive or population outcomes in the field. This paper looked at 17 streams with varying degrees of urbanization to assess the use of biomarkers associated with reproduction or stress in predicting reproductive success of fathead minnows. In addition, the relationship between biomarkers and water quality measures in streams with varying degrees of urbanization was examined. Liver vitellogenin mRNA was correlated with reproduction within a period of 11. d prior to sampling irrespective of habitat, but its correlation with egg output declined at 12. d and beyond indicating its usefulness as a short-term biomarker but its limits as a biomarker of total reproductive output. Stress biomarkers such as glutathione S-transferase may be better correlated with factors affecting reproduction over a longer term. There was a significant correlation between GST mRNA and a variety of anthropogenic pollutants. There was also an inverse correlation between glutathione S-transferase and the amount of the watershed designated as wetland. Egg production over the 21-d was negatively correlated with the amount of urbanization and positively correlated to wetland habitats. This study supports the development of multiple biomarkers linking oxidative stress and other non-reproductive endpoints to changes in aquatic habitats will be useful for predicting the health of fish populations and identifying the environmental factors that may need mitigation for sustainable population management. ?? 2010 Elsevier Ltd.

Adsorbing/dissolving Lyoprotectant Matrix Technology for Non-cryogenic Storage of Archival Human Sera

NASA Astrophysics Data System (ADS)

Solivio, Morwena J.; Less, Rebekah; Rynes, Mathew L.; Kramer, Marcus; Aksan, Alptekin

2016-04-01

Despite abundant research conducted on cancer biomarker discovery and validation, to date, less than two-dozen biomarkers have been approved by the FDA for clinical use. One main reason is attributed to inadvertent use of low quality biospecimens in biomarker research. Most proteinaceous biomarkers are extremely susceptible to pre-analytical factors such as collection, processing, and storage. For example, cryogenic storage imposes very harsh chemical, physical, and mechanical stresses on biospecimens, significantly compromising sample quality. In this communication, we report the development of an electrospun lyoprotectant matrix and isothermal vitrification methodology for non-cryogenic stabilization and storage of liquid biospecimens. The lyoprotectant matrix was mainly composed of trehalose and dextran (and various low concentration excipients targeting different mechanisms of damage), and it was engineered to minimize heterogeneity during vitrification. The technology was validated using five biomarkers; LDH, CRP, PSA, MMP-7, and C3a. Complete recovery of LDH, CRP, and PSA levels was achieved post-rehydration while more than 90% recovery was accomplished for MMP-7 and C3a, showing promise for isothermal vitrification as a safe, efficient, and low-cost alternative to cryogenic storage.

Biomarkers--a pot of gold or a can of worms?: Meeting report from the 2nd World Congress on Biomarkers & Clinical Research, 2011, Baltimore, USA.

PubMed

Weber, Georg F; Warren, Jeremy; Shoma, Hitoshi; Chen, Tao; Halim, Abdel; Chakravarty, Geetika

2012-08-01

Biomarkers are biological agents used as indicators of biological states. In clinical applications, biomarkers reflect the presence, severity, or progression of disease states. They may also predict risk or responsiveness of a disease to a given treatment. There has been increasingly intense research interest in biomarkers, yet their translation into routine clinical use is lagging. To stimulate communication and cross-fertilization, the 2nd World Congress on Biomarkers & Clinical Research was held in Baltimore, MD, USA in 2011. The symposium covered a broad range of basic and applied biomarker research with the intent to facilitate bench-to-bedside developments. Sessions discussed DNA-based, proteomic, and blood-borne markers. The presentations covered biomarkers for cancer, other various diseases, and toxicological agents. Other topics included biomarker data assimilation, validation, standardization and quality control, as well as molecular imaging and informatics. New high-throughput assays, model systems and emerging technologies give reasons to hope for further rapid progress in the field.

Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

PubMed Central

Chen, Hao; Zhu, Zhitu; Zhu, Yichun; Wang, Jian; Mei, Yunqing; Cheng, Yunfeng

2015-01-01

It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein–protein or gene–gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed. PMID:25560835

Potential role of blood biomarkers in the management of nontraumatic intracerebral hemorrhage.

PubMed

Senn, Rebecca; Elkind, Mitchell S V; Montaner, Joan; Christ-Crain, Mirjam; Katan, Mira

2014-01-01

Intracerebral hemorrhage (ICH), a subtype of stroke associated with high mortality and disability, accounts for 13% of all strokes. Basic and clinical research has contributed to our understanding of the complex pathophysiology of neuronal injury in ICH. Outcome rates, however, remain stable, and questions regarding acute management of ICH remain unanswered. Newer research is aiming at matching measured levels of serum proteins, enzymes, or cells to different stages of brain damage, suggesting that blood biomarkers may assist in acute diagnosis, therapeutic decisions, and prognostication. This paper provides an overview on the most promising blood biomarkers and their potential role in the diagnosis and management of spontaneous ICH. Information was collected from studies, reviews, and guidelines listed in PubMed up to November 2013 on blood biomarkers of nontraumatic ICH in humans. We describe the potential role and limitations of GFAP, S100B/RAGE, and ApoC-III as diagnostic biomarkers, β-​Amyloid as a biomarker for etiological classification, and 27 biomarkers for prognosis of mortality and functional outcome. Within the group of prognostic markers we discuss markers involved in coagulation processes (e.g., D-Dimers), neuroendocrine markers (e.g., copeptin), systemic metabolic markers (e.g., blood glucose levels), markers of inflammation (e.g., IL-6), as well as growth factors (e.g., VEGF), and others (e.g., glutamate). Some of those blood biomarkers are agents of pathologic processes associated with hemorrhagic stroke but also other diseases, whereas others play more distinct pathophysiological roles and help in understanding the basic mechanisms of brain damage and/or recovery in ICH. Numerous blood biomarkers are associated with different pathophysiological pathways in ICH, and some of them promise to be useful in the management of ICH, eventually contributing additional information to current tools for diagnosis, therapy monitoring, risk stratification, or intervention. Up to date, however, no blood biomarker of ICH has been studied sufficiently to find its way into clinical routine yet; well-designed, large-scale, clinical studies addressing relevant clinical questions are needed. We suggest that the effectiveness of biomarker research in ICH might be improved by international cooperation and shared resources for large validation studies, such as provided by the consortium on stroke biomarker research (http://stroke-biomarkers.​com/page.php?title=Resources). © 2014 S. Karger AG, Basel.

A blood-based predictor for neocortical Aβ burden in Alzheimer's disease: results from the AIBL study.

PubMed

Burnham, S C; Faux, N G; Wilson, W; Laws, S M; Ames, D; Bedo, J; Bush, A I; Doecke, J D; Ellis, K A; Head, R; Jones, G; Kiiveri, H; Martins, R N; Rembach, A; Rowe, C C; Salvado, O; Macaulay, S L; Masters, C L; Villemagne, V L

2014-04-01

Dementia is a global epidemic with Alzheimer's disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based screen.

Utility of a New Model to Diagnose an Alcohol Basis for Steatohepatitis

PubMed Central

Dunn, Winston; Angulo, Paul; Sanderson, Schuyler; Jamil, Laith H.; Stadheim, Linda; Rosen, Charles; Malinchoc, Michael; Kamath, Patrick S.; Shah, Vijay

2007-01-01

Background and Aims Distinguishing an alcohol basis from a nonalcoholic basis for the clinical and histological spectrum of steatohepatitic liver disease is difficult owing to unreliability of alcohol consumption history. Unfortunately, various biomarkers have had limited utility in distinguishing alcoholic liver disease (ALD) from nonalcoholic fatty liver disease (NAFLD). Thus, the aim of our study was to create and validate a model to diagnose ALD in patients with steatohepatitis. Methods Cross-sectional cohort study was performed at Mayo Clinic; Rochester, Minnesota to create a model using multivariable logistic regression analysis. This model was validated in three independent data-sets comprising patients of varying severity of steatohepatitis spanning over 10 years. Results Logistic regression identified mean corpuscular volume, AST/ALT ratio, body-mass index, and gender as the most important variables that separated patients with ALD from NAFLD. These variables were used to generate the ALD/NAFLD Index (ANI); with ANI of greater than 0 incrementally favoring ALD, and ANI of less than 0 incrementally favoring a diagnosis of NAFLD, thus making ALD unlikely. ANI had a c-statistic of 0.989 in the derivation sample, and 0.974, 0.989, 0.767 in the three validation samples. ANI performance characteristics were significantly better than several conventional and recently proposed biomarkers used to differentiate ALD from NAFLD including the histopathological marker Protein Tyrosine Phosphatase 1b, AST/ALT ratio, gamma-glutamyl transferase and Carbohydrate Deficient Transferrin. Conclusion ANI, derived from easily available objective variables, accurately differentiates ALD from NAFLD in hospitalized, ambulatory and pre-transplant patients and compares favorably to other traditional and proposed biomarkers. PMID:17030176

Identification of Antibody Targets for Tuberculosis Serology using High-Density Nucleic Acid Programmable Protein Arrays*

PubMed Central

Song, Lusheng; Wallstrom, Garrick; Yu, Xiaobo; Hopper, Marika; Van Duine, Jennifer; Steel, Jason; Park, Jin; Wiktor, Peter; Kahn, Peter; Brunner, Al; Wilson, Douglas; Jenny-Avital, Elizabeth R.; Qiu, Ji; Labaer, Joshua; Magee, D. Mitchell; Achkar, Jacqueline M.

2017-01-01

Better and more diverse biomarkers for the development of simple point-of-care tests for active tuberculosis (TB), a clinically heterogeneous disease, are urgently needed. We generated a proteomic Mycobacterium tuberculosis (Mtb) High-Density Nucleic Acid Programmable Protein Array (HD-NAPPA) that used a novel multiplexed strategy for expedited high-throughput screening for antibody responses to the Mtb proteome. We screened sera from HIV uninfected and coinfected TB patients and controls (n = 120) from the US and South Africa (SA) using the multiplex HD-NAPPA for discovery, followed by deconvolution and validation through single protein HD-NAPPA with biologically independent samples (n = 124). We verified the top proteins with enzyme-linked immunosorbent assays (ELISA) using the original screening and validation samples (n = 244) and heretofore untested samples (n = 41). We identified 8 proteins with TB biomarker value; four (Rv0054, Rv0831c, Rv2031c and Rv0222) of these were previously identified in serology studies, and four (Rv0948c, Rv2853, Rv3405c, Rv3544c) were not known to elicit antibody responses. Using ELISA data, we created classifiers that could discriminate patients' TB status according to geography (US or SA) and HIV (HIV- or HIV+) status. With ROC curve analysis under cross validation, the classifiers performed with an AUC for US/HIV- at 0.807; US/HIV+ at 0.782; SA/HIV- at 0.868; and SA/HIV+ at 0.723. With this study we demonstrate a new platform for biomarker/antibody screening and delineate its utility to identify previously unknown immunoreactive proteins. PMID:28223349

[Biomarkers and imaging for diagnosis and stratification of rheumatoid arthritis and spondylarthritis in the BMBF consortium ArthroMark].

PubMed

Häupl, T; Skapenko, A; Hoppe, B; Skriner, K; Burkhardt, H; Poddubnyy, D; Ohrndorf, S; Sewerin, P; Mansmann, U; Stuhlmüller, B; Schulze-Koops, H; Burmester, G-R

2018-05-01

Rheumatic diseases are among the most common chronic inflammatory disorders. Besides severe pain and progressive destruction of the joints, rheumatoid arthritis (RA), spondyloarthritides (SpA) and psoriatic arthritis (PsA) impair working ability, reduce quality of life and if treated insufficiently may enhance mortality. With the introduction of biologics to treat these diseases, the demand for biomarkers of early diagnosis and therapeutic stratification has been growing continuously. The main goal of the consortium ArthroMark is to identify new biomarkers and to apply modern imaging technologies for diagnosis, follow-up assessment and stratification of patients with RA, SpA and PsA. With the development of new biomarkers for these diseases, the ArthroMark project contributes to research in chronic diseases of the musculoskeletal system. The cooperation between different national centers will utilize site-specific resources, such as biobanks and clinical studies for sharing and gainful networking of individual core areas in biomarker analysis. Joint data management and harmonization of data assessment as well as best practice characterization of patients with new imaging technologies will optimize quality of marker validation.

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

Roadmap and standard operating procedures for biobanking and discovery of neurochemical markers in ALS.

PubMed

Otto, Markus; Bowser, Robert; Turner, Martin; Berry, James; Brettschneider, Johannes; Connor, James; Costa, Júlia; Cudkowicz, Merit; Glass, Jonathan; Jahn, Olaf; Lehnert, Stefan; Malaspina, Andrea; Parnetti, Lucilla; Petzold, Axel; Shaw, Pamela; Sherman, Alexander; Steinacker, Petra; Süssmuth, Sigurd; Teunissen, Charlotte; Tumani, Hayrettin; Wuolikainen, Anna; Ludolph, Albert

2012-01-01

Despite major advances in deciphering the neuropathological hallmarks of amyotrophic lateral sclerosis (ALS), validated neurochemical biomarkers for monitoring disease activity, earlier diagnosis, defining prognosis and unlocking key pathophysiological pathways are lacking. Although several candidate biomarkers exist, translation into clinical application is hindered by small sample numbers, especially longitudinal, for independent verification. This review considers the potential routes to the discovery of neurochemical markers in ALS, and provides a consensus statement on standard operating procedures that will facilitate multicenter collaboration, validation and ultimately clinical translation.

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

Systematic review and meta-analysis of immunohistochemical prognostic biomarkers in resected oesophageal adenocarcinoma

PubMed Central

McCormick Matthews, L H; Noble, F; Tod, J; Jaynes, E; Harris, S; Primrose, J N; Ottensmeier, C; Thomas, G J; Underwood, T J

2015-01-01

Background: Oesophageal adenocarcinoma (OAC) is one of the fastest rising malignancies with continued poor prognosis. Many studies have proposed novel biomarkers but, to date, no immunohistochemical markers of survival after oesophageal resection have entered clinical practice. Here, we systematically review and meta-analyse the published literature, to identify potential biomarkers. Methods: Relevant articles were identified via Ovid medline 1946–2013. For inclusion, studies had to conform to REporting recommendations for tumor MARKer (REMARK) prognostic study criteria. The primary end-point was a pooled hazard ratio (HR) and variance, summarising the effect of marker expression on prognosis. Results: A total of 3059 articles were identified. After exclusion of irrelevant titles and abstracts, 214 articles were reviewed in full. Nine molecules had been examined in more than one study (CD3, CD8, COX-2, EGFR, HER2, Ki67, LgR5, p53 and VEGF) and were meta-analysed. Markers with largest survival effects were COX-2 (HR=2.47, confidence interval (CI)=1.15–3.79), CD3 (HR=0.51, 95% CI=0.32–0.70), CD8 (HR=0.55, CI=0.31–0.80) and EGFR (HR=1.65, 95% CI=1.14–2.16). Discussion: Current methods have not delivered clinically useful molecular prognostic biomarkers in OAC. We have highlighted the paucity of good-quality robust studies in this field. A genome-to-protein approach would be better suited for the development and subsequent validation of biomarkers. Large collaborative projects with standardised methodology will be required to generate clinically useful biomarkers. PMID:26110972

Company Profile: AKESOgen, Inc.

