Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

PubMed

Tang, Hsin-Yao; Beer, Lynn A; Barnhart, Kurt T; Speicher, David W

2011-09-02

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

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.

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers

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

Matheis, Katja A., E-mail: katja.matheis@boehringer-ingelheim.com; Com, Emmanuelle; High-Throughput Proteomics Core Facility OUEST-genopole

2011-04-15

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with 'omics' data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinicalmore » chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.« less

Neuropathological biomarker candidates in brain tumors: key issues for translational efficiency.

PubMed

Hainfellner, J A; Heinzl, H

2010-01-01

Brain tumors comprise a large spectrum of rare malignancies in children and adults that are often associated with severe neurological symptoms and fatal outcome. Neuropathological tumor typing provides both prognostic and predictive tissue information which is the basis for optimal postoperative patient management and therapy. Molecular biomarkers may extend and refine prognostic and predictive information in a brain tumor case, providing more individualized and optimized treatment options. In the recent past a few neuropathological brain tumor biomarkers have translated smoothly into clinical use whereas many candidates show protracted translation. We investigated the causes of protracted translation of candidate brain tumor biomarkers. Considering the research environment from personal, social and systemic perspectives we identified eight determinants of translational success: methodology, funding, statistics, organization, phases of research, cooperation, self-reflection, and scientific progeny. Smoothly translating biomarkers are associated with low degrees of translational complexity whereas biomarkers with protracted translation are associated with high degrees. Key issues for translational efficiency of neuropathological brain tumor biomarker research seem to be related to (i) the strict orientation to the mission of medical research, that is the improval of medical practice as primordial purpose of research, (ii) definition of research priorities according to clinical needs, and (iii) absorption of translational complexities by means of operatively beneficial standards. To this end, concrete actions should comprise adequate scientific education of young investigators, and shaping of integrative diagnostics and therapy research both on the local level and the level of influential international brain tumor research platforms.

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

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

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.

Biomarker candidates for the detection of an infectious etiology of febrile neutropenia.

PubMed

Richter, Martin E; Neugebauer, Sophie; Engelmann, Falco; Hagel, Stefan; Ludewig, Katrin; La Rosée, Paul; Sayer, Herbert G; Hochhaus, Andreas; von Lilienfeld-Toal, Marie; Bretschneider, Tom; Pausch, Christine; Engel, Christoph; Brunkhorst, Frank M; Kiehntopf, Michael

2016-04-01

Infections and subsequent septicemia are major complications in neutropenic patients with hematological malignancies. Here, we identify biomarker candidates for the early detection of an infectious origin, and monitoring of febrile neutropenia (FN). Proteome, metabolome, and conventional biomarkers from 20 patients with febrile neutropenia without proven infection (FNPI) were compared to 28 patients with proven infection, including 17 patients with bacteremia. Three peptides (mass to charge ratio 1017.4-1057.3; p-values 0.011-0.024), six proteins (mass to charge ratio 6881-17,215; p-values 0.002-0.004), and six phosphatidylcholines (p-values 0.007-0.037) were identified that differed in FNPI patients compared to patients with infection or bacteremia. Seven of these marker candidates discriminated FNPI from infection at fever onset with higher sensitivity and specificity (ROC-AUC 0.688-0.824) than conventional biomarkers i.e., procalcitonin, C-reactive protein, or interleukin-6 (ROC-AUC 0.535-0.672). In a post hoc analysis, monitoring the time course of four lysophosphatidylcholines, threonine, and tryptophan allowed for discrimination of patients with or without resolution of FN (ROC-AUC 0.648-0.919) with higher accuracy compared to conventional markers (ROC-AUC 0.514-0.871). Twenty-one promising biomarker candidates for the early detection of an infectious origin or for monitoring the course of FN were found which might overcome known shortcomings of conventional markers.

Biomarker Candidates of Chlamydophila pneumoniae Proteins and Protein Fragments Identified by Affinity-Proteomics Using FTICR-MS and LC-MS/MS

NASA Astrophysics Data System (ADS)

Susnea, Iuliana; Bunk, Sebastian; Wendel, Albrecht; Hermann, Corinna; Przybylski, Michael

2011-04-01

We report here an affinity-proteomics approach that combines 2D-gel electrophoresis and immunoblotting with high performance mass spectrometry to the identification of both full length protein antigens and antigenic fragments of Chlamydophila pneumoniae (C. pneumoniae). The present affinity-mass spectrometry approach effectively utilized high resolution FTICR mass spectrometry and LC-tandem-MS for protein identification, and enabled the identification of several new highly antigenic C. pneumoniae proteins that were not hitherto reported or previously detected only in other Chlamydia species, such as Chlamydia trachomatis. Moreover, high resolution affinity-MS provided the identification of several neo-antigenic protein fragments containing N- and C-terminal, and central domains such as fragments of the membrane protein Pmp21 and the secreted chlamydial proteasome-like factor (Cpaf), representing specific biomarker candidates.

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

PubMed Central

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

2015-01-01

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancy in the world and are characterized by poor prognosis and a low survival rate. Saliva is oral fluid with intimate contact with OSCC. Besides non-invasive, simple, and rapid to collect, saliva is a potential source of biomarkers. In this study, we build an SRM assay that targets fourteen OSCC candidate biomarker proteins, which were evaluated in a set of clinically-derived saliva samples. Using Skyline software package, we demonstrated a statistically significant higher abundance of the C1R, LCN2, SLPI, FAM49B, TAGLN2, CFB, C3, C4B, LRG1, SERPINA1 candidate biomarkers in the saliva of OSCC patients. Furthermore, our study also demonstrated that CFB, C3, C4B, SERPINA1 and LRG1 are associated with the risk of developing OSCC. Overall, this study successfully used targeted proteomics to measure in saliva a panel of biomarker candidates for OSCC. PMID:26552850

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

Identification of Candidate Biomarkers Associated with Response to Vedolizumab in Inflammatory Bowel Disease.

PubMed

Boden, Elisa K; Shows, Donna M; Chiorean, Michael V; Lord, James D

2018-01-25

Vedolizumab is an anti-α4β7 monoclonal antibody approved for the treatment of inflammatory bowel disease (IBD). This exploratory study aimed to identify biomarkers associated with vedolizumab response. Twenty-six IBD patients (15 with Crohn's, 11 with ulcerative or indeterminate colitis) initiating vedolizumab at a single center between 2014 and 2016 underwent sampling of serum and peripheral blood mononuclear cells (PBMCs) before and during vedolizumab therapy. Response was defined as steroid-free improvement in endoscopic score or Harvey-Bradshaw index/simple clinical colitis activity index (reduction greater than 3 or total less than 3). PBMCs were evaluated for immunophenotype and expression of α4β7 integrin on lymphocytes before and during vedolizumab therapy. Serum vedolizumab levels and α4β7 saturation were measured serially after induction. Fourteen out of 26 (54%) patients treated with vedolizumab responded to therapy. Pretreatment α4β7 expression was higher in responders on multiple subsets of T, B, and NK cells, with terminal effector memory (p = .0009 for CD4 and .0043 for CD8) and NK cells (p = .0047) best discriminating between responders and nonresponders. During therapy, log 10 serum vedolizumab levels at trough were higher in responders than nonresponders (p = .0007). Conversely, the percentage of effector memory T cells with free α4β7 at trough was lower in responders than nonresponders (p < .0001). However, loss of α4β7 saturation with vedolizumab was more sensitive to low serum vedolizumab in nonresponders. Pretreatment α4β7 expression and α4β7 receptor saturation during maintenance therapy were identified as candidate biomarkers for vedolizumab response.

Newborn screening for autism: in search of candidate biomarkers

PubMed Central

Mizejewski, Gerald J; Lindau-Shepard, Barbara; Pass, Kenneth A

2013-01-01

Background Autism spectrum disorder (ASD) represents a wide range of neurodevelopmental disorders characterized by impairments in social interaction, language, communication and range of interests. Autism is usually diagnosed in children 3–5 years of age using behavioral characteristics; thus, diagnosis shortly after birth would be beneficial for early initiation of treatment. Aim This retrospective study sought to identify newborns at risk for ASD utilizing bloodspot specimens in an immunoassay. Materials & methods The present study utilized stored frozen specimens from ASD children already diagnosed at 15–36 months of age. The newborn specimens and controls were analyzed by immunoassay in a multiplex system that included 90 serum biomarkers and subjected to statisical analysis. Results Three sets of five biomarkers associated with ASD were found that differed from control groups. The 15 candidate biomarkers were then discussed regarding their association with ASD. Conclusion This study determined that a statistically selected panel of 15 biomarkers successfully discriminated presumptive newborns at risk for ASD from those of nonaffected controls. PMID:23547820

Methodology and Applications of Disease Biomarker Identification in Human Serum

PubMed Central

Sahab, Ziad J.; Semaan, Suzan M.; Sang, Qing-Xiang Amy

2007-01-01

Biomarkers are biomolecules that serve as indicators of biological and pathological processes, or physiological and pharmacological responses to a drug treatment. Because of the high abundance of albumin and heterogeneity of plasma lipoproteins and glycoproteins, biomarkers are difficult to identify in human serum. Due to the clinical significance the identification of disease biomarkers in serum holds great promise for personalized medicine, especially for disease diagnosis and prognosis. This review summarizes some common and emerging proteomics techniques utilized in the separation of serum samples and identification of disease signatures. The practical application of each protein separation or identification technique is analyzed using specific examples. Biomarkers of cancers of prostate, breast, ovary, and lung in human serum have been reviewed, as well as those of heart disease, arthritis, asthma, and cystic fibrosis. Despite the advancement of technology few biomarkers have been approved by the Food and Drug Administration for disease diagnosis and prognosis due to the complexity of structure and function of protein biomarkers and lack of high sensitivity, specificity, and reproducibility for those putative biomarkers. The combination of different types of technologies and statistical analysis may provide more effective methods to identify and validate new disease biomarkers in blood. PMID:19662190

Proteomic Candidate Biomarkers of Drug-Induced Nephrotoxicity in the Rat

PubMed Central

Rouse, Rodney; Siwy, Justyna; Mullen, William; Mischak, Harald; Metzger, Jochen; Hanig, Joseph

2012-01-01

Improved biomarkers of acute nephrotoxicity are coveted by the drug development industry, regulatory agencies, and clinicians. In an effort to identify such biomarkers, urinary peptide profiles of rats treated with two different nephrotoxins were investigated. 493 marker candidates were defined that showed a significant response to cis-platin comparing a cis-platin treated cohort to controls. Next, urine samples from rats that received three consecutive daily doses of 150 or 300 mg/kg gentamicin were examined. 557 potential biomarkers were initially identified; 108 of these gentamicin-response markers showed a clear temporal response to treatment. 39 of the cisplatin-response markers also displayed a clear response to gentamicin. Of the combined 147 peptides, 101 were similarly regulated by gentamicin or cis-platin and 54 could be identified by tandem mass spectrometry. Most were collagen type I and type III fragments up-regulated in response to gentamicin treatment. Based on these peptides, classification models were generated and validated in a longitudinal study. In agreement with histopathology, the observed changes in classification scores were transient, initiated after the first dose, and generally persistent over a period of 10–20 days before returning to control levels. The data support the hypothesis that gentamicin-induced renal toxicity up-regulates protease activity, resulting in an increase in several specific urinary collagen fragments. Urinary proteomic biomarkers identified here, especially those common to both nephrotoxins, may serve as a valuable tool to investigate potential new drug candidates for the risk of nephrotoxicity. PMID:22509332

Biomarkers in DILI: One More Step Forward

PubMed Central

Robles-Díaz, Mercedes; Medina-Caliz, Inmaculada; Stephens, Camilla; Andrade, Raúl J.; Lucena, M. Isabel

2016-01-01

Despite being relatively rare, drug-induced liver injury (DILI) is a serious condition, both for the individual patient due to the risk of acute liver failure, and for the drug development industry and regulatory agencies due to associations with drug development attritions, black box warnings, and postmarketing withdrawals. A major limitation in DILI diagnosis and prediction is the current lack of specific biomarkers. Despite refined usage of traditional liver biomarkers in DILI, reliable disease outcome predictions are still difficult to make. These limitations have driven the growing interest in developing new more sensitive and specific DILI biomarkers, which can improve early DILI prediction, diagnosis, and course of action. Several promising DILI biomarker candidates have been discovered to date, including mechanistic-based biomarker candidates such as glutamate dehydrogenase, high-mobility group box 1 protein and keratin-18, which can also provide information on the injury mechanism of different causative agents. Furthermore, microRNAs have received much attention lately as potential non-invasive DILI biomarker candidates, in particular miR-122. Advances in “omics” technologies offer a new approach for biomarker exploration studies. The ability to screen a large number of molecules (e.g., metabolites, proteins, or DNA) simultaneously enables the identification of ‘toxicity signatures,’ which may be used to enhance preclinical safety assessments and disease diagnostics. Omics-based studies can also provide information on the underlying mechanisms of distinct forms of DILI that may further facilitate the identification of early diagnostic biomarkers and safer implementation of personalized medicine. In this review, we summarize recent advances in the area of DILI biomarker studies. PMID:27597831

Candidate-based proteomics in the search for biomarkers of cardiovascular disease

PubMed Central

Anderson, Leigh

2005-01-01

The key concept of proteomics (looking at many proteins at once) opens new avenues in the search for clinically useful biomarkers of disease, treatment response and ageing. As the number of proteins that can be detected in plasma or serum (the primary clinical diagnostic samples) increases towards 1000, a paradoxical decline has occurred in the number of new protein markers approved for diagnostic use in clinical laboratories. This review explores the limitations of current proteomics protein discovery platforms, and proposes an alternative approach, applicable to a range of biological/physiological problems, in which quantitative mass spectrometric methods developed for analytical chemistry are employed to measure limited sets of candidate markers in large sets of clinical samples. A set of 177 candidate biomarker proteins with reported associations to cardiovascular disease and stroke are presented as a starting point for such a ‘directed proteomics’ approach. PMID:15611012

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.

Automated analysis of immunohistochemistry images identifies candidate location biomarkers for cancers.

PubMed

Kumar, Aparna; Rao, Arvind; Bhavani, Santosh; Newberg, Justin Y; Murphy, Robert F

2014-12-23

Molecular biomarkers are changes measured in biological samples that reflect disease states. Such markers can help clinicians identify types of cancer or stages of progression, and they can guide in tailoring specific therapies. Many efforts to identify biomarkers consider genes that mutate between normal and cancerous tissues or changes in protein or RNA expression levels. Here we define location biomarkers, proteins that undergo changes in subcellular location that are indicative of disease. To discover such biomarkers, we have developed an automated pipeline to compare the subcellular location of proteins between two sets of immunohistochemistry images. We used the pipeline to compare images of healthy and tumor tissue from the Human Protein Atlas, ranking hundreds of proteins in breast, liver, prostate, and bladder based on how much their location was estimated to have changed. The performance of the system was evaluated by determining whether proteins previously known to change location in tumors were ranked highly. We present a number of candidate location biomarkers for each tissue, and identify biochemical pathways that are enriched in proteins that change location. The analysis technology is anticipated to be useful not only for discovering new location biomarkers but also for enabling automated analysis of biomarker distributions as an aid to determining diagnosis.

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.

Identification of multiple novel protein biomarkers shed by human serous ovarian tumors into the blood of immunocompromised mice and verified in patient sera.

PubMed

Beer, Lynn A; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L; Zhang, Rugang; Liu, Qin; Speicher, David W

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples.

Identification of Multiple Novel Protein Biomarkers Shed by Human Serous Ovarian Tumors into the Blood of Immunocompromised Mice and Verified in Patient Sera

PubMed Central

Beer, Lynn A.; Wang, Huan; Tang, Hsin-Yao; Cao, Zhijun; Chang-Wong, Tony; Tanyi, Janos L.; Zhang, Rugang; Liu, Qin; Speicher, David W.

2013-01-01

The most cancer-specific biomarkers in blood are likely to be proteins shed directly by the tumor rather than less specific inflammatory or other host responses. The use of xenograft mouse models together with in-depth proteome analysis for identification of human proteins in the mouse blood is an under-utilized strategy that can clearly identify proteins shed by the tumor. In the current study, 268 human proteins shed into mouse blood from human OVCAR-3 serous tumors were identified based upon human vs. mouse species differences using a four-dimensional plasma proteome fractionation strategy. A multi-step prioritization and verification strategy was subsequently developed to efficiently select some of the most promising biomarkers from this large number of candidates. A key step was parallel analysis of human proteins detected in the tumor supernatant, because substantially greater sequence coverage for many of the human proteins initially detected in the xenograft mouse plasma confirmed assignments as tumor-derived human proteins. Verification of candidate biomarkers in patient sera was facilitated by in-depth, label-free quantitative comparisons of serum pools from patients with ovarian cancer and benign ovarian tumors. The only proteins that advanced to multiple reaction monitoring (MRM) assay development were those that exhibited increases in ovarian cancer patients compared with benign tumor controls. MRM assays were facilely developed for all 11 novel biomarker candidates selected by this process and analysis of larger pools of patient sera suggested that all 11 proteins are promising candidate biomarkers that should be further evaluated on individual patient blood samples. PMID:23544127

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2016-10-18

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

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G; Ward, David C; Bray-Ward, Patricia

2015-03-10

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

Identification of cancer protein biomarkers using proteomic techniques

DOEpatents

Mor, Gil G.; Ward, David C.; Bray-Ward, Patricia

2010-02-23

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

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

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

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

2008-09-01

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

47 CFR 73.4190 - Political candidate authorization notice and sponsorship identification.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 4 2010-10-01 2010-10-01 false Political candidate authorization notice and sponsorship identification. 73.4190 Section 73.4190 Telecommunication FEDERAL COMMUNICATIONS COMMISSION....4190 Political candidate authorization notice and sponsorship identification. (a) See Joint Public...

Practical analytical approach for the identification of biomarker candidates in prediabetic state based upon metabonomic study by ultraperformance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry.

PubMed

Tsutsui, Haruhito; Maeda, Toshio; Toyo'oka, Toshimasa; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki

2010-08-06

The number of diabetic patients has recently been increasing worldwide. Thus, the discovery of potential diabetic biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, is strongly required. The diagnosis of the prediabetic state in humans is a very difficult issue because of the lifestyle differences in each person and ethical consideration. Upon the basis of these considerations, animal experiments using ddY strain mice (ddY-H), which undergo naturally occurring diabetes along with age, were carried out in this study. Biomarker discovery based upon a metabonome study is now quite common, the same as that in the proteome analysis. Reversed-phase liquid chromatography-mass spectrometry (LC-MS) has mainly been used for the extensive analysis of low-molecular mass compounds including metabolites. The metabolites in the plasma of diabetic mice (ddY-H) and normal mice (ddY-L) were exhaustively separated and detected by ultraperformance liquid chromatography along with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS) using T3-C18 and HS-F5 columns. The biomarker candidates related to diabetes mellitus were extracted from the metabolite profiling of ddY-H and ddY-L at 5, 9 13, and 20 weeks old using a multivariate statistical analysis such as orthogonal partial least-squares-discriminant analysis (OPLS-DA). Various metabolites and unknown compounds were detected as biomarker candidates related to diabetic mellitus. Furthermore, the concentration of several metabolites on Lysine biosynthesis and Lysine degradation pathways were remarkably changed between the 9-week old ddY-H and ddY-L mice. Because a couple of biomarker candidates related to the prediabetic state were identified using the present approach, the metabolite profiling study could be helpful for understanding the abnormal state of various diseases.

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms.

PubMed

Le-Niculescu, H; Balaraman, Y; Patel, S D; Ayalew, M; Gupta, J; Kuczenski, R; Shekhar, A; Schork, N; Geyer, M A; Niculescu, A B

2011-05-24

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the

Candidate Proteins, Metabolites and Transcripts in the Biomarkers for Spinal Muscular Atrophy (BforSMA) Clinical Study

PubMed Central

Finkel, Richard S.; Crawford, Thomas O.; Swoboda, Kathryn J.; Kaufmann, Petra; Juhasz, Peter; Li, Xiaohong; Guo, Yu; Li, Rebecca H.; Trachtenberg, Felicia; Forrest, Suzanne J.; Kobayashi, Dione T.; Chen, Karen S.; Joyce, Cynthia L.; Plasterer, Thomas

2012-01-01

Background Spinal Muscular Atrophy (SMA) is a neurodegenerative motor neuron disorder resulting from a homozygous mutation of the survival of motor neuron 1 (SMN1) gene. The gene product, SMN protein, functions in RNA biosynthesis in all tissues. In humans, a nearly identical gene, SMN2, rescues an otherwise lethal phenotype by producing a small amount of full-length SMN protein. SMN2 copy number inversely correlates with disease severity. Identifying other novel biomarkers could inform clinical trial design and identify novel therapeutic targets. Objective: To identify novel candidate biomarkers associated with disease severity in SMA using unbiased proteomic, metabolomic and transcriptomic approaches. Materials and Methods: A cross-sectional single evaluation was performed in 108 children with genetically confirmed SMA, aged 2–12 years, manifesting a broad range of disease severity and selected to distinguish factors associated with SMA type and present functional ability independent of age. Blood and urine specimens from these and 22 age-matched healthy controls were interrogated using proteomic, metabolomic and transcriptomic discovery platforms. Analyte associations were evaluated against a primary measure of disease severity, the Modified Hammersmith Functional Motor Scale (MHFMS) and to a number of secondary clinical measures. Results A total of 200 candidate biomarkers correlate with MHFMS scores: 97 plasma proteins, 59 plasma metabolites (9 amino acids, 10 free fatty acids, 12 lipids and 28 GC/MS metabolites) and 44 urine metabolites. No transcripts correlated with MHFMS. Discussion In this cross-sectional study, “BforSMA” (Biomarkers for SMA), candidate protein and metabolite markers were identified. No transcript biomarker candidates were identified. Additional mining of this rich dataset may yield important insights into relevant SMA-related pathophysiology and biological network associations. Additional prospective studies are needed to confirm

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

USDA-ARS?s Scientific Manuscript database

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

Identification of candidate diagnostic serum biomarkers for Kawasaki disease using proteomic analysis

PubMed Central

Kimura, Yayoi; Yanagimachi, Masakatsu; Ino, Yoko; Aketagawa, Mao; Matsuo, Michie; Okayama, Akiko; Shimizu, Hiroyuki; Oba, Kunihiro; Morioka, Ichiro; Imagawa, Tomoyuki; Kaneko, Tetsuji; Yokota, Shumpei; Hirano, Hisashi; Mori, Masaaki

2017-01-01

Kawasaki disease (KD) is a systemic vasculitis and childhood febrile disease that can lead to cardiovascular complications. The diagnosis of KD depends on its clinical features, and thus it is sometimes difficult to make a definitive diagnosis. In order to identify diagnostic serum biomarkers for KD, we explored serum KD-related proteins, which differentially expressed during the acute and recovery phases of two patients by mass spectrometry (MS). We identified a total of 1,879 proteins by MS-based proteomic analysis. The levels of three of these proteins, namely lipopolysaccharide-binding protein (LBP), leucine-rich alpha-2-glycoprotein (LRG1), and angiotensinogen (AGT), were higher in acute phase patients. In contrast, the level of retinol-binding protein 4 (RBP4) was decreased. To confirm the usefulness of these proteins as biomarkers, we analyzed a total of 270 samples, including those collected from 55 patients with acute phase KD, by using western blot analysis and microarray enzyme-linked immunosorbent assays (ELISAs). Over the course of this experiment, we determined that the expression level of these proteins changes specifically in the acute phase of KD, rather than the recovery phase of KD or other febrile illness. Thus, LRG1 could be used as biomarkers to facilitate KD diagnosis based on clinical features. PMID:28262744

Global Cell Proteome Profiling, Phospho-signaling and Quantitative 
Proteomics for Identification of New Biomarkers in Acute Myeloid 
Leukemia Patients

PubMed Central

Aasebø, Elise; Forthun, Rakel B.; Berven, Frode; Selheim, Frode; Hernandez-Valladares, Maria

2016-01-01

The identification of protein biomarkers for acute myeloid leukemia (AML) that could find applications in AML diagnosis and prognosis, treatment and the selection for bone marrow transplant requires substantial comparative analyses of the proteomes from AML patients. In the past years, several studies have suggested some biomarkers for AML diagnosis or AML classification using methods for sample preparation with low proteome coverage and low resolution mass spectrometers. However, most of the studies did not follow up, confirm or validate their candidates with more patient samples. Current proteomics methods, new high resolution and fast mass spectrometers allow the identification and quantification of several thousands of proteins obtained from few tens of μg of AML cell lysate. Enrichment methods for posttranslational modifications (PTM), such as phosphorylation, can isolate several thousands of site-specific phosphorylated peptides from AML patient samples, which subsequently can be quantified with high confidence in new mass spectrometers. While recent reports aiming to propose proteomic or phosphoproteomic biomarkers on the studied AML patient samples have taken advantage of the technological progress, the access to large cohorts of AML patients to sample from and the availability of appropriate control samples still remain challenging. PMID:26306748

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.

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry — Technical and Statistical Considerations during Initial Discovery

PubMed Central

Orton, Dennis J.; Doucette, Alan A.

2013-01-01

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification. PMID:28250400

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

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

Duijvesz, Diederick; Burnum-Johnson, Kristin E.; Gritsenko, Marina A.

Introduction: Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, biomarker discovery from body fluids is often hampered by the high abundance of many proteins unrelated to disease. An attractive alternative biomarker discovery approach is the isolation of small vesicles (exosomes, ~100 nm). They contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific marker discovery. Profiling prostate cancer-derived exosomes could reveal new markers for this malignancy. Materials and Methods: Exosomes were isolated from 2 immortalized primary prostate epithelial cellsmore » (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. Proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode, followed by the Accurate Mass and Time (AMT) tag approach. Exosomal proteins were validated by Western blotting. A Tissue Micro Array, containing 481 different PCa samples (radical prostatectomy), was used to correlate candidate markers with several clinical-pathological parameters such as PSA, Gleason score, biochemical recurrence, and (PCa-related) death. Results: Proteomic characterization resulted in the identification of 263 proteins by at least 2 peptides. Specifically analysis of exosomes from PNT2C2, RWPE-1, PC346C, and VCaP identified 248, 233, 169, and 216 proteins, respectively. Statistical analyses revealed 52 proteins differently expressed between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. The Tissue Micro 4 Array showed strong correlation of higher Gleason scores and local recurrence with increased cytoplasmic XPO1 (P<0.001). Conclusions: Differentially abundant proteins of cell line-derived exosomes make a clear subdivision

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children.

PubMed

Wong, Hector R; Cvijanovich, Natalie Z; Hall, Mark; Allen, Geoffrey L; Thomas, Neal J; Freishtat, Robert J; Anas, Nick; Meyer, Keith; Checchia, Paul A; Lin, Richard; Bigham, Michael T; Sen, Anita; Nowak, Jeffrey; Quasney, Michael; Henricksen, Jared W; Chopra, Arun; Banschbach, Sharon; Beckman, Eileen; Harmon, Kelli; Lahni, Patrick; Shanley, Thomas P

2012-10-29

Differentiating between sterile inflammation and bacterial infection in critically ill patients with fever and other signs of the systemic inflammatory response syndrome (SIRS) remains a clinical challenge. The objective of our study was to mine an existing genome-wide expression database for the discovery of candidate diagnostic biomarkers to predict the presence of bacterial infection in critically ill children. Genome-wide expression data were compared between patients with SIRS having negative bacterial cultures (n = 21) and patients with sepsis having positive bacterial cultures (n = 60). Differentially expressed genes were subjected to a leave-one-out cross-validation (LOOCV) procedure to predict SIRS or sepsis classes. Serum concentrations of interleukin-27 (IL-27) and procalcitonin (PCT) were compared between 101 patients with SIRS and 130 patients with sepsis. All data represent the first 24 hours of meeting criteria for either SIRS or sepsis. Two hundred twenty one gene probes were differentially regulated between patients with SIRS and patients with sepsis. The LOOCV procedure correctly predicted 86% of the SIRS and sepsis classes, and Epstein-Barr virus-induced gene 3 (EBI3) had the highest predictive strength. Computer-assisted image analyses of gene-expression mosaics were able to predict infection with a specificity of 90% and a positive predictive value of 94%. Because EBI3 is a subunit of the heterodimeric cytokine, IL-27, we tested the ability of serum IL-27 protein concentrations to predict infection. At a cut-point value of ≥5 ng/ml, serum IL-27 protein concentrations predicted infection with a specificity and a positive predictive value of >90%, and the overall performance of IL-27 was generally better than that of PCT. A decision tree combining IL-27 and PCT improved overall predictive capacity compared with that of either biomarker alone. Genome-wide expression analysis has provided the foundation for the identification of IL-27 as a novel

Interleukin-27 is a novel candidate diagnostic biomarker for bacterial infection in critically ill children

PubMed Central

2012-01-01

for the identification of IL-27 as a novel candidate diagnostic biomarker for predicting bacterial infection in critically ill children. Additional studies will be required to test further the diagnostic performance of IL-27. The microarray data reported in this article have been deposited in the Gene Expression Omnibus under accession number GSE4607. PMID:23107287

Rapid Characterization of Candidate Biomarkers for Pancreatic Cancer Using Cell Microarrays (CMAs)

PubMed Central

Kim, Min-Sik; Kuppireddy, Sarada V.; Sakamuri, Sruthi; Singal, Mukul; Getnet, Derese; Harsha, H. C.; Goel, Renu; Balakrishnan, Lavanya; Jacob, Harrys K. C.; Kashyap, Manoj K.; Tankala, Shantal G.; Maitra, Anirban; Iacobuzio-Donahue, Christine A.; Jaffee, Elizabeth; Goggins, Michael G.; Velculescu, Victor E.; Hruban, Ralph H.; Pandey, Akhilesh

2013-01-01

Tissue microarrays have become a valuable tool for high-throughput analysis using immunohistochemical labeling. However, the large majority of biochemical studies are carried out in cell lines to further characterize candidate biomarkers or therapeutic targets with subsequent studies in animals or using primary tissues. Thus, cell line-based microarrays could be a useful screening tool in some situations. Here, we constructed a cell microarray (CMA) containing a panel of 40 pancreatic cancer cell lines available from American Type Culture Collection in addition to those locally available at Johns Hopkins. As proof of principle, we performed immunocytochemical labeling of an epithelial cell adhesion molecule (Ep-CAM), a molecule generally expressed in the epithelium, on this pancreatic cancer CMA. In addition, selected molecules that have been previously shown to be differentially expressed in pancreatic cancer in the literature were validated. For example, we observed strong labeling of CA19-9 antigen, a prognostic and predictive marker for pancreatic cancer. We also carried out a bioinformatics analysis of a literature curated catalog of pancreatic cancer biomarkers developed previously by our group and identified two candidate biomarkers, HLA class I and transmembrane protease, serine 4 (TMPRSS4), and examined their expression in the cell lines represented on the pancreatic cancer CMAs. Our results demonstrate the utility of CMAs as a useful resource for rapid screening of molecules of interest and suggest that CMAs can become a universal standard platform in cancer research. PMID:22985314

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

PubMed

Moon, Myungjin; Nakai, Kenta

2018-04-01

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

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

Clinical Neuropathology practice news 2-2014: ATRX, a new candidate biomarker in gliomas.

PubMed

Haberler, Christine; Wöhrer, Adelheid

2014-01-01

Genome-wide molecular approaches have substantially elucidated molecular alterations and pathways involved in the oncogenesis of brain tumors. In gliomas, several molecular biomarkers including IDH mutation, 1p/19q co-deletion, and MGMT promotor methylation status have been introduced into neuropathological practice. Recently, mutations of the ATRX gene have been found in various subtypes and grades of gliomas and were shown to refine the prognosis of malignant gliomas in combination with IDH and 1p/19q status. Mutations of ATRX are associated with loss of nuclear ATRX protein expression, detectable by a commercially available antibody, thus turning ATRX into a promising prognostic candidate biomarker in the routine neuropathological setting.

Large-Scale SRM Screen of Urothelial Bladder Cancer Candidate Biomarkers in Urine.

PubMed

Duriez, Elodie; Masselon, Christophe D; Mesmin, Cédric; Court, Magali; Demeure, Kevin; Allory, Yves; Malats, Núria; Matondo, Mariette; Radvanyi, François; Garin, Jérôme; Domon, Bruno

2017-04-07

Urothelial bladder cancer is a condition associated with high recurrence and substantial morbidity and mortality. Noninvasive urinary tests that would detect bladder cancer and tumor recurrence are required to significantly improve patient care. Over the past decade, numerous bladder cancer candidate biomarkers have been identified in the context of extensive proteomics or transcriptomics studies. To translate these findings in clinically useful biomarkers, the systematic evaluation of these candidates remains the bottleneck. Such evaluation involves large-scale quantitative LC-SRM (liquid chromatography-selected reaction monitoring) measurements, targeting hundreds of signature peptides by monitoring thousands of transitions in a single analysis. The design of highly multiplexed SRM analyses is driven by several factors: throughput, robustness, selectivity and sensitivity. Because of the complexity of the samples to be analyzed, some measurements (transitions) can be interfered by coeluting isobaric species resulting in biased or inconsistent estimated peptide/protein levels. Thus the assessment of the quality of SRM data is critical to allow flagging these inconsistent data. We describe an efficient and robust method to process large SRM data sets, including the processing of the raw data, the detection of low-quality measurements, the normalization of the signals for each protein, and the estimation of protein levels. Using this methodology, a variety of proteins previously associated with bladder cancer have been assessed through the analysis of urine samples from a large cohort of cancer patients and corresponding controls in an effort to establish a priority list of most promising candidates to guide subsequent clinical validation studies.

A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma.

PubMed

Percy, Andrew J; Mohammed, Yassene; Yang, Juncong; Borchers, Christoph H

2015-12-01

An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this 'absolute' quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. The assembled biomarker assessment kit - the 'BAK-76' - contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

A novel quantification-driven proteomic strategy identifies an endogenous peptide of pleiotrophin as a new biomarker of Alzheimer's disease.

PubMed

Skillbäck, Tobias; Mattsson, Niklas; Hansson, Karl; Mirgorodskaya, Ekaterina; Dahlén, Rahil; van der Flier, Wiesje; Scheltens, Philip; Duits, Floor; Hansson, Oskar; Teunissen, Charlotte; Blennow, Kaj; Zetterberg, Henrik; Gobom, Johan

2017-10-17

We present a new, quantification-driven proteomic approach to identifying biomarkers. In contrast to the identification-driven approach, limited in scope to peptides that are identified by database searching in the first step, all MS data are considered to select biomarker candidates. The endopeptidome of cerebrospinal fluid from 40 Alzheimer's disease (AD) patients, 40 subjects with mild cognitive impairment, and 40 controls with subjective cognitive decline was analyzed using multiplex isobaric labeling. Spectral clustering was used to match MS/MS spectra. The top biomarker candidate cluster (215% higher in AD compared to controls, area under ROC curve = 0.96) was identified as a fragment of pleiotrophin located near the protein's C-terminus. Analysis of another cohort (n = 60 over four clinical groups) verified that the biomarker was increased in AD patients while no change in controls, Parkinson's disease or progressive supranuclear palsy was observed. The identification of the novel biomarker pleiotrophin 151-166 demonstrates that our quantification-driven proteomic approach is a promising method for biomarker discovery, which may be universally applicable in clinical proteomics.

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 identification of potential biomarkers of pediatric Acute Lymphoblastic Leukemia

PubMed Central

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

2009-01-01

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

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

PubMed

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

2012-09-18

Aberrantly glycosylated proteins related to liver cancer progression were captured with specific lectin and identified from human plasma by multiple reaction monitoring (MRM) mass spectrometry as multiple biomarkers for hepatocellular carcinoma (HCC). The lectin fractionation for fucosylated protein glycoforms in human plasma was conducted with a fucose-specific aleuria aurantia lectin (AAL). Following tryptic digestion of the lectin-captured fraction, plasma samples from 30 control cases (including 10 healthy, 10 hepatitis B virus [HBV], and 10 cirrhosis cases) and 10 HCC cases were quantitatively analyzed by MRM to identify which glycoproteins are viable HCC biomarkers. A1AG1, AACT, A1AT, and CERU were found to be potent biomarkers to differentiate HCC plasma from control plasmas. The AUROC generated independently from these four biomarker candidates ranged from 0.73 to 0.92. However, the lectin-coupled MRM assay with multiple combinations of biomarker candidates is superior statistically to those generated from the individual candidates with AUROC more than 0.95, which can be an alternative to the immunoassay inevitably requiring tedious development of multiple antibodies against biomarker candidates to be verified. Eventually the lectin-coupled, targeted proteomic mass spectrometry (MRM MS) platform was found to be efficient to identify multiple biomarkers from human plasma according to cancer progression. Copyright © 2012 Elsevier B.V. All rights reserved.

Identifying Exosome-Derived MicroRNAs as Candidate Biomarkers of Frailty.

PubMed

Ipson, B R; Fletcher, M B; Espinoza, S E; Fisher, A L

2018-01-01

Frailty is a geriatric syndrome associated with progressive physical decline and significantly increases risk for falls, disability, hospitalizations, and death. However, much remains unknown regarding the biological mechanisms that contribute to aging and frailty, and to date, there are no clinically used prognostic or diagnostic molecular biomarkers. The present study profiled exosome-derived microRNAs isolated from the plasma of young, robust older, and frail older individuals and identified eight miRNAs that are uniquely enriched in frailty: miR-10a-3p, miR-92a-3p, miR-185-3p, miR-194-5p, miR-326, miR-532-5p, miR-576-5p, and miR-760. Furthermore, since exosomes can deliver miRNAs to alter cellular activity and behavior, these miRNAs may also provide insights into the biological mechanisms underlying frailty; KEGG analysis of their target genes revealed multiple pathways implicated in aging and age-related processes. Although further validation and research studies are warranted, our study identified eight novel candidate biomarkers of frailty that may help to elucidate the multifactorial pathogenesis of frailty.

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

Toxicogenomic identification of biomarkers of acute respiratory exposure sensitizing agents

EPA Science Inventory

Allergy induction requires multiple exposures to an agent. Therefore the development of high-throughput or in vitro assays for effective screening of potential sensitizers will require the identification of biomarkers. The goal of this preliminary study was to identify potential ...

Identification and Quantification of Preterm Birth Biomarkers in Human Cervicovaginal Fluid by Liquid Chromatography/Tandem Mass Spectrometry

PubMed Central

Shah, Sumit J.; Yu, Kenneth H.; Sangar, Vineet; Parry, Samuel I.; Blair, Ian A.

2009-01-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain < 0.5 % of the endogenous unlabeled forms. Identified proteins were screened to provide a set of fifteen candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the fifteen candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger

Identification and quantification of preterm birth biomarkers in human cervicovaginal fluid by liquid chromatography/tandem mass spectrometry.

PubMed

Shah, Sumit J; Yu, Kenneth H; Sangar, Vineet; Parry, Samuel I; Blair, Ian A

2009-05-01

Spontaneous preterm birth (PTB) before 37 completed weeks of gestation resulting from preterm labor (PTL) is a leading contributor of perinatal morbidity and mortality. Early identification of at-risk women by reliable screening tests could alleviate this health issue; however, conventional methods such as obstetric history and clinical risk factors, uterine activity monitoring, biochemical markers, and cervical sonography for screening women at risk for PTB have proven unsuccessful in lowering the rate of PTB. Cervicovaginal fluid (CVF) might prove to be a useful, readily available biological fluid for identifying diagnostic PTB biomarkers. Human columnar epithelial endocervical-1 (End1) and vaginal (Vk2) cell secretomes were employed to generate a stable isotope labeled proteome (SILAP) standard to facilitate characterization and relative quantification of proteins present in CVF. The SILAP standard was prepared using stable isotope labeling by amino acids in cell culture (SILAC) of End1 and Vk2 through seven passages. The labeled secreted proteins from both cell lines were combined and characterized by liquid-chromatography-tandem mass spectrometry (LC-MS/MS). In total, 1211 proteins were identified in the End1-Vk2 SILAP standard, with 236 proteins being consistently identified in each of the replicates analyzed. Individual proteins were found to contain <0.5% of the endogenous unlabeled forms. Identified proteins were screened to provide a set of 15 candidates that have either previously been identified as potential PTB biomarkers or could be linked mechanistically to PTB. Stable isotope dilution LC-multiple reaction monitoring (MRM/MS) assays were then developed for conducting relative quantification of the 15 candidate biomarkers in human CVF samples from term and PTB cases. Three proteins were significantly elevated in PTB cases (desmoplakin isoform 1, stratifin, and thrombospondin 1 precursor), providing a foundation for further validation in larger patient

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.

Gene expression profiles of putative biomarker candidates in Mycobacterium avium subsp. paratuberculosis-infected cattle.

PubMed

Park, Hyun-Eui; Shin, Min-Kyoung; Park, Hong-Tae; Jung, Myunghwan; Cho, Yong Il; Yoo, Han Sang

2016-06-01

This study was conducted to analyze the gene expression of prognostic potential biomarker candidates using the whole blood of cattle naturally infected with ITALIC! Mycobacterium aviumsubsp. ITALIC! paratuberculosis(MAP). We conducted real-time PCR to evaluate 23 potential biomarker candidates. Experimental animals were divided into four groups based on fecal MAP PCR and serum ELISA. Seven ( ITALIC! KLRB1, ITALIC! HGF, ITALIC! MPO, ITALIC! LTF, ITALIC! SERPINE1, ITALIC! S100A8and ITALIC! S100A9) genes were up-regulated in fecal MAP-positive cattle and three ( ITALIC! KLRB1, ITALIC! MPOand ITALIC! S100A9) were up-regulated in MAP-seropositive cattle relative to uninfected cattle. In subclinically infected animals, 17 genes ( ITALIC! TFRC, ITALIC! S100A8, ITALIC! S100A9, ITALIC! MPO, ITALIC! GBP6, ITALIC! LTF, ITALIC! KLRB1, ITALIC! SERPINE1, ITALIC! PIGR, ITALIC! IL-10, ITALIC! CXCR3, ITALIC! CD14, ITALIC! MMP9, ITALIC! ELANE, ITALIC! CHI3L1, ITALIC! HPand ITALIC! HGF) were up-regulated compared with the control group. Moreover, six genes ( ITALIC! CXCR3, ITALIC! HP, ITALIC! HGF, ITALIC! LTF, ITALIC! TFRCand ITALIC! GBP6) showed significant differences between experimental groups. Taken together, our data suggest that six genes ( ITALIC! LTF, ITALIC! HGF, ITALIC! HP, ITALIC! CXCR3, ITALIC! GBP6and ITALIC! TFRC) played essential roles in the immune response to MAP during the subclinical stage and therefore might be useful as prognostic biomarkers. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Bayesian additive decision trees of biomarker by treatment interactions for predictive biomarker detection and subgroup identification.

PubMed

Zhao, Yang; Zheng, Wei; Zhuo, Daisy Y; Lu, Yuefeng; Ma, Xiwen; Liu, Hengchang; Zeng, Zhen; Laird, Glen

2017-10-11

Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarker detection and subgroup identification. In this article, we propose a novel decision tree-based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting. Gibbs sampler is implemented in the MCMC procedure, which updates the prognostic trees and the interaction tree separately. We use the posterior distribution of the interaction tree to construct the predictive scores of the biomarkers and to identify the subgroup where the treatment is superior to the control. Numerical simulations show that our proposed method performs well under various settings comparing to existing methods. We also demonstrate an application of our method in a real clinical trial.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

PubMed Central

Arias, Carlos Roberto; Yeh, Hsiang-Yuan; Soo, Von-Wun

2012-01-01

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. PMID:22654636

Developments in the Identification of Glycan Biomarkers for the Detection of Cancer

PubMed Central

Ruhaak, L. Renee; Miyamoto, Suzanne; Lebrilla, Carlito B.

2013-01-01

Changes in glycosylation readily occur in cancer and other disease states. Thanks to recent advances in the development of analytical techniques and instrumentation, especially in mass spectrometry, it is now possible to identify blood-derived glycan-based biomarkers using glycomics strategies. This review is an overview of the developments made in the search for glycan-based cancer biomarkers and the technologies currently in use. It is anticipated that the progressing instrumental and bioinformatics developments will allow the identification of relevant glycan biomarkers for the diagnosis, early detection, and monitoring of cancer treatment with sufficient sensitivity and specificity for clinical use. PMID:23365456

Top-Down Quantitative Proteomics Identified Phosphorylation of Cardiac Troponin I as a Candidate Biomarker for Chronic Heart Failure

PubMed Central

Zhang, Jiang; Guy, Moltu J.; Norman, Holly S.; Chen, Yi-Chen; Xu, Qingge; Dong, Xintong; Guner, Huseyin; Wang, Sijian; Kohmoto, Takushi; Young, Ken H.; Moss, Richard L.; Ge, Ying

2011-01-01

The rapid increase in the prevalence of chronic heart failure (CHF) worldwide underscores an urgent need to identify biomarkers for the early detection of CHF. Post-translational modifications (PTMs) are associated with many critical signaling events during disease progression and thus offer a plethora of candidate biomarkers. We have employed top-down quantitative proteomics methodology for comprehensive assessment of PTMs in whole proteins extracted from normal and diseased tissues. We have systematically analyzed thirty-six clinical human heart tissue samples and identified phosphorylation of cardiac troponin I (cTnI) as a candidate biomarker for CHF. The relative percentages of the total phosphorylated cTnI forms over the entire cTnI populations (%Ptotal) were 56.4±3.5%, 36.9±1.6%, 6.1±2.4%, and 1.0±0.6% for postmortem hearts with normal cardiac function (n=7), early-stage of mild hypertrophy (n=5), severe hypertrophy/dilation (n=4), and end-stage CHF (n=6), respectively. In fresh transplant samples, the %Ptotal of cTnI from non-failing donor (n=4), and end-stage failing hearts (n=10) were 49.5±5.9% and 18.8±2.9%, respectively. Top-down MS with electron capture dissociation unequivocally localized the altered phosphorylation sites to Ser22/23 and determined the order of phosphorylation/dephosphorylation. This study represents the first clinical application of top-down MS-based quantitative proteomics for biomarker discovery from tissues, highlighting the potential of PTM as disease biomarkers. PMID:21751783

Toxicogenomic identification of biomarkers of acute respiratory expsoure to sensitizing agents

EPA Science Inventory

Allergy induction requires multiple exposures to an agent. Therefore the development of high-throughput or in vitro assays for effective screening of potential sensitizers will require the identification of biomarkers. The goal of this preliminary study was to identify potential ...

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.

New Candidate Biomarkers in the Female Genital Tract to Evaluate Microbicide Toxicity

PubMed Central

Rasoul, Bareza; Fong, Julie; Works, Melissa G.; Shew, Kenneth; Yiu, Ying; Mirsalis, Jon; D'Andrea, Annalisa

2014-01-01

Vaginal microbicides hold great promise for the prevention of viral diseases like HIV, but the failure of several microbicide candidates in clinical trials has raised important questions regarding the parameters to be evaluated to determine in vivo efficacy in humans. Clinical trials of the candidate microbicides nonoxynol-9 (N9) and cellulose sulfate revealed an increase in HIV infection, vaginal inflammation, and recruitment of HIV susceptible lymphocytes, highlighting the need to identify biomarkers that can accurately predict microbicide toxicity early in preclinical development and in human trials. We used quantitative proteomics and RT-PCR approaches in mice and rabbits to identify protein changes in vaginal fluid and tissue in response to treatment with N9 or benzalkonium chloride (BZK). We compared changes generated with N9 and BZK treatment to the changes generated in response to tenofovir gel, a candidate microbicide that holds promise as a safe and effective microbicide. Both compounds down regulated mucin 5 subtype B, and peptidoglycan recognition protein 1 in vaginal tissue; however, mucosal brush samples also showed upregulation of plasma proteins fibrinogen, plasminogen, apolipoprotein A-1, and apolipoprotein C-1, which may be a response to the erosive nature of N9 and BZK. Additional proteins down-regulated in vaginal tissue by N9 or BZK treatment include CD166 antigen, olfactomedin-4, and anterior gradient protein 2 homolog. We also observed increases in the expression of C-C chemokines CCL3, CCL5, and CCL7 in response to treatment. There was concordance in expression level changes for several of these proteins using both the mouse and rabbit models. Using a human vaginal epithelial cell line, the expression of mucin 5 subtype B and olfactomedin-4 were down-regulated in response to N9, suggesting these markers could apply to humans. These data identifies new proteins that after further validation could become part of a panel of biomarkers to

Engineered gold nanoparticles for identification of novel ovarian biomarkers

NASA Astrophysics Data System (ADS)

Giri, Karuna

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

Identification of candidate biomarkers of the exposure to PCBs in contaminated cattle: A gene expression- and proteomic-based approach.

PubMed

Girolami, F; Badino, P; Spalenza, V; Manzini, L; Renzone, G; Salzano, A M; Dal Piaz, F; Scaloni, A; Rychen, G; Nebbia, C

2018-05-28

Dioxins and polychlorinated biphenyls (PCBs) are widespread and persistent contaminants. Through a combined gene expression/proteomic-based approach, candidate biomarkers of the exposure to such environmental pollutants in cattle subjected to a real eco-contamination event were identified. Animals were removed from the polluted area and fed a standard ration for 6 months. The decontamination was monitored by evaluating dioxin and PCB levels in pericaudal fat two weeks after the removal from the contaminated area (day 0) and then bimonthly for six months (days 59, 125 and 188). Gene expression measurements demonstrated that CYP1B1 expression was significantly higher in blood lymphocytes collected in contaminated animals (day 0), and decreased over time during decontamination. mRNA levels of interleukin 2 showed an opposite quantitative trend. MALDI-TOF-MS polypeptide profiling of serum samples ascertained a progressive decrease (from day 0 to 188) of serum levels of fibrinogen β-chain and serpin A3-7-like fragments, apolipoprotein (APO) C-II and serum amyloid A-4 protein, along with an augmented representation of transthyretin isoforms, as well as APOC-III and APOA-II proteins during decontamination. When differentially represented species were combined with serum antioxidant, acute phase and proinflammatory protein levels already ascertained in the same animals (Cigliano et al., 2016), bioinformatics unveiled an interaction network linking together almost all components. This suggests the occurrence of a complex PCB-responsive mechanism associated with animal contamination/decontamination, including a cohort of protein/polypeptide species involved in blood redox homeostasis, inflammation and lipid transport. All together, these results suggest the use in combination of such biomarkers for identifying PCB-contaminated animals, and for monitoring the restoring of their healthy condition following a decontamination process. Copyright © 2018 Elsevier B.V. All

Integrated Proteomic Profiling of Cell Line Conditioned Media and Pancreatic Juice for the Identification of Pancreatic Cancer Biomarkers

PubMed Central

Makawita, Shalini; Smith, Chris; Batruch, Ihor; Zheng, Yingye; Rückert, Felix; Grützmann, Robert; Pilarsky, Christian; Gallinger, Steven; Diamandis, Eleftherios P.