PubMed

Bouzyk, Mark; Boisjoli, Robert

2012-07-01

Rapid advancement of genomics, genetic and bioinformatic technologies have paved the way for an explosion of opportunities in pharmacogenomics, which is reflected by the growing number of biomarkers in the 'personalized medicine cabinet'. AKESOgen, Inc. (GA, USA) has been established to meet and champion these needs. AKESOgen, Inc. is a biomarker, genomics and pharmacogenomics contract research organization that services the academic, pharmaceutical, biotechnology and agricultural sectors. AKESOgen, Inc. performs biomarker profiling and genomics services utilizing different types of markers (e.g., DNA, RNA and methylation) for the research and development market. AKESOgen, Inc. establishes and validates biomarkers in the clinical trials arena and provides expertise in biobanking.

Meta-Analysis and Experimental Validation Identified FREM2 and SPRY1 as New Glioblastoma Marker Candidates.

PubMed

Vidak, Marko; Jovcevska, Ivana; Samec, Neja; Zottel, Alja; Liovic, Mirjana; Rozman, Damjana; Dzeroski, Saso; Juvan, Peter; Komel, Radovan

2018-05-04

Glioblastoma (GB) is the most aggressive brain malignancy. Although some potential glioblastoma biomarkers have already been identified, there is a lack of cell membrane-bound biomarkers capable of distinguishing brain tissue from glioblastoma and/or glioblastoma stem cells (GSC), which are responsible for the rapid post-operative tumor reoccurrence. In order to find new GB/GSC marker candidates that would be cell surface proteins (CSP), we have performed meta-analysis of genome-scale mRNA expression data from three data repositories (GEO, ArrayExpress and GLIOMASdb). The search yielded ten appropriate datasets, and three (GSE4290/GDS1962, GSE23806/GDS3885, and GLIOMASdb) were used for selection of new GB/GSC marker candidates, while the other seven (GSE4412/GDS1975, GSE4412/GDS1976, E-GEOD-52009, E-GEOD-68848, E-GEOD-16011, E-GEOD-4536, and E-GEOD-74571) were used for bioinformatic validation. The selection identified four new CSP-encoding candidate genes— CD276 , FREM2 , SPRY1 , and SLC47A1 —and the bioinformatic validation confirmed these findings. A review of the literature revealed that CD276 is not a novel candidate, while SLC47A1 had lower validation test scores than the other new candidates and was therefore not considered for experimental validation. This validation revealed that the expression of FREM2—but not SPRY1—is higher in glioblastoma cell lines when compared to non-malignant astrocytes. In addition, FREM2 gene and protein expression levels are higher in GB stem-like cell lines than in conventional glioblastoma cell lines. FREM2 is thus proposed as a novel GB biomarker and a putative biomarker of glioblastoma stem cells. Both FREM2 and SPRY1 are expressed on the surface of the GB cells, while SPRY1 alone was found overexpressed in the cytosol of non-malignant astrocytes.

Quantification of proteins in urine samples using targeted mass spectrometry methods.

PubMed

Khristenko, Nina; Domon, Bruno

2015-01-01

Numerous clinical proteomics studies are focused on the development of biomarkers to improve either diagnostics for early disease detection or the monitoring of the response to the treatment. Although, a wealth of biomarker candidates are available, their evaluation and validation in a true clinical setup remains challenging. In biomarkers evaluation studies, a panel of proteins of interest are systematically analyzed in a large cohort of samples. However, in spite of the latest progresses in mass spectrometry, the consistent detection of pertinent proteins in high complex biological samples is still a challenging task. Thus, targeted LC-MS/MS methods are better suited for the systematic analysis of biomarkers rather than shotgun approaches. This chapter describes the workflow used to perform targeted quantitative analyses of proteins in urinary samples. The peptides, as surrogates of the protein of interest, are commonly measured using a triple quadrupole mass spectrometers operated in selected reaction monitoring (SRM) mode. More recently, the advances in targeted LC-MS/MS analysis based on parallel reaction monitoring (PRM) performed on a quadrupole-orbitrap instrument have allowed to increase the specificity and selectivity of the measurements.

Sweetening the pot: adding glycosylation to the biomarker discovery equation.

PubMed

Drake, Penelope M; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N Leigh; Regnier, Fred E; Gibson, Bradford W; Fisher, Susan J

2010-02-01

Cancer has profound effects on gene expression, including a cell's glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate compared with their protein backbones. In this article, we survey clinical tests that target carbohydrate modifications for diagnosing and treating cancer. We present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling, and metastasis and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies--multiple reaction monitoring and lectin-antibody arrays--as potential tools for biomarker validation studies in pursuit of clinically useful tests. The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses.

Sweetening the pot: adding glycosylation to the biomarker discovery equation

PubMed Central

Drake, Penelope M.; Cho, Wonryeon; Li, Bensheng; Prakobphol, Akraporn; Johansen, Eric; Anderson, N. Leigh; Regnier, Fred E.; Gibson, Bradford W.; Fisher, Susan J.

2010-01-01

Background Cancer has profound effects on gene expression, including a cell’s glycosylation machinery. Thus, tumors produce glycoproteins that carry oligosaccharides with structures that are markedly different from the same protein produced by a normal cell. A single protein can have many glycosylation sites that greatly amplify the signals they generate as compared to their protein backbones. Content We survey clinical tests that target carbohydrate modifications. for diagnosing and treating cancer. Next, we present the biological relevance of glycosylation to disease progression by highlighting the role these structures play in adhesion, signaling and metastasis, and then address current methodological approaches to biomarker discovery that capitalize on selectively capturing tumor-associated glycoforms to enrich and identify disease-related candidate analytes. Finally, we discuss emerging technologies—multiple reaction monitoring and lectin-antibody arrays—as potential tools for biomarker validation studies in pursuit of clinically useful tests. Summary The future of carbohydrate-based biomarker studies has arrived. At all stages, from discovery through verification and deployment into clinics, glycosylation should be considered a primary readout or a way of increasing the sensitivity and specificity of protein-based analyses. PMID:19959616

Biomarkers for early detection of Alzheimer disease.

PubMed

Barber, Robert C

2010-09-01

The existence of an effective biomarker for early detection of Alzheimer disease would facilitate improved diagnosis and stimulate therapeutic trials. Multidisciplinary clinical diagnosis of Alzheimer disease is time consuming and expensive and relies on experts who are rarely available outside of specialty clinics. Thus, many patients do not receive proper diagnosis until the disease has progressed beyond stages in which treatments are maximally effective. In the clinical trial setting, rapid, cost-effective screening of patients for Alzheimer disease is of paramount importance for the development of new treatments. Neuroimaging of cortical amyloid burden and volumetric changes in the brain and assessment of protein concentrations (eg, β-amyloid 1-42, total tau, phosphorylated tau) in cerebrospinal fluid are diagnostic tools that are not widely available. Known genetic markers do not provide sufficient discriminatory power between different forms of dementia to be useful in isolation. Recent studies using panels of biomarkers for diagnosis of Alzheimer disease or mild cognitive impairment have been promising, though no such studies have been cross-validated in independent samples of subjects. The ideal biomarker enabling early detection of Alzheimer disease has not yet been identified.

Validation of Molecular Biomarkers for the Early Detection of Lung Cancer in the setting of Indeterminate Pulmonary Nodules (Lung Team Project #2) — EDRN Public Portal

Cancer.gov

To characterize intra or within subject reproducibility and variability To characterize inter or across subject variability by adenoma phenotype (normal vs. adenoma) To evaluate biomarker expression in relation to long term adenoma recurrence

Validation of Biomarkers for Prostate Cancer Prognosis

DTIC Science & Technology

2016-11-01

NUMBER 6. AUTHOR(S) Ziding Feng, Ph.D. 5d. PROJECT NUMBER 5e. TASK NUMBER Email : ZFeng3@mdanderson.org 5f. WORK UNIT NUMBER 7. PERFORMING...algorithm to facilitate the scoring of TMA stains. We will work with investigators to write papers reporting tested TMA Biomarkers. 15. SUBJECT TERMS

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

PubMed

Martyanov, Viktor; Whitfield, Michael L

2016-01-01

The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib

PubMed Central

Li, Bin; Shin, Hyunjin; Gulbekyan, Georgy; Pustovalova, Olga; Nikolsky, Yuri; Hope, Andrew; Bessarabova, Marina; Schu, Matthew; Kolpakova-Hart, Elona; Merberg, David; Dorner, Andrew; Trepicchio, William L.

2015-01-01

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug’s known mechanism of action. Also, the models predict each drug’s potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets. PMID:26107615

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib.

PubMed

Li, Bin; Shin, Hyunjin; Gulbekyan, Georgy; Pustovalova, Olga; Nikolsky, Yuri; Hope, Andrew; Bessarabova, Marina; Schu, Matthew; Kolpakova-Hart, Elona; Merberg, David; Dorner, Andrew; Trepicchio, William L

2015-01-01

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug's known mechanism of action. Also, the models predict each drug's potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.

Novel Autoantibody Serum and Cerebrospinal Fluid Biomarkers in Veterans with Gulf War Illness

DTIC Science & Technology

2017-10-01

health of veterans with GWI is not improving. Such blood-based autoantibodies may prove useful as biomarkers of GWI, upon validation of the findings using...status 1-3 1-4 1b. Obtain DOD Human Research Protections Office (HRPO) approvals or Exempt Status 1-3 1-4 Milestone(s) Achieved: Regulatory...Syndrome (IBS), OP pesticide and nerve agent exposures in GW veterans  Biomarkers of prior brain injury in GW veterans against their

Beyond Reliability

PubMed Central

2008-01-01

The validity of psychiatric diagnosis rests in part on a demonstration that identifiable biomarkers exist for major psychiatric illnesses. Recent evidence supports the existence of several biomarkers or endophenotypes for both schizophrenia and bipolar disorder. As we learn more about how these biomarkers relate to the symptoms, course, and treatment response of major psychiatric disorders, the “objectivity” of psychiatric diagnosis will increase. However, psychiatry is and will remain a clinically based discipline, aimed at comprehensively understanding and relieving human suffering. PMID:19727304

Biomarkers of Aging: From Function to Molecular Biology

PubMed Central

Wagner, Karl-Heinz; Cameron-Smith, David; Wessner, Barbara; Franzke, Bernhard

2016-01-01

Aging is a major risk factor for most chronic diseases and functional impairments. Within a homogeneous age sample there is a considerable variation in the extent of disease and functional impairment risk, revealing a need for valid biomarkers to aid in characterizing the complex aging processes. The identification of biomarkers is further complicated by the diversity of biological living situations, lifestyle activities and medical treatments. Thus, there has been no identification of a single biomarker or gold standard tool that can monitor successful or healthy aging. Within this short review the current knowledge of putative biomarkers is presented, focusing on their application to the major physiological mechanisms affected by the aging process including physical capability, nutritional status, body composition, endocrine and immune function. This review emphasizes molecular and DNA-based biomarkers, as well as recent advances in other biomarkers such as microRNAs, bilirubin or advanced glycation end products. PMID:27271660

MicroRNAs are suitable for assessment as biomarkers from formalin-fixed paraffin-embedded tissue, and miR-24 represents an appropriate reference microRNA for diffuse large B-cell lymphoma studies.

PubMed

Culpin, Rachel Emily; Sieniawski, Michal; Proctor, Stephen John; Menon, Geetha; Mainou-Fowler, Tryfonia

2013-03-01

Tissue biopsy specimens in the form of formalin-fixed paraffin-embedded tissue (FFPET) represent a valuable resource for biomarker identification and validation. However, to date, they remain an underused asset due to uncertainty regarding RNA extraction and the reliability of downstream techniques, including quantitative RT-PCR. Recently, much interest has emerged in the study of microRNAs; small single-stranded RNAs with a role in transcriptional regulation, that are thought to be well preserved in FFPET. In this study, we show that microRNA expression is comparable between FFPET and matched fresh-frozen samples (miR-17-5p: p=0.01, miR-92: p=0.003), and demonstrate that no significant deterioration in expression occurs over prolonged FFPET storage (p=0.06). Furthermore, microRNA expression is equivalent dependant on RNA extraction method (p<0.001) or DNAse treatment of total RNA (p<0.001). Finally, we validate miR-24 as a suitable reference microRNA for diffuse large B-cell lymphoma (DLBCL) FFPET studies.

Improved Diagnostic Accuracy of Alzheimer's Disease by Combining Regional Cortical Thickness and Default Mode Network Functional Connectivity: Validated in the Alzheimer's Disease Neuroimaging Initiative Set.

PubMed

Park, Ji Eun; Park, Bumwoo; Kim, Sang Joon; Kim, Ho Sung; Choi, Choong Gon; Jung, Seung Chai; Oh, Joo Young; Lee, Jae-Hong; Roh, Jee Hoon; Shim, Woo Hyun

2017-01-01

To identify potential imaging biomarkers of Alzheimer's disease by combining brain cortical thickness (CThk) and functional connectivity and to validate this model's diagnostic accuracy in a validation set. Data from 98 subjects was retrospectively reviewed, including a study set (n = 63) and a validation set from the Alzheimer's Disease Neuroimaging Initiative (n = 35). From each subject, data for CThk and functional connectivity of the default mode network was extracted from structural T1-weighted and resting-state functional magnetic resonance imaging. Cortical regions with significant differences between patients and healthy controls in the correlation of CThk and functional connectivity were identified in the study set. The diagnostic accuracy of functional connectivity measures combined with CThk in the identified regions was evaluated against that in the medial temporal lobes using the validation set and application of a support vector machine. Group-wise differences in the correlation of CThk and default mode network functional connectivity were identified in the superior temporal ( p < 0.001) and supramarginal gyrus ( p = 0.007) of the left cerebral hemisphere. Default mode network functional connectivity combined with the CThk of those two regions were more accurate than that combined with the CThk of both medial temporal lobes (91.7% vs. 75%). Combining functional information with CThk of the superior temporal and supramarginal gyri in the left cerebral hemisphere improves diagnostic accuracy, making it a potential imaging biomarker for Alzheimer's disease.

Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

PubMed

Xu, Rengyi; Mesaros, Clementina; Weng, Liwei; Snyder, Nathaniel W; Vachani, Anil; Blair, Ian A; Hwang, Wei-Ting

2017-07-01

We compared three statistical methods in selecting a panel of serum lipid biomarkers for mesothelioma and asbestos exposure. Serum samples from mesothelioma, asbestos-exposed subjects and controls (40 per group) were analyzed. Three variable selection methods were considered: top-ranked predictors from univariate model, stepwise and least absolute shrinkage and selection operator. Crossed-validated area under the receiver operating characteristic curve was used to compare the prediction performance. Lipids with high crossed-validated area under the curve were identified. Lipid with mass-to-charge ratio of 372.31 was selected by all three methods comparing mesothelioma versus control. Lipids with mass-to-charge ratio of 1464.80 and 329.21 were selected by two models for asbestos exposure versus control. Different methods selected a similar set of serum lipids. Combining candidate biomarkers can improve prediction.

Surrogate endpoints and emerging surrogate endpoints for risk reduction of cardiovascular disease.

PubMed

Rasnake, Crystal M; Trumbo, Paula R; Heinonen, Therese M

2008-02-01

This article reviews surrogate endpoints and emerging biomarkers that were discussed at the annual "Cardiovascular Biomarkers and Surrogate Endpoints" symposium cosponsored by the US Food and Drug Administration (FDA) and the Montreal Heart Institute. The FDA's Center for Food Safety and Applied Nutrition (CFSAN) uses surrogate endpoints in its scientific review of a substance/disease relationship for a health claim. CFSAN currently recognizes three validated surrogate endpoints: blood pressure, blood total cholesterol, and blood low-density lipoprotein (LDL) concentration in its review of a health claim for cardiovascular disease (CVD). Numerous potential surrogate endpoints of CVD are being evaluated as the pathophysiology of heart disease is becoming better understood. However, these emerging biomarkers need to be validated as surrogate endpoints before they are used by CFSAN in the evaluation of a CVD health claim.

Human cervicovaginal fluid biomarkers to predict term and preterm labor

PubMed Central

Heng, Yujing J.; Liong, Stella; Permezel, Michael; Rice, Gregory E.; Di Quinzio, Megan K. W.; Georgiou, Harry M.

2015-01-01

Preterm birth (PTB; birth before 37 completed weeks of gestation) remains the major cause of neonatal morbidity and mortality. The current generation of biomarkers predictive of PTB have limited utility. In pregnancy, the human cervicovaginal fluid (CVF) proteome is a reflection of the local biochemical milieu and is influenced by the physical changes occurring in the vagina, cervix and adjacent overlying fetal membranes. Term and preterm labor (PTL) share common pathways of cervical ripening, myometrial activation and fetal membranes rupture leading to birth. We therefore hypothesize that CVF biomarkers predictive of labor may be similar in both the term and preterm labor setting. In this review, we summarize some of the existing published literature as well as our team's breadth of work utilizing the CVF for the discovery and validation of putative CVF biomarkers predictive of human labor. Our team established an efficient method for collecting serial CVF samples for optimal 2-dimensional gel electrophoresis resolution and analysis. We first embarked on CVF biomarker discovery for the prediction of spontaneous onset of term labor using 2D-electrophoresis and solution array multiple analyte profiling. 2D-electrophoretic analyses were subsequently performed on CVF samples associated with PTB. Several proteins have been successfully validated and demonstrate that these biomarkers are associated with term and PTL and may be predictive of both term and PTL. In addition, the measurement of these putative biomarkers was found to be robust to the influences of vaginal microflora and/or semen. The future development of a multiple biomarker bed-side test would help improve the prediction of PTB and the clinical management of patients. PMID:26029118

Biomarkers for early detection of pancreatic cancer — EDRN Public Portal

Cancer.gov

Background: The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Methods: Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Results: The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively correlated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected 1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Conclusions: Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combination offered some advantage of CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis, however further study will be needed to fully define the implications of these findings.

Using non-invasive biomarkers to identify hepatic fibrosis in people with type 2 diabetes mellitus: the Edinburgh type 2 diabetes study.

PubMed

Morling, Joanne R; Fallowfield, Jonathan A; Guha, Indra N; Nee, Lisa D; Glancy, Stephen; Williamson, Rachel M; Robertson, Christine M; Strachan, Mark W J; Price, Jackie F

2014-02-01

It is difficult to determine the different stages of non-alcoholic fatty liver disease without the use of invasive liver biopsy. In this study we investigated five non-invasive biomarkers used previously to detect hepatic fibrosis and determined the level of agreement between them in order to inform future research. In the Edinburgh Type 2 Diabetes Study, a population-based cohort aged 60-74 years with type 2 diabetes, 831 participants underwent ultrasound assessment for fatty liver and had serum aspartate aminotransferase to alanine aminotransferase ratio (AST/ALT), aspartate to platelet ratio index (APRI), European Liver Fibrosis panel (ELF), Fibrosis-4 Score (FIB4) and liver stiffness measurement (LSM) measured. Literature based cut-offs yielded marked differences in the proportions of the cohort with probable liver fibrosis in the full cohort. Agreement between the top 5% of the distribution for each biomarker pair was poor. APRI and FIB4 had the best positive agreement at 76.4%, but agreement for all of the other serum biomarker pairs was between 18% and 34%. Agreement with LSM was poor (9-16%). We found poor correlation between the five biomarkers of liver fibrosis studied. Using the top 5% of each biomarker resulted in good agreement on the absence of advanced liver disease but poor agreement on the presence of advanced disease. Further work is required to validate these markers against liver biopsy and to determine their predictive value for clinical liver-related endpoints, in a range of different low and high risk population groups.

Serum Metabolite Biomarkers Discriminate Healthy Smokers from COPD Smokers

PubMed Central

Chen, Qiuying; Deeb, Ruba S.; Ma, Yuliang; Staudt, Michelle R.; Crystal, Ronald G.; Gross, Steven S.

2015-01-01

COPD (chronic obstructive pulmonary disease) is defined by a fixed expiratory airflow obstruction associated with disordered airways and alveolar destruction. COPD is caused by cigarette smoking and is the third greatest cause of mortality in the US. Forced expiratory volume in 1 second (FEV1) is the only validated clinical marker of COPD, but it correlates poorly with clinical features and is not sensitive enough to predict the early onset of disease. Using LC/MS global untargeted metabolite profiling of serum samples from a well-defined cohort of healthy smokers (n = 37), COPD smokers (n = 41) and non-smokers (n = 37), we sought to discover serum metabolic markers with known and/or unknown molecular identities that are associated with early-onset COPD. A total of 1,181 distinct molecular ions were detected in 95% of sera from all study subjects and 23 were found to be differentially-expressed in COPD-smokers vs. healthy-smokers. These 23 putative biomarkers were differentially-correlated with lung function parameters and used to generate a COPD prediction model possessing 87.8% sensitivity and 86.5% specificity. In an independent validation set, this model correctly predicted COPD in 8/10 individuals. These serum biomarkers included myoinositol, glycerophopshoinositol, fumarate, cysteinesulfonic acid, a modified version of fibrinogen peptide B (mFBP), and three doubly-charged peptides with undefined sequence that significantly and positively correlate with mFBP levels. Together, elevated levels of serum mFBP and additional disease-associated biomarkers point to a role for chronic inflammation, thrombosis, and oxidative stress in remodeling of the COPD airways. Serum metabolite biomarkers offer a promising and accessible window for recognition of early-stage COPD. PMID:26674646

Exosomal Fetuin-A identified by proteomics: a novel urinary biomarker for detecting acute kidney injury

PubMed Central

Zhou, Hua; Pisitkun, Trairak; Aponte, Angel; Yuen, Peter S.T.; Hoffert, Jason D.; Yasuda, Hideo; Hu, Xuzhen; Chawla, Lakhmir; Shen, Rong-Fong; Knepper, Mark A.; Star., Robert A.

2008-01-01

Urinary exosomes containing apical membrane and intracellular fluid are normally secreted into the urine from all nephron segments, and may carry protein markers of renal dysfunction and structural injury. We aimed to discover biomarkers in urinary exosomes to detect acute kidney injury (AKI) which has a high mortality and morbidity. Animals were injected intravenously with cisplatin. Urinary exosomes were isolated by differential centrifugation. Protein changes were evaluated by two-dimensional difference in gel electrophoresis and changed proteins were identified by MALDI-TOF-TOF or LC-MS/MS. The identified candidate biomarkers were validated by western blotting in individual urine samples from rats subjected to cisplatin injection; bilateral ischemia and reperfusion (I/R); volume depletion (VD); and ICU patients with and without AKI. We identified 18 proteins that were increased and 9 proteins that were decreased 8 hr after cisplatin. Most of the candidates could not be validated by western blotting. However, exosomal Fetuin-A increased 52.5-fold at day 2 (1 day before serum creatinine increase and tubule damage) and remained elevated 51.5-fold at day 5 (peak renal injury) after cisplatin injection. By immuno-electron microscopy and elution studies, Fetuin-A was located inside urinary exosomes. Urinary Fetuin-A was increased 31.6-fold in the early phase (2~8hr) of ischemia/reperfusion, but not in prerenal azotemia. Urinary exosomal Fetuin-A also increased in three ICU patients with AKI compared to the patients without AKI. We conclude that 1) Proteomic analysis of urinary exosomes can provide biomarker candidates for the diagnosis of AKI; 2) Urinary Fetuin-A might be a predictive biomarker of structural renal injury. PMID:17021608

Patterns of Circulating Inflammatory Biomarkers in Older Persons with Varying Levels of Physical Performance: A Partial Least Squares-Discriminant Analysis Approach

PubMed Central

Marzetti, Emanuele; Landi, Francesco; Marini, Federico; Cesari, Matteo; Buford, Thomas W.; Manini, Todd M.; Onder, Graziano; Pahor, Marco; Bernabei, Roberto; Leeuwenburgh, Christiaan; Calvani, Riccardo

2014-01-01

Background: Chronic, low-grade inflammation and declining physical function are hallmarks of the aging process. However, previous attempts to correlate individual inflammatory biomarkers with physical performance in older people have produced mixed results. Given the complexity of the inflammatory response, the simultaneous analysis of an array of inflammatory mediators may provide more insights into the relationship between inflammation and age-related physical function decline. This study was designed to explore the association between a panel of inflammatory markers and physical performance in older adults through a multivariate statistical approach. Methods: Community-dwelling older persons were categorized into “normal walkers” (NWs; n = 27) or “slow walkers” (SWs; n = 11) groups using 0.8 m s−1 as the 4-m gait speed cutoff. A panel of 14 circulating inflammatory biomarkers was assayed by multiplex analysis. Partial least squares-discriminant analysis (PLS-DA) was used to identify patterns of inflammatory mediators associated with gait speed categories. Results: The optimal complexity of the PLS-DA model was found to be five latent variables. The proportion of correct classification was 88.9% for NW subjects (74.1% in cross-validation) and 90.9% for SW individuals (81.8% in cross-validation). Discriminant biomarkers in the model were interleukin 8, myeloperoxidase, and tumor necrosis factor alpha (all higher in the SW group), and P-selectin, interferon gamma, and granulocyte–macrophage colony-stimulating factor (all higher in the NW group). Conclusion: Distinct profiles of circulating inflammatory biomarkers characterize older subjects with different levels of physical performance. The dissection of these patterns may provide novel insights into the role played by inflammation in the disabling cascade and possible new targets for interventions. PMID:25593902

Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma

PubMed Central

Addona, Terri A; Abbatiello, Susan E; Schilling, Birgit; Skates, Steven J; Mani, D R; Bunk, David M; Spiegelman, Clifford H; Zimmerman, Lisa J; Ham, Amy-Joan L; Keshishian, Hasmik; Hall, Steven C; Allen, Simon; Blackman, Ronald K; Borchers, Christoph H; Buck, Charles; Cardasis, Helene L; Cusack, Michael P; Dodder, Nathan G; Gibson, Bradford W; Held, Jason M; Hiltke, Tara; Jackson, Angela; Johansen, Eric B; Kinsinger, Christopher R; Li, Jing; Mesri, Mehdi; Neubert, Thomas A; Niles, Richard K; Pulsipher, Trenton C; Ransohoff, David; Rodriguez, Henry; Rudnick, Paul A; Smith, Derek; Tabb, David L; Tegeler, Tony J; Variyath, Asokan M; Vega-Montoto, Lorenzo J; Wahlander, Åsa; Waldemarson, Sofia; Wang, Mu; Whiteaker, Jeffrey R; Zhao, Lei; Anderson, N Leigh; Fisher, Susan J; Liebler, Daniel C; Paulovich, Amanda G; Regnier, Fred E; Tempst, Paul; Carr, Steven A

2010-01-01

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low µg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma. PMID:19561596

Reconciled rat and human metabolic networks for comparative toxicogenomics and biomarker predictions

PubMed Central

Blais, Edik M.; Rawls, Kristopher D.; Dougherty, Bonnie V.; Li, Zhuo I.; Kolling, Glynis L.; Ye, Ping; Wallqvist, Anders; Papin, Jason A.