2011-01-01

Pancreatic cancer is one of the leading causes of cancer-related deaths, for which serological biomarkers are urgently needed. Most discovery-phase studies focus on the use of one biological source for analysis. The present study details the combined mining of pancreatic cancer-related cell line conditioned media and pancreatic juice for identification of putative diagnostic leads. Using strong cation exchange chromatography, followed by LC-MS/MS on an LTQ-Orbitrap mass spectrometer, we extensively characterized the proteomes of conditioned media from six pancreatic cancer cell lines (BxPc3, MIA-PaCa2, PANC1, CAPAN1, CFPAC1, and SU.86.86), the normal human pancreatic ductal epithelial cell line HPDE, and two pools of six pancreatic juice samples from ductal adenocarcinoma patients. All samples were analyzed in triplicate. Between 1261 and 2171 proteins were identified with two or more peptides in each of the cell lines, and an average of 521 proteins were identified in the pancreatic juice pools. In total, 3479 nonredundant proteins were identified with high confidence, of which ∼40% were extracellular or cell membrane-bound based on Genome Ontology classifications. Three strategies were employed for identification of candidate biomarkers: (1) examination of differential protein expression between the cancer and normal cell lines using label-free protein quantification, (2) integrative analysis, focusing on the overlap of proteins among the multiple biological fluids, and (3) tissue specificity analysis through mining of publically available databases. Preliminary verification of anterior gradient homolog 2, syncollin, olfactomedin-4, polymeric immunoglobulin receptor, and collagen alpha-1(VI) chain in plasma samples from pancreatic cancer patients and healthy controls using ELISA, showed a significant increase (p < 0.01) of these proteins in plasma from pancreatic cancer patients. The combination of these five proteins showed an improved area under the receiver

Variables Affecting Preservice Teacher Candidate Identification of Teacher Sexual Misconduct

ERIC Educational Resources Information Center

Haverland, Jeffrey A.

2017-01-01

Using a quantitative research model, this study explored variables affecting pre-service teacher candidate identification of teacher sexual misconduct through a scenario-based survey instrument. Independent variables in this study were respondent gender, student gender, teacher gender, student age-related ambiguity (students depicted were 17),…

Multiplexed MRM-based quantitation of candidate cancer biomarker proteins in undepleted and non-enriched human plasma.

PubMed

Percy, Andrew J; Chambers, Andrew G; Yang, Juncong; Borchers, Christoph H

2013-07-01

An emerging approach for multiplexed targeted proteomics involves bottom-up LC-MRM-MS, with stable isotope-labeled internal standard peptides, to accurately quantitate panels of putative disease biomarkers in biofluids. In this paper, we used this approach to quantitate 27 candidate cancer-biomarker proteins in human plasma that had not been treated by immunoaffinity depletion or enrichment techniques. These proteins have been reported as biomarkers for a variety of human cancers, from laryngeal to ovarian, with breast cancer having the highest correlation. We implemented measures to minimize the analytical variability, improve the quantitative accuracy, and increase the feasibility and applicability of this MRM-based method. We have demonstrated excellent retention time reproducibility (median interday CV: 0.08%) and signal stability (median interday CV: 4.5% for the analytical platform and 6.1% for the bottom-up workflow) for the 27 biomarker proteins (represented by 57 interference-free peptides). The linear dynamic range for the MRM assays spanned four orders-of-magnitude, with 25 assays covering a 10(3) -10(4) range in protein concentration. The lowest abundance quantifiable protein in our biomarker panel was insulin-like growth factor 1 (calculated concentration: 127 ng/mL). Overall, the analytical performance of this assay demonstrates high robustness and sensitivity, and provides the necessary throughput and multiplexing capabilities required to verify and validate cancer-associated protein biomarker panels in human plasma, prior to clinical use. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Candidate immune biomarkers for radioimmunotherapy.

PubMed

Levy, Antonin; Nigro, Giulia; Sansonetti, Philippe J; Deutsch, Eric

2017-08-01

Newly available immune checkpoint blockers (ICBs), capable to revert tumor immune tolerance, are revolutionizing the anticancer armamentarium. Recent evidence also established that ionizing radiation (IR) could produce antitumor immune responses, and may as well synergize with ICBs. Multiple radioimmunotherapy combinations are thenceforth currently assessed in early clinical trials. Past examples have highlighted the need for treatment personalization, and there is an unmet need to decipher immunological biomarkers that could allow selecting patients who could benefit from these promising but expensive associations. Recent studies have identified potential predictive and prognostic immune assays at the cellular (tumor microenvironment composition), genomic (mutational/neoantigen load), and peripheral blood levels. Within this review, we collected the available evidence regarding potential personalized immune biomarker-directed radiation therapy strategies that might be used for patient selection in the era of radioimmunotherapy. Copyright © 2017. Published by Elsevier B.V.

Circulating miR-132-3p as a Candidate Diagnostic Biomarker for Malignant Mesothelioma

PubMed Central

Gawrych, Katarzyna; Casjens, Swaantje; Brik, Alexander; Lehnert, Martin; Taeger, Dirk; Pesch, Beate; Kollmeier, Jens; Bauer, Torsten T.; Johnen, Georg; Brüning, Thomas

2017-01-01

The use of circulating microRNAs as biomarkers has opened new opportunities for diagnosis of cancer because microRNAs exhibit tumor-specific expression profiles. The aim of this study was the identification of circulating microRNAs in human plasma as potential biomarkers for the diagnosis of malignant mesothelioma. For discovery, TaqMan Low Density Array Human MicroRNA Cards were used to analyze 377 microRNAs in plasma samples from 21 mesothelioma patients and 21 asbestos-exposed controls. For verification, individual TaqMan microRNA assays were used for quantitative real-time PCR in plasma samples from 22 mesothelioma patients and 44 asbestos-exposed controls. The circulating miR-132-3p showed different expression levels between mesothelioma patients and asbestos-exposed controls. For discrimination, sensitivity of 86% and specificity of 61% were calculated. Circulating miR-132-3p in plasma was not affected by hemolysis and no impact of age or smoking status on miR-132-3p levels could be observed. For the combination of miR-132-3p with the previously described miR-126, sensitivity of 77% and specificity of 86% were calculated. The results of this study indicate that miR-132-3p might be a new promising diagnostic biomarker for malignant mesothelioma. It is indicated that the combination of miR-132-3p with other individual biomarkers improves the biomarker performance. PMID:28321148

Integrating Soluble Biomarkers and Imaging Technologies in the Identification of Vulnerable Atherosclerotic Patients

PubMed Central

Páramo, José A.; Rodríguez JA, José A.; Orbe, Josune

2006-01-01

The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease. PMID:19690647

Integrating soluble biomarkers and imaging technologies in the identification of vulnerable atherosclerotic patients.

PubMed

Páramo, José A; Rodríguez Ja, José A; Orbe, Josune

2007-02-07

The clinical utility of a biomarker depends on its ability to identify high-risk individuals to optimally manage the patient. A new biomarker would be of clinical value if it is accurate and reliable, provides good sensitivity and specificity, and is available for widespread application. Data are accumulating on the potential clinical utility of integrating imaging technologies and circulating biomarkers for the identification of vulnerable (high-risk) cardiovascular patients. A multi-biomarker strategy consisting of markers of inflammation, hemostasis and thrombosis, proteolysis and oxidative stress, combined with new imaging modalities (optical coherence tomography, virtual histology plus IVUS, PET) can increase our ability to identify such thombosis-prone patients. In an ideal scenario, cardiovascular biomarkers and imaging combined will provide a better diagnostic tool to identify high-risk individuals and also more efficient methods for effective therapies to reduce such cardiovascular risk. However, additional studies are required in order to show that this approach can contribute to improved diagnostic and therapeutic of atherosclerotic disease.

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

Identification of serum biomarkers in dogs naturally infected with Babesia canis canis using a proteomic approach

PubMed Central

2014-01-01

Background Canine babesiosis is a tick-borne disease that is caused by the haemoprotozoan parasites of the genus Babesia. There are limited data on serum proteomics in dogs, and none of the effect of babesiosis on the serum proteome. The aim of this study was to identify the potential serum biomarkers of babesiosis using proteomic techniques in order to increase our understanding about disease pathogenesis. Results Serum samples were collected from 25 dogs of various breeds and sex with naturally occurring babesiosis caused by B. canis canis. Blood was collected on the day of admission (day 0), and subsequently on the 1st and 6th day of treatment. Two-dimensional electrophoresis (2DE) of pooled serum samples of dogs with naturally occurring babesiosis (day 0, day 1 and day 6) and healthy dogs were run in triplicate. 2DE image analysis showed 64 differentially expressed spots with p ≤ 0.05 and 49 spots with fold change ≥2. Six selected spots were excised manually and subjected to trypsin digest prior to identification by electrospray ionisation mass spectrometry on an Amazon ion trap tandem mass spectrometry (MS/MS). Mass spectrometry data was processed using Data Analysis software and the automated Matrix Science Mascot Daemon server. Protein identifications were assigned using the Mascot search engine to interrogate protein sequences in the NCBI Genbank database. A number of differentially expressed serum proteins involved in inflammation mediated acute phase response, complement and coagulation cascades, apolipoproteins and vitamin D metabolism pathway were identified in dogs with babesiosis. Conclusions Our findings confirmed two dominant pathogenic mechanisms of babesiosis, haemolysis and acute phase response. These results may provide possible serum biomarker candidates for clinical monitoring of babesiosis and this study could serve as the basis for further proteomic investigations in canine babesiosis. PMID:24885808

Identification of Dlk1-Dio3 imprinted gene cluster noncoding RNAs as novel candidate biomarkers for liver tumor promotion.

PubMed

Lempiäinen, Harri; Couttet, Philippe; Bolognani, Federico; Müller, Arne; Dubost, Valérie; Luisier, Raphaëlle; Del Rio Espinola, Alberto; Vitry, Veronique; Unterberger, Elif B; Thomson, John P; Treindl, Fridolin; Metzger, Ute; Wrzodek, Clemens; Hahne, Florian; Zollinger, Tulipan; Brasa, Sarah; Kalteis, Magdalena; Marcellin, Magali; Giudicelli, Fanny; Braeuning, Albert; Morawiec, Laurent; Zamurovic, Natasa; Längle, Ulrich; Scheer, Nico; Schübeler, Dirk; Goodman, Jay; Chibout, Salah-Dine; Marlowe, Jennifer; Theil, Diethilde; Heard, David J; Grenet, Olivier; Zell, Andreas; Templin, Markus F; Meehan, Richard R; Wolf, Roland C; Elcombe, Clifford R; Schwarz, Michael; Moulin, Pierre; Terranova, Rémi; Moggs, Jonathan G

2013-02-01

The molecular events during nongenotoxic carcinogenesis and their temporal order are poorly understood but thought to include long-lasting perturbations of gene expression. Here, we have investigated the temporal sequence of molecular and pathological perturbations at early stages of phenobarbital (PB) mediated liver tumor promotion in vivo. Molecular profiling (mRNA, microRNA [miRNA], DNA methylation, and proteins) of mouse liver during 13 weeks of PB treatment revealed progressive increases in hepatic expression of long noncoding RNAs and miRNAs originating from the Dlk1-Dio3 imprinted gene cluster, a locus that has recently been associated with stem cell pluripotency in mice and various neoplasms in humans. PB induction of the Dlk1-Dio3 cluster noncoding RNA (ncRNA) Meg3 was localized to glutamine synthetase-positive hypertrophic perivenous hepatocytes, suggesting a role for β-catenin signaling in the dysregulation of Dlk1-Dio3 ncRNAs. The carcinogenic relevance of Dlk1-Dio3 locus ncRNA induction was further supported by in vivo genetic dependence on constitutive androstane receptor and β-catenin pathways. Our data identify Dlk1-Dio3 ncRNAs as novel candidate early biomarkers for mouse liver tumor promotion and provide new opportunities for assessing the carcinogenic potential of novel compounds.

Evaluation of the biomarker candidate MFAP4 for non-invasive assessment of hepatic fibrosis in hepatitis C patients.

PubMed

Bracht, Thilo; Mölleken, Christian; Ahrens, Maike; Poschmann, Gereon; Schlosser, Anders; Eisenacher, Martin; Stühler, Kai; Meyer, Helmut E; Schmiegel, Wolff H; Holmskov, Uffe; Sorensen, Grith L; Sitek, Barbara

2016-07-04

The human microfibrillar-associated protein 4 (MFAP4) is located to extracellular matrix fibers and plays a role in disease-related tissue remodeling. Previously, we identified MFAP4 as a serum biomarker candidate for hepatic fibrosis and cirrhosis in hepatitis C patients. The aim of the present study was to elucidate the potential of MFAP4 as biomarker for hepatic fibrosis with a focus on the differentiation of no to moderate (F0-F2) and severe fibrosis stages and cirrhosis (F3 and F4, Desmet-Scheuer scoring system). MFAP4 levels were measured using an AlphaLISA immunoassay in a retrospective study including n = 542 hepatitis C patients. We applied a univariate logistic regression model based on MFAP4 serum levels and furthermore derived a multivariate model including also age and gender. Youden-optimal cutoffs for binary classification were determined for both models without restrictions and considering a lower limit of 80 % sensitivity (correct classification of F3 and F4), respectively. To assess the generalization error, leave-one-out cross validation (LOOCV) was performed. MFAP4 levels were shown to differ between no to moderate fibrosis stages F0-F2 and severe stages (F3 and F4) with high statistical significance (t test on log scale, p value <2.2·10(-16)). In the LOOCV, the univariate classification resulted in 85.8 % sensitivity and 54.9 % specificity while the multivariate model yielded 81.3 % sensitivity and 61.5 % specificity (restricted approaches). We confirmed the applicability of MFAP4 as a novel serum biomarker for assessment of hepatic fibrosis and identification of high-risk patients with severe fibrosis stages in hepatitis C. The combination of MFAP4 with existing tests might lead to a more accurate non-invasive diagnosis of hepatic fibrosis and allow a cost-effective disease management in the era of new direct acting antivirals.

Putting the Oxylipidome to Work: A Novel Lipidomics Pipeline Reveals Candidate Biomarkers for Photooxidative Stress in Phytoplankton

NASA Astrophysics Data System (ADS)

Collins, J.; Edwards, B. R.; Fredricks, H. F.; Van Mooy, B. A.

2016-02-01

The lipids of marine plankton encompass a diversity of biochemical functions and chemotaxonomic specificities that make them ideal molecular biomarkers in living biomass. While core, nonpolar lipids such as free fatty acids (FFA) have formed the basis for many biomarker studies in fresh biomass, methods that enable the simultaneous profiling of core lipids and intact polar lipids (IPL) have opened new avenues for characterization of environmental stressors. We demonstrate the application of a novel, rules-based lipidomics data analysis pipeline to putatively identify a broad range of intact polar lipids, intact oxidized lipids (ox-lipids) and oxylipins in accurate-mass HPLC-ESI-MS data. Using mass spectra from a lipid peroxidation experiment conducted under the natural, ultraviolet-enriched light field in West Antarctica, we use the pipeline to identify ox-lipid and oxylipin biomarkers that might serve as indicators of photooxidative stress in phytoplankton. The lipidomics pipeline derives much of its functionality from two boutique lipid-oxylipin databases, which together contain entries for more than 60,000 candidate lipid biomarkers. These databases and all scripts required by the pipeline will be publicly available online to other users.

Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows.

PubMed

Tian, He; Wang, Weiyu; Zheng, Nan; Cheng, Jianbo; Li, Songli; Zhang, Yangdong; Wang, Jiaqi

2015-07-01

Controlling heat stress (HS) is a global challenge for the dairy industry. However, simple and reliable biomarkers that aid the diagnoses of HS-induced metabolic disorders have not yet been identified. In this work, an integrated metabolomic and lipidomic approach using (1)H nuclear magnetic resonance and ultra-fast LC-MS was employed to investigate the discrimination of plasma metabolic profiles between HS-free and HS lactating dairy cows. Targeted detection using LC-MS in multiple reaction monitoring mode was used to verify the reliability of the metabolites as biomarker candidates. Overall, 41 metabolites were identified as candidates for lactating dairy cows exposed to HS, among which 13 metabolites, including trimethylamine, glucose, lactate, betaine, creatine, pyruvate, acetoacetate, acetone, β-hydroxybutyrate, C16 sphinganine, lysophosphatidylcholine (18:0), phosphatidylcholine (16:0/14:0), and arachidonic acid, had high sensitivity and specificity in diagnosing HS status, and are likely to be the potential biomarkers of HS dairy cows. All of these potentially diagnostic biomarkers were involved in carbohydrate, amino acid, lipid, or gut microbiome-derived metabolism, indicating that HS affected the metabolic pathways in lactating dairy cows. Further research is warranted to evaluate these biomarkers in practical applications and to elucidate the physiological mechanisms of HS-induced metabolic disorders. Heat stress (HS) annually causes huge losses to global dairy industry, including animal performance decrease, metabolic disorder and health problem. So far, physiological mechanisms underlying HS of dairy cows still remain elusive. To our best knowledge, this is the first attempt to elucidate the HS-induced metabolic disorders of dairy cows using integrated (1)H NMR and LC-MS-based metabolic study. The results not only provided potential diagnostic biomarkers for HS lactating dairy cows, but also significantly explored the related physiological mechanisms

Sepsis and identification of reliable biomarkers for postoperative period prognosis.

PubMed

Siloşi, Cristian Adrian; Siloşi, Isabela; Pădureanu, Vlad; Bogdan, Maria; Mogoantă, Stelian Ştefăniţă; Ciurea, Marius Eugen; Cojocaru, Manole; Boldeanu, Lidia; Avrămescu, Carmen Silvia; Boldeanu, Mihail Virgil; Popa, Dragoş George

2018-01-01

Sepsis is currently defined as the presence of organ dysfunction occurring as the result of a disturbed host response to a serious infection. Sepsis is one of the most common diseases, which cause mortality and a considerable absorber of healthcare resources. Despite progress in technology and improving knowledge of pathophysiology, the disease mechanism is still poorly understood. At present, diagnosis is based on non-specific physiological criteria and on the late identification of the pathogen. For these reasons, the diagnosis may be uncertain, treatment delayed or an immunomodulatory therapy cannot be established. An early and reliable diagnosis is essential to achieve better outcomes on disease progression. The host response to infection involves hundreds of many mediators of which have been proposed as biomarkers. There is a need for new diagnostic approaches for sepsis, new sepsis biomarkers that can aid in diagnosis, therapeutic decision and monitoring of the response to therapy. The differentiation of sepsis from non-infectious systemic inflammatory response syndrome is difficult, and the search for a highly accurate biomarker of sepsis has become one important objective of the medicine. The goal of our review is to summarize the recent advances on the most commonly studied serum biomarkers, evaluated in clinical and experimental studies, for early diagnosis of sepsis and their informative value in diagnosis, prognosis, or response to therapy. In this context, we have tracked the clinical utility of measuring serum biomarkers, such as procalcitonin, pro- and anti-inflammatory cytokines, C-reactive protein, leptin and their combinations. Currently, has not been identified an ideal biomarker to aid in the diagnosis of sepsis. It is hoped that the discovery of new serum markers, as well as their combinations, will serve for the diagnosis and prognosis of sepsis.

Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

PubMed Central

Arellano-Garcia, Martha E.; Li, Roger; Liu, Xiaojun; Xie, Yongming; Yan, Xiaofei; Loo, Joseph A.; Hu, Shen

2010-01-01

Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC). A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B). We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients. PMID:20957082

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

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

PubMed Central

2014-01-01

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

[Identification of candidate genes and expression profiles, as doping biomarkers].

PubMed

Paparini, A; Impagnatiello, F; Pistilli, A; Rinaldi, M; Gianfranceschi, G; Signori, E; Stabile, A M; Fazio, V; Rende, M; Romano Spica, V

2007-01-01

Administration of prohibited substances to enhance athletic performance represents an emerging medical, social, ethical and legal issue. Traditional controls are based on direct detection of substances or their catabolites. However out-of-competition doping may not be easily revealed by standard analytical methods. Alternative indirect control strategies are based on the evaluation of mid- and long-term effects of doping in tissues. Drug-induced long-lasting changes of gene expression may be taken as effective indicators of doping exposure. To validate this approach, we used real-time PCR to monitor the expression pattern of selected genes in human haematopoietic cells exposed to nandrolone, insulin-like growth factor I (IGF-I) or growth hormone (GH). Some candidate genes were found significantly and consistently modulated by treatments. Nandrolone up-regulated AR, ESR2 and PGR in K562 cells, and SRD5A1, PPARA and JAK2 in Jurkat cells; IGF-I up-regulated EPOR and PGR in HL60 cells, and SRD5A1 in Jurkat; GH up-regulated SRD5A1 and GHR in K562. GATA1 expression was down-regulated in IGF-1-treated HL60, ESR2 was down-regulated in nandrolone-treated Jurkat, and AR and PGR were down-regulated in GH-treated Jurkat. This pilot study shows the potential of molecular biology-based strategies in anti-doping controls.

Identification of Biomarkers of Impaired Sensory Profiles among Autistic Patients

PubMed Central

El-Ansary, Afaf; Hassan, Wail M.; Qasem, Hanan; Das, Undurti N.

2016-01-01

Background Autism is a neurodevelopmental disorder that displays significant heterogeneity. Comparison of subgroups within autism, and analyses of selected biomarkers as measure of the variation of the severity of autistic features such as cognitive dysfunction, social interaction impairment, and sensory abnormalities might help in understanding the pathophysiology of autism. Methods and Participants In this study, two sets of biomarkers were selected. The first included 7, while the second included 6 biomarkers. For set 1, data were collected from 35 autistic and 38 healthy control participants, while for set 2, data were collected from 29 out of the same 35 autistic and 16 additional healthy subjects. These markers were subjected to a principal components analysis using either covariance or correlation matrices. Moreover, libraries composed of participants categorized into units were constructed. The biomarkers used include, PE (phosphatidyl ethanolamine), PS (phosphatidyl serine), PC (phosphatidyl choline), MAP2K1 (Dual specificity mitogen-activated protein kinase kinase 1), IL-10 (interleukin-10), IL-12, NFκB (nuclear factor-κappa B); PGE2 (prostaglandin E2), PGE2-EP2, mPGES-1 (microsomal prostaglandin synthase E-1), cPLA2 (cytosolic phospholipase A2), 8-isoprostane, and COX-2 (cyclo-oxygenase-2). Results While none of the studied markers correlated with CARS and SRS as measure of cognitive and social impairments, six markers significantly correlated with sensory profiles of autistic patients. Multiple regression analysis identifies a combination of PGES, mPGES-1, and PE as best predictors of the degree of sensory profile impairment. Library identification resulted in 100% correct assignments of both autistic and control participants based on either set 1 or 2 biomarkers together with a satisfactory rate of assignments in case of sensory profile impairment using different sets of biomarkers. Conclusion The two selected sets of biomarkers were effective to

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

PubMed

Iyappan, Anandhi; Kawalia, Shweta Bagewadi; Raschka, Tamara; Hofmann-Apitius, Martin; Senger, Philipp

2016-07-08

Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framework to help decipher the complex interactions that occur at molecular and cellular levels. This motivates the need for the development of an approach integrating highly curated and heterogeneous data into a disease model of different regulatory data layers. Although several disease models exist, they often do not consider the quality of underlying data. Moreover, even with the current advancements in semantic web technology, we still do not have cure for complex diseases like Alzheimer's disease. One of the key reasons accountable for this could be the increasing gap between generated data and the derived knowledge. In this paper, we describe an approach, called as NeuroRDF, to develop an integrative framework for modeling curated knowledge in the area of complex neurodegenerative diseases. The core of this strategy lies in the usage of well curated and context specific data for integration into one single semantic web-based framework, RDF. This increases the probability of the derived knowledge to be novel and reliable in a specific disease context. This infrastructure integrates highly curated data from databases (Bind, IntAct, etc.), literature (PubMed), and gene expression resources (such as GEO and ArrayExpress). We illustrate the effectiveness of our approach by asking real-world biomedical questions that link these resources to prioritize the plausible biomarker candidates. Among the 13 prioritized candidate genes, we identified MIF to be a potential emerging candidate due to its role as a pro-inflammatory cytokine. We additionally report on the effort and challenges faced during generation of such an indication-specific knowledge base comprising of curated and quality-controlled data. Although many alternative approaches

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease

PubMed Central

Choi1, Yong Seok; Lee, Kelvin H.

2016-01-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (> 90%) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R2 = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78%), and inter-day reproducibility (average CV = 9.85%). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard. PMID:26404792

Multiple reaction monitoring assay based on conventional liquid chromatography and electrospray ionization for simultaneous monitoring of multiple cerebrospinal fluid biomarker candidates for Alzheimer's disease.