2017-01-01

The laboratory rat has been used as a surrogate to study human biology for more than a century. Here we present the first genome-scale network reconstruction of Rattus norvegicus metabolism, iRno, and a significantly improved reconstruction of human metabolism, iHsa. These curated models comprehensively capture metabolic features known to distinguish rats from humans including vitamin C and bile acid synthesis pathways. After reconciling network differences between iRno and iHsa, we integrate toxicogenomics data from rat and human hepatocytes, to generate biomarker predictions in response to 76 drugs. We validate comparative predictions for xanthine derivatives with new experimental data and literature-based evidence delineating metabolite biomarkers unique to humans. Our results provide mechanistic insights into species-specific metabolism and facilitate the selection of biomarkers consistent with rat and human biology. These models can serve as powerful computational platforms for contextualizing experimental data and making functional predictions for clinical and basic science applications. PMID:28176778

Using biomarkers to assess the validity of sexual behavior reporting across interview modes among young women in Kampala, Uganda

PubMed Central

Kelly, Christine A.; Hewett, Paul C.; Mensch, Barbara S.; Rankin, Johanna; Nsobya, Sam; Kalibala, Sam; Kakande, Pamela

2015-01-01

Understanding the transmission dynamics of HIV and other sexually transmitted infections is critically dependent on accurate behavioral data. This paper investigates the effect of questionnaire delivery mode on the quality of sexual behavior reporting in a survey conducted in Kampala in 2010 among 18–24 year old females using the women’s instrument of the 2006 Uganda Demographic and Health Survey. We compare the reported prevalence of five sexual outcomes across three interview modes: traditional face-to-face interview (FTFI) in which question rewording was permitted, FTFI administered via computer-assisted personal interviewing (CAPI) in which questions were read as written, and audio computer-assisted self-interviewing (ACASI). We then assess the validity of the data by evaluating reporting of sexual experience against three biological markers. Results suggest that ACASI elicits higher reporting of some key indicators than face-to-face interviews, but self-reports from all interview methods were subject to validity concerns when compared with biomarker data. The paper highlights the important role biomarkers play in sexual behavior research. PMID:24615574

EV-Associated MMP9 in High-Grade Serous Ovarian Cancer Is Preferentially Localized to Annexin V-Binding EVs.

PubMed

Reiner, Agnes T; Tan, Sisareuth; Agreiter, Christiane; Auer, Katharina; Bachmayr-Heyda, Anna; Aust, Stefanie; Pecha, Nina; Mandorfer, Mattias; Pils, Dietmar; Brisson, Alain R; Zeillinger, Robert; Lim, Sai Kiang

2017-01-01

High-grade serous ovarian cancer (HGSOC) is the most aggressive type of ovarian cancer and is responsible for most deaths caused by gynecological cancers. Numerous candidate biomarkers were identified for this disease in the last decades, but most were not sensitive or specific enough for clinical applications. Hence, new biomarkers for HGSOC are urgently required. This study aimed to identify new markers by isolating different extracellular vesicle (EV) types from the ascites of ovarian cancer patients according to their affinities for lipid-binding proteins and analyzing their protein cargo. This approach circumvents the low signal-to-noise ratio when using biological fluids for biomarker discovery and the issue of contamination by large non-EV complexes. We isolated and analyzed three distinct EV populations from the ascites of patients with ovarian cancer or cirrhosis and observed that Annexin V-binding EVs have higher levels of matrix metalloproteinase 9 in malignant compared to portal-hypertensive ascites. As this protein was not detected in other EV populations, this study validates our approach of using different EV types for optimal biomarker discovery. Furthermore, MMP9 in Annexin V-binding EVs could be a HGSOC biomarker with enhanced specificity, because its identification requires detection of two distinct components, that is, lipid and protein.

A Tissue Systems Pathology Assay for High-Risk Barrett's Esophagus.

PubMed

Critchley-Thorne, Rebecca J; Duits, Lucas C; Prichard, Jeffrey W; Davison, Jon M; Jobe, Blair A; Campbell, Bruce B; Zhang, Yi; Repa, Kathleen A; Reese, Lia M; Li, Jinhong; Diehl, David L; Jhala, Nirag C; Ginsberg, Gregory; DeMarshall, Maureen; Foxwell, Tyler; Zaidi, Ali H; Lansing Taylor, D; Rustgi, Anil K; Bergman, Jacques J G H M; Falk, Gary W

2016-06-01

Better methods are needed to predict risk of progression for Barrett's esophagus. We aimed to determine whether a tissue systems pathology approach could predict progression in patients with nondysplastic Barrett's esophagus, indefinite for dysplasia, or low-grade dysplasia. We performed a nested case-control study to develop and validate a test that predicts progression of Barrett's esophagus to high-grade dysplasia (HGD) or esophageal adenocarcinoma (EAC), based upon quantification of epithelial and stromal variables in baseline biopsies. Data were collected from Barrett's esophagus patients at four institutions. Patients who progressed to HGD or EAC in ≥1 year (n = 79) were matched with patients who did not progress (n = 287). Biopsies were assigned randomly to training or validation sets. Immunofluorescence analyses were performed for 14 biomarkers and quantitative biomarker and morphometric features were analyzed. Prognostic features were selected in the training set and combined into classifiers. The top-performing classifier was assessed in the validation set. A 3-tier, 15-feature classifier was selected in the training set and tested in the validation set. The classifier stratified patients into low-, intermediate-, and high-risk classes [HR, 9.42; 95% confidence interval, 4.6-19.24 (high-risk vs. low-risk); P < 0.0001]. It also provided independent prognostic information that outperformed predictions based on pathology analysis, segment length, age, sex, or p53 overexpression. We developed a tissue systems pathology test that better predicts risk of progression in Barrett's esophagus than clinicopathologic variables. The test has the potential to improve upon histologic analysis as an objective method to risk stratify Barrett's esophagus patients. Cancer Epidemiol Biomarkers Prev; 25(6); 958-68. ©2016 AACR. ©2016 American Association for Cancer Research.

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

PubMed Central

2010-01-01

Background To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Methods Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Results Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Conclusions Coronin-1C could be a candidate biomarker to predict HCC invasive behavior. PMID:20181269

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

PubMed

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

2016-03-01

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

Circulating microRNAs as novel biomarkers for bone diseases - Complex signatures for multifactorial diseases?

PubMed

Hackl, Matthias; Heilmeier, Ursula; Weilner, Sylvia; Grillari, Johannes

2016-09-05

Biomarkers are essential tools in clinical research and practice. Useful biomarkers must combine good measurability, validated association with biological processes or outcomes, and should support clinical decision making if used in clinical practice. Several types of validated biomarkers have been reported in the context of bone diseases. However, because these biomarkers face certain limitations there is an interest in the identification of novel biomarkers for bone diseases, specifically in those that are tightly linked to the disease pathology leading to increased fracture-risk. MicroRNAs (miRNAs) are the most abundant RNA species to be found in cell-free blood. Encapsulated within microvesicles or bound to proteins, circulating miRNAs are remarkably stable analytes that can be measured using gold-standard technologies such as quantitative polymerase-chain-reaction (qPCR). Nevertheless, the analysis of circulating miRNAs faces several pre-analytical as well as analytical challenges. From a biological view, there is accumulating evidence that miRNAs play essential roles in the regulation of various biological processes including bone homeostasis. Moreover, specific changes in miRNA transcription levels or miRNA secretory levels have been linked to the development and progression of certain bone diseases. Only recently, results from circulating miRNAs analysis in patients with osteopenia, osteoporosis and fragility fractures have been reported. By comparing these findings to studies on circulating miRNAs in cellular senescence and aging or muscle physiology and sarcopenia, several overlaps were observed. This suggests that signatures observed during osteoporosis might not be specific to the pathophysiology in bone, but rather integrate information from several tissue types. Despite these promising first data, more work remains to be done until circulating miRNAs can serve as established and robust diagnostic tools for bone diseases in clinical research, clinical routine and in personalized medicine. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Biomarkers to guide clinical therapeutics in rheumatology?

PubMed

Robinson, William H; Mao, Rong

2016-03-01

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. 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. 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.

Identification of Unique Blood and Urine Biomarkers in Influenza Virus and Staphylococcus aureus Co-infection: A Preliminary Study.

PubMed

Prescott, Meagan A; Pastey, Manoj K

2010-12-05

Each year, there are estimated to be approximately 200,000 hospitalizations and 36,000 deaths due to influenza in the United States. Reports have indicated that most deaths are not directly due to influenza virus, but to secondary bacterial pneumonia, predominantly staphylococcal in origin. Here we identify the presence of candidate blood and urine biomarkers in mice with Staphyococcus aureus and influenza virus co-infection. In this pilot study, mice were grouped into four treatments: co-infected with influenza virus and S. aureus, singly infected with influenza virus or S. aureus, and a control group of uninfected mice (PBS treated). Gene expression changes were identified by DNA-microarrays from blood samples taken at day five post infection. Proteomic changes were obtained from urine samples collected at three and five days post infection using 2-D DIGE followed by protein ID by mass spectrometry. Differentially expressed genes and/or proteins were identified as candidate biomarkers for future validation in larger studies.

Prospective evaluation of 64 serum autoantibodies as biomarkers for early detection of colorectal cancer in a true screening setting.

PubMed

Chen, Hongda; Werner, Simone; Butt, Julia; Zörnig, Inka; Knebel, Phillip; Michel, Angelika; Eichmüller, Stefan B; Jäger, Dirk; Waterboer, Tim; Pawlita, Michael; Brenner, Hermann

2016-03-29

Novel blood-based screening tests are strongly desirable for early detection of colorectal cancer (CRC). We aimed to identify and evaluate autoantibodies against tumor-associated antigens as biomarkers for early detection of CRC. 380 clinically identified CRC patients and samples of participants with selected findings from a cohort of screening colonoscopy participants in 2005-2013 (N=6826) were included in this analysis. Sixty-four serum autoantibody markers were measured by multiplex bead-based serological assays. A two-step approach with selection of biomarkers in a training set, and validation of findings in a validation set, the latter exclusively including participants from the screening setting, was applied. Anti-MAGEA4 exhibited the highest sensitivity for detecting early stage CRC and advanced adenoma. Multi-marker combinations substantially increased sensitivity at the price of a moderate loss of specificity. Anti-TP53, anti-IMPDH2, anti-MDM2 and anti-MAGEA4 were consistently included in the best-performing 4-, 5-, and 6-marker combinations. This four-marker panel yielded a sensitivity of 26% (95% CI, 13-45%) for early stage CRC at a specificity of 90% (95% CI, 83-94%) in the validation set. Notably, it also detected 20% (95% CI, 13-29%) of advanced adenomas. Taken together, the identified biomarkers could contribute to the development of a useful multi-marker blood-based test for CRC early detection.

A computational method for computing an Alzheimer’s Disease Progression Score; experiments and validation with the ADNI dataset

PubMed Central

Jedynak, Bruno M.; Liu, Bo; Lang, Andrew; Gel, Yulia; Prince, Jerry L.

2014-01-01

Understanding the time-dependent changes of biomarkers related to Alzheimer’s disease (AD) is a key to assessing disease progression and to measuring the outcomes of disease-modifying therapies. In this paper, we validate an Alzheimer’s disease progression score model which uses multiple biomarkers to quantify the AD progression of subjects following three assumptions: (1) there is a unique disease progression for all subjects, (2) each subject has a different age of onset and rate of progression, and (3) each biomarker is sigmoidal as a function of disease progression. Fitting the parameters of this model is a challenging problem which we approach using an alternating least squares optimization algorithm. In order to validate this optimization scheme under realistic conditions, we use the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. With the help of Monte Carlo simulations, we show that most of the global parameters of the model are tightly estimated, thus enabling an ordering of the biomarkers that fit the model well, ordered as: the Rey auditory verbal learning test with 30 minutes delay, the sum of the two lateral hippocampal volumes divided by the intra-cranial volume, followed by (the clinical dementia rating sum of boxes score and the mini mental state examination score) in no particular order and lastly the Alzheimer’s disease assessment scale-cognitive subscale. PMID:25444605

Precision medicine for suicidality: from universality to subtypes and personalization

PubMed Central

Niculescu, A B; Le-Niculescu, H; Levey, D F; Phalen, P L; Dainton, H L; Roseberry, K; Niculescu, E M; Niezer, J O; Williams, A; Graham, D L; Jones, T J; Venugopal, V; Ballew, A; Yard, M; Gelbart, T; Kurian, S M; Shekhar, A; Schork, N J; Sandusky, G E; Salomon, D R

2017-01-01

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a ‘liquid biopsy’ approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator. PMID:28809398

Precision medicine for suicidality: from universality to subtypes and personalization.

PubMed

Niculescu, A B; Le-Niculescu, H; Levey, D F; Phalen, P L; Dainton, H L; Roseberry, K; Niculescu, E M; Niezer, J O; Williams, A; Graham, D L; Jones, T J; Venugopal, V; Ballew, A; Yard, M; Gelbart, T; Kurian, S M; Shekhar, A; Schork, N J; Sandusky, G E; Salomon, D R

2017-09-01

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a 'liquid biopsy' approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator.

Proteomics of gliomas: Initial biomarker discovery and evolution of technology

PubMed Central

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

2011-01-01

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. PMID:21852429

Potential oxidative stress biomarkers of mild cognitive impairment due to Alzheimer disease.

PubMed

García-Blanco, Ana; Baquero, Miguel; Vento, Máximo; Gil, Esperanza; Bataller, Luis; Cháfer-Pericás, Consuelo

2017-02-15

The high and increasing incidence of Alzheimer Disease (AD) worldwide is a major global concern. Classical diagnosis is carried out in the dementia phase, often in the moderate stages when treatment efficacy is limited. Nowadays, early diagnosis, even in pre-dementia stages, is possible in selected cases within an appropriate clinical setting, employing cerebral spinal fluid (CSF) sample analysis and neuroimaging procedures. In spite of the accurate diagnosis achieved by novel CSF biomarkers or positron emission tomography beta-amyloid tracers, these tests are invasive and expensive. Therefore, important work is being carried out to discover reliable biomarkers in peripheral biofluids (blood, plasma, urine) to be incorporated in clinical routine for early AD diagnosis. Although the nature of AD pathogenesis is complex, it is known that oxidative stress plays a key role, for which biomarkers are easily determined in peripheral biofluids. This review summarizes recent research on oxidative stress biomarkers in mild cognitive impairment due to AD. Among them, a promising research line is the study of the relationship between lipid peroxidation biomarkers and early AD clinical features. Results show a pronounced imbalance between scientific production and clinical reality due to the lack of clinical validation. We conclude that an important field in oxidative stress biomarkers could be developed with the aim to help clinicians in early disease diagnosis, effective treatment initiation and reliable disease monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical validity of cerebrospinal fluid Aβ42, tau, and phospho-tau as biomarkers for Alzheimer's disease in the context of a structured 5-phase development framework.

PubMed

Mattsson, Niklas; Lönneborg, Anders; Boccardi, Marina; Blennow, Kaj; Hansson, Oskar

2017-04-01

Novel diagnostic criteria for Alzheimer's disease (AD) incorporate biomarkers, but their maturity for implementation in clinical practice at the prodromal stage (mild cognitive impairment [MCI]) is unclear. Here, we evaluate cerebrospinal fluid (CSF) β-amyloid 42 (Aβ42), total tau, and phosphorylated tau in the light of a 5-phase framework for biomarker development. Ample evidence is available for phase 1 (identifying useful leads) and phase 2 (assessing the accuracy for AD dementia versus controls) for CSF biomarkers. Phase 3 (utility in MCI) is partially achieved. In cohorts with long follow-up time, CSF Aβ42, total tau, and phosphorylated tau have high diagnostic accuracy for MCI due to AD. Phase 4 (performance in real world) is ongoing, and phase 5 studies (quantify impact and costs) are to come. Our results highlight priorities to pursue and to enable the proper use of CSF biomarkers in the clinic. Priorities are to reduce measurement variability by introduction of fully automated assay systems; to increase diagnostic specificity toward non-AD neurocognitive diseases at the MCI stage; and to clarify the role of CSF biomarkers versus other biomarker modalities in clinical practice and in design of clinical trials. These efforts are currently ongoing. Copyright © 2016 Elsevier Inc. All rights reserved.

Multimodal Classification of Alzheimer’s Disease and Mild Cognitive Impairment

PubMed Central

Zhang, Daoqiang; Wang, Yaping; Zhou, Luping; Yuan, Hong; Shen, Dinggang

2011-01-01

Effective and accurate diagnosis of Alzheimer’s disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment (MCI)), has attracted more and more attentions recently. So far, multiple biomarkers have been shown sensitive to the diagnosis of AD and MCI, i.e., structural MR imaging (MRI) for brain atrophy measurement, functional imaging (e.g., FDG-PET) for hypometabolism quantification, and cerebrospinal fluid (CSF) for quantification of specific proteins. However, most existing research focuses on only a single modality of biomarkers for diagnosis of AD and MCI, although recent studies have shown that different biomarkers may provide complementary information for diagnosis of AD and MCI. In this paper, we propose to combine three modalities of biomarkers, i.e., MRI, FDG-PET, and CSF biomarkers, to discriminate between AD (or MCI) and healthy controls, using a kernel combination method. Specifically, ADNI baseline MRI, FDG-PET, and CSF data from 51 AD patients, 99 MCI patients (including 43 MCI converters who had converted to AD within 18 months and 56 MCI non-converters who had not converted to AD within 18 months), and 52 healthy controls are used for development and validation of our proposed multimodal classification method. In particular, for each MR or FDG-PET image, 93 volumetric features are extracted from the 93 regions of interest (ROIs), automatically labeled by an atlas warping algorithm. For CSF biomarkers, their original values are directly used as features. Then, a linear support vector machine (SVM) is adopted to evaluate the classification accuracy, using a 10-fold cross-validation. As a result, for classifying AD from healthy controls, we achieve a classification accuracy of 93.2% (with a sensitivity of 93% and a specificity of 93.3%) when combining all three modalities of biomarkers, and only 86.5% when using even the best individual modality of biomarkers. Similarly, for classifying MCI from healthy controls, we achieve a classification accuracy of 76.4% (with a sensitivity of 81.8% and a specificity of 66%) for our combined method, and only 72% even using the best individual modality of biomarkers. Further analysis on MCI sensitivity of our combined method indicates that 91.5% of MCI converters and 73.4% of MCI non-converters are correctly classified. Moreover, we also evaluate the classification performance when employing a feature selection method to select the most discriminative MR and FDG-PET features. Again, our combined method shows considerably better performance, compared to the case of using an individual modality of biomarkers. PMID:21236349

Traumatic brain injury produced by exposure to blasts, a critical problem in current wars: biomarkers, clinical studies, and animal models

NASA Astrophysics Data System (ADS)

Dixon, C. Edward

2011-06-01

Traumatic brain injury (TBI) resulting from exposure to blast energy released by Improvised Explosive Devices (IEDs) has been recognized as the "signature injury" of Operation Iraqi Freedom and Operation Enduring Freedom. Repeated exposure to mild blasts may produce subtle deficits that are difficult to detect and quantify. Several techniques have been used to detect subtle brain dysfunction including neuropsychological assessments, computerized function testing and neuroimaging. Another approach is based on measurement of biologic substances (e.g. proteins) that are released into the body after a TBI. Recent studies measuring biomarkers in CSF and serum from patients with severe TBI have demonstrated the diagnostic, prognostic, and monitoring potential. Advancement of the field will require 1) biochemical mining for new biomarker candidates, 2) clinical validation of utility, 3) technical advances for more sensitive, portable detectors, 4) novel statistical approach to evaluate multiple biomarkers, and 5) commercialization. Animal models have been developed to simulate elements of blast-relevant TBI including gas-driven shock tubes to generate pressure waves similar to those produced by explosives. These models can reproduce hallmark clinical neuropathological responses such as neuronal degeneration and inflammation, as well as behavioral impairments. An important application of these models is to screen novel therapies and conduct proteomic, genomic, and lipodomic studies to mine for new biomarker candidates specific to blast relevant TBI.

Serum Prognostic Biomarkers in Head and Neck Cancer Patients

PubMed Central

Lin, Ho-Sheng; Siddiq, Fauzia; Talwar, Harvinder S.; Chen, Wei; Voichita, Calin; Draghici, Sorin; Jeyapalan, Gerald; Chatterjee, Madhumita; Fribley, Andrew; Yoo, George H.; Sethi, Seema; Kim, Harold; Sukari, Ammar; Folbe, Adam J.; Tainsky, Michael A.

2014-01-01

Objectives/Hypothesis A reliable estimate of survival is important as it may impact treatment choice. The objective of this study is to identify serum autoantibody biomarkers that can be used to improve prognostication for patients affected with head and neck squamous cell carcinoma (HNSCC). Study Design Prospective cohort study. Methods A panel of 130 serum biomarkers, previously selected for cancer detection using microarray-based serological profiling and specialized bioinformatics, were evaluated for their potential as prognostic biomarkers in a cohort of 119 HNSCC patients followed for up to 12.7 years. A biomarker was considered positive if its reactivity to the particular patient’s serum was greater than one standard deviation above the mean reactivity to sera from the other 118 patients, using a leave-one-out cross-validation model. Survival curves were estimated according to the Kaplan-Meier method, and statistically significant differences in survival were examined using the log rank test. Independent prognostic biomarkers were identified following analysis using multivariate Cox proportional hazards models. Results Poor overall survival was associated with African Americans (hazard ratio [HR] for death =2.61; 95% confidence interval [CI]: 1.58–4.33; P =.000), advanced stage (HR =2.79; 95% CI: 1.40–5.57; P =.004), and recurrent disease (HR =6.66; 95% CI: 2.54–17.44; P =.000). On multivariable Cox analysis adjusted for covariates (race and stage), six of the 130 markers evaluated were found to be independent prognosticators of overall survival. Conclusions The results shown here are promising and demonstrate the potential use of serum biomarkers for prognostication in HNSCC patients. Further clinical trials to include larger samples of patients across multiple centers may be warranted. PMID:24347532

Lysophosphatidylcholine and amide as metabolites for detecting alzheimer disease using ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabonomics.

PubMed

Cui, Yu; Liu, Xiuqin; Wang, Maoqing; Liu, Liyan; Sun, Xiaohong; Ma, Lan; Xie, Wei; Wang, Chao; Tang, Sisi; Wang, Decai; Wu, Qunhong

2014-10-01

Alzheimer disease (AD) can be diagnosed by clinical and neuropsychologic tests and at autopsy, but there are no simple effective diagnostic methods for detecting biomarkers in patients at early stages of cognitive impairment. Early metabolic alterations that may facilitate AD diagnosis have not been thoroughly explored. We applied a nontargeted metabonomic approach using ultrahigh-performance liquid chromatography-quadrupole time-of-flight mass spectrometry to analyze serum and urine samples from 46 patients with AD and 36 healthy controls. Metabolite profiles were processed using multivariate analysis to identify potential metabolites, which were further confirmed using tandem mass spectrometry. Ultrahigh-performance liquid chromatography mass spectrometry methods were additionally used to quantify potentially important biomarkers. Independent samples were then selected to validate the identified biomarkers. There was a clear separation between healthy controls and AD patients; AD patient samples had disordered amino acid and phospholipid metabolism and dysregulated palmitic amide. Receiver operator characteristic curve and quantification suggested that palmitic amide, lysophosphatidylcholine (LysoPC, 18:0), LysoPC(18:2), L-glutamine, and 5-L-glutamylglycine were the optimal metabolites. In addition, areas under the curve from the palmitic amide, LysoPC(18:2), and 5-L-glutamylglycine in the validation study were 0.714, 0.996, and 0.734, respectively. These data elucidate the metabolic alterations associated with AD and suggest new biomarkers for AD diagnosis, thereby permitting early intervention designed to prevent disease progression.

Early Detection Research Network (EDRN) | Division of Cancer Prevention

Cancer.gov

http://edrn.nci.nih.gov/EDRN is a collaborative network that maintains comprehensive infrastructure and resources critical to the discovery, development and validation of biomarkers for cancer risk and early detection. The program comprises a public/private sector consortium to accelerate the development of biomarkers that will change medical practice, ensure data

Biomarkers: background, classification and guidelines for applications in nutritional epidemiology

USDA-ARS?s Scientific Manuscript database

One of the main problems in nutritional epidemiology is to assess food intake as well as nutrient/food component intake to a high level of validity and reliability. To help in this process, the need to have good biomarkers that more objectively allow us to evaluate the diet consumed in a more standa...

The Biomarker-Surrogacy Evaluation Schema: a review of the biomarker-surrogate literature and a proposal for a criterion-based, quantitative, multidimensional hierarchical levels of evidence schema for evaluating the status of biomarkers as surrogate endpoints.

PubMed

Lassere, Marissa N

2008-06-01

There are clear advantages to using biomarkers and surrogate endpoints, but concerns about clinical and statistical validity and systematic methods to evaluate these aspects hinder their efficient application. Section 2 is a systematic, historical review of the biomarker-surrogate endpoint literature with special reference to the nomenclature, the systems of classification and statistical methods developed for their evaluation. In Section 3 an explicit, criterion-based, quantitative, multidimensional hierarchical levels of evidence schema - Biomarker-Surrogacy Evaluation Schema - is proposed to evaluate and co-ordinate the multiple dimensions (biological, epidemiological, statistical, clinical trial and risk-benefit evidence) of the biomarker clinical endpoint relationships. The schema systematically evaluates and ranks the surrogacy status of biomarkers and surrogate endpoints using defined levels of evidence. The schema incorporates the three independent domains: Study Design, Target Outcome and Statistical Evaluation. Each domain has items ranked from zero to five. An additional category called Penalties incorporates additional considerations of biological plausibility, risk-benefit and generalizability. The total score (0-15) determines the level of evidence, with Level 1 the strongest and Level 5 the weakest. The term ;surrogate' is restricted to markers attaining Levels 1 or 2 only. Surrogacy status of markers can then be directly compared within and across different areas of medicine to guide individual, trial-based or drug-development decisions. This schema would facilitate communication between clinical, researcher, regulatory, industry and consumer participants necessary for evaluation of the biomarker-surrogate-clinical endpoint relationship in their different settings.

A tuberculosis biomarker database: the key to novel TB diagnostics.

PubMed

Yerlikaya, Seda; Broger, Tobias; MacLean, Emily; Pai, Madhukar; Denkinger, Claudia M

2017-03-01

New diagnostic innovations for tuberculosis (TB), including point-of-care solutions, are critical to reach the goals of the End TB Strategy. However, despite decades of research, numerous reports on new biomarker candidates, and significant investment, no well-performing, simple and rapid TB diagnostic test is yet available on the market, and the search for accurate, non-DNA biomarkers remains a priority. To help overcome this 'biomarker pipeline problem', FIND and partners are working on the development of a well-curated and user-friendly TB biomarker database. The web-based database will enable the dynamic tracking of evidence surrounding biomarker candidates in relation to target product profiles (TPPs) for needed TB diagnostics. It will be able to accommodate raw datasets and facilitate the verification of promising biomarker candidates and the identification of novel biomarker combinations. As such, the database will simplify data and knowledge sharing, empower collaboration, help in the coordination of efforts and allocation of resources, streamline the verification and validation of biomarker candidates, and ultimately lead to an accelerated translation into clinically useful tools. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Is prostate-specific antigen a valid surrogate end point for survival in hormonally treated patients with metastatic prostate cancer? Joint research of the European Organisation for Research and Treatment of Cancer, the Limburgs Universitair Centrum, and AstraZeneca Pharmaceuticals.

PubMed

Collette, Laurence; Burzykowski, Tomasz; Carroll, Kevin J; Newling, Don; Morris, Tom; Schröder, Fritz H

2005-09-01

The long duration of phase III clinical trials of overall survival (OS) slows down the treatment-development process. It could be shortened by using surrogate end points. Prostate-specific antigen (PSA) is the most studied biomarker in prostate cancer (PCa). This study attempts to validate PSA end points as surrogates for OS in advanced PCa. Individual data from 2,161 advanced PCa patients treated in studies comparing bicalutamide to castration were used in a meta-analytic approach to surrogate end-point validation. PSA response, PSA normalization, time to PSA progression, and longitudinal PSA measurements were considered. The known association between PSA and OS at the individual patient level was confirmed. The association between the effect of intervention on any PSA end point and on OS was generally low (determination coefficient, < 0.69). It is a common misconception that high correlation between biomarkers and true end point justify the use of the former as surrogates. To statistically validate surrogate end points, a high correlation between the treatment effects on the surrogate and true end point needs to be established across groups of patients treated with two alternative interventions. The levels of association observed in this study indicate that the effect of hormonal treatment on OS cannot be predicted with a high degree of precision from observed treatment effects on PSA end points, and thus statistical validity is unproven. In practice, non-null treatment effects on OS can be predicted only from precisely estimated large effects on time to PSA progression (TTPP; hazard ratio, < 0.50).

Validating Biomarkers for PTSD

DTIC Science & Technology

2015-04-01

Recall Participants by Site Recruitment Site Procedure Q1 Q2 Q3 Q4 Year 1 Total NYUMC BCI * 6 5 4 6 21 Blood draw 0 8 4 4 16 Self-report 0 7 4 4...15 Brain imaging 1 8 5 0 14 NCT** 0 7 4 4 15 JJPVAMC/MMSM BCI * 2 4 6 3 15 Blood draw 1 4 4 2 11 Self-report 2 2 5 1 10 Brain imaging 1 2 2 0 5...NCT** 0 4 5 1 10 * BCI = Baseline Clinical Interview **NCT = Neurocognitive Testing Table 3. Completed Procedures for Validating Biomarkers New

Biomarkers and low risk in heart failure. Data from COACH and TRIUMPH.