PubMed

Choi, Yong Seok; Lee, Kelvin H

2016-03-01

Alzheimer's disease (AD) is the most common type of dementia, but early and accurate diagnosis remains challenging. Previously, a panel of cerebrospinal fluid (CSF) biomarker candidates distinguishing AD and non-AD CSF accurately (>90 %) was reported. Furthermore, a multiple reaction monitoring (MRM) assay based on nano liquid chromatography tandem mass spectrometry (nLC-MS/MS) was developed to help validate putative AD CSF biomarker candidates including proteins from the panel. Despite the good performance of the MRM assay, wide acceptance may be challenging because of limited availability of nLC-MS/MS systems in laboratories. Thus, here, a new MRM assay based on conventional LC-MS/MS is presented. This method monitors 16 peptides representing 16 (of 23) biomarker candidates that belonged to the previous AD CSF panel. A 30-times more concentrated sample than the sample used for the previous study was loaded onto a high capacity trap column, and all 16 MRM transitions showed good linearity (average R(2) = 0.966), intra-day reproducibility (average coefficient of variance (CV) = 4.78 %), and inter-day reproducibility (average CV = 9.85 %). The present method has several advantages such as a shorter analysis time, no possibility of target variability, and no need for an internal standard.

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

PubMed

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

2017-03-07

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

Biomarkers for Alzheimer's disease: academic, industry and regulatory perspectives.

PubMed

Hampel, Harald; Frank, Richard; Broich, Karl; Teipel, Stefan J; Katz, Russell G; Hardy, John; Herholz, Karl; Bokde, Arun L W; Jessen, Frank; Hoessler, Yvonne C; Sanhai, Wendy R; Zetterberg, Henrik; Woodcock, Janet; Blennow, Kaj

2010-07-01

Advances in therapeutic strategies for Alzheimer's disease that lead to even small delays in onset and progression of the condition would significantly reduce the global burden of the disease. To effectively test compounds for Alzheimer's disease and bring therapy to individuals as early as possible there is an urgent need for collaboration between academic institutions, industry and regulatory organizations for the establishment of standards and networks for the identification and qualification of biological marker candidates. Biomarkers are needed to monitor drug safety, to identify individuals who are most likely to respond to specific treatments, to stratify presymptomatic patients and to quantify the benefits of treatments. Biomarkers that achieve these characteristics should enable objective business decisions in portfolio management and facilitate regulatory approval of new therapies.

Serum microRNA biomarker identification in a residential cohort with elevated polychlorinated biphenyl exposures

EPA Science Inventory

Exposure to liver toxicants can result in or exacerbate fatty liver disease. Recent evidence suggests that serum-derived microRNAs (miRs) may improve identification of chemical-induced fatty liver disease relative to traditional protein-based biomarkers alone. Historical serum sa...

Computational Biomarker Pipeline from Discovery to Clinical Implementation: Plasma Proteomic Biomarkers for Cardiac Transplantation

PubMed Central

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

2013-01-01

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

Odor identification as a biomarker of preclinical AD in older adults at risk

PubMed Central

Poirier, Judes; Etienne, Pierre; Tremblay-Mercier, Jennifer; Frenette, Joanne; Rosa-Neto, Pedro; Breitner, John C.S.

2017-01-01

Objective: To assess odor identification (OI) as an indicator of presymptomatic Alzheimer disease (AD) pathogenesis in cognitively normal aging individuals at increased risk of AD dementia. Methods: In 274 members of the PREVENT-AD cohort of healthy aging persons with a parental or multiple-sibling history of AD dementia, we assessed the cross-sectional association of OI with potential indicators of presymptomatic AD. Some 101 participants donated CSF, thus enabling assessment of AD pathology with the biomarkers total tau (t-tau), phospho-tau (P181-tau), and their ratios with β-amyloid (Aβ1-42). Adjusted analyses considered age, cognition, APOE ε4 status, education, and sex as covariates. We measured OI using the University of Pennsylvania Smell Identification Test and cognitive performance using the Repeatable Battery for Assessment of Neuropsychological Status. Standard kits provided assays of the AD biomarkers. Analyses used robust-fit linear regression models. Results: Reduced OI was associated with lower cognitive score and older age, as well as increased ratios of CSF t-tau and P181-tau to Aβ1-42 (all p < 0.02). However, the observed associations of OI with age and cognition were unapparent in adjusted models that restricted observations to CSF donors and included AD biomarkers. OI showed little association with CSF Aβ1-42 alone except in APOE ε4 carriers having lowest-quartile Aβ1-42 levels. Conclusions: These findings from healthy high-risk older individuals suggest that OI reflects degree of preclinical AD pathology, while its relationships with age and cognition result from the association of these latter variables with such pathology. Diminished OI may be a practical and affordable biomarker of AD pathology. PMID:28659431

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

PubMed

Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Current status of predictive biomarkers for neoadjuvant therapy in esophageal cancer

PubMed Central

Uemura, Norihisa; Kondo, Tadashi

2014-01-01

Neoadjuvant therapy has been proven to be extremely valuable and is widely used for advanced esophageal cancer. However, a significant proportion of treated patients (60%-70%) does not respond well to neoadjuvant treatments and develop severe adverse effects. Therefore, predictive markers for individualization of multimodality treatments are urgently needed in esophageal cancer. Recently, molecular biomarkers that predict the response to neoadjuvant therapy have been explored in multimodal approaches in esophageal cancer and successful examples of biomarker identification have been reported. In this review, promising candidates for predictive molecular biomarkers developed by using multiple molecular approaches are reviewed. Moreover, treatment strategies based on the status of predicted biomarkers are discussed, while considering the international differences in the clinical background. However, in the absence of adequate treatment options related to the results of the biomarker test, the usefulness of these diagnostic tools is limited and new effective therapies for biomarker-identified nonresponders to cancer treatment should be concurrent with the progress of predictive technologies. Further improvement in the prognosis of esophageal cancer patients can be achieved through the introduction of novel therapeutic approaches in clinical practice. PMID:25133032

Exploring candidate biomarkers for lung and prostate cancers using gene expression and flux variability analysis.

PubMed

Asgari, Yazdan; Khosravi, Pegah; Zabihinpour, Zahra; Habibi, Mahnaz

2018-02-19

Genome-scale metabolic models have provided valuable resources for exploring changes in metabolism under normal and cancer conditions. However, metabolism itself is strongly linked to gene expression, so integration of gene expression data into metabolic models might improve the detection of genes involved in the control of tumor progression. Herein, we considered gene expression data as extra constraints to enhance the predictive powers of metabolic models. We reconstructed genome-scale metabolic models for lung and prostate, under normal and cancer conditions to detect the major genes associated with critical subsystems during tumor development. Furthermore, we utilized gene expression data in combination with an information theory-based approach to reconstruct co-expression networks of the human lung and prostate in both cohorts. Our results revealed 19 genes as candidate biomarkers for lung and prostate cancer cells. This study also revealed that the development of a complementary approach (integration of gene expression and metabolic profiles) could lead to proposing novel biomarkers and suggesting renovated cancer treatment strategies which have not been possible to detect using either of the methods alone.

A proteomic analysis identifies candidate early biomarkers to predict ovarian hyperstimulation syndrome in polycystic ovarian syndrome patients.

PubMed

Wu, Lan; Sun, Yazhou; Wan, Jun; Luan, Ting; Cheng, Qing; Tan, Yong

2017-07-01

Ovarian hyperstimulation syndrome (OHSS) is a potentially life‑threatening, iatrogenic complication that occurs during assisted reproduction. Polycystic ovarian syndrome (PCOS) significantly increases the risk of OHSS during controlled ovarian stimulation. Therefore, a more effective early prediction technique is required in PCOS patients. Quantitative proteomic analysis of serum proteins indicates the potential diagnostic value for disease. In the present study, the authors revealed the differentially expressed proteins in OHSS patients with PCOS as new diagnostic biomarkers. The promising proteins obtained from liquid chromatography‑mass spectrometry were subjected to ELISA and western blotting assay for further confirmation. A total of 57 proteins were identified with significant difference, of which 29 proteins were upregulated and 28 proteins were downregulated in OHSS patients. Haptoglobin, fibrinogen and lipoprotein lipase were selected as candidate biomarkers. Receiver operating characteristic curve analysis demonstrated all three proteins may have potential as biomarkers to discriminate OHSS in PCOS patients. Haptoglobin, fibrinogen and lipoprotein lipase have never been reported as a predictive marker of OHSS in PCOS patients, and their potential roles in OHSS occurrence deserve further studies. The proteomic results reported in the present study may gain deeper insights into the pathophysiology of OHSS.

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.

Circulating microRNAs in Pancreatic Juice as Candidate Biomarkers of Pancreatic Cancer

PubMed Central

Wang, Jin; Raimondo, Massimo; Guha, Sushovan; Chen, Jinyun; Diao, Lixia; Dong, Xiaoqun; Wallace, Michael B.; Killary, Ann M.; Frazier, Marsha L.; Woodward, Timothy A.; Wang, Jing; Sen, Subrata

2014-01-01

Development of sensitive and specific biomarkers, preferably those circulating in body fluids is critical for early diagnosis of cancer. This study performed profiling of microRNAs (miRNAs) in exocrine pancreatic secretions (pancreatic juice) by microarray analysis utilizing pancreatic juice from 6 pancreatic ductal adenocarcinoma (PDAC) patients and two pooled samples from 6 non-pancreatic, non-healthy (NPNH) as controls. Differentially circulating miRNAs were subsequently validated in 88 pancreatic juice samples from 50 PDAC, 19 chronic pancreatitis (CP) patients and 19 NPNH controls. A marked difference in the profiles of four circulating miRNAs (miR-205, miR-210, miR-492, and miR-1427) was observed in pancreatic juice collected from patients with PDAC and those without pancreatic disease. Elevated levels of the four miRNAs together predicted PDAC with a specificity of 88% and sensitivity of 87%. Inclusion of serum CA19-9 level increased the sensitivity to 91% and the specificity to 100%. Enrichment of the four miRNAs in pancreatic juice was associated with decreased OS, as was the combination of miR-205 and miR-210. Higher contents of miR-205 and miR-210 were also associated with lymph node metastasis. Elevated levels of circulating miR-205, miR-210, miR-492, and miR-1247 in pancreatic juice are, therefore, promising candidate biomarkers of disease and poor prognosis in patients with PDAC. PMID:25258651

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

PubMed Central

Yamada, Takashi; Hashimoto, Ryu-ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Abstract Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. PMID:28977523

Peptide fingerprinting of Alzheimer's disease in cerebrospinal fluid: identification and prospective evaluation of new synaptic biomarkers.

PubMed

Jahn, Holger; Wittke, Stefan; Zürbig, Petra; Raedler, Thomas J; Arlt, Sönke; Kellmann, Markus; Mullen, William; Eichenlaub, Martin; Mischak, Harald; Wiedemann, Klaus

2011-01-01

Today, dementias are diagnosed late in the course of disease. Future treatments have to start earlier in the disease process to avoid disability requiring new diagnostic tools. The objective of this study is to develop a new method for the differential diagnosis and identification of new biomarkers of Alzheimer's disease (AD) using capillary-electrophoresis coupled to mass-spectrometry (CE-MS) and to assess the potential of early diagnosis of AD. Cerebrospinal fluid (CSF) of 159 out-patients of a memory-clinic at a University Hospital suffering from neurodegenerative disorders and 17 cognitively-healthy controls was used to create differential peptide pattern for dementias and prospective blinded-comparison of sensitivity and specificity for AD diagnosis against the Criterion standard in a naturalistic prospective sample of patients. Sensitivity and specificity of the new method compared to standard diagnostic procedures and identification of new putative biomarkers for AD was the main outcome measure. CE-MS was used to reliably detect 1104 low-molecular-weight peptides in CSF. Training-sets of patients with clinically secured sporadic Alzheimer's disease, frontotemporal dementia, and cognitively healthy controls allowed establishing discriminative biomarker pattern for diagnosis of AD. This pattern was already detectable in patients with mild cognitive impairment (MCI). The AD-pattern was tested in a prospective sample of patients (n = 100) and AD was diagnosed with a sensitivity of 87% and a specificity of 83%. Using CSF measurements of beta-amyloid1-42, total-tau, and phospho(181)-tau, AD-diagnosis had a sensitivity of 88% and a specificity of 67% in the same sample. Sequence analysis of the discriminating biomarkers identified fragments of synaptic proteins like proSAAS, apolipoprotein J, neurosecretory protein VGF, phospholemman, and chromogranin A. The method may allow early differential diagnosis of various dementias using specific peptide fingerprints

Fibrinogen gamma-A chain precursor in CSF: a candidate biomarker for Alzheimer's disease

PubMed Central

Lee, Joung Wook; Namkoong, Hong; Kim, Hyun Kee; Kim, Sanghee; Hwang, Dong Whi; Na, Hae Ri; Ha, Seon-Ah; Kim, Jae-Ryong; Kim, Jin Woo

2007-01-01

Background Cerebrospinal fluid (CSF) may be valuable for exploring protein markers for the diagnosis of Alzheimer's disease (AD). The prospect of early detection and treatment, to slow progression, holds hope for aging populations with increased average lifespan. The aim of the present study was to investigate candidate CSF biological markers in patients with mild cognitive impairment (MCI) and AD and compare them with age-matched normal control subjects. Methods We applied proteomics approaches to analyze CSF samples derived from 27 patients with AD, 3 subjects with MCI and 30 controls. The AD group was subdivided into three groups by clinical severity according to clinical dementia rating (CDR), a well known clinical scale for dementia. Results We demonstrated an elevated level of fibrinogen gamma-A chain precursor protein in CSF from patients with mild cognitive impairment and AD compared to the age-matched normal subjects. Moreover, its expression was more prominent in the AD group than in the MCI and correlated with disease severity and progression. In contrast, fibrinogen gamma-A chain precursor protein was detected very low in the age-matched normal group. Conclusion These findings suggest that the CSF level of fibrinogen gamma-A chain precursor may be a candidate biomarker for AD. PMID:17565664

Parkinson's disease biomarkers: perspective from the NINDS Parkinson's Disease Biomarkers Program

PubMed Central

Gwinn, Katrina; David, Karen K; Swanson-Fischer, Christine; Albin, Roger; Hillaire-Clarke, Coryse St; Sieber, Beth-Anne; Lungu, Codrin; Bowman, F DuBois; Alcalay, Roy N; Babcock, Debra; Dawson, Ted M; Dewey, Richard B; Foroud, Tatiana; German, Dwight; Huang, Xuemei; Petyuk, Vlad; Potashkin, Judith A; Saunders-Pullman, Rachel; Sutherland, Margaret; Walt, David R; West, Andrew B; Zhang, Jing; Chen-Plotkin, Alice; Scherzer, Clemens R; Vaillancourt, David E; Rosenthal, Liana S

2017-01-01

Biomarkers for Parkinson's disease (PD) diagnosis, prognostication and clinical trial cohort selection are an urgent need. While many promising markers have been discovered through the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP) and other mechanisms, no single PD marker or set of markers are ready for clinical use. Here we discuss the current state of biomarker discovery for platforms relevant to PDBP. We discuss the role of the PDBP in PD biomarker identification and present guidelines to facilitate their development. These guidelines include: harmonizing procedures for biofluid acquisition and clinical assessments, replication of the most promising biomarkers, support and encouragement of publications that report negative findings, longitudinal follow-up of current cohorts including the PDBP, testing of wearable technologies to capture readouts between study visits and development of recently diagnosed (de novo) cohorts to foster identification of the earliest markers of disease onset. PMID:28644039

Predictive biomarkers of sensitivity to the phosphatidylinositol 3' kinase inhibitor GDC-0941 in breast cancer preclinical models.

PubMed

O'Brien, Carol; Wallin, Jeffrey J; Sampath, Deepak; GuhaThakurta, Debraj; Savage, Heidi; Punnoose, Elizabeth A; Guan, Jane; Berry, Leanne; Prior, Wei Wei; Amler, Lukas C; Belvin, Marcia; Friedman, Lori S; Lackner, Mark R

2010-07-15

The class I phosphatidylinositol 3' kinase (PI3K) plays a major role in proliferation and survival in a wide variety of human cancers. A key factor in successful development of drugs targeting this pathway is likely to be the identification of responsive patient populations with predictive diagnostic biomarkers. This study sought to identify candidate biomarkers of response to the selective PI3K inhibitor GDC-0941. We used a large panel of breast cancer cell lines and in vivo xenograft models to identify candidate predictive biomarkers for a selective inhibitor of class I PI3K that is currently in clinical development. The approach involved pharmacogenomic profiling as well as analysis of gene expression data sets from cells profiled at baseline or after GDC-0941 treatment. We found that models harboring mutations in PIK3CA, amplification of human epidermal growth factor receptor 2, or dual alterations in two pathway components were exquisitely sensitive to the antitumor effects of GDC-0941. We found that several models that do not harbor these alterations also showed sensitivity, suggesting a need for additional diagnostic markers. Gene expression studies identified a collection of genes whose expression was associated with in vitro sensitivity to GDC-0941, and expression of a subset of these genes was found to be intimately linked to signaling through the pathway. Pathway focused biomarkers and the gene expression signature described in this study may have utility in the identification of patients likely to benefit from therapy with a selective PI3K inhibitor. Copyright 2010 AACR.

Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

PubMed Central

Shattuck-Hufnagel, S.; Choi, J. Y.; Moro-Velázquez, L.; Gómez-García, J. A.

2017-01-01

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting. PMID:29240814

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.

Prespecified candidate biomarkers identify follicular lymphoma patients who achieved longer progression-free survival with bortezomib-rituximab versus rituximab.

PubMed

Coiffier, Bertrand; Li, Weimin; Henitz, Erin D; Karkera, Jayaprakash D; Favis, Reyna; Gaffney, Dana; Shapiro, Alice; Theocharous, Panteli; Elsayed, Yusri A; van de Velde, Helgi; Schaffer, Michael E; Osmanov, Evgenii A; Hong, Xiaonan; Scheliga, Adriana; Mayer, Jiri; Offner, Fritz; Rule, Simon; Teixeira, Adriana; Romejko-Jarosinska, Joanna; de Vos, Sven; Crump, Michael; Shpilberg, Ofer; Zinzani, Pier Luigi; Cakana, Andrew; Esseltine, Dixie-Lee; Mulligan, George; Ricci, Deborah

2013-05-01

Identify subgroups of patients with relapsed/refractory follicular lymphoma deriving substantial progression-free survival (PFS) benefit with bortezomib-rituximab versus rituximab in the phase III LYM-3001 study. A total of 676 patients were randomized to five 5-week cycles of bortezomib-rituximab or rituximab. The primary end point was PFS; this prespecified analysis of candidate protein biomarkers and genes was an exploratory objective. Archived tumor tissue and whole blood samples were collected at baseline. Immunohistochemistry and genetic analyses were completed for 4 proteins and 8 genes. In initial pairwise analyses, using individual single-nucleotide polymorphism genotypes, one biomarker pair (PSMB1 P11A C/G heterozygote, low CD68 expression) was associated with a significant PFS benefit with bortezomib-rituximab versus rituximab, controlling for multiple comparison corrections. The pair was analyzed under dominant, recessive, and additive genetic models, with significant association with PFS seen under the dominant model (G/G+C/G). In patients carrying this biomarker pair [PSMB1 P11A G allele, low CD68 expression (≤50 CD68-positive cells), population frequency: 43.6%], median PFS was 14.2 months with bortezomib-rituximab versus 9.1 months with rituximab (HR 0.47, P < 0.0001), and there was a significant overall survival benefit (HR 0.49, P = 0.0461). Response rates were higher and time to next antilymphoma therapy was longer in the bortezomib-rituximab group. In biomarker-negative patients, no significant efficacy differences were seen between treatment groups. Similar proportions of patients had high-risk features in the biomarker-positive and biomarker-negative subsets. Patients with PSMB1 P11A (G allele) and low CD68 expression seemed to have significantly longer PFS and greater clinical benefit with bortezomib-rituximab versus rituximab. ©2013 AACR.

The MCP-4/MCP-1 ratio in plasma is a candidate circadian biomarker for chronic post-traumatic stress disorder

PubMed Central

Dalgard, C; Eidelman, O; Jozwik, C; Olsen, C H; Srivastava, M; Biswas, R; Eudy, Y; Rothwell, S W; Mueller, G P; Yuan, P; Drevets, W C; Manji, H K; Vythlingam, M; Charney, D S; Neumeister, A; Ursano, R J; Jacobowitz, D M; Pollard, H B; Bonne, O

2017-01-01

Post-traumatic stress disorder (PTSD) is psychiatric disease, which can occur following exposure to traumatic events. PTSD may be acute or chronic, and can have a waxing and waning course of symptoms. It has been hypothesized that proinflammatory cytokines and chemokines in the cerebrospinal fluid (CSF) or plasma might be mediators of the psychophysiological mechanisms relating a history of trauma exposure to changes in behavior and mental health disorders, and medical morbidity. Here we test the cytokine/chemokine hypothesis for PTSD by examining levels of 17 classical cytokines and chemokines in CSF, sampled at 0900 hours, and in plasma sampled hourly for 24 h. The PTSD and healthy control patients are from the NIMH Chronic PTSD and healthy control cohort, initially described by Bonne et al. (2011), in which the PTSD patients have relatively low comorbidity for major depressive disorder (MDD), drug or alcohol use. We find that in plasma, but not CSF, the bivariate MCP4 (CCL13)/ MCP1(CCL2) ratio is ca. twofold elevated in PTSD patients compared with healthy controls. The MCP-4/MCP-1 ratio is invariant over circadian time, and is independent of gender, body mass index or the age at which the trauma was suffered. By contrast, MIP-1β is a candidate biomarker for PTSD only in females, whereas TARC is a candidate biomarker for PTSD only in males. It remains to be discovered whether these disease-specific differences in circadian expression for these specific immune signaling molecules are biomarkers, surrogates, or drivers for PTSD, or whether any of these analytes could contribute to therapy. PMID:28170001

Bladder cancer biomarker discovery using global metabolomic profiling of urine.

PubMed

Wittmann, Bryan M; Stirdivant, Steven M; Mitchell, Matthew W; Wulff, Jacob E; McDunn, Jonathan E; Li, Zhen; Dennis-Barrie, Aphrihl; Neri, Bruce P; Milburn, Michael V; Lotan, Yair; Wolfert, Robert L

2014-01-01

Bladder cancer (BCa) is a common malignancy worldwide and has a high probability of recurrence after initial diagnosis and treatment. As a result, recurrent surveillance, primarily involving repeated cystoscopies, is a critical component of post diagnosis patient management. Since cystoscopy is invasive, expensive and a possible deterrent to patient compliance with regular follow-up screening, new non-invasive technologies to aid in the detection of recurrent and/or primary bladder cancer are strongly needed. In this study, mass spectrometry based metabolomics was employed to identify biochemical signatures in human urine that differentiate bladder cancer from non-cancer controls. Over 1000 distinct compounds were measured including 587 named compounds of known chemical identity. Initial biomarker identification was conducted using a 332 subject sample set of retrospective urine samples (cohort 1), which included 66 BCa positive samples. A set of 25 candidate biomarkers was selected based on statistical significance, fold difference and metabolic pathway coverage. The 25 candidate biomarkers were tested against an independent urine sample set (cohort 2) using random forest analysis, with palmitoyl sphingomyelin, lactate, adenosine and succinate providing the strongest predictive power for differentiating cohort 2 cancer from non-cancer urines. Cohort 2 metabolite profiling revealed additional metabolites, including arachidonate, that were higher in cohort 2 cancer vs. non-cancer controls, but were below quantitation limits in the cohort 1 profiling. Metabolites related to lipid metabolism may be especially interesting biomarkers. The results suggest that urine metabolites may provide a much needed non-invasive adjunct diagnostic to cystoscopy for detection of bladder cancer and recurrent disease management.

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Adjacent slice prostate cancer prediction to inform MALDI imaging biomarker analysis

NASA Astrophysics Data System (ADS)

Chuang, Shao-Hui; Sun, Xiaoyan; Cazares, Lisa; Nyalwidhe, Julius; Troyer, Dean; Semmes, O. John; Li, Jiang; McKenzie, Frederic D.

2010-03-01

Prostate cancer is the second most common type of cancer among men in US [1]. Traditionally, prostate cancer diagnosis is made by the analysis of prostate-specific antigen (PSA) levels and histopathological images of biopsy samples under microscopes. Proteomic biomarkers can improve upon these methods. MALDI molecular spectra imaging is used to visualize protein/peptide concentrations across biopsy samples to search for biomarker candidates. Unfortunately, traditional processing methods require histopathological examination on one slice of a biopsy sample while the adjacent slice is subjected to the tissue destroying desorption and ionization processes of MALDI. The highest confidence tumor regions gained from the histopathological analysis are then mapped to the MALDI spectra data to estimate the regions for biomarker identification from the MALDI imaging. This paper describes a process to provide a significantly better estimate of the cancer tumor to be mapped onto the MALDI imaging spectra coordinates using the high confidence region to predict the true area of the tumor on the adjacent MALDI imaged slice.

A computational method for the identification of new candidate carcinogenic and non-carcinogenic chemicals.

PubMed

Chen, Lei; Chu, Chen; Lu, Jing; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-09-01

Cancer is one of the leading causes of human death. Based on current knowledge, one of the causes of cancer is exposure to toxic chemical compounds, including radioactive compounds, dioxin, and arsenic. The identification of new carcinogenic chemicals may warn us of potential danger and help to identify new ways to prevent cancer. In this study, a computational method was proposed to identify potential carcinogenic chemicals, as well as non-carcinogenic chemicals. According to the current validated carcinogenic and non-carcinogenic chemicals from the CPDB (Carcinogenic Potency Database), the candidate chemicals were searched in a weighted chemical network constructed according to chemical-chemical interactions. Then, the obtained candidate chemicals were further selected by a randomization test and information on chemical interactions and structures. The analyses identified several candidate carcinogenic chemicals, while those candidates identified as non-carcinogenic were supported by a literature search. In addition, several candidate carcinogenic/non-carcinogenic chemicals exhibit structural dissimilarity with validated carcinogenic/non-carcinogenic chemicals.