PubMed

Meijers, Wouter C; de Boer, Rudolf A; van Veldhuisen, Dirk J; Jaarsma, Tiny; Hillege, Hans L; Maisel, Alan S; Di Somma, Salvatore; Voors, Adriaan A; Peacock, W Frank

2015-12-01

Traditionally, risk stratification in heart failure (HF) emphasizes assessment of high risk. We aimed to determine if biomarkers could identify patients with HF at low risk for death or HF rehospitalization. This analysis was a substudy of The Coordinating Study Evaluating Outcomes of Advising and Counselling in Heart Failure (COACH) trial. Enrolment of HF patients occurred before discharge. We defined low risk as the absence of death and/or HF rehospitalizations at 180 days. We tested a diverse group of 29 biomarkers on top of a clinical risk model, with and without N-terminal pro-B-type natriuretic peptide (NT-proBNP), and defined the low risk biomarker cut-off at the 10th percentile associated with high positive predictive value. The best performing biomarkers together with NT-proBNP and cardiac troponin I (cTnI) were re-evaluated in a validation cohort of 285 HF patients. Of 592 eligible COACH patients, the mean (± SD) age was 71 (± 11) years and median (IQR) NT-proBNP was 2521 (1301-5634) pg/mL. Logistic regression analysis showed that only galectin-3, fully adjusted, was significantly associated with the absence of events at 180 days (OR 8.1, 95% confidence interval 1.06-50.0, P = 0.039). Galectin-3, showed incremental value when added to the clinical risk model without NT-proBNP (increase in area under the curve from 0.712 to 0.745, P = 0.04). However, no biomarker showed significant improvement by net reclassification improvement on top of the clinical risk model, with or without NT-proBNP. We confirmed our results regarding galectin-3, NT-proBNP, and cTnI in the independent validation cohort. We describe the value of various biomarkers to define low risk, and demonstrate that galectin-3 identifies HF patients at (very) low risk for 30-day and 180-day mortality and HF rehospitalizations after an episode of acute HF. Such patients might be safely discharged. © 2015 The Authors European Journal of Heart Failure © 2015 European Society of Cardiolog.

Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons.

PubMed

Obuchowski, Nancy A; Reeves, Anthony P; Huang, Erich P; Wang, Xiao-Feng; Buckler, Andrew J; Kim, Hyun J Grace; Barnhart, Huiman X; Jackson, Edward F; Giger, Maryellen L; Pennello, Gene; Toledano, Alicia Y; Kalpathy-Cramer, Jayashree; Apanasovich, Tatiyana V; Kinahan, Paul E; Myers, Kyle J; Goldgof, Dmitry B; Barboriak, Daniel P; Gillies, Robert J; Schwartz, Lawrence H; Sullivan, Daniel C

2015-02-01

Quantitative biomarkers from medical images are becoming important tools for clinical diagnosis, staging, monitoring, treatment planning, and development of new therapies. While there is a rich history of the development of quantitative imaging biomarker (QIB) techniques, little attention has been paid to the validation and comparison of the computer algorithms that implement the QIB measurements. In this paper we provide a framework for QIB algorithm comparisons. We first review and compare various study designs, including designs with the true value (e.g. phantoms, digital reference images, and zero-change studies), designs with a reference standard (e.g. studies testing equivalence with a reference standard), and designs without a reference standard (e.g. agreement studies and studies of algorithm precision). The statistical methods for comparing QIB algorithms are then presented for various study types using both aggregate and disaggregate approaches. We propose a series of steps for establishing the performance of a QIB algorithm, identify limitations in the current statistical literature, and suggest future directions for research. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guo, Xuejiang; Tang, Keqi

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers wouldmore » ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode, also known as multiple reaction monitoring (MRM), is capable of quantitatively measuring hundreds of candidate protein biomarkers from a relevant clinical sample in a single analysis. The specificity, reproducibility and sensitivity could be as good as ELISA. Furthermore, SRM MS can also quantify protein isoforms and post-translational modifications, for which traditional antibody-based immunoassays often don’t exist.« less

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

PubMed

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 biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other "omics" technologies can provide added selectivity and sensitivity in preclinical drug safety testing.

Circulating microRNA-150-5p as a novel biomarker for advanced heart failure: A genome-wide prospective study.

PubMed

Scrutinio, Domenico; Conserva, Francesca; Passantino, Andrea; Iacoviello, Massimo; Lagioia, Rocco; Gesualdo, Loreto

2017-06-01

Circulating microRNAs (miRs) are promising biomarkers for heart failure (HF). Previous studies have provided inconsistent miR "signatures." The phenotypic and pathophysiologic heterogeneity of HF may have contributed to this inconsistency. In this study we assessed whether advanced HF (AHF) patients present a distinct miR signature compared with healthy subjects (HS) and mild to moderate HF (MHF) patients. The study consisted of 2 phases: a screening phase and a validation phase. In the screening phase, 752 miRs were profiled in HS and MHF and AHF patients (N = 15), using the real-time quantitative polymerase chain reaction (RT-qPCR) technique and global mean normalization. In the validation phase, the miRs found to be significantly dysregulated in AHF patients compared with both HS and MHF patients were validated in 15 HS, 25 patients with MHF and 29 with AHF, using RT-qPCR, and normalizing to exogenous (cel-miR-39) and endogenous controls. In the screening phase, 5 miRs were found to be significantly dysregulated: -26a-5p; -145-3p; -150-5p; -485-3p; and -487b-3p. In the validation phase, miR-150-5p was confirmed to be significantly downregulated in AHF patients when compared with both HS and MHF patients, irrespective of the normalization method used. miR-26a-5p was confirmed to be significantly dysregulated only when normalized to cell-miR-39. Dysregulation of the other miRs could not be confirmed. miR-150-5p was significantly associated with maladaptive remodeling, disease severity and outcome. Our data suggest miR-150-5p as a novel circulating biomarker for AHF. The association of miR-150-5p with maladaptive remodeling, disease severity and outcome supports the pathophysiologic relevance of downregulated miR-150-5p expression to AHF. Copyright © 2017 International Society for the Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.

PubMed

Liu, Rong; Guo, Cheng-Xian; Zhou, Hong-Hao

2015-01-01

This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this approach in clinical settings, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed.

A unique set of 6 circulating microRNAs for early detection of non-small cell lung cancer.

PubMed

Halvorsen, Ann Rita; Bjaanæs, Maria; LeBlanc, Marissa; Holm, Are M; Bolstad, Nils; Rubio, Luis; Peñalver, Juan Carlos; Cervera, José; Mojarrieta, Julia Cruz; López-Guerrero, Jose Antonio; Brustugun, Odd Terje; Helland, Åslaug

2016-06-14

Circulating microRNAs are promising biomarkers for diagnosis, predication and prognostication of diseases. Lung cancer is the cancer disease accountable for most cancer deaths, largely due to being diagnosed at late stages. Therefore, diagnosing lung cancer patients at an early stage is crucial for improving the outcome. The purpose of this study was to identify circulating microRNAs for detection of early stage lung cancer, capable of discriminating lung cancer patients from those with chronic obstructive pulmonary disease (COPD) and healthy volunteers. We identified 7 microRNAs separating lung cancer patients from controls. By using RT-qPCR, we validated 6 microRNAs (miR-429, miR-205, miR-200b, miR-203, miR-125b and miR-34b) with a significantly higher abundance in serum from NSCLC patients. Furthermore, the 6 miRNAs were validated in a different dataset, revealing an area under the receiver operating characteristic curve of 0.89 for stage I-IV and 0.88 for stage I/II. We profiled the expression of 754 unique microRNAs by TaqMan Low Density Arrays, and analyzed serum from 38 patients with NSCLC, 16 patients suffering from COPD and 16 healthy volunteers from Norway, to explore their potential as diagnostic biomarkers. For validation, we analyzed serum collected from high-risk individuals enrolled in the Valencia branch of the International Early Lung Cancer Action Program screening trial (n=107) in addition to 51 lung cancer patients. Considering the accessibility and stability of circulating miRNAs, these 6 microRNAs are promising biomarkers as a supplement in future screening studies.

Validation of α-Synuclein as a CSF Biomarker for Sporadic Creutzfeldt-Jakob Disease.

PubMed

Llorens, Franc; Kruse, Niels; Karch, André; Schmitz, Matthias; Zafar, Saima; Gotzmann, Nadine; Sun, Ting; Köchy, Silja; Knipper, Tobias; Cramm, Maria; Golanska, Ewa; Sikorska, Beata; Liberski, Pawel P; Sánchez-Valle, Raquel; Fischer, Andre; Mollenhauer, Brit; Zerr, Inga

2018-03-01

The analysis of cerebrospinal fluid (CSF) biomarkers gains importance in the differential diagnosis of prion diseases. However, no single diagnostic tool or combination of them can unequivocally confirm prion disease diagnosis. Electrochemiluminescence (ECL)-based immunoassays have demonstrated to achieve high diagnostic accuracy in a variety of sample types due to their high sensitivity and dynamic range. Quantification of CSF α-synuclein (a-syn) by an in-house ECL-based ELISA assay has been recently reported as an excellent approach for the diagnosis of sporadic Creutzfeldt-Jakob disease (sCJD), the most prevalent form of human prion disease. In the present study, we validated a commercially available ECL-based a-syn ELISA platform as a diagnostic test for correct classification of sCJD cases. CSF a-syn was analysed in 203 sCJD cases with definite diagnosis and in 445 non-CJD cases. We investigated reproducibility and stability of CSF a-syn and made recommendations for its analysis in the sCJD diagnostic workup. A sensitivity of 98% and a specificity of 97% were achieved when using an optimal cut-off of 820 pg/mL a-syn. Moreover, we were able to show a negative correlation between a-syn levels and disease duration suggesting that CSF a-syn may be a good prognostic marker for sCJD patients. The present study validates the use of a-syn as a CSF biomarker of sCJD and establishes the clinical and pre-analytical parameters for its use in differential diagnosis in clinical routine. Additionally, the current test presents some advantages compared to other diagnostic approaches: it is fast, economic, requires minimal amount of CSF and a-syn levels are stable along disease progression.

Development and validation of a Luminex assay for detection of a predictive biomarker for PROSTVAC-VF therapy

PubMed Central

Lucas, Julie L.; Tacheny, Erin A.; Ferris, Allison; Galusha, Michelle; Srivastava, Apurva K.; Ganguly, Aniruddha; Williams, P. Mickey; Sachs, Michael C.; Thurin, Magdalena; Tricoli, James V.; Ricker, Winnie; Gildersleeve, Jeffrey C.

2017-01-01

Cancer therapies can provide substantially improved survival in some patients while other seemingly similar patients receive little or no benefit. Strategies to identify patients likely to respond well to a given therapy could significantly improve health care outcomes by maximizing clinical benefits while reducing toxicities and adverse effects. Using a glycan microarray assay, we recently reported that pretreatment serum levels of IgM specific to blood group A trisaccharide (BG-Atri) correlate positively with overall survival of cancer patients on PROSTVAC-VF therapy. The results suggested anti-BG-Atri IgM measured prior to treatment could serve as a biomarker for identifying patients likely to benefit from PROSTVAC-VF. For continued development and clinical application of serum IgM specific to BG-Atri as a predictive biomarker, a clinical assay was needed. In this study, we developed and validated a Luminex-based clinical assay for measuring serum IgM specific to BG-Atri. IgM levels were measured with the Luminex assay and compared to levels measured using the microarray for 126 healthy individuals and 77 prostate cancer patients. This assay provided reproducible and consistent results with low %CVs, and tolerance ranges were established for the assay. IgM levels measured using the Luminex assay were found to be highly correlated to the microarray results with R values of 0.93–0.95. This assay is a Laboratory Developed Test (LDT) and is suitable for evaluating thousands of serum samples in CLIA certified laboratories that have validated the assay. In addition, the study demonstrates that discoveries made using neoglycoprotein-based microarrays can be readily migrated to a clinical assay. PMID:28771597

VALIDATION AND EVALUATION OF BIOMARKERS IN WORKERS EXPOSED TO BENZENE IN CHINA

EPA Science Inventory

Qu and colleagues recruited 181 healthy workers in several factories in the Tianjin region of China. These subjects formed part of a cohort of thousands identified by the U.S. National Cancer Institute (NCI) and the China Academy of Preventive Medicine for a study to evalua...

MEASUREMENT OF ORGANOPHOSPHATE METABOLITES IN POSTPARTUM MECONIUM AS A POTENTIAL BIOMARKER OF PRENATAL EXPOSURE: A VALIDATION STUDY. (R827027)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

USE OF PHARMACOKINETIC MODELING TO DESIGN STUDIES FOR PATHWAY-SPECIFIC EXPOSURE MODEL EVALUATION

EPA Science Inventory

Validating an exposure pathway model is difficult because the biomarker, which is often used to evaluate the model prediction, is an integrated measure for exposures from all the exposure routes/pathways. The purpose of this paper is to demonstrate a method to use pharmacokeneti...

The δ13C Value of Fingerstick Blood Is a Valid, Reliable, and Sensitive Biomarker of Sugar-Sweetened Beverage Intake in Children and Adolescents.