IDENTIFICATION OF CANDIDATE HOUSES FOR NORTH FLORIDA PORTION OF THE FLORIDA RADON MITIGATION PROJECT

EPA Science Inventory

The report gives results of a study to locate candidate houses for a proposed radon mitigation research and demonstration project in North Florida. he effort involved: 1) identification of target geographical areas, 2) radon monitoring in identified clusters, and 3) house charact...

Current status of fluid biomarkers in mild traumatic brain injury

PubMed Central

Kulbe, Jacqueline R.; Geddes, James W.

2015-01-01

Mild traumatic brain injury (mTBI) affects millions of people annually and is difficult to diagnose. Mild injury is insensitive to conventional imaging techniques and diagnoses are often made using subjective criteria such as self-reported symptoms. Many people who sustain a mTBI develop persistent post-concussive symptoms. Athletes and military personnel are at great risk for repeat injury which can result in second impact syndrome or chronic traumatic encephalopathy. An objective and quantifiable measure, such as a serum biomarker, is needed to aid in mTBI diagnosis, prognosis, return to play/duty assessments, and would further elucidate mTBI pathophysiology. The majority of TBI biomarker research focuses on severe TBI with few studies specific to mild injury. Most studies use a hypothesis-driven approach, screening biofluids for markers known to be associated with TBI pathophysiology. This approach has yielded limited success in identifying markers that can be used clinically, additional candidate biomarkers are needed. Innovative and unbiased methods such as proteomics, microRNA arrays, urinary screens, autoantibody identification and phage display would complement more traditional approaches to aid in the discovery of novel mTBI biomarkers. PMID:25981889

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.

Indel-seq: a fast-forward genetics approach for identification of trait-associated putative candidate genomic regions and its application in pigeonpea (Cajanus cajan).

PubMed

Singh, Vikas K; Khan, Aamir W; Saxena, Rachit K; Sinha, Pallavi; Kale, Sandip M; Parupalli, Swathi; Kumar, Vinay; Chitikineni, Annapurna; Vechalapu, Suryanarayana; Sameer Kumar, Chanda Venkata; Sharma, Mamta; Ghanta, Anuradha; Yamini, Kalinati Narasimhan; Muniswamy, Sonnappa; Varshney, Rajeev K

2017-07-01

Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time-consuming. In recent years, a number of single nucleotide polymorphism (SNP)-based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion-deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel-seq approach, which is a combination of whole-genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel-seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW- and SMD-resistant and FW- and SMD-susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel-seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel-seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

MicroRNA-206: A Potential Circulating Biomarker Candidate for Amyotrophic Lateral Sclerosis

PubMed Central

Toivonen, Janne M.; Manzano, Raquel; Oliván, Sara; Zaragoza, Pilar; García-Redondo, Alberto; Osta, Rosario

2014-01-01

Amyotrophic lateral sclerosis (ALS) is a lethal motor neuron disease that progressively debilitates neuronal cells that control voluntary muscle activity. Biomarkers are urgently needed to facilitate ALS diagnosis and prognosis, and as indicators of therapeutic response in clinical trials. microRNAs (miRNAs), small posttranscriptional modifiers of gene expression, are frequently altered in disease conditions. Besides their important regulatory role in variety of biological processes, miRNAs can also be released into the circulation by pathologically affected tissues and display remarkable stability in body fluids. In a mouse model of ALS that expresses mutated human superoxide dismutase 1 (SOD1-G93A) skeletal muscle is one of the tissues affected early by mutant SOD1 toxicity. To find biomarkers for ALS, we studied miRNA alterations from skeletal muscle and plasma of SOD1-G93A mice, and subsequently tested the levels of the affected miRNAs in the serum from human ALS patients. Fast-twitch and slow-twitch muscles from symptomatic SOD1-G93A mice (age 90 days) and their control littermates were first studied using miRNA microarrays and then evaluated with quantitative PCR from five age groups from neonatal to the terminal disease stage (10–120 days). Among those miRNA changed in various age/gender/muscle groups (miR-206, -1, -133a, -133b, -145, -21, -24), miR-206 was the only one consistently altered during the course of the disease pathology. In both sexes, mature miR-206 was increased in fast-twitch muscles preferably affected in the SOD1-G93A model, with highest expression towards the most severely affected animals. Importantly, miR-206 was also increased in the circulation of symptomatic animals and in a group of 12 definite ALS patients tested. We conclude that miR-206 is elevated in the circulation of symptomatic SOD1-G93A mice and possibly in human ALS patients. Although larger scale studies on ALS patients are warranted, miR-206 is a promising candidate

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Human alpha defensin 5 is a candidate biomarker to delineate inflammatory bowel disease

PubMed Central

Williams, Amanda D.; Korolkova, Olga Y.; Sakwe, Amos M.; Geiger, Timothy M.; James, Samuel D.; Muldoon, Roberta L.; Herline, Alan J.; Goodwin, J. Shawn; Izban, Michael G.; Washington, Mary K.; Smoot, Duane T.; Ballard, Billy R.; Gazouli, Maria

2017-01-01

�-Defensin-5 is a potential candidate biomarker to molecularly differentiate Crohn's colitis from ulcerative colitis, to our knowledge. These data give us both a potential diagnostic marker in Human α-Defensin-5 and insight to develop future mechanistic studies to better understand crypt biology in Crohn's colitis. PMID:28817680

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.

Biomarkers and personalized medicine: current status and further perspectives with special focus on dermatology.

PubMed

Landeck, Lilla; Kneip, Christoph; Reischl, Joachim; Asadullah, Khusru

2016-05-01

Biomarkers are of increasingly high importance in medicine, particularly in the realm of 'personalized medicine'. They are valuable for predicting prognosis and dose selection. Moreover, they may be helpful in detecting therapeutic and adverse responses and in patient stratification based on efficacy or safety prediction. Thus, biomarkers are essential tools for the selection of appropriate patients for treatment with certain drugs to and enable personalized medicine, that is 'providing the right treatment to the right patient, at the right dose at the right time'. Currently, there are six drugs approved for dermatological indications with recommended or mandatory biomarker testing. Most of them are used to treat melanoma and human immunodeficiency virus infection. In contrast to the few fully validated biomarkers, many exploratory biomarkers and biomarker candidates have potential applications. Prognostic biomarkers are of particular significance for malignant conditions. Similarly, diagnostic biomarkers are important in autoimmune diseases. Disease severity biomarkers are helpful tools in the treatment for inflammatory skin diseases. Identification, qualification and implementation of the different kinds of biomarkers are challenging and frequently necessitate collaborative efforts. This is particularly true for stratification biomarkers that require a companion diagnostic marker that is co-developed with a certain drug. In this article general definitions and requirements for biomarkers as well as for the impact of biomarkers in dermatology are reviewed and opportunities and challenges are discussed. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Do we have biomarkers to predict response to neoadjuvant and adjuvant chemotherapy and immunotherapy in bladder cancer?

PubMed Central

Wezel, Felix; Vallo, Stefan

2017-01-01

Radical cystectomy (RC) is the standard of care treatment of localized muscle-invasive bladder cancer (BC). However, about 50% of patients develop metastases within 2 years after cystectomy. Neoadjuvant cisplatin-based chemotherapy before cystectomy improves the overall survival (OS) in patients with muscle-invasive BC. Pathological response to neoadjuvant treatment is a strong predictor of better disease-specific survival. Nevertheless, some patients do not benefit from chemotherapy. The identification of reliable biomarkers enabling clinicians to identify patients who might benefit from chemotherapy is a very important clinical task. An identification tool could lead to individualized therapy, optimizing response rates. In addition, unnecessary treatment with chemotherapy which potentially leads to a loss of quality of life and which might also might cause a delay of cystectomy in a neoadjuvant setting could be avoided. The present review aims to summarize and discuss the current literature on biomarkers for the prediction of response to systemic therapy in muscle-invasive BC. Tremendous efforts in genetic and molecular characterization have led to the identification of predictive candidate biomarkers in urothelial carcinoma (UC), although prospective validation is pending. Ongoing clinical trials examining the benefit of individual therapies in UC of the bladder (UCB) by molecular patient selection hold promise to shed light on this question. PMID:29354494

Fluid Biomarkers in Alzheimer Disease

PubMed Central

Blennow, Kaj; Zetterberg, Henrik; Fagan, Anne M.

2012-01-01

Research progress has provided detailed understanding of the molecular pathogenesis of Alzheimer disease (AD). This knowledge has been translated into new drug candidates with putative disease-modifying effects, which are now being tested in clinical trials. The promise of effective therapy has created a great need for biomarkers able to detect AD in the predementia phase, because drugs will probably be effective only if neurodegeneration is not too advanced. In this chapter, cerebrospinal fluid (CSF) and plasma biomarkers are reviewed. The core CSF biomarkers total tau (T-tau), phosphorylated tau (P-tau) and the 42 amino acid form of β-amyloid (Aβ42) reflect AD pathology, and have high diagnostic accuracy to diagnose AD with dementia and prodromal AD in mild cognitive impairment cases. The rationale for the use of CSF biomarkers to identify and monitor the mechanism of action of new drug candidates is also outlined in this chapter. PMID:22951438

Biomarkers in sarcoidosis.

PubMed

Chopra, Amit; Kalkanis, Alexandros; Judson, Marc A

2016-11-01

Numerous biomarkers have been evaluated for the diagnosis, assessment of disease activity, prognosis, and response to treatment in sarcoidosis. In this report, we discuss the clinical and research utility of several biomarkers used to evaluate sarcoidosis. Areas covered: The sarcoidosis biomarkers discussed include serologic tests, imaging studies, identification of inflammatory cells and genetic analyses. Literature was obtained from medical databases including PubMed and Web of Science. Expert commentary: Most of the biomarkers examined in sarcoidosis are not adequately specific or sensitive to be used in isolation to make clinical decisions. However, several sarcoidosis biomarkers have an important role in the clinical management of sarcoidosis when they are coupled with clinical data including the results of other biomarkers.

The Identification of Novel Potential Injury Mechanisms and Candidate Biomarkers in Renal Allograft Rejection by Quantitative Proteomics*

PubMed Central

Sigdel, Tara K.; Salomonis, Nathan; Nicora, Carrie D.; Ryu, Soyoung; He, Jintang; Dinh, Van; Orton, Daniel J.; Moore, Ronald J.; Hsieh, Szu-Chuan; Dai, Hong; Thien-Vu, Minh; Xiao, Wenzhong; Smith, Richard D.; Qian, Wei-Jun; Camp, David G.; Sarwal, Minnie M.

2014-01-01

Early transplant dysfunction and failure because of immunological and nonimmunological factors still presents a significant clinical problem for transplant recipients. A critical unmet need is the noninvasive detection and prediction of immune injury such that acute injury can be reversed by proactive immunosuppression titration. In this study, we used iTRAQ -based proteomic discovery and targeted ELISA validation to discover and validate candidate urine protein biomarkers from 262 renal allograft recipients with biopsy-confirmed allograft injury. Urine samples were randomly split into a training set of 108 patients and an independent validation set of 154 patients, which comprised the clinical biopsy-confirmed phenotypes of acute rejection (AR) (n = 74), stable graft (STA) (n = 74), chronic allograft injury (CAI) (n = 58), BK virus nephritis (BKVN) (n = 38), nephrotic syndrome (NS) (n = 8), and healthy, normal control (HC) (n = 10). A total of 389 proteins were measured that displayed differential abundances across urine specimens of the injury types (p < 0.05) with a significant finding that SUMO2 (small ubiquitin-related modifier 2) was identified as a “hub” protein for graft injury irrespective of causation. Sixty-nine urine proteins had differences in abundance (p < 0.01) in AR compared with stable graft, of which 12 proteins were up-regulated in AR with a mean fold increase of 2.8. Nine urine proteins were highly specific for AR because of their significant differences (p < 0.01; fold increase >1.5) from all other transplant categories (HLA class II protein HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4). Increased levels of three of these proteins, fibrinogen beta (FGB; p = 0.04), fibrinogen gamma (FGG; p = 0.03), and HLA DRB1 (p = 0.003) were validated by ELISA in AR using an independent sample set. The fibrinogen proteins further segregated AR from BK virus nephritis (FGB p = 0.03, FGG p = 0.02), a finding that supports the utility of

Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

PubMed

Wostyn, Peter; De Deyn, Peter Paul

2017-11-01

A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

Genome-Wide Identification of Molecular Mimicry Candidates in Parasites

PubMed Central

Ludin, Philipp; Nilsson, Daniel; Mäser, Pascal

2011-01-01

Among the many strategies employed by parasites for immune evasion and host manipulation, one of the most fascinating is molecular mimicry. With genome sequences available for host and parasite, mimicry of linear amino acid epitopes can be investigated by comparative genomics. Here we developed an in silico pipeline for genome-wide identification of molecular mimicry candidate proteins or epitopes. The predicted proteome of a given parasite was broken down into overlapping fragments, each of which was screened for close hits in the human proteome. Control searches were carried out against unrelated, free-living eukaryotes to eliminate the generally conserved proteins, and with randomized versions of the parasite proteins to get an estimate of statistical significance. This simple but computation-intensive approach yielded interesting candidates from human-pathogenic parasites. From Plasmodium falciparum, it returned a 14 amino acid motif in several of the PfEMP1 variants identical to part of the heparin-binding domain in the immunosuppressive serum protein vitronectin. And in Brugia malayi, fragments were detected that matched to periphilin-1, a protein of cell-cell junctions involved in barrier formation. All the results are publicly available by means of mimicDB, a searchable online database for molecular mimicry candidates from pathogens. To our knowledge, this is the first genome-wide survey for molecular mimicry proteins in parasites. The strategy can be adopted to any pair of host and pathogen, once appropriate negative control organisms are chosen. MimicDB provides a host of new starting points to gain insights into the molecular nature of host-pathogen interactions. PMID:21408160

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013.

PubMed

Viglio, Simona; Stolk, Jan; Iadarola, Paolo; Giuliano, Serena; Luisetti, Maurizio; Salvini, Roberta; Fumagalli, Marco; Bardoni, Anna

2014-01-22

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

The Identification of Zebrafish Mutants Showing Alterations in Senescence-Associated Biomarkers

PubMed Central

Uchiyama, Junzo; Koshimizu, Eriko; Qi, Jie; Nanjappa, Purushothama; Imamura, Shintaro; Islam, Asiful; Neuberg, Donna; Amsterdam, Adam; Roberts, Thomas M.

2008-01-01

There is an interesting overlap of function in a wide range of organisms between genes that modulate the stress responses and those that regulate aging phenotypes and, in some cases, lifespan. We have therefore screened mutagenized zebrafish embryos for the altered expression of a stress biomarker, senescence-associated β-galactosidase (SA-β-gal) in our current study. We validated the use of embryonic SA-β-gal production as a screening tool by analyzing a collection of retrovirus-insertional mutants. From a pool of 306 such mutants, we identified 11 candidates that showed higher embryonic SA-β-gal activity, two of which were selected for further study. One of these mutants is null for a homologue of Drosophila spinster, a gene known to regulate lifespan in flies, whereas the other harbors a mutation in a homologue of the human telomeric repeat binding factor 2 (terf2) gene, which plays roles in telomere protection and telomere-length regulation. Although the homozygous spinster and terf2 mutants are embryonic lethal, heterozygous adult fish are viable and show an accelerated appearance of aging symptoms including lipofuscin accumulation, which is another biomarker, and shorter lifespan. We next used the same SA-β-gal assay to screen chemically mutagenized zebrafish, each of which was heterozygous for lesions in multiple genes, under the sensitizing conditions of oxidative stress. We obtained eight additional mutants from this screen that, when bred to homozygosity, showed enhanced SA-β-gal activity even in the absence of stress, and further displayed embryonic neural and muscular degenerative phenotypes. Adult fish that are heterozygous for these mutations also showed the premature expression of aging biomarkers and the accelerated onset of aging phenotypes. Our current strategy of mutant screening for a senescence-associated biomarker in zebrafish embryos may thus prove to be a useful new tool for the genetic dissection of vertebrate stress response and

Biomarkers of delirium as a clue to diagnosis and pathogenesis of Wernicke-Korsakoff syndrome.

PubMed

Wijnia, J W; Oudman, E

2013-12-01

Wernicke's encephalopathy (WE) and Korsakoff's syndrome are considered to be different stages of the same disorder due to thiamine deficiency, which is called Wernicke-Korsakoff syndrome (WKS). The earliest biochemical change is the decrease of α-ketoglutarate-dehydrogenase activity in astrocytes. According to autopsy-based series, mental status changes are present in 82% of WE cases. The objective of the present review is to identify possible underlying mechanisms relating the occurrence of delirium to WKS. Studies involving delirium in WKS, however, are rare. Therefore, first, a search was done for candidate biomarkers of delirium irrespective of the clinical setting. Secondly, the results were focused on identification of these biomarkers in reports on WKS. In various settings, 10 biochemical and/or genetic biomarkers showed strong associations with the occurrence of delirium. For WKS three of these candidate biomarkers were identified, namely brain tissue cell counts of CD68 positive cells as a marker of microglial activation, high cerebrospinal fluid lactate levels, and MHPG, a metabolite of norepinephrine. Based on current literature, markers of microglial activation may present an interesting patho-etiological relationship between thiamine deficiency and delirium in WKS. In WKS cases, changes in astroglia and microglial proliferation were reported. The possible loss-of-function mechanisms following thiamine deficiency in WKS are proposed to come from microglial activation, resulting in a delirium in the initial phase of WKS. © 2013 The Author(s) European Journal of Neurology © 2013 EFNS.

Label-Free LC-MS/MS Proteomic Analysis of Cerebrospinal Fluid Identifies Protein/Pathway Alterations and Candidate Biomarkers for Amyotrophic Lateral Sclerosis.

PubMed

Collins, Mahlon A; An, Jiyan; Hood, Brian L; Conrads, Thomas P; Bowser, Robert P

2015-11-06

Analysis of the cerebrospinal fluid (CSF) proteome has proven valuable to the study of neurodegenerative disorders. To identify new protein/pathway alterations and candidate biomarkers for amyotrophic lateral sclerosis (ALS), we performed comparative proteomic profiling of CSF from sporadic ALS (sALS), healthy control (HC), and other neurological disease (OND) subjects using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 1712 CSF proteins were detected and relatively quantified by spectral counting. Levels of several proteins with diverse biological functions were significantly altered in sALS samples. Enrichment analysis was used to link these alterations to biological pathways, which were predominantly related to inflammation, neuronal activity, and extracellular matrix regulation. We then used our CSF proteomic profiles to create a support vector machines classifier capable of discriminating training set ALS from non-ALS (HC and OND) samples. Four classifier proteins, WD repeat-containing protein 63, amyloid-like protein 1, SPARC-like protein 1, and cell adhesion molecule 3, were identified by feature selection and externally validated. The resultant classifier distinguished ALS from non-ALS samples with 83% sensitivity and 100% specificity in an independent test set. Collectively, our results illustrate the utility of CSF proteomic profiling for identifying ALS protein/pathway alterations and candidate disease biomarkers.

Schizophrenia proteomics: biomarkers on the path to laboratory medicine?

PubMed Central

Lakhan, Shaheen Emmanuel

2006-01-01

Over two million Americans are afflicted with schizophrenia, a debilitating mental health disorder with a unique symptomatic and epidemiological profile. Genomics studies have hinted towards candidate schizophrenia susceptibility chromosomal loci and genes. Modern proteomic tools, particularly mass spectrometry and expression scanning, aim to identify both pathogenic-revealing and diagnostically significant biomarkers. Only a few studies on basic proteomics have been conducted for psychiatric disorders relative to the plethora of cancer specific experiments. One such proteomic utility enables the discovery of proteins and biological marker fingerprinting profiling techniques (SELDI-TOF-MS), and then subjects them to tandem mass spectrometric fragmentation and de novo protein sequencing (MALDI-TOF/TOF-MS) for the accurate identification and characterization of the proteins. Such utilities can explain the pathogenesis of neuro-psychiatric disease, provide more objective testing methods, and further demonstrate a biological basis to mental illness. Although clinical proteomics in schizophrenia have yet to reveal a biomarker with diagnostic specificity, methods that better characterize the disorder using endophenotypes can advance findings. Schizophrenia biomarkers could potentially revolutionize its psychopharmacology, changing it into a more hypothesis and genomic/proteomic-driven science. PMID:16846510

Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

PubMed Central

Zhang, Cathy X. Y.; Brooks, Brian W.; Huang, Hongsheng; Pagotto, Franco

2016-01-01

ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is

Biomarkers of acute respiratory allergen exposure: Screening for sensitization potential

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

Pucheu-Haston, Cherie M., E-mail: Pucheu-Haston.Cherie@epa.go; Copeland, Lisa B.; Vallanat, Beena

2010-04-15

Effective hazard screening will require the development of high-throughput or in vitro assays for the identification of potential sensitizers. The goal of this preliminary study was to identify potential biomarkers that differentiate the response to allergens vs non-allergens following an acute exposure in naive individuals. Female BALB/c mice received a single intratracheal aspiration exposure to Metarhizium anisopliae crude antigen (MACA) or bovine serum albumin (BSA) in Hank's Balanced Salt Solution (HBSS) or HBSS alone. Mice were terminated after 1, 3, 6, 12, 18 and 24 h. Bronchoalveolar lavage fluid (BALF) was evaluated to determine total and differential cellularity, total proteinmore » concentration and LDH activity. RNA was isolated from lung tissue for microarray analysis and qRT-PCR. MACA administration induced a rapid increase in BALF neutrophils, lymphocytes, eosinophils and total protein compared to BSA or HBSS. Microarray analysis demonstrated differential expression of genes involved in cytokine production, signaling, inflammatory cell recruitment, adhesion and activation in 3 and 12 h MACA-treated samples compared to BSA or HBSS. Further analyses allowed identification of approx 100 candidate biomarker genes. Eleven genes were selected for further assessment by qRT-PCR. Of these, 6 demonstrated persistently increased expression (Ccl17, Ccl22, Ccl7, Cxcl10, Cxcl2, Saa1), while C3ar1 increased from 6-24 h. In conclusion, a single respiratory exposure of mice to an allergenic mold extract induces an inflammatory response which is distinct in phenotype and gene transcription from the response to a control protein. Further validation of these biomarkers with additional allergens and irritants is needed. These biomarkers may facilitate improvements in screening methods.« less

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

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.

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

GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

PubMed

Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

2016-12-05

Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

Bioinformatics-Based Identification of Candidate Genes from QTLs Associated with Cell Wall Traits in Populus

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

Ranjan, Priya; Yin, Tongming; Zhang, Xinye

2009-11-01

Quantitative trait locus (QTL) studies are an integral part of plant research and are used to characterize the genetic basis of phenotypic variation observed in structured populations and inform marker-assisted breeding efforts. These QTL intervals can span large physical regions on a chromosome comprising hundreds of genes, thereby hampering candidate gene identification. Genome history, evolution, and expression evidence can be used to narrow the genes in the interval to a smaller list that is manageable for detailed downstream functional genomics characterization. Our primary motivation for the present study was to address the need for a research methodology that identifies candidatemore » genes within a broad QTL interval. Here we present a bioinformatics-based approach for subdividing candidate genes within QTL intervals into alternate groups of high probability candidates. Application of this approach in the context of studying cell wall traits, specifically lignin content and S/G ratios of stem and root in Populus plants, resulted in manageable sets of genes of both known and putative cell wall biosynthetic function. These results provide a roadmap for future experimental work leading to identification of new genes controlling cell wall recalcitrance and, ultimately, in the utility of plant biomass as an energy feedstock.« less

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

PubMed

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

2014-09-09

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

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

EPA Science Inventory

Book Chapter 18, titled Application in pesticide analysis: Liquid chromatography - A review of the state of science for biomarker discovery and identification, will be published in the book titled High Performance Liquid Chromatography in Pesticide Residue Analysis (Part of the C...

How Nanotechnology and Biomedical Engineering Are Supporting the Identification of Predictive Biomarkers in Neuro-Oncology.

PubMed

Ganau, Mario; Paris, Marco; Syrmos, Nikolaos; Ganau, Laura; Ligarotti, Gianfranco K I; Moghaddamjou, Ali; Prisco, Lara; Ambu, Rossano; Chibbaro, Salvatore

2018-02-26

The field of neuro-oncology is rapidly progressing and internalizing many of the recent discoveries coming from research conducted in basic science laboratories worldwide. This systematic review aims to summarize the impact of nanotechnology and biomedical engineering in defining clinically meaningful predictive biomarkers with a potential application in the management of patients with brain tumors. Data were collected through a review of the existing English literature performed on Scopus, MEDLINE, MEDLINE in Process, EMBASE, and/or Cochrane Central Register of Controlled Trials: all available basic science and clinical papers relevant to address the above-stated research question were included and analyzed in this study. Based on the results of this systematic review we can conclude that: (1) the advances in nanotechnology and bioengineering are supporting tremendous efforts in optimizing the methods for genomic, epigenomic and proteomic profiling; (2) a successful translational approach is attempting to identify a growing number of biomarkers, some of which appear to be promising candidates in many areas of neuro-oncology; (3) the designing of Randomized Controlled Trials will be warranted to better define the prognostic value of those biomarkers and biosignatures.

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.

Innovative methodology for the identification of soluble biomarkers in fresh tissues

PubMed Central

Bellahcène, Akeila; Hirano, Touko; Peulen, Olivier; Blomme, Arnaud; Hennequière, Vincent; Mutijima, Eugene; Boniver, Jacques; Meuwis, Marie-Alice; Josse, Claire; Koopmansch, Benjamin; Segers, Karin; Yokobori, Takehiko; Fahmy, Karim; Thiry, Marc; Coimbra, Carla; Garbacki, Nancy; Colige, Alain; Baiwir, Dominique; Bours, Vincent; Louis, Edouard; Detry, Olivier; Delvenne, Philippe; Nishiyama, Masahiko; Castronovo, Vincent

2018-01-01

The identification of diagnostic and prognostic biomarkers from early lesions, measurable in liquid biopsies remains a major challenge, particularly in oncology. Fresh human material of high quality is required for biomarker discovery but is often not available when it is totally required for clinical pathology investigation. Hence, all OMICs studies are done on residual and less clinically relevant biological samples. Here after, we present an innovative, simple, and non-destructive, procedure named EXPEL that uses rapid, pressure-assisted, interstitial fluid extrusion, preserving the specimen for full routine clinical pathology investigation. In the meantime, the technique allows a comprehensive OMICs analysis (proteins, metabolites, miRNAs and DNA). As proof of concept, we have applied EXPEL on freshly collected human colorectal cancer and liver metastases tissues. We demonstrate that the procedure efficiently allows the extraction, within a few minutes, of a wide variety of biomolecules holding diagnostic and prognostic potential while keeping both tissue morphology and antigenicity unaltered. Our method enables, for the first time, both clinicians and scientists to explore identical clinical material regardless of its origin and size, which has a major positive impact on translation to the clinic. PMID:29535834

Non-Halal biomarkers identification based on Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography-Time of Flight Mass Spectroscopy (GC-TOF MS) techniques

NASA Astrophysics Data System (ADS)

Witjaksono, Gunawan; Saputra, Irwan; Latief, Marsad; Jaswir, Irwandi; Akmeliawati, Rini; Abdelkreem Saeed Rabih, Almur

2017-11-01

Consumption of meat from halal (lawful) sources is essential for Muslims. The identification of non-halal meat is one of the main issues that face consumers in meat markets, especially in non-Islamic countries. Pig is one of the non-halal sources of meat, and hence pig meat and its derivatives are forbidden for Muslims to consume. Although several studies have been conducted to identify the biomarkers for nonhalal meats like pig meat, these studies are still in their infancy stages, and as a result there is no universal biomarker which could be used for clear cut identification. The purpose of this paper is to use Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography-Time of Flight Mass Spectroscopy (GC-TOF MS) techniques to study fat of pig, cow, lamb and chicken to find possible biomarkers for pig fat (lard) identification. FTIR results showed that lard and chicken fat have unique peaks at wavenumbers 1159.6 cm-1, 1743.4 cm-1, 2853.1 cm-1 and 2922.5 cm-1 compared to lamb and beef fats which did not show peaks at these wavenumbers. On the other hand, GC/MS-TOF results showed that the concentration of 1,2,3-trimethyl-Benzene, Indane, and Undecane in lard are 250, 14.5 and 1.28 times higher than their concentrations in chicken fat, respectively, and 91.4, 2.3 and 1.24 times higher than their concentrations in cow fat, respectively. These initial results clearly indicate that there is a possibility to find biomarkers for non-halal identification.

Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.

PubMed

Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne

2018-01-10

Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.

Analysis of the ectoenzymes ADA, ALP, ENPP1, and ENPP3, in the contents of ovarian endometriomas as candidate biomarkers of endometriosis.

PubMed

Trapero, Carla; Jover, Lluis; Fernández-Montolí, Maria Eulàlia; García-Tejedor, Amparo; Vidal, August; Gómez de Aranda, Inmaculada; Ponce, Jordi; Matias-Guiu, Xavier; Martín-Satué, Mireia

2018-02-01

The diagnosis of endometriosis, a prevalent chronic disease with a strong inflammatory component, is usually delayed due to the lack of noninvasive diagnostic tests. Purinergic signaling, a key cell pathway, is altered in many inflammatory disorders. The aim of the present work was to evaluate the levels of adenosine deaminase (ADA), alkaline phosphatase (ALP), ecto-nucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1), and ENPP3, elements of purinergic signaling, as biomarker candidates for endometriosis. A case-control comparative study was conducted to determine ADA, ALP, ENPP1 and ENPP3 levels in echo-guided aspirated fluids of endometriomas (case group) and simple ovarian cysts (control group) using the ELISA technique. Adenosine deaminase, ALP, ENPP1, and ENPP3 were present and quantifiable in the contents of endometriomas and simple cysts. There were significant differences in ADA and ENPP1 levels in endometriomas in comparison with simple cysts (2787 U/L and 103.9 ng/mL more in endometriomas, for ADA and ENPP1, respectively). Comparisons of ALP and ENPP3 levels between the two groups did not reveal significant differences. The ectoenzymes ADA and ENPP1 are biomarker candidates for endometriosis. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identification of EBP50 as a Specific Biomarker for Carcinogens Via the Analysis of Mouse Lymphoma Cellular Proteome

PubMed Central

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-01-01

To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens. PMID:22434383

Identification of EBP50 as a specific biomarker for carcinogens via the analysis of mouse lymphoma cellular proteome.

PubMed

Lee, Yoen Jung; Choi, In-Kwon; Sheen, Yhun Yhong; Park, Sue Nie; Kwon, Ho Jeong

2012-03-01

To identify specific biomarkers generated upon exposure of L5178Y mouse lymphoma cells to carcinogens, 2-DE and MALDI-TOF MS analysis were conducted using the cellular proteome of L5178Y cells that had been treated with the known carcinogens, 1,2-dibromoethane and O-nitrotoluene and the noncarcinogens, emodin and D-mannitol. Eight protein spots that showed a greater than 1.5-fold increase or decrease in intensity following carcinogen treatment compared with treatment with noncarcinogens were selected. Of the identified proteins, we focused on the candidate biomarker ERM-binding phosphoprotein 50 (EBP50), the expression of which was specifically increased in response to treatment with the carcinogens. The expression level of EBP50 was determined by western analysis using polyclonal rabbit anti-EBP50 antibody. Further, the expression level of EBP50 was increased in cells treated with seven additional carcinogens, verifying that EBP50 could serve as a specific biomarker for carcinogens.

Experimental Design in Clinical 'Omics Biomarker Discovery.

PubMed

Forshed, Jenny

2017-11-03

This tutorial highlights some issues in the experimental design of clinical 'omics biomarker discovery, how to avoid bias and get as true quantities as possible from biochemical analyses, and how to select samples to improve the chance of answering the clinical question at issue. This includes the importance of defining clinical aim and end point, knowing the variability in the results, randomization of samples, sample size, statistical power, and how to avoid confounding factors by including clinical data in the sample selection, that is, how to avoid unpleasant surprises at the point of statistical analysis. The aim of this Tutorial is to help translational clinical and preclinical biomarker candidate research and to improve the validity and potential of future biomarker candidate findings.

Safety Lead Optimization and Candidate Identification: Integrating New Technologies into Decision-Making.

PubMed

Dambach, Donna M; Misner, Dinah; Brock, Mathew; Fullerton, Aaron; Proctor, William; Maher, Jonathan; Lee, Dong; Ford, Kevin; Diaz, Dolores

2016-04-18

Discovery toxicology focuses on the identification of the most promising drug candidates through the development and implementation of lead optimization strategies and hypothesis-driven investigation of issues that enable rational and informed decision-making. The major goals are to [a] identify and progress the drug candidate with the best overall drug safety profile for a therapeutic area, [b] remove the most toxic drugs from the portfolio prior to entry into humans to reduce clinical attrition due to toxicity, and [c] establish a well-characterized hazard and translational risk profile to enable clinical trial designs. This is accomplished through a framework that balances the multiple considerations to identify a drug candidate with the overall best drug characteristics and provides a cogent understanding of mechanisms of toxicity. The framework components include establishing a target candidate profile for each program that defines the qualities of a successful candidate based on the intended therapeutic area, including the risk tolerance for liabilities; evaluating potential liabilities that may result from engaging the therapeutic target (pharmacology-mediated or on-target) and that are chemical structure-mediated (off-target); and characterizing identified liabilities. Lead optimization and investigation relies upon the integrated use of a variety of technologies and models (in silico, in vitro, and in vivo) that have achieved a sufficient level of qualification or validation to provide confidence in their use. We describe the strategic applications of various nonclinical models (established and new) for a holistic and integrated risk assessment that is used for rational decision-making. While this review focuses on strategies for small molecules, the overall concepts, approaches, and technologies are generally applicable to biotherapeutics.

Molecular Diagnosis and Biomarker Identification on SELDI proteomics data by ADTBoost method.

PubMed

Wang, Lu-Yong; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

Clinical proteomics is an emerging field that will have great impact on molecular diagnosis, identification of disease biomarkers, drug discovery and clinical trials in the post-genomic era. Protein profiling in tissues and fluids in disease and pathological control and other proteomics techniques will play an important role in molecular diagnosis with therapeutics and personalized healthcare. We introduced a new robust diagnostic method based on ADTboost algorithm, a novel algorithm in proteomics data analysis to improve classification accuracy. It generates classification rules, which are often smaller and easier to interpret. This method often gives most discriminative features, which can be utilized as biomarkers for diagnostic purpose. Also, it has a nice feature of providing a measure of prediction confidence. We carried out this method in amyotrophic lateral sclerosis (ALS) disease data acquired by surface enhanced laser-desorption/ionization-time-of-flight mass spectrometry (SELDI-TOF MS) experiments. Our method is shown to have outstanding prediction capacity through the cross-validation, ROC analysis results and comparative study. Our molecular diagnosis method provides an efficient way to distinguish ALS disease from neurological controls. The results are expressed in a simple and straightforward alternating decision tree format or conditional format. We identified most discriminative peaks in proteomic data, which can be utilized as biomarkers for diagnosis. It will have broad application in molecular diagnosis through proteomics data analysis and personalized medicine in this post-genomic era.

LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data.

PubMed

Koelmel, Jeremy P; Kroeger, Nicholas M; Ulmer, Candice Z; Bowden, John A; Patterson, Rainey E; Cochran, Jason A; Beecher, Christopher W W; Garrett, Timothy J; Yost, Richard A

2017-07-10

Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiology. We introduce LipidMatch, an R-based tool for lipid identification for liquid chromatography tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be observed for identification. Rule-based identification allows for correct annotation of lipids based on the fragments observed, unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of experimental fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in positive mode and 98% in negative ion mode. LipidMatch allows users to annotate lipids across a wide range of high resolution tandem mass spectrometry

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

PubMed Central

Fleisher, Brett; Clarke, Charlotte; Ait-Oudhia, Sihem

2016-01-01

Triple-negative breast cancer (TNBC) is a complex heterogeneous disease characterized by the absence of three hallmark receptors: human epidermal growth factor receptor 2, estrogen receptor, and progesterone receptor. Compared to other breast cancer subtypes, TNBC is more aggressive, has a higher prevalence in African-Americans, and more frequently affects younger patients. Currently, TNBC lacks clinically accepted targets for tailored therapy, warranting the need for candidate biomarkers. BiomarkerBase, an online platform used to find biomarkers reported in clinical trials, was utilized to screen all potential biomarkers for TNBC and select only the ones registered in completed TNBC trials through clinicaltrials.gov. The selected candidate biomarkers were classified as surrogate, prognostic, predictive, or pharmacodynamic (PD) and organized by location in the blood, on the cell surface, in the cytoplasm, or in the nucleus. Blood biomarkers include vascular endothelial growth factor/vascular endothelial growth factor receptor and interleukin-8 (IL-8); cell surface biomarkers include EGFR, insulin-like growth factor binding protein, c-Kit, c-Met, and PD-L1; cytoplasm biomarkers include PIK3CA, pAKT/S6/p4E-BP1, PTEN, ALDH1, and the PIK3CA/AKT/mTOR-related metabolites; and nucleus biomarkers include BRCA1, the gluco-corticoid receptor, TP53, and Ki67. Candidate biomarkers were further organized into a “cellular protein network” that demonstrates potential connectivity. This review provides an inventory and reference point for promising biomarkers for breakthrough targeted therapies in TNBC. PMID:27785100

Comparison of Protein Immunoprecipitation-Multiple Reaction Monitoring with ELISA for Assay of Biomarker Candidates in Plasma

PubMed Central

2013-01-01

Quantitative analysis of protein biomarkers in plasma is typically done by ELISA, but this method is limited by the availability of high-quality antibodies. An alternative approach is protein immunoprecipitation combined with multiple reaction monitoring mass spectrometry (IP-MRM). We compared IP-MRM to ELISA for the analysis of six colon cancer biomarker candidates (metalloproteinase inhibitor 1 (TIMP1), cartilage oligomeric matrix protein (COMP), thrombospondin-2 (THBS2), endoglin (ENG), mesothelin (MSLN) and matrix metalloproteinase-9 (MMP9)) in plasma from colon cancer patients and noncancer controls. Proteins were analyzed by multiplex immunoprecipitation from plasma with the ELISA capture antibodies, further purified by SDS-PAGE, digested and analyzed by stable isotope dilution MRM. IP-MRM provided linear responses (r = 0.978–0.995) between 10 and 640 ng/mL for the target proteins spiked into a “mock plasma” matrix consisting of 60 mg/mL bovine serum albumin. Measurement variation (coefficient of variation at the limit of detection) for IP-MRM assays ranged from 2.3 to 19%, which was similar to variation for ELISAs of the same samples. IP-MRM and ELISA measurements for all target proteins except ENG were highly correlated (r = 0.67–0.97). IP-MRM with high-quality capture antibodies thus provides an effective alternative method to ELISA for protein quantitation in biological fluids. PMID:24224610

Identification of novel biomarker candidates for hypertrophic cardiomyopathy and other cardiovascular diseases leading to heart failure.

PubMed

Rehulkova, H; Rehulka, P; Myslivcova Fucikova, A; Stulik, J; Pudil, R

2016-11-23

In-depth proteome discovery analysis represents new strategy in an effort to identify novel reliable specific protein markers for hypertrophic cardiomyopathy and other life threatening cardiovascular diseases. To systematically identify novel protein biomarkers of cardiovascular diseases with high mortality we employed an isobaric tag for relative and absolute quantitation (iTRAQ) proteome technology to make comparative analysis of plasma samples obtained from patients suffering from non-obstructive hypertrophic cardiomyopathy, stable dilated cardiomyopathy, aortic valve stenosis, chronic stable coronary artery disease and stable arterial hypertension. We found 128 plasma proteins whose abundances were uniquely regulated among the analyzed cardiovascular pathologies. 49 of them have not been described yet. Additionally, application of statistical exploratory analyses of the measured protein profiles indicated the relationship in pathophysiology of the examined cardiovascular pathologies.

Emerging biomarkers for cancer immunotherapy in melanoma.

PubMed

Axelrod, Margaret L; Johnson, Douglas B; Balko, Justin M

2017-09-14

The treatment and prognosis of metastatic melanoma has changed substantially since the advent of novel immune checkpoint inhibitors (ICI), agents that enhance the anti-tumor immune response. Despite the success of these agents, clinically actionable biomarkers to aid patient and regimen selection are lacking. Herein, we summarize and review the evidence for candidate biomarkers of response to ICIs in melanoma. Many of these candidates can be examined as parts of a known molecular pathway of immune response, while others are clinical in nature. Due to the ability of ICIs to illicit dramatic and durable responses, well-validated biomarkers that can be effectively implemented in the clinic will require strong negative predictive values that do not limit patients with who may benefit from ICI therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma

PubMed Central

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

Background There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Methods Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. Results The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. Conclusions TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC. PMID:27798689

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma.

PubMed

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC.

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.

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

PubMed

Crager, Michael R; Ahmed, Murat

2014-01-01

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

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

Identification of Biomarkers of Exposure to FTOHs and PAPs in Humans Using a Targeted and Nontargeted Analysis Approach.

PubMed

Dagnino, Sonia; Strynar, Mark J; McMahen, Rebecca L; Lau, Christopher S; Ball, Carol; Garantziotis, Stavros; Webster, Thomas F; McClean, Michael D; Lindstrom, Andrew B

2016-09-20

Although historic perfluorinated compounds are currently under scrutiny and growing regulatory control in the world, little is known about human exposure to other polyfluorinated compounds presently in use. Fluorotelomer alcohols (FTOHs) and polyfluoroalkyl phosphate esters (PAPs) are known to degrade to terminal perfluorinated acids and toxic reactive intermediates through metabolic pathways. Therefore, it is important to characterize their human exposure by the identification of unique biomarkers. With the use of liquid chromatography-mass spectrometry-time-of-flight analysis (LC-MS-TOF), we developed a workflow for the identification of metabolites for the 8:2 FTOH and 8:2 diPAP. Analysis of serum and urine of dosed rats indicated the 8:2 FTOH-sulfate and the 8:2 diPAP as potential biomarkers. These compounds, as well as 25 other fluorinated compounds and metabolites, were analyzed in human serum and urine samples from the general population (n = 100) and office workers (n = 30). The 8:2 FTOH-sulfate was measured for the first time in human samples in 5 to 10% of the serum samples, ranging from 50 to 80 pg/mL. The 8:2 diPAP was measured in 58% of the samples, ranging from 100 to 800 pg/mL. This study indicates the FTOH-sulfate conjugate as a biomarker of exposure to FTOHs and PAPs in humans.

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

PubMed

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

2015-07-02

Lung cancer is the leading cause of cancer-related deaths and has an overall 5-year survival rate lower than 15%. Large-scale clinical trials have demonstrated a significant relative reduction in mortality in high-risk individuals with low-dose computed tomography screening. However, biomarkers capable of identifying the most at-risk population and detecting lung cancer before it becomes clinically apparent are urgently needed in the clinic. Here, we report the identification of urine biomarkers capable of detecting lung cancer. Using the well-characterized inducible Kras (G12D) mouse model of lung cancer, we identified alterations in the urine proteome in tumor-bearing mice compared with sibling controls. Marked differences at the proteomic level were also detected between the urine of patients and that of healthy population controls. Importantly, we identified 7 proteins commonly found to be significantly up-regulated in both tumor-bearing mice and patients. In an independent cohort, we showed that 2 of the 7 proteins were up-regulated in urine samples from lung cancer patients but not in those from controls. The kinetics of these proteins correlated with the disease state in the mouse model. These tumor biomarkers could potentially aid in the early detection of lung cancer.

Identification and localization of trauma-related biomarkers using matrix assisted laser desorption/ionization imaging mass spectrometry

NASA Astrophysics Data System (ADS)

Jones, Kirstin; Reilly, Matthew A.; Glickman, Randolph D.

2017-02-01

Current treatments for ocular and optic nerve trauma are largely ineffective and may have adverse side effects; therefore, new approaches are needed to understand trauma mechanisms. Identification of trauma-related biomarkers may yield insights into the molecular aspects of tissue trauma that can contribute to the development of better diagnostics and treatments. The conventional approach for protein biomarker measurement largely relies on immunoaffinity methods that typically can only be applied to analytes for which antibodies or other targeting means are available. Matrix assisted laser-assisted desorption/ionization imaging mass spectrometry (MALDI-IMS) is a specialized application of mass spectrometry that not only is well suited to the discovery of novel or unanticipated biomarkers, but also provides information about the spatial localization of biomarkers in tissue. We have been using MALDI-IMS to find traumarelated protein biomarkers in retina and optic nerve tissue from animal models subjected to ocular injury produced by either blast overpressure or mechanical torsion. Work to date by our group, using MALDI-IMS, found that the pattern of protein expression is modified in the injured ocular tissue as soon as 24 hr post-injury, compared to controls. Specific proteins may be up- or down-regulated by trauma, suggesting different tissue responses to a given injury. Ongoing work is directed at identifying the proteins affected and mapping their expression in the ocular tissue, anticipating that systematic analysis can be used to identify targets for prospective therapies for ocular trauma.

Identification of specific bovine blood biomarkers with a non-targeted approach using HPLC ESI tandem mass spectrometry.

PubMed

Lecrenier, M C; Marbaix, H; Dieu, M; Veys, P; Saegerman, C; Raes, M; Baeten, V

2016-12-15

Animal by-products are valuable protein sources in animal nutrition. Among them are blood products and blood meal, which are used as high-quality material for their beneficial effects on growth and health. Within the framework of the feed ban relaxation, the development of complementary methods in order to refine the identification of processed animal proteins remains challenging. The aim of this study was to identify specific biomarkers that would allow the detection of bovine blood products and processed animal proteins using tandem mass spectrometry. Seventeen biomarkers were identified: nine peptides for bovine plasma powder; seven peptides for bovine haemoglobin powder, including six peptides for bovine blood meal; and one peptide for porcine blood. They were not detected in several commercial compound feed or feed materials, such as blood by-products of other animal origins, milk-derived products and fish meal. These biomarkers could be used for developing a species-specific and blood-specific detection method. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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

PubMed Central

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

2008-01-01

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

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity

PubMed Central

Barkla, Bronwyn J.

2016-01-01

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised. PMID:28248236

Identification of Abiotic Stress Protein Biomarkers by Proteomic Screening of Crop Cultivar Diversity.

PubMed

Barkla, Bronwyn J

2016-09-08

Modern day agriculture practice is narrowing the genetic diversity in our food supply. This may compromise the ability to obtain high yield under extreme climactic conditions, threatening food security for a rapidly growing world population. To identify genetic diversity, tolerance mechanisms of cultivars, landraces and wild relatives of major crops can be identified and ultimately exploited for yield improvement. Quantitative proteomics allows for the identification of proteins that may contribute to tolerance mechanisms by directly comparing protein abundance under stress conditions between genotypes differing in their stress responses. In this review, a summary is provided of the data accumulated from quantitative proteomic comparisons of crop genotypes/cultivars which present different stress tolerance responses when exposed to various abiotic stress conditions, including drought, salinity, high/low temperature, nutrient deficiency and UV-B irradiation. This field of research aims to identify molecular features that can be developed as biomarkers for crop improvement, however without accurate phenotyping, careful experimental design, statistical robustness and appropriate biomarker validation and verification it will be challenging to deliver what is promised.

Nonclinical safety biomarkers of drug-induced vascular injury: current status and blueprint for the future.

PubMed

Mikaelian, Igor; Cameron, Mark; Dalmas, Deidre A; Enerson, Bradley E; Gonzalez, Raymond J; Guionaud, Silvia; Hoffmann, Peter K; King, Nicholas M P; Lawton, Michael P; Scicchitano, Marshall S; Smith, Holly W; Thomas, Roberta A; Weaver, James L; Zabka, Tanja S

2014-06-01

Better biomarkers are needed to identify, characterize, and/or monitor drug-induced vascular injury (DIVI) in nonclinical species and patients. The Predictive Safety Testing Consortium (PSTC), a precompetitive collaboration of pharmaceutical companies and the U.S. Food and Drug Administration (FDA), formed the Vascular Injury Working Group (VIWG) to develop and qualify translatable biomarkers of DIVI. The VIWG focused its research on acute DIVI because early detection for clinical and nonclinical safety monitoring is desirable. The VIWG developed a strategy based on the premise that biomarkers of DIVI in rat would be translatable to humans due to the morphologic similarity of vascular injury between species regardless of mechanism. The histomorphologic lexicon for DIVI in rat defines degenerative and adaptive findings of the vascular endothelium and smooth muscles, and characterizes inflammatory components. We describe the mechanisms of these changes and their associations with candidate biomarkers for which advanced analytical method validation was completed. Further development is recommended for circulating microRNAs, endothelial microparticles, and imaging techniques. Recommendations for sample collection and processing, analytical methods, and confirmation of target localization using immunohistochemistry and in situ hybridization are described. The methods described are anticipated to aid in the identification and qualification of translational biomarkers for DIVI. © 2014 by The Author(s).

Factors and Trends Affecting the Identification of a Reliable Biomarker for Diesel Exhaust Exposure

PubMed Central

2014-01-01

The monitoring of human exposures to diesel exhaust continues to be a vexing problem for specialists seeking information on the potential health effects of this ubiquitous combustion product. Exposure biomarkers have yielded a potential solution to this problem by providing a direct measure of an individual's contact with key components in the exhaust stream. Spurred by the advent of new, highly sensitive, analytical methods capable of detecting substances at very low levels, there have been numerous attempts at identifying a stable and specific biomarker. Despite these new techniques, there is currently no foolproof method for unambiguously separating diesel exhaust exposures from those arising from other combustion sources. Diesel exhaust is a highly complex mixture of solid, liquid, and gaseous components whose exact composition can be affected by many variables, including engine technology, fuel composition, operating conditions, and photochemical aging. These factors together with those related to exposure methodology, epidemiological necessity, and regulatory reform can have a decided impact on the success or failure of future research aimed at identifying a suitable biomarker of exposure. The objective of this review is to examine existing information on exposure biomarkers for diesel exhaust and to identify those factors and trends that have had an impact on the successful identification of metrics for both occupational and community settings. The information will provide interested parties with a template for more thoroughly understanding those factors affecting diesel exhaust emissions and for identifying those substances and research approaches holding the greatest promise for future success. PMID:25170242

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

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

RNA Sequencing Identifies Novel Translational Biomarkers of Kidney Fibrosis

PubMed Central

Craciun, Florin L.; Bijol, Vanesa; Ajay, Amrendra K.; Rao, Poornima; Kumar, Ramya K.; Hutchinson, John; Hofmann, Oliver; Joshi, Nikita; Luyendyk, James P.; Kusebauch, Ulrike; Moss, Christopher L.; Srivastava, Anand; Himmelfarb, Jonathan; Waikar, Sushrut S.; Moritz, Robert L.