PubMed

MacDougall, Carly R; Hill, Catelyn E; Jahren, A Hope; Savla, Jyoti; Riebl, Shaun K; Hedrick, Valisa E; Raynor, Hollie A; Dunsmore, Julie C; Frisard, Madlyn I; Davy, Brenda M

2018-01-01

Reliance on self-reported dietary intake methods is a commonly cited research limitation, and dietary misreporting is a particular problem in children and adolescents. Objective indicators of dietary intake, such as dietary biomarkers, are needed to overcome this research limitation. The added sugar (AS) biomarker δ13C, which measures the relative abundance of 13C to 12C, has demonstrated preliminary validity in adults. The purpose of this investigation was to determine the comparative validity, test-retest reliability, and sensitivity of the δ13C biomarker to detect AS and sugar-sweetened beverage (SSB) intake using fingerstick blood samples in children and adolescents. Children (aged 6-11 y, n = 126, 56% male, mean ± SD age: 9 ± 2 y) and adolescents (aged 12-18 y, n = 200, 44% male, mean ± SD age: 15 ± 2 y) completed 4 testing sessions within a 3-wk period. Participants' height, weight, demographic characteristics, and health history were determined at the first session; 24-h recalls were obtained at each visit and fingerstick blood samples were collected at visits 1 and 3. Samples were analyzed for δ13C value using natural abundance stable isotope mass spectrometry. δ13C value was compared with dietary outcomes in the full sample, and in child and adolescent subgroups. t Tests and correlational analyses were used to assess biomarker validity and reliability, whereas logistic regression and area under the receiver-operator characteristic curve (AUC) were used to evaluate sensitivity. Reported mean ± SD AS consumption was 82.2 ± 35.8 g/d and 329 ± 143 kcal/d, and SSB consumption was 222 ± 243 mL/d and 98 ± 103 kcal/d. Mean δ13C value was -19.65 ± 0.69‰, and was lower in children than in adolescents (-19.80 ± 0.67‰ compared with -19.56 ± 0.67‰, P = 0.002). δ13C values were similar across sessions (visit 1: -19.66 ± 0.68‰; visit 3: -19.64 ± 0.68‰; r = 0.99, P < 0.001) and were associated (P < 0.001) with intake of total AS (grams, kilocalories: r = 0.29) and SSB (milliliters, kilocalories: r = 0.35). The biomarker was able to better discriminate between high and low SSB consumers than high and low AS consumers, as demonstrated by the AUC (0.75 and 0.62, respectively). The δ13C biomarker is a promising, minimally invasive, objective biomarker of SSB intake in children and adolescents. Further evaluation using controlled feeding designs is warranted. Registered at clinicaltrials.gov as NCT02455388. © 2018 American Society for Nutrition. All rights reserved.

Quantification of six potential unspecific human biomarkers of 1-vinyl-2-pyrrolidone exposure in Sprague-Dawley rat urine using gas chromatography coupled with triple mass spectrometry.

PubMed

Bertram, J; Schettgen, T; Kraus, T

2017-11-15

The monomer 1-vinyl-2-pyrrolidone (VP) is a substance with excellent solvent features. It is used in a wide variety of pharmaceutical, cosmetic, food industrial or technical applications and produced on an industrial scale. Since VP has caused adenocarcinoma of the nasal cavity and liver cell carcinoma in long-term experiments with rats, a human biomarker would be appreciated for risk assessment. A sensitive analytical electron ionization gas chromatography/tandem mass spectrometry (GC/MS/MS) method for the determination of six possible biomarkers for VP in urine was established and validated. Two isotope-labeled internal standards (ISTD) were used for quantification. A simple and easy to use freeze-drying step was performed prior to derivatization with N-tert-butyldimethylsilyl-N-methyltrifluoracetamide (MTBSTFA) and following sample extraction for cleanup purposes. A calibration curve with six calibration standards ranging from 50 μg/L to 2000 μg/L (10-fold higher for H-OPAA) in urine was prepared. Validation results were satisfactory with recoveries ranging from 88.2 to 110.2 % with two exceptions for the lowest quality control for two substances without ISTD (126.4 % and 139.3 %). Three of the substances could be identified as VP metabolites in an exposure study with Sprague-Dawley (SD) rats. A quick and easy to use method has been established for six target molecules investigated for a better understanding of the metabolism of VP. Two of three substances identified as metabolites of VP could serve as a nonspecific human biomarker for VP exposure as shown with an excerpt of an exposure study performed in SD rats. Copyright © 2017 John Wiley & Sons, Ltd.

Systemic Inflammation-Based Biomarkers and Survival in HIV-Positive Subject With Solid Cancer in an Italian Multicenter Study.

PubMed

Raffetti, Elena; Donato, Francesco; Pezzoli, Chiara; Digiambenedetto, Simona; Bandera, Alessandra; Di Pietro, Massimo; Di Filippo, Elisa; Maggiolo, Franco; Sighinolfi, Laura; Fornabaio, Chiara; Castelnuovo, Filippo; Ladisa, Nicoletta; Castelli, Francesco; Quiros Roldan, Eugenia

2015-08-15

Recently, some systemic inflammation-based biomarkers have been demonstrated useful for predicting risk of death in patients with solid cancer independently of tumor characteristics. This study aimed to investigate the prognostic role of systemic inflammation-based biomarkers in HIV-infected patients with solid tumors and to propose a risk score for mortality in these subjects. Clinical and pathological data on solid AIDS-defining cancer (ADC) and non-AIDS-defining cancer (NADC), diagnosed between 1998 and 2012 in an Italian cohort, were analyzed. To evaluate the prognostic role of systemic inflammation- and nutrition-based markers, univariate and multivariable Cox regression models were applied. To compute the risk score equation, the patients were randomly assigned to a derivation and a validation sample. A total of 573 patients (76.3% males) with a mean age of 46.2 years (SD = 10.3) were enrolled. 178 patients died during a median of 3.2 years of follow-up. For solid NADCs, elevated Glasgow Prognostic Score, modified Glasgow Prognostic Score, neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, and Prognostic Nutritional Index were independently associated with risk of death; for solid ADCs, none of these markers was associated with risk of death. For solid NADCs, we computed a mortality risk score on the basis of age at cancer diagnosis, intravenous drug use, and Prognostic Nutritional Index. The areas under the receiver operating characteristic curve were 0.67 (95% confidence interval: 0.58 to 0.75) in the derivation sample and 0.66 (95% confidence interval: 0.54 to 0.79) in the validation sample. Inflammatory biomarkers were associated with risk of death in HIV-infected patients with solid NADCs but not with ADCs.

A Microfluidic Immunostaining System Enables Quality Assured and Standardized Immunohistochemical Biomarker Analysis

NASA Astrophysics Data System (ADS)

Kwon, Seyong; Cho, Chang Hyun; Kwon, Youngmee; Lee, Eun Sook; Park, Je-Kyun

2017-04-01

Immunohistochemistry (IHC) plays an important role in biomarker-driven cancer therapy. Although there has been a high demand for standardized and quality assured IHC, it has rarely been achieved due to the complexity of IHC testing and the subjective validation-based process flow of IHC quality control. We present here a microfluidic immunostaining system for the standardization of IHC by creating a microfluidic linearly graded antibody (Ab)-staining device and a reference cell microarray. Unlike conventional efforts, our system deals primarily with the screening of biomarker staining conditions for quantitative quality assurance testing in IHC. We characterized the microfluidic matching of Ab staining intensity using three HER2 Abs produced by different manufacturers. The quality of HER2 Ab was also validated using tissues of breast cancer patients, demonstrating that our system is an efficient and powerful tool for the standardization and quality assurance of IHC.

Peptidomics of urine and other biofluids for cancer diagnostics.

PubMed

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

2014-08-01

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

Sparse representation based biomarker selection for schizophrenia with integrated analysis of fMRI and SNPs.

PubMed

Cao, Hongbao; Duan, Junbo; Lin, Dongdong; Shugart, Yin Yao; Calhoun, Vince; Wang, Yu-Ping

2014-11-15

Integrative analysis of multiple data types can take advantage of their complementary information and therefore may provide higher power to identify potential biomarkers that would be missed using individual data analysis. Due to different natures of diverse data modality, data integration is challenging. Here we address the data integration problem by developing a generalized sparse model (GSM) using weighting factors to integrate multi-modality data for biomarker selection. As an example, we applied the GSM model to a joint analysis of two types of schizophrenia data sets: 759,075 SNPs and 153,594 functional magnetic resonance imaging (fMRI) voxels in 208 subjects (92 cases/116 controls). To solve this small-sample-large-variable problem, we developed a novel sparse representation based variable selection (SRVS) algorithm, with the primary aim to identify biomarkers associated with schizophrenia. To validate the effectiveness of the selected variables, we performed multivariate classification followed by a ten-fold cross validation. We compared our proposed SRVS algorithm with an earlier sparse model based variable selection algorithm for integrated analysis. In addition, we compared with the traditional statistics method for uni-variant data analysis (Chi-squared test for SNP data and ANOVA for fMRI data). Results showed that our proposed SRVS method can identify novel biomarkers that show stronger capability in distinguishing schizophrenia patients from healthy controls. Moreover, better classification ratios were achieved using biomarkers from both types of data, suggesting the importance of integrative analysis. Copyright © 2014 Elsevier Inc. All rights reserved.

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

2014-12-05

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.

Differential proteomic and tissue expression analyses identify valuable diagnostic biomarkers of hepatocellular differentiation and hepatoid adenocarcinomas.

PubMed

Reis, Henning; Padden, Juliet; Ahrens, Maike; Pütter, Carolin; Bertram, Stefanie; Pott, Leona L; Reis, Anna-Carinna; Weber, Frank; Juntermanns, Benjamin; Hoffmann, Andreas-C; Eisenacher, Martin; Schlaak, Joörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-10-01

The exact discrimination of lesions with true hepatocellular differentiation from secondary tumours and neoplasms with hepatocellular histomorphology like hepatoid adenocarcinomas (HAC) is crucial. Therefore, we aimed to identify ancillary protein biomarkers by using complementary proteomic techniques (2D-DIGE, label-free MS). The identified candidates were immunohistochemically validated in 14 paired samples of hepatocellular carcinoma (HCC) and non-tumourous liver tissue (NT). The candidates and HepPar1/Arginase1 were afterwards tested for consistency in a large cohort of hepatocellular lesions and NT (n = 290), non-hepatocellular malignancies (n = 383) and HAC (n = 13). Eight non-redundant, differentially expressed proteins were suitable for further immunohistochemical validation and four (ABAT, BHMT, FABP1, HAOX1) for further evaluation. Sensitivity and specificity rates for HCC/HAC were as follows: HepPar1 80.2%, 94.3% / 80.2%, 46.2%; Arginase1 82%, 99.4% / 82%, 69.2%; BHMT 61.4%, 93.8% / 61.4%, 100%; ABAT 84.4%, 33.7% / 84.4%, 30.8%; FABP1 87.2%, 95% / 87.2%, 69.2%; HAOX1 95.5%, 36.3% / 95.5%, 46.2%. The best 2×/3× biomarker panels for the diagnosis of HCC consisted of Arginase1/HAOX1 and BHMT/Arginase1/HAOX1 and for HAC consisted of Arginase1/FABP1 and BHMT/Arginase1/FABP1. In summary, we successfully identified, validated and benchmarked protein biomarker candidates of hepatocellular differentiation. BHMT in particular exhibited superior diagnostic characteristics in hepatocellular lesions and specifically in HAC. BHMT is therefore a promising (panel based) biomarker candidate in the differential diagnostic process of lesions with hepatocellular aspect.

The use of multiplexed MRM for the discovery of biomarkers to differentiate iron-deficiency anemia from anemia of inflammation.

PubMed

Domanski, Dominik; Cohen Freue, Gabriela V; Sojo, Luis; Kuzyk, Michael A; Ratkay, Leslie; Parker, Carol E; Goldberg, Y Paul; Borchers, Christoph H

2012-06-27

In this study we demonstrate the use of a multiplexed MRM-based assay to distinguish among normal (NL) and iron-metabolism disorder mouse models, particularly, iron-deficiency anemia (IDA), inflammation (INFL), and inflammation and anemia (INFL+IDA). Our initial panel of potential biomarkers was based on the analysis of 14 proteins expressed by candidate genes involved in iron transport and metabolism. Based on this study, we were able to identify a panel of 8 biomarker proteins: apolipoprotein A4 (APO4), transferrin, transferrin receptor 1, ceruloplasmin, haptoglobin, lactoferrin, hemopexin, and matrix metalloproteinase-8 (MMP8) that clearly distinguish among the normal and disease models. Within this set of proteins, transferrin showed the best individual classification accuracy over all samples (72%) and within the NL group (94%). Compared to the best single-protein biomarker, transferrin, the use of the composite 8-protein biomarker panel improved the classification accuracy from 94% to 100% in the NL group, from 50% to 72% in the INFL group, from 66% to 96% in the IDA group, and from 79% to 83% in the INFL+IDA group. Based on these findings, validation of the utility of this potentially important biomarker panel in human samples in an effort to differentiate IDA, inflammation, and combinations thereof, is now warranted. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry. Copyright © 2011 Elsevier B.V. All rights reserved.

In-Depth Characterization and Validation of Human Urine Metabolomes Reveal Novel Metabolic Signatures of Lower Urinary Tract Symptoms

NASA Astrophysics Data System (ADS)

Hao, Ling; Greer, Tyler; Page, David; Shi, Yatao; Vezina, Chad M.; Macoska, Jill A.; Marker, Paul C.; Bjorling, Dale E.; Bushman, Wade; Ricke, William A.; Li, Lingjun

2016-08-01

Lower urinary tract symptoms (LUTS) are a range of irritative or obstructive symptoms that commonly afflict aging population. The diagnosis is mostly based on patient-reported symptoms, and current medication often fails to completely eliminate these symptoms. There is a pressing need for objective non-invasive approaches to measure symptoms and understand disease mechanisms. We developed an in-depth workflow combining urine metabolomics analysis and machine learning bioinformatics to characterize metabolic alterations and support objective diagnosis of LUTS. Machine learning feature selection and statistical tests were combined to identify candidate biomarkers, which were statistically validated with leave-one-patient-out cross-validation and absolutely quantified by selected reaction monitoring assay. Receiver operating characteristic analysis showed highly-accurate prediction power of candidate biomarkers to stratify patients into disease or non-diseased categories. The key metabolites and pathways may be possibly correlated with smooth muscle tone changes, increased collagen content, and inflammation, which have been identified as potential contributors to urinary dysfunction in humans and rodents. Periurethral tissue staining revealed a significant increase in collagen content and tissue stiffness in men with LUTS. Together, our study provides the first characterization and validation of LUTS urinary metabolites and pathways to support the future development of a urine-based diagnostic test for LUTS.

Crucial considerations for pipelines to validate circulating biomarkers for breast cancer.

PubMed

Ewaisha, Radwa; Gawryletz, Chelsea D; Anderson, Karen S

2016-01-01

Despite decades of progress in breast imaging, breast cancer remains the second most common cause of cancer mortality in women. The rapidly proliferative breast cancers that are associated with high relapse rates and mortality frequently present in younger women, in unscreened individuals, or in the intervals between screening mammography. Biomarkers exist for monitoring metastatic disease, such as CEA, CA27.29 and CA15-3, but there are no circulating biomarkers clinically available for early detection, prognosis, or monitoring for clinical relapse. There has been significant progress in the discovery of potential circulating biomarkers, including proteins, autoantibodies, nucleic acids, exosomes, and circulating tumor cells, but the vast majority of these biomarkers have not progressed beyond initial research discovery, and none have yet been approved for clinical use in early stage disease. Here, the authors review the crucial considerations of developing pipelines for the rapid evaluation of circulating biomarkers for breast cancer.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amacher, David E.