2016-01-01

CKD is the gradual, asymptomatic loss of kidney function, but current tests only identify CKD when significant loss has already happened. Several potential biomarkers of CKD have been reported, but none have been approved for preclinical or clinical use. Using RNA sequencing in a mouse model of folic acid-induced nephropathy, we identified ten genes that track kidney fibrosis development, the common pathologic finding in patients with CKD. The gene expression of all ten candidates was confirmed to be significantly higher (approximately ten- to 150-fold) in three well established, mechanistically distinct mouse models of kidney fibrosis than in models of nonfibrotic AKI. Protein expression of these genes was also high in the folic acid model and in patients with biopsy-proven kidney fibrosis. mRNA expression of the ten genes increased with increasing severity of kidney fibrosis, decreased in response to therapeutic intervention, and increased only modestly (approximately two- to five-fold) with liver fibrosis in mice and humans, demonstrating specificity for kidney fibrosis. Using targeted selected reaction monitoring mass spectrometry, we detected three of the ten candidates in human urine: cadherin 11 (CDH11), macrophage mannose receptor C1 (MRC1), and phospholipid transfer protein (PLTP). Furthermore, urinary levels of each of these three proteins distinguished patients with CKD (n=53) from healthy individuals (n=53; P<0.05). In summary, we report the identification of urinary CDH11, MRC1, and PLTP as novel noninvasive biomarkers of CKD. PMID:26449608

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.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

Identification of 10 Candidate Biomarkers Distinguishing Tuberculous and Malignant Pleural Fluid by Proteomic Methods.

PubMed

Lee, Chang Youl; Hong, Ji Young; Lee, Myung Goo; Suh, In Bum

2017-11-01

Pleural effusion, an accumulation of fluid in the pleural space, usually occurs in patients when the rate of fluid formation exceeds the rate of fluid removal. The differential diagnosis of tuberculous pleurisy and malignant pleural effusion is a difficult task in high tuberculous prevalence areas. The aim of the present study was to identify novel biomarkers for the diagnosis of pleural fluid using proteomics technology. We used samples from five patients with transudative pleural effusions for internal standard, five patients with tuberculous pleurisy, and the same numbers of patients having malignant effusions were enrolled in the study. We analyzed the proteins in pleural fluid from patients using a technique that combined two-dimensional liquid-phase electrophoresis and matrix assisted laser desorption/ionization-time of flight-mass spectrometry. We identified a total of 10 proteins with statistical significance. Among 10 proteins, trasthyretin, haptoglobin, metastasis-associated protein 1, t-complex protein 1, and fibroblast growth factor-binding protein 1 were related with malignant pleural effusions and human ceruloplasmin, lysozyme precursor, gelsolin, clusterin C complement lysis inhibitor, and peroxirexdoxin 3 were expressed several times or more in tuberculous pleural effusions. Highly expressed proteins in malignant pleural effusion were associated with carcinogenesis and cell growth, and proteins associated with tuberculous pleural effusion played a role in the response to inflammation and fibrosis. These findings will aid in the development of novel diagnostic tools for tuberculous pleurisy and malignant pleural effusion of lung cancer. © Copyright: Yonsei University College of Medicine 2017

Antibody arrays in biomarker discovery.

PubMed

Wilson, Jarad J; Burgess, Rob; Mao, Ying-Qing; Luo, Shuhong; Tang, Hao; Jones, Valerie Sloane; Weisheng, Bao; Huang, Ren-Yu; Chen, Xuesong; Huang, Ruo-Pan

2015-01-01

All of life is regulated by complex and organized chemical reactions that help dictate when to grow, to move, to reproduce, and to die. When these processes go awry, or are interrupted by pathological agents, diseases such as cancer, autoimmunity, or infections can result. Cytokines, chemokines, growth factors, adipokines, and other chemical moieties make up a vast subset of these chemical reactions that are altered in disease states, and monitoring changes in these molecules could provide for the identification of disease biomarkers. From the first identification of carcinoembryonic antigen, to the discovery of prostate-specific antigen, to numerous others described within, biomarkers of disease are detectable in a plethora of sample types. The growing number of biomarkers for infection, autoimmunity, and cancer allow for increasingly early detection, to identification of novel drug targets, to prognostic indicators of disease outcome. However, more and more studies are finding that a single cytokine or growth factor is insufficient as a true disease biomarker and that a more global perspective is needed to understand true disease biology. Such a broad view requires a multiplexed platform for chemical detection, and antibody arrays meet and exceed this need by performing this detection in a high-throughput fashion. Herein, we will discuss how antibody arrays have evolved, and how they have helped direct new drug target design, helped identify therapeutic disease markers, and helped in earlier disease detection. From asthma to renal disease, and neurological dysfunction to immunologic disorders, antibody arrays afford a bright future for new biomarkers discovery. © 2015 Elsevier Inc. All rights reserved.

CNS Injury: Posttranslational Modification of the Tau Protein as a Biomarker.

PubMed

Caprelli, Mitchell T; Mothe, Andrea J; Tator, Charles H

2017-11-01

The ideal biomarker for central nervous system (CNS) trauma in patients would be a molecular marker specific for injured nervous tissue that would provide a consistent and reliable assessment of the presence and severity of injury and the prognosis for recovery. One candidate biomarker is the protein tau, a microtubule-associated protein abundant in the axonal compartment of CNS neurons. Following axonal injury, tau becomes modified primarily by hyperphosphorylation of its various amino acid residues and cleavage into smaller fragments. These posttrauma products can leak into the cerebrospinal fluid or bloodstream and become candidate biomarkers of CNS injury. This review examines the primary molecular changes that tau undergoes following traumatic brain injury and spinal cord injury, and reviews the current literature in traumatic CNS biomarker research with a focus on the potential for hyperphosphorylated and cleaved tau as sensitive biomarkers of injury.

Molecular biomarkers for grass pollen immunotherapy

PubMed Central

Popescu, Florin-Dan

2014-01-01

Grass pollen allergy represents a significant cause of allergic morbidity worldwide. Component-resolved diagnosis biomarkers are increasingly used in allergy practice in order to evaluate the sensitization to grass pollen allergens, allowing the clinician to confirm genuine sensitization to the corresponding allergen plant sources and supporting an accurate prescription of allergy immunotherapy (AIT), an important approach in many regions of the world with great plant biodiversity and/or where pollen seasons may overlap. The search for candidate predictive biomarkers for grass pollen immunotherapy (tolerogenic dendritic cells and regulatory T cells biomarkers, serum blocking antibodies biomarkers, especially functional ones, immune activation and immune tolerance soluble biomarkers and apoptosis biomarkers) opens new opportunities for the early detection of clinical responders for AIT, for the follow-up of these patients and for the development of new allergy vaccines. PMID:25237628

MFAP4: a candidate biomarker for hepatic and pulmonary fibrosis?

PubMed

Mölleken, Christian; Poschmann, Gereon; Bonella, Francesco; Costabel, Ulrich; Sitek, Barbara; Stühler, Kai; Meyer, Helmut E; Schmiegel, Wolff H; Marcussen, Niels; Helmer, Michael; Nielsen, Ole; Hansen, Søren; Schlosser, Anders; Holmskov, Uffe; Sorensen, Grith Lykke

2016-03-29

Several comparable mechanisms have been identified for hepatic and pulmonary fibrosis. The human microfibrillar associated glycoprotein 4 (MFAP4), produced by activated myofibroblasts, is a ubiquitous protein playing a potential role in extracellular matrix (ECM) turnover and was recently identified as biomarker for hepatic fibrosis in hepatitis C patients. The current study aimed to evaluate serum levels of MFAP4 in patients with pulmonary fibrosis in order to test its potential as biomarker in clinical practice. A further aim was to determine whether MFAP4 deficiency in mice affects the formation of pulmonary fibrosis in the bleomycin model of lung fibrosis. 91 patients with idiopathic pulmonary fibrosis (IPF), 23 with hypersensitivity pneumonitis (HP) and 31 healthy subjects were studied. In the mouse model, C57BL/6 Mfap4+/+ and Mfap4-/- mice between 6-8 weeks of age were studied. Serum levels of MFAP4 were measured by ELISA in patients and in mice. Surfactant protein D (SP-D) and LDH were measured as comparison biomarkers in patients with pulmonary fibrosis. Morphometric assessment and the Sircol kit were used to determine the amount of collagen in the lung tissue in the mouse model. Serum levels of MFAP4 were not elevated in lung fibrosis - neither in the patients with IPF or HP nor in the animal model. Furthermore no significant correlations with pulmonary function tests of IPF patients could be found for MFAP4. MFAP4 levels were increased in BAL of bleomycin treated mice with pulmonary fibrosis. MFAP4 is not elevated in sera of patients with pulmonary fibrosis or bleomycin treated mice with pulmonary fibrosis. This may be due to different pathogenic mechanisms of liver and lung fibrogenesis. MFAP4 seems to be useful as serum biomarker for hepatic but not for lung fibrosis.

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

PubMed Central

Tonry, Claire L.; Leacy, Emma; Raso, Cinzia; Finn, Stephen P.; Armstrong, John; Pennington, Stephen R.

2016-01-01

Prostate Cancer (PCa) is the second most commonly diagnosed cancer in men worldwide. Although increased expression of prostate-specific antigen (PSA) is an effective indicator for the recurrence of PCa, its intended use as a screening marker for PCa is of considerable controversy. Recent research efforts in the field of PCa biomarkers have focused on the identification of tissue and fluid-based biomarkers that would be better able to stratify those individuals diagnosed with PCa who (i) might best receive no treatment (active surveillance of the disease); (ii) would benefit from existing treatments; or (iii) those who are likely to succumb to disease recurrence and/or have aggressive disease. The growing demand for better prostate cancer biomarkers has coincided with the development of improved discovery and evaluation technologies for multiplexed measurement of proteins in bio-fluids and tissues. This review aims to (i) provide an overview of these technologies as well as describe some of the candidate PCa protein biomarkers that have been discovered using them; (ii) address some of the general limitations in the clinical evaluation and validation of protein biomarkers; and (iii) make recommendations for strategies that could be adopted to improve the successful development of protein biomarkers to deliver improvements in personalized PCa patient decision making. PMID:27438858

Progress on the biomarkers for tuberculosis diagnosis.

PubMed

Fu, Tiwei; Xie, Jianping

2011-01-01

Tuberculosis (TB) remains a major threat to global health. Biomarkers derived from pathogen-host interaction can facilitate the monitoring of active TB. The recent progress regarding such biomarkers is summarized, including those can be used from serum, sputum, urine, or breath monitoring. A wide range of potential biomarkers such as protein antigens, cell-free nucleic acids, and lipoarabinomannose were compiled. The possible use of biomarkers for infection identification and monitoring drug efficacy are also presented.

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

Identification of quantitative trait loci and candidate genes for cadmium tolerance in Populus

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

Induri, Brahma R; Ellis, Danielle R; Slavov, Goncho T.

2012-01-01

Understanding genetic variation for the response of Populus to heavy metals like cadmium (Cd) is an important step in elucidating the underlying mechanisms of tolerance. In this study, a pseudo-backcross pedigree of Populus trichocarpa Torr. & Gray and Populus deltoides Bart. was characterized for growth and performance traits after Cd exposure. A total of 16 quantitative trait loci (QTL) at logarithm of odds (LOD) ratio 2.5 were detected for total dry weight, its components and root volume. Major QTL for Cd responses were mapped to two different linkage groups and the relative allelic effects were in opposing directions on themore » two chromosomes, suggesting differential mechanisms at these two loci. The phenotypic variance explained by Cd QTL ranged from 5.9 to 11.6% and averaged 8.2% across all QTL. A whole-genome microarray study led to the identification of nine Cd-responsive genes from these QTL. Promising candidates for Cd tolerance include an NHL repeat membrane-spanning protein, a metal transporter and a putative transcription factor. Additional candidates in the QTL intervals include a putative homolog of a glutamate cysteine ligase, and a glutathione-S-transferase. Functional characterization of these candidate genes should enhance our understanding of Cd metabolism and transport and phytoremediation capabilities of Populus.« less

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates.

PubMed

Alanazi, Ibrahim O; AlYahya, Sami A; Ebrahimie, Esmaeil; Mohammadi-Dehcheshmeh, Manijeh

2018-06-15

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer. Particular attention was paid to non-coding biomarkers. In total, 60 MicroRNA biomarkers were reported for lung cancer, including some prognostic biomarkers. MIR21, MIR155, MALAT1, and MIR31 were the top non-coding RNA biomarkers of lung cancer. Text mining identified 447 proteins which have been studied as biomarkers in lung cancer. EGFR (receptor), TP53 (transcription factor), KRAS, CDKN2A, ENO2, KRT19, RASSF1, GRP (ligand), SHOX2 (transcription factor), and ERBB2 (receptor) were the most studied proteins. Within small molecules, thymosin-a1, oestrogen, and 8-OHdG have received more attention. We found some chromosomal bands, such as 7q32.2, 18q12.1, 6p12, 11p15.5, and 3p21.3 that are highly involved in deriving lung cancer biomarkers. Copyright © 2018 Elsevier B.V. All rights reserved.

Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds.

PubMed

Nagaraja, Sridevi; Chen, Lin; DiPietro, Luisa A; Reifman, Jaques; Mitrophanov, Alexander Y

2018-02-20

Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.

Sexual characteristics of male guppies Poecilia reticulata serve as effect biomarkers of estrogens

NASA Astrophysics Data System (ADS)

Tian, Hua; Li, Yun; Wang, Wei; Zhao, Fei; Gao, Su; Ru, Shaoguo

2017-10-01

Guppies (Poecilia reticulata) are considered a candidate model species for the identification and testing of endocrine-disrupting chemicals. Male guppies may be used to address the challenge of making potential linkages between alterations of biomarkers, both at the cellular and organ level, and adverse outcomes. In the present study, a predictive relationship between sex characteristics and reproductive output was observed in male guppies that underwent a long-term toxicity test with 0.5 μg/L 17β-estradiol administered during the juvenile period. Radioimmunoassay and western blot analyses demonstrated that 17β-estradiol exposure caused a significant increase in testicular 17β-estradiol levels as well as the induction of exposure biomarkers, namely hepatic vitellogenin. Exposure to 17β-estradiol also caused a significant decrease in testosterone levels, which consequently reduced the gonadosomatic index, sperm counts, and the coloration index. These changes of male sexual characteristics further translated into adverse influences on reproduction, as measured by a decrease in off spring production and survival rate. Our results suggest that the above-mentioned sexual characteristics of male guppies may be considered potential in vivo biomarkers of estrogen effects on reproduction.

Breast cancer and protein biomarkers

PubMed Central

Gam, Lay-Harn

2012-01-01

Breast cancer is a healthcare concern of women worldwide. Despite procedures being available for diagnosis, prognosis and treatment of breast cancer, researchers are working intensively on the disease in order to improve the life quality of breast cancer patients. At present, there is no single treatment known to bring a definite cure for breast cancer. One of the possible solutions for combating breast cancer is through identification of reliable protein biomarkers that can be effectively used for early detection, prognosis and treatments of the cancer. Therefore, the task of identification of biomarkers for breast cancer has become the focus of many researchers worldwide. PMID:24520539

Towards the identification and quantification of candidate metabolites of tebuconazole fungicide.

NASA Astrophysics Data System (ADS)

El Azhari, Najoi; Dermou, Eftychia; Botteri, Lucio; Lucini, Luigi; Karas, Panagiotis; Karpouzas, Dimitris; Tsiamis, George; Martin-Laurent, Fabrice; Trevisan, Marco; Rossi, Riccardo; Ferrari, Federico

2017-04-01

Tebuconazole belongs to the family of triazole fungicides, used for crop protection and human health applications. In the environment, the dissipation of the parent molecule leads to the formation of metabolites that are of unknown identity or toxicity. In order to identify and determine the putative identity of those metabolites and their po- tential toxicity, a quadrupole time-of-flight (Q-TOF) approach is often used. Q-SAR ap- proaches help to predict their toxicity by comparing them to a known database of mole- cules with known properties. All together the information on the candidate by-products may help to select relevant sub-set of metabolites for further quantification by LC or GC coupled with MS. It is thereby possible to select putative toxic compounds for further quanti- fication using chemical analysis. Previous work allowed the identification of potential metabolites of tebuconazole. Triazole, triazolyl acetic acid and p-chlorophenol were suspected to result from the decomposition of tebuconazole. Tebuconazole degradation kinetics was followed for 125 days by quanti- fying the dissipation of the parent molecule and the emergence of the three candidate metabolites by LC/MS for tebuconazole, triazol and triazolyl acetate and by GC/MS for p- chlorophenol. The data allowed the proposition of several metabolic pathways.

Computational prediction of human salivary proteins from blood circulation and application to diagnostic biomarker identification.

PubMed

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer.

Computational Prediction of Human Salivary Proteins from Blood Circulation and Application to Diagnostic Biomarker Identification

PubMed Central

Wang, Jiaxin; Liang, Yanchun; Wang, Yan; Cui, Juan; Liu, Ming; Du, Wei; Xu, Ying

2013-01-01

Proteins can move from blood circulation into salivary glands through active transportation, passive diffusion or ultrafiltration, some of which are then released into saliva and hence can potentially serve as biomarkers for diseases if accurately identified. We present a novel computational method for predicting salivary proteins that come from circulation. The basis for the prediction is a set of physiochemical and sequence features we found to be discerning between human proteins known to be movable from circulation to saliva and proteins deemed to be not in saliva. A classifier was trained based on these features using a support-vector machine to predict protein secretion into saliva. The classifier achieved 88.56% average recall and 90.76% average precision in 10-fold cross-validation on the training data, indicating that the selected features are informative. Considering the possibility that our negative training data may not be highly reliable (i.e., proteins predicted to be not in saliva), we have also trained a ranking method, aiming to rank the known salivary proteins from circulation as the highest among the proteins in the general background, based on the same features. This prediction capability can be used to predict potential biomarker proteins for specific human diseases when coupled with the information of differentially expressed proteins in diseased versus healthy control tissues and a prediction capability for blood-secretory proteins. Using such integrated information, we predicted 31 candidate biomarker proteins in saliva for breast cancer. PMID:24324552

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

Identification of aldolase A as a potential diagnostic biomarker for colorectal cancer based on proteomic analysis using formalin-fixed paraffin-embedded tissue.

PubMed

Yamamoto, Tetsushi; Kudo, Mitsuhiro; Peng, Wei-Xia; Takata, Hideyuki; Takakura, Hideki; Teduka, Kiyoshi; Fujii, Takenori; Mitamura, Kuniko; Taga, Atsushi; Uchida, Eiji; Naito, Zenya

2016-10-01

Colorectal cancer (CRC) is one of the most common cancers worldwide, and many patients are already at an advanced stage when they are diagnosed. Therefore, novel biomarkers for early detection of colorectal cancer are required. In this study, we performed a global shotgun proteomic analysis using formalin-fixed and paraffin-embedded (FFPE) CRC tissue. We identified 84 candidate proteins whose expression levels were differentially expressed in cancer and non-cancer regions. A label-free semiquantitative method based on spectral counting and gene ontology (GO) analysis led to a total of 21 candidate proteins that could potentially be detected in blood. Validation studies revealed cyclophilin A, annexin A2, and aldolase A mRNA and protein expression levels were significantly higher in cancer regions than in non-cancer regions. Moreover, an in vitro study showed that secretion of aldolase A into the culture medium was clearly suppressed in CRC cells compared to normal colon epithelium. These findings suggest that decreased aldolase A in blood may be a novel biomarker for the early detection of CRC.

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

Synovitis biomarkers: ex vivo characterization of three biomarkers for identification of inflammatory osteoarthritis.

PubMed

Kjelgaard-Petersen, Cecilie; Siebuhr, Anne Sofie; Christiansen, Thorbjørn; Ladel, Christoph; Karsdal, Morten; Bay-Jensen, Anne-Christine

2015-01-01

Characterize biomarkers measuring extracellular matrix turnover of inflamed osteoarthritis synovium. Human primary fibroblast-like synoviocytes and synovial membrane explants (SMEs) treated with various cytokines and growth factors were assessed by C1M, C3M, and acMMP3 in the conditioned medium. TNFα significantly increased C1M up to seven-fold (p = 0.0002), C3M up to 24-fold (p = 0.0011), and acMMP3 up to 14-fold (p < 0.0001) in SMEs. IL-1β also significantly increased C1M up to five-fold (p = 0.00094), C3M four-fold (p = 0.007), and acMMP3 18-fold (p < 0.0001) in SMEs. The biomarkers C1M, C3M, and acMMP-3 were synovitis biomarkers ex vivo and provide a translational tool together with the SME model.

On the identification of biomarkers for non-small cell lung cancer in serum and pleural effusion.

PubMed

Rodríguez-Piñeiro, A M; Blanco-Prieto, S; Sánchez-Otero, N; Rodríguez-Berrocal, F J; de la Cadena, M Páez

2010-06-16

The current imperative need for new biomarkers of non-small cell lung cancer (NSCLC) prompted us to compare the proteome of serum and pleural effusion samples from cancer patients with those with benign lung diseases as pneumonia or tuberculosis. Samples were prefractionated through affinity chromatography prior to 2D-DIGE to detect proteins with altered expression in cancer patients. Overall, we identified more potential biomarkers in pleural effusion, which is closer to the affected organ, than in serum. Nevertheless, in both cases principal component analysis demonstrated that the pattern of significantly altered proteins discriminates between disease groups. The biomarker candidates comprise proteins increased in malignant pleural effusions as gelsolin and the metalloproteinase inhibitor 2, and others with lower levels as S100-A8 and S100-A9. The most interesting protein was the pigment epithelium-derived factor (PEDF), which is related to angiogenesis inhibition, and was significantly overexpressed both in serum and pleural effusion from NSCLC patients. More than 12 PEDF isoforms were specifically immunodetected in both fluids in 2-D blots, most of them overexpressed in NSCLC. Thus, further validation would be ideally directed to quantify individual PEDF isoforms, as it may be only one or some of them the ones altered in the cancer process. Copyright 2010 Elsevier B.V. All rights reserved.

Identification of serum miRNAs by nano-quantum dots microarray as diagnostic biomarkers for early detection of non-small cell lung cancer.

PubMed

Fan, Lihong; Qi, Huiwei; Teng, Junliang; Su, Bo; Chen, Hao; Wang, Changhui; Xia, Qing

2016-06-01

Circulating microRNAs (miRNAs) are potential noninvasive biomarkers for cancer detection. We used preoperative serum samples from non-small cell lung cancer (NSCLC) patients and healthy controls to investigate whether serum levels of candidate miRNAs could be used as diagnostic biomarkers in patients with resectable NSCLC and whether they were associated with clinicopathologic characteristics. We initially detected expression of 12 miRNAs using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) in preoperative serum samples of 94 NSCLC patients and 58 healthy controls. We further validated our results using the fluorescence quantum dots liquid bead array for differentially expressed miRNAs in serum samples of 70 NSCLC patients and 54 healthy controls. Receiver operating characteristic (ROC) analysis was performed to select the best diagnostic miRNA cutoff value. A predictive model of miRNAs for NSCLC was derived by multivariate logistic regression. We found that five serum miRNAs (miR-16-5p, miR-17b-5p, miR-19-3p, miR-20a-5p, and miR-92-3p) were significantly downregulated in NSCLC, while miR-15b-5p was significantly upregulated (p < 0.05). Multivariate logistic regression analysis revealed that miR-15b-5p, miR-16-5p, and miR-20a-5p expression were independent diagnostic factors for the identification of patients with NSCLC after adjustment for patient's age and sex. In addition, the expression of serum miR-106-5p was higher in stage I than in stages IIa-IIIb, and no significant association was observed between expression of miRNAs and other variables including pathological type, tumor size, and lymph nodes status. Six serum miRNAs could potentially serve as noninvasive diagnostic biomarkers for resectable NSCLC. The predictive model combining miR-15b-5p, miR-16-5p, and miR-20a-5p was the best diagnostic approach.

Identification and validation of biomarkers of IgV(H) mutation status in chronic lymphocytic leukemia using microfluidics quantitative real-time polymerase chain reaction technology.

PubMed

Abruzzo, Lynne V; Barron, Lynn L; Anderson, Keith; Newman, Rachel J; Wierda, William G; O'brien, Susan; Ferrajoli, Alessandra; Luthra, Madan; Talwalkar, Sameer; Luthra, Rajyalakshmi; Jones, Dan; Keating, Michael J; Coombes, Kevin R

2007-09-01

To develop a model incorporating relevant prognostic biomarkers for untreated chronic lymphocytic leukemia patients, we re-analyzed the raw data from four published gene expression profiling studies. We selected 88 candidate biomarkers linked to immunoglobulin heavy-chain variable region gene (IgV(H)) mutation status and produced a reliable and reproducible microfluidics quantitative real-time polymerase chain reaction array. We applied this array to a training set of 29 purified samples from previously untreated patients. In an unsupervised analysis, the samples clustered into two groups. Using a cutoff point of 2% homology to the germline IgV(H) sequence, one group contained all 14 IgV(H)-unmutated samples; the other contained all 15 mutated samples. We confirmed the differential expression of 37 of the candidate biomarkers using two-sample t-tests. Next, we constructed 16 different models to predict IgV(H) mutation status and evaluated their performance on an independent test set of 20 new samples. Nine models correctly classified 11 of 11 IgV(H)-mutated cases and eight of nine IgV(H)-unmutated cases, with some models using three to seven genes. Thus, we can classify cases with 95% accuracy based on the expression of as few as three genes.