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 intendedmore » 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 biological fluids with varying immunoreactivity which can present bioanalytical challenges when first discovered. The potential success of these efforts is greatly enhanced by recent advances in two closely linked technologies, toxicoproteomics and targeted, quantitative mass spectrometry. This review focuses on the examination of the current status of these technologies as they relate to the discovery and development of novel preclinical biomarkers of hepatotoxicity. A critical assessment of the current literature reveals two distinct lines of safety biomarker investigation, (1) peripheral fluid biomarkers of organ toxicity and (2) tissue or cell-based toxicity signatures. Improved peripheral fluid biomarkers should allow the sensitive detection of potential organ toxicity prior to the onset of overt organ pathology. Advancements in tissue or cell-based toxicity biomarkers will provide sensitive in vitro or ex vivo screening systems based on toxicity pathway markers. An examination of the current practices in clinical pathology and the critical evaluation of some recently proposed biomarker candidates in comparison to the desired characteristics of an ideal toxicity biomarker lead this author to conclude that a combination of selected biomarkers will be more informative if not predictive of potential animal organ toxicity than any single biomarker, new or old. For the practical assessment of combinations of conventional and/or novel toxicity biomarkers in rodent and large animal preclinical species, mass spectrometry has emerged as the premier analytical tool compared to specific immunoassays or functional assays. Selected and multiple reaction monitoring mass spectrometry applications make it possible for this same basic technology to be used in the progressive stages of biomarker discovery, development, and more importantly, routine study applications without the use of specific antibody reagents. This technology combined with other 'omics' technologies can provide added selectivity and sensitivity in preclinical drug safety testing.« less

Commercialisation of Biomarker Tests for Mental Illnesses: Advances and Obstacles.

PubMed

Chan, Man K; Cooper, Jason D; Bahn, Sabine

2015-12-01

Substantial strides have been made in the field of biomarker research for mental illnesses over the past few decades. However, no US FDA-cleared blood-based biomarker tests have been translated into routine clinical practice. Here, we review the challenges associated with commercialisation of research findings and discuss how these challenges can impede scientific impact and progress. Overall evidence indicates that a lack of research funding and poor reproducibility of findings were the most important obstacles to commercialization of biomarker tests. Fraud, pre-analytical and analytical limitations, and inappropriate statistical analysis are major contributors to poor reproducibility. Increasingly, these issues are acknowledged and actions are being taken to improve data validity, raising the hope that robust biomarker tests will become available in the foreseeable future. Copyright © 2015 Elsevier Ltd. All rights reserved.

Head-to-Head Comparison and Evaluation of 92 Plasma Protein Biomarkers for Early Detection of Colorectal Cancer in a True Screening Setting.

PubMed

Chen, Hongda; Zucknick, Manuela; Werner, Simone; Knebel, Phillip; Brenner, Hermann

2015-07-15

Novel noninvasive blood-based screening tests are strongly desirable for early detection of colorectal cancer. We aimed to conduct a head-to-head comparison of the diagnostic performance of 92 plasma-based tumor-associated protein biomarkers for early detection of colorectal cancer in a true screening setting. Among all available 35 carriers of colorectal cancer and a representative sample of 54 men and women free of colorectal neoplasms recruited in a cohort of screening colonoscopy participants in 2005-2012 (N = 5,516), the plasma levels of 92 protein biomarkers were measured. ROC analyses were conducted to evaluate the diagnostic performance. A multimarker algorithm was developed through the Lasso logistic regression model and validated in an independent validation set. The .632+ bootstrap method was used to adjust for the potential overestimation of diagnostic performance. Seventeen protein markers were identified to show statistically significant differences in plasma levels between colorectal cancer cases and controls. The adjusted area under the ROC curves (AUC) of these 17 individual markers ranged from 0.55 to 0.70. An eight-marker classifier was constructed that increased the adjusted AUC to 0.77 [95% confidence interval (CI), 0.59-0.91]. When validating this algorithm in an independent validation set, the AUC was 0.76 (95% CI, 0.65-0.85), and sensitivities at cutoff levels yielding 80% and 90% specificities were 65% (95% CI, 41-80%) and 44% (95% CI, 24-72%), respectively. The identified profile of protein biomarkers could contribute to the development of a powerful multimarker blood-based test for early detection of colorectal cancer. ©2015 American Association for Cancer Research.

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

PubMed

Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

2014-09-01

Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

PubMed Central

Hartwell, Matthew J.; Özbek, Umut; Holler, Ernst; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J.; Ayuk, Francis; Efebera, Yvonne A.; Hexner, Elizabeth O.; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Chen, Yi-Bin; Devine, Steven; Jagasia, Madan; Kitko, Carrie L.; Litzow, Mark R.; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Yanik, Gregory A.; Levine, John E.; Ferrara, James L.M.

2017-01-01

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation. PMID:28194439

Application of Biomarkers in the Development of Drugs Intended for the Treatment of Osteoarthritis

PubMed Central

Kraus, Virginia Byers; Burnett, Bruce; Coindreau, Javier; Cottrell, Susan; Eyre, David; Gendreau, Michael; Gardiner, Jennifer; Garnero, Patrick; Hardin, John; Henrotin, Yves; Heinegård, Dick; Ko, Amy; Lohmander, Stefan; Matthews, Gloria; Menetski, Joseph; Moskowitz, Roland; Persiani, Stefano; Poole, Robin; Rousseau, Jean Charles; Todman, Martin

2013-01-01

Objective Osteoarthritis (OA) is a chronic and slowly progressive disease for which biomarkers may be able to provide a more rapid indication of therapeutic responses to therapy than is currently available; this could accelerate and facilitate OA drug discovery and development programs. The goal of this document is to provide a summary and guide to the application of in vitro (biochemical and other soluble) biomarkers in the development of drugs for OA and to outline and stimulate a research agenda that will further this goal. Methods The Biomarkers Working Group representing experts in the field of OA biomarker research from both academia and industry developed this consensus document between 2007–2009 at the behest of the Osteoarthritis Research Society International (OARSI FDA initiative). Results This document summarizes definitions and classification systems for biomarkers, the current outcome measures used in OA clinical trials, applications and potential utility of biomarkers for development of OA therapeutics, the current state of qualification of OA-related biomarkers, pathways for biomarker qualification, critical needs to advance the use of biomarkers for drug development, recommendations regarding practices and clinical trials, and a research agenda to advance the science of OA-related biomarkers. Conclusions Although many OA-related biomarkers are currently available they exist in various states of qualification and validation. The biomarkers that are likely to have the earliest beneficial impact on clinical trials fall into two general categories, those that will allow targeting of subjects most likely to either respond and/or progress (prognostic value) within a reasonable and manageable time frame for a clinical study (for instance within one to two years for an OA trial), and those that provide early feedback for preclinical decision-making and for trial organizers that a drug is having the desired biochemical effect. As in vitro biomarkers are increasingly investigated in the context of specific drug treatments, advances in the field can be expected that will lead to rapid expansion of the list of available biomarkers with increasing understanding of the molecular processes that they represent. PMID:21396468

Quantification of free and total desmosine and isodesmosine in human urine by liquid chromatography tandem mass spectrometry: a comparison of the surrogate-analyte and the surrogate-matrix approach for quantitation.

PubMed

Ongay, Sara; Hendriks, Gert; Hermans, Jos; van den Berge, Maarten; ten Hacken, Nick H T; van de Merbel, Nico C; Bischoff, Rainer

2014-01-24

In spite of the data suggesting the potential of urinary desmosine (DES) and isodesmosine (IDS) as biomarkers for elevated lung elastic fiber turnover, further validation in large-scale studies of COPD populations, as well as the analysis of longitudinal samples is required. Validated analytical methods that allow the accurate and precise quantification of DES and IDS in human urine are mandatory in order to properly evaluate the outcome of such clinical studies. In this work, we present the development and full validation of two methods that allow DES and IDS measurement in human urine, one for the free and one for the total (free+peptide-bound) forms. To this end we compared the two principle approaches that are used for the absolute quantification of endogenous compounds in biological samples, analysis against calibrators containing authentic analyte in surrogate matrix or containing surrogate analyte in authentic matrix. The validated methods were employed for the analysis of a small set of samples including healthy never-smokers, healthy current-smokers and COPD patients. This is the first time that the analysis of urinary free DES, free IDS, total DES, and total IDS has been fully validated and that the surrogate analyte approach has been evaluated for their quantification in biological samples. Results indicate that the presented methods have the necessary quality and level of validation to assess the potential of urinary DES and IDS levels as biomarkers for the progression of COPD and the effect of therapeutic interventions. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

Wilson, Jennifer L; Altman, Russ B

2018-02-01

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

Crowdsourcing Disease Biomarker Discovery Research: The IP4IC Study.

PubMed

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

2018-05-01

Biomarker discovery is limited by readily assessable, cost efficient human samples available in large numbers that represent the entire heterogeneity of the disease. We developed a novel, active participation crowdsourcing method to determine BP-RS (Bladder Permeability Defect Risk Score). It is based on noninvasive urinary cytokines to discriminate patients with interstitial cystitis/bladder pain syndrome who had Hunner lesions from controls and patients with interstitial cystitis/bladder pain syndrome but without Hunner lesions. We performed a national crowdsourcing study in cooperation with the Interstitial Cystitis Association. Patients answered demographic, symptom severity and urinary frequency questionnaires on a HIPAA (Health Insurance Portability and Accountability Act) compliant website. Urine samples were collected at home, stabilized with a preservative and sent to Beaumont Hospital for analysis. The expression of 3 urinary cytokines was used in a machine learning algorithm to develop BP-RS. The IP4IC study collected a total of 448 urine samples, representing 153 patients (147 females and 6 males) with interstitial cystitis/bladder pain syndrome, of whom 54 (50 females and 4 males) had Hunner lesions. A total of 159 female and 136 male controls also participated, who were age matched. A defined BP-RS was calculated to predict interstitial cystitis/bladder pain syndrome with Hunner lesions or a bladder permeability defect etiology with 89% validity. In this novel participation crowdsourcing study we obtained a large number of urine samples from 46 states, which were collected at home, shipped and stored at room temperature. Using a machine learning algorithm we developed BP-RS to quantify the risk of interstitial cystitis/bladder pain syndrome with Hunner lesions, which is indicative of a bladder permeability defect etiology. To our knowledge BP-RS is the first validated urine biomarker assay for interstitial cystitis/bladder pain syndrome and one of the first biomarker assays to be developed using crowdsourcing. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Success, Failure, and Transparency in Biomarker-Based Drug Development: A Case Study of Cholesteryl Ester Transfer Protein Inhibitors.

PubMed

Hey, Spencer Phillips; Franklin, Jessica M; Avorn, Jerry; Kesselheim, Aaron S

2017-06-01

Although biomarkers are used as surrogate measures for drug targeting and approval and are generally based on plausible biological hypotheses, some are found to not correlate well with clinical outcomes. Over-reliance on inadequately validated biomarkers in drug development can lead to harm to trial subjects and patients and to research waste. To shed greater light on the process and ethics of biomarker-based drug development, we conducted a systematic portfolio analysis of cholesterol ester transfer protein inhibitors, a drug class designed to improve lipid profiles and prevent cardiovascular events. Despite years of development, no cholesterol ester transfer protein inhibitor has yet been approved for clinical use. We searched PubMed and Clinicaltrials.gov for clinical studies of 5 known cholesterol ester transfer protein inhibitors: anacetrapib, dalcetrapib, evacetrapib, TA-8995, and torcetrapib. Published reports and registration records were extracted for patient demographic characteristics and study authors' recommendations of clinical usage or further testing. We used Accumulating Evidence and Research Organization graphing to depict the portfolio of research activities and a Poisson model to examine trends. We identified 100 studies for analysis that involved 96 944 human subjects. The data from only 41 201 (42%) of the human subjects had been presented in a published report. For the 3 discontinued cholesterol ester transfer protein inhibitors, we found a pattern of consistently positive results on lipid-modification end points followed by negative results using clinical end points. Inefficiencies and harms can arise if a biomarker hypothesis continues to drive trials despite successive failures. Regulators, research funding bodies, and public policy makers may need to play a greater role in evaluating and coordinating biomarker-driven research programs. © 2017 American Heart Association, Inc.

miR-758-3p: a blood-based biomarker that’s influence on the expression of CERP/ABCA1 may contribute to the progression of obesity to metabolic syndrome

PubMed Central

O’Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O’Driscoll, Lorraine

2018-01-01

Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p’s predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome. PMID:29507696

miR-758-3p: a blood-based biomarker that's influence on the expression of CERP/ABCA1 may contribute to the progression of obesity to metabolic syndrome.

PubMed

O'Neill, Sadhbh; Larsen, Mette Bohl; Gregersen, Søren; Hermansen, Kjeld; O'Driscoll, Lorraine

2018-02-06

Due to increasing prevalence of obesity, a simple method or methods for the diagnosis of metabolic syndrome are urgently required to reduce the risk of associated cardiovascular disease, diabetes and cancer. This study aimed to identify a miRNA biomarker that may distinguish metabolic syndrome from obesity and to investigate if such a miRNA may have functional relevance for metabolic syndrome. 52 adults with clinical obesity (n=26) or metabolic syndrome (n=26) were recruited. Plasma specimens were procured from all and were randomly designated to discovery and validation cohorts. miRNA discovery profiling was performed, using array technology, on plasma RNA. Validation was performed by quantitative polymerase chain reaction. The functional effect of miR-758-3p on its predicted target, cholesterol efflux regulatory protein/ATP-binding cassette transporter, was investigated using HepG2 liver cells. Custom miRNA profiling of 25 miRNAs in the discovery cohort found miR-758-3p to be detected in the obese cohort but undetected in the metabolic syndrome cohort. miR-758-3p was subsequently validated as a potential biomarker for metabolic syndrome by quantitative polymerase chain reaction. Bioinformatics analysis identified cholesterol efflux regulatory protein/ATP-binding cassette transporter as miR-758-3p's predicted target. Specifically, mimicking miR-758-3p in HepG2 cells suppressed cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression; conversely, inhibiting miR-758-3p increased cholesterol efflux regulatory protein/ATP-binding cassette transporter protein expression. miR-758-3p holds potential as a blood-based biomarker for distinguishing progression from obesity to metabolic syndrome and as a driver in controlling cholesterol efflux regulatory protein/ATP-binding cassette transporter expression, indicating it potential role in cholesterol control in metabolic syndrome.