Cerebrospinal Fluid Biomarkers for Huntington's Disease.

PubMed

Byrne, Lauren M; Wild, Edward J

2016-01-01

Cerebrospinal fluid (CSF) is enriched in brain-derived components and represents an accessible and appealing means of interrogating the CNS milieu to study neurodegenerative diseases and identify biomarkers to facilitate the development of novel therapeutics. Many such CSF biomarkers have been proposed for Huntington's disease (HD) but none has been validated for clinical trial use. Across many studies proposing dozens of biomarker candidates, there is a notable lack of statistical power, consistency, rigor and validation. Here we review proposed CSF biomarkers including neurotransmitters, transglutaminase activity, kynurenine pathway metabolites, oxidative stress markers, inflammatory markers, neuroendocrine markers, protein markers of neuronal death, proteomic approaches and mutant huntingtin protein itself. We reflect on the need for large-scale, standardized CSF collections with detailed phenotypic data to validate and qualify much-needed CSF biomarkers for clinical trial use in HD.

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.

Synovitis biomarkers: ex vivo characterization of three biomarkers for identification of inflammatory osteoarthritis

PubMed Central

Kjelgaard-Petersen, Cecilie; Siebuhr, Anne Sofie; Christiansen, Thorbjørn; Ladel, Christoph; Karsdal, Morten; Bay-Jensen, Anne-Christine

2015-01-01

Abstract Objective: Characterize biomarkers measuring extracellular matrix turnover of inflamed osteoarthritis synovium. Methods: Human primary fibroblast-like synoviocytes and synovial membrane explants (SMEs) treated with various cytokines and growth factors were assessed by C1M, C3M, and acMMP3 in the conditioned medium. Results: TNFα significantly increased C1M up to seven-fold (p = 0.0002), C3M up to 24-fold (p = 0.0011), and acMMP3 up to 14-fold (p < 0.0001) in SMEs. IL-1β also significantly increased C1M up to five-fold (p = 0.00094), C3M four-fold (p = 0.007), and acMMP3 18-fold (p < 0.0001) in SMEs. Conclusion: The biomarkers C1M, C3M, and acMMP-3 were synovitis biomarkers ex vivo and provide a translational tool together with the SME model. PMID:26863055

Identification of a three-biomarker panel in urine for early detection of pancreatic adenocarcinoma

PubMed Central

Radon, Tomasz P; Massat, Nathalie J; Jones, Richard; Alrawashdeh, Wasfi; Dumartin, Laurent; Ennis, Darren; Duffy, Stephen W; Kocher, Hemant M; Pereira, Stephen P; Nascimento, Cristiane M; Real, Francisco X; Malats, Núria; Neoptolemos, John; Costello, Eithne; Greenhalf, William; Lemoine, Nick R; Crnogorac-Jurcevic, Tatjana

2015-01-01

Purpose Non-invasive biomarkers for early detection of pancreatic ductal adenocarcinoma (PDAC) are currently not available. Here, we aimed to identify a set of urine proteins able to distinguish patients with early stage PDAC from healthy individuals (H). Experimental design Proteomes of 18 urine samples from healthy controls, chronic pancreatitis and PDAC patients (six/group) were assayed using GeLC/MS/MS analysis. The selected biomarkers were subsequently validated using ELISA assays using multiple logistic regression applied to a training dataset in a multicentre cohort comprising 488 urine samples. Results LYVE-1, REG1A and TFF1 were selected as candidate biomarkers. When comparing PDAC (n=192) to healthy (n=87) urines, the resulting areas under the receiver operating characteristic curves (AUCs) of the panel were 0.89 (95%CI 0.84-0.94) in the training (70% of the data), and 0.92 (95%CI 0.86-0.98) in the validation (30% of the data) datasets. When comparing PDAC stage I-II (n=71) to healthy urines, the panel achieved AUCs of 0.90 (95%CI 0.84-0.96) and 0.93 (95%CI 0.84-1.00) in the training and validation datasets, respectively. In PDAC stage I-II and healthy samples with matching plasma CA19.9 the panel achieved a higher AUC of 0.97 (95%CI 0.94-0.99) than CA19.9 (AUC=0.88, 95%CI 0.81-0.95, p=0.005). Adding plasma CA19.9 to the panel increased the AUC from 0.97 (95%CI 0.94-0.99) to 0.99 (95%CI 0.97-1.00, p=0.04) but did not improve the comparison of stage I-IIA PDAC (n=17) to healthy urine. Conclusion We have established a novel, three-protein biomarker panel that is able to detect patients with early stage pancreatic cancer in urine specimens. PMID:26240291

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

Perinatal biomarkers in prematurity: Early identification of neurologic injury

PubMed Central

Andrikopoulou, Maria; Almalki, Ahmad; Farzin, Azadeh; Cordeiro, Christina N.; Johnston, Michael V.; Burd, Irina

2014-01-01

Over the past few decades, biomarkers have become increasingly utilized as non-invasive tools in the early diagnosis and management of various clinical conditions. In perinatal medicine, the improved survival of extremely premature infants who are at high risk for adverse neurologic outcomes has increased the demand for the discovery of biomarkers in detecting and predicting the prognosis of infants with neonatal brain injury. By enabling the clinician to recognize potential brain damage early, biomarkers could allow clinicians to intervene at the early stages of disease, and to monitor the efficacy of those interventions. This review will first examine the potential perinatal biomarkers for neurologic complications of prematurity, specifically, intraventricular hemorrhage (IVH), periventricular leukomalacia (PVL) and posthemorrhagic hydrocephalus (PHH). It will also evaluate knowledge gained from animal models regarding the pathogenesis of perinatal brain injury in prematurity. PMID:24768951

Blood biomarkers in Alzheimer's disease.

PubMed

Altuna-Azkargorta, M; Mendioroz-Iriarte, M

2018-05-08

The early diagnosis of Alzheimer's disease (AD) via the use of biomarkers could facilitate the implementation and monitoring of early therapeutic interventions with the potential capacity to significantly modify the course of the disease. Classic cerebrospinal fluid biomarkers and approved structural and functional neuroimaging have a limited clinical application given their invasive nature and/or high cost. The identification of more accessible and less costly biomarkers, such as blood biomarkers, would facilitate application in clinical practice. We present a literature review of the main blood biochemical biomarkers with potential use for diagnosing Alzheimer's disease. Blood biomarkers are cost and time effective with regard to cerebrospinal fluid biomarkers. However, the immediate applicability of blood biochemical biomarkers in clinical practice is not very likely. The main limitations come from the difficulties in measuring and standardising thresholds between different laboratories and in failures to replicate results. Among all the molecules studied, apoptosis and neurodegeneration biomarkers and the biomarker panels obtained through omics approaches, such as isolated or combined metabolomics, offer the most promising results. Copyright © 2018 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data

PubMed Central

Bean, Heather D.; Hill, Jane E.; Dimandja, Jean-Marie D.

2015-01-01

The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly- resolved peaks, especially those at the extremes of the detector linear range, and no influence on well- chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. PMID:25857541

Identification of novel diagnostic biomarkers for thyroid carcinoma.

PubMed

Wang, Xiliang; Zhang, Qing; Cai, Zhiming; Dai, Yifan; Mou, Lisha

2017-12-19

Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. We further represent a diagnostic panel with expression cutoff values. Our results demonstrate the potential application of those four molecules as novel independent biomarkers for THCA diagnosis.

Identification of Potential Plasma Biomarkers for Nonalcoholic Fatty Liver Disease by Integrating Transcriptomics and Proteomics in Laying Hens.

PubMed

Tsai, Meng-Tsz; Chen, Yu-Jen; Chen, Ching-Yi; Tsai, Mong-Hsun; Han, Chia-Li; Chen, Yu-Ju; Mersmann, Harry J; Ding, Shih-Torng

2017-03-01

Background: Prevalent worldwide obesity is associated with increased incidence of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome. The identification of noninvasive biomarkers for NAFLD is of recent interest. Because primary de novo lipogenesis occurs in chicken liver as in human liver, adult chickens with age-associated steatosis resembling human NAFLD is an appealing animal model. Objective: The objective of this study was to screen potential biomarkers in the chicken model for NAFLD by transcriptomic and proteomic analysis. Methods: Hy-Line W-36 laying hens were fed standard feed from 25 to 45 wk of age to induce fatty liver. They were killed every 4 wk, and liver and plasma were collected at each time point to assess fatty liver development and for transcriptomic and proteomic analysis. Next, selected biomarkers were confirmed in additional experiments by providing supplements of the hepatoprotective nutrients betaine [300, 600, or 900 parts per million (ppm) in vivo; 2 mM in vitro] or docosahexaenoic acid (DHA; 1% in vivo; 100 μM in vitro) to 30-wk-old Hy-Line W-36 laying hens for 4 mo and to Hy-Line W-36 chicken primary hepatocytes with oleic acid-induced steatosis. Liver or hepatocyte lipid contents and the expression of biomarkers were then examined. Results: Plasma acetoacetyl-CoA synthetase (AACS), dipeptidyl-peptidase 4 (DPP4), glutamine synthetase (GLUL), and glutathione S -transferase (GST) concentrations are well-established biomarkers for NAFLD. Selected biomarkers had significant positive associations with hepatic lipid deposition ( P < 0.001). Betaine (900 ppm in vivo; 2 mM in vitro) and DHA (1% in vivo; 100 μM in vitro) supplementation both resulted in lower steatosis accompanied by the reduced expression of selected biomarkers in vivo and in vitro ( P < 0.05). Conclusion: This study used adult laying hens to identify biomarkers for NAFLD and indicated that AACS, DPP4, GLUL, and GST could be considered to be potential diagnostic

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.

Serum VEGF-C levels as a candidate biomarker of hypervolemia in chronic kidney disease

PubMed Central

Sahutoglu, Tuncay; Sakaci, Tamer; Hasbal, Nuri B.; Ahbap, Elbis; Kara, Ekrem; Sumerkan, Mutlu C.; Sevinc, Mustafa; Akgol, Cuneyt; Koc, Yener; Basturk, Taner; Unsal, Abdulkadir

2017-01-01

Abstract Attaining and maintaining optimal “dry weight” is one of the principal goals during maintenance hemodialysis (MHD). Recent studies have shown a close relationship between Na+ load and serum vascular endothelial growth factor-C (VEGF-C) levels; thus, we aimed to investigate the role of VEGF-C as a candidate biomarker of hypervolemia. Physical examination, basic laboratory tests, N-terminal pro b-type natriuretic peptide (NT-ProBNP), echocardiography, and bioimpedance spectroscopy data of 3 groups of study subjects (euvolemic MHD patients, healthy controls, and hypervolemic chronic kidney disease [CKD] patients) were analyzed. Research data for MHD patients were obtained both before the first and after the last hemodialysis (HD) sessions of the week. Data of 10 subjects from each study groups were included in the analysis. Serum VEGF-C levels were significantly higher in hypervolemic CKD versus in MHD patients both before the first and after the last HD sessions (P = .004 and P = .000, respectively). Healthy controls had serum VEGF-C levels similar to and higher than MHD patients before the first and after the last HD sessions of the week (P = .327 and P = .021, respectively). VEGF-C levels were correlated with bioimpedance spectroscopy results (r2 0.659, P = .000) and edema (r2 0.494, P =0.006), but not with ejection fraction (EF) (r2 −0.251, P = .134), blood pressures (systolic r2 0.037, P = 0.824, diastolic r2 −0.067, P = .691), and NT-ProBNP (r2 −0.047, P = .773). These findings suggest that serum VEGF-C levels could be a potential new biomarker of hypervolemia. The lack of correlation between VEGF-C and EF may hold a promise to eliminate this common confounder. Further studies are needed to define the clinical utility of VEGF-C in volume management. PMID:28471955

The use of biomarkers in the military: from theory to practice.

PubMed

Yehuda, Rachel; Neylan, Thomas C; Flory, Janine D; McFarlane, Alexander C

2013-09-01

This paper provides a summary of relevant issues covered in the conference, "The Use of Biomarkers in the Military: Theory to Practice" held at the New York Academy of Science on September 14, 2012. The conference covered the state of the science in identification of PTSD biomarkers, including, the definition of different classes of biomarkers pertaining to PTSD. The aim of the satellite conference was to bring together researchers who have been supported by the Department of Defense, Veterans Administration, National Institutes of Health, and other agencies around the world, who are interested in the identification of biomarkers for PTSD risk, diagnosis, symptom severity and treatment response, for a discussion of salient issues regarding biomarker development for PTSD, as well as special considerations for the use of biomarkers in the military. Copyright © 2013. Published by Elsevier Ltd.

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

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

Systemic lupus erythematosus biomarkers: the challenging quest

PubMed Central

Wren, Jonathan D.; Munroe, Melissa E.; Mohan, Chandra

2017-01-01

Abstract SLE, a multisystem heterogeneous disease, is characterized by production of antibodies to cellular components, with activation of both the innate and the adaptive immune system. Decades of investigation of blood biomarkers has resulted in incremental improvements in the understanding of SLE. Owing to the heterogeneity of immune dysregulation, no single biomarker has emerged as a surrogate for disease activity or prediction of disease. Beyond identification of surrogate biomarkers, a multitude of clinical trials have sought to inhibit elevated SLE biomarkers for therapeutic benefit. Armed with new -omics technologies, the necessary yet daunting quest to identify better surrogate biomarkers and successful therapeutics for SLE continues with tenacity. PMID:28013203

Serum Immunoproteomics Combined With Pathological Reassessment of Surgical Specimens Identifies TCP-1ζ Autoantibody as a Potential Biomarker in Thyroid Neoplasia.

PubMed

Belousov, Pavel V; Bogolyubova, Apollinariya V; Kim, Yan S; Abrosimov, Alexander Y; Kopylov, Arthur T; Tvardovskiy, Andrey A; Lanshchakov, Kirill V; Sazykin, Alexei Y; Dvinskikh, Nina Y; Bobrovskaya, Yana I; Selivanova, Lilia S; Shilov, Evgeniy S; Schwartz, Anton M; Shebzukhov, Yuriy V; Severskaia, Natalya V; Vanushko, Vladimir E; Moshkovskii, Sergei A; Nedospasov, Sergei A; Kuprash, Dmitry V

2015-09-01

Current methods of preoperative diagnostics frequently fail to discriminate between benign and malignant thyroid neoplasms. In encapsulated follicular-patterned tumors (EnFPT), this discrimination is challenging even using histopathological analysis. Autoantibody response against tumor-associated antigens is a well-documented phenomenon with prominent diagnostic potential; however, autoantigenicity of thyroid tumors remains poorly explored. Objectives were exploration of tumor-associated antigen repertoire of thyroid tumors and identification of candidate autoantibody biomarkers capable of discrimination between benign and malignant thyroid neoplasms. Proteins isolated from FTC-133 cells were subjected to two-dimensional Western blotting using pooled serum samples of patients originally diagnosed with either papillary thyroid carcinoma (PTC) or EnFPT represented by apparently benign follicular thyroid adenomas, as well as healthy individuals. Immunoreactive proteins were identified using liquid chromatography-tandem mass-spectrometry. Pathological reassessment of EnFPT was performed applying nonconservative criteria for capsular invasion and significance of focal PTC nuclear changes (PTC-NCs). Recombinant T-complex protein 1 subunitζ (TCP-1ζ) was used to examine an expanded serum sample set of patients with various thyroid neoplasms (n = 89) for TCP-1ζ autoantibodies. All patients were included in tertiary referral centers. A protein demonstrating a distinct pattern of EnFPT-specific seroreactivity was identified as TCP-1ζ protein. A subsequent search for clinicopathological correlates of TCP-1ζ seroreactivity revealed nonclassical capsular invasion or focal PTC-NC in all TCP-1ζ antibody-positive cases. Further studies in an expanded sample set confirmed the specificity of TCP-1ζ autoantibodies to malignant EnFPT. We identified TCP-1ζ autoantibodies as a potential biomarker for presurgical discrimination between benign and malignant encapsulated follicular

Identification of novel diagnostic biomarkers for thyroid carcinoma

PubMed Central

Wang, Xiliang; Zhang, Qing; Cai, Zhiming; Dai, Yifan; Mou, Lisha

2017-01-01

Thyroid carcinoma (THCA) is the most universal endocrine malignancy worldwide. Unfortunately, a limited number of large-scale analyses have been performed to identify biomarkers for THCA. Here, we conducted a meta-analysis using 505 THCA patients and 59 normal controls from The Cancer Genome Atlas. After identifying differentially expressed long non-coding RNA (lncRNA) and protein coding genes (PCG), we found vast difference in various lncRNA-PCG co-expressed pairs in THCA. A dysregulation network with scale-free topology was constructed. Four molecules (LA16c-380H5.2, RP11-203J24.8, MLF1 and SDC4) could potentially serve as diagnostic biomarkers of THCA with high sensitivity and specificity. We further represent a diagnostic panel with expression cutoff values. Our results demonstrate the potential application of those four molecules as novel independent biomarkers for THCA diagnosis. PMID:29340074

Cytokines and MicroRNAs as Candidate Biomarkers for Systemic Lupus Erythematosus

PubMed Central

Stypińska, Barbara; Paradowska-Gorycka, Agnieszka

2015-01-01

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease, with varied course and symptoms. Its etiology is very complex and not clearly understood. There is growing evidence of the important role of cytokines in SLE pathogenesis, as well as their utility as biomarkers and targets in new therapies. Other potential new SLE biomarkers are microRNAs. Recently, over one hundred different microRNAs have been demonstrated to have a significant impact on the immune system. Various alterations in these microRNAs, associated with disease pathogenesis, have been described. They influence the signaling pathways and functions of immune response cells. Here, we aim to review the emerging new data on SLE etiology and pathogenesis. PMID:26473848

Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets.

PubMed

Wang, Maoqing; Yang, Xue; Ren, Lihong; Li, Songtao; He, Xuan; Wu, Xiaoyan; Liu, Tingting; Lin, Liqun; Li, Ying; Sun, Changhao

2014-09-05

Nutritional rickets is a worldwide public health problem; however, the current diagnostic methods retain shortcomings for accurate diagnosis of nutritional rickets. To identify urinary biomarkers associated with nutritional rickets and establish a noninvasive diagnosis method, urinary metabonomics analysis by ultra-performance liquid chromatography/quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis were employed to investigate the metabolic alterations associated with nutritional rickets in 200 children with or without nutritional rickets. The pathophysiological changes and pathogenesis of nutritional rickets were illustrated by the identified biomarkers. By urinary metabolic profiling, 31 biomarkers of nutritional rickets were identified and five candidate biomarkers for clinical diagnosis were screened and identified by quantitative analysis and receiver operating curve analysis. Urinary levels of five candidate biomarkers were measured using mass spectrometry or commercial kits. In the validation step, the combination of phosphate and sebacic acid was able to give a noninvasive and accurate diagnostic with high sensitivity (94.0%) and specificity (71.2%). Furthermore, on the basis of the pathway analysis of biomarkers, our urinary metabonomics analysis gives new insight into the pathogenesis and pathophysiology of nutritional rickets.

Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry.

PubMed

Tsutsui, Haruhito; Maeda, Toshio; Min, Jun Zhe; Inagaki, Shinsuke; Higashi, Tatsuya; Kagawa, Yoshiyuki; Toyo'oka, Toshimasa

2011-05-12

The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study. The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB. Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on

Red blood cell populations and membrane levels of peroxiredoxin 2 as candidate biomarkers to reveal blood doping.

PubMed

Marrocco, Cristina; Pallotta, Valeria; D'alessandro, Angelo; Alves, Gilda; Zolla, Lello

2012-05-01

Blood doping represents one main trend in doping strategies. Blood doping refers to the practice of boosting the number of red blood cells (RBCs) in the bloodstream in order to enhance athletic performance, by means of blood transfusions, administration of erythropoiesis-stimulating substances, blood substitutes, natural or artificial altitude facilities, and innovative gene therapies. While detection of recombinant EPO and homologous transfusion is already feasible through electrophoretic, mass spectrometry or flow cytometry-based approaches, no method is currently available to tackle doping strategies relying on autologous transfusions. We exploited an in vitro model of autologous transfusion through a 1:10 dilution of concentrated RBCs after 30 days of storage upon appropriate dilution in freshly withdrawn RBCs from the same donor. Western blot towards membrane Prdx2 and Percoll density gradients were exploited to assess their suitability as biomarkers of transfusion. Membrane Prdx2 was visible in day 30 samples albeit not in day 0, while it was still visible in the 1:10 dilution of day 30 in day 0 RBCs. Cell gradients also highlighted changes in the profile of the RBC subpopulations upon dilution of stored RBCs in the fresh ones. From this preliminary in vitro investigation it emerges that Prdx2 and RBC populations might be further tested as candidate biomarkers of blood doping through autologous transfusion, though it is yet to be assessed whether the kinetics in vivo of Prdx2 exposure in the membrane of transfused RBCs will endow a sufficient time-window to allow reliable anti-doping testing.

Red blood cell populations and membrane levels of peroxiredoxin 2 as candidate biomarkers to reveal blood doping

PubMed Central

Marrocco, Cristina; Pallotta, Valeria; D’Alessandro, Angelo; Alves, Gilda; Zolla, Lello

2012-01-01

Background Blood doping represents one main trend in doping strategies. Blood doping refers to the practice of boosting the number of red blood cells (RBCs) in the bloodstream in order to enhance athletic performance, by means of blood transfusions, administration of erythropoiesis-stimulating substances, blood substitutes, natural or artificial altitude facilities, and innovative gene therapies. While detection of recombinant EPO and homologous transfusion is already feasible through electrophoretic, mass spectrometry or flow cytometry-based approaches, no method is currently available to tackle doping strategies relying on autologous transfusions. Materials and methods. We exploited an in vitro model of autologous transfusion through a 1:10 dilution of concentrated RBCs after 30 days of storage upon appropriate dilution in freshly withdrawn RBCs from the same donor. Western blot towards membrane Prdx2 and Percoll density gradients were exploited to assess their suitability as biomarkers of transfusion. Results Membrane Prdx2 was visible in day 30 samples albeit not in day 0, while it was still visible in the 1:10 dilution of day 30 in day 0 RBCs. Cell gradients also highlighted changes in the profile of the RBC subpopulations upon dilution of stored RBCs in the fresh ones. Discussion. From this preliminary in vitro investigation it emerges that Prdx2 and RBC populations might be further tested as candidate biomarkers of blood doping through autologous transfusion, though it is yet to be assessed whether the kinetics in vivo of Prdx2 exposure in the membrane of transfused RBCs will endow a sufficient time-window to allow reliable anti-doping testing. PMID:22890272

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

Urinary and Blood MicroRNA-126 and -770 are Potential Noninvasive Biomarker Candidates for Diabetic Nephropathy: a Meta-Analysis.

PubMed

Park, Sungjin; Moon, SeongRyeol; Lee, Kiyoung; Park, Ie Byung; Lee, Dae Ho; Nam, Seungyoon

2018-01-01

Diabetic nephropathy (DN), a major diabetic microvascular complication, has a long and growing list of biomarkers, including microRNA biomarkers, which have not been consistent across preclinical and clinical studies. This meta-analysis aims to identify significant blood- and urine-incident microRNAs as diagnostic/prognostic biomarker candidates for DN. PubMed, Web of Science, and Cochrane Library were searched from their earliest records through 12th Dec 2016. Relevant publications for the meta-analysis included (1) human participants; (2) microRNAs in blood and urine; (3) DN studies; and (4) English language. Four reviewers, including two physicians, independently and blindly extracted published data regarding microRNA profiles in blood and/or urine from subjects with diabetic nephropathy. A random-effect model was used to pool the data. Statistical associations between diabetic nephropathy and urinary or blood microRNA expression levels were assessed. Fourteen out of 327 studies (n=2,747 patients) were selected. Blood or urinary microRNA expression data of diabetic nephropathy were pooled for this analysis. The hsa-miR-126 family was significantly (OR: 0.57; 95% CI: 0.44-0.74; p-value < 0.0001) downregulated in blood from patients with diabetic kidney disease, while its urinary level was upregulated (OR: 2931.12; 95% CI: 9.96-862623.21; p-value = 0.0059). The hsa-miR-770 family microRNA were significantly (OR: 10.24; 95% CI: 2.37-44.25; p-value = 0.0018) upregulated in both blood and urine from patients with diabetic nephropathy. Our meta-analysis suggests that hsa-miR-126 and hsa-miR-770 family microRNA may have important diagnostic and pathogenetic implications for DN, which warrants further systematic clinical studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

Identification of downy mildew resistance gene candidates by positional cloning in maize (Zea mays subsp. mays; Poaceae)1

PubMed Central

Kim, Jae Yoon; Moon, Jun-Cheol; Kim, Hyo Chul; Shin, Seungho; Song, Kitae; Kim, Kyung-Hee; Lee, Byung-Moo

2017-01-01

Premise of the study: Positional cloning in combination with phenotyping is a general approach to identify disease-resistance gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combined strategy to improve the identification of disease-resistance gene candidates. Methods and Results: Downy mildew (DM)–resistant maize was selected from five cultivars using a spreader row technique. Positional cloning and bioinformatics tools were used to identify the DM-resistance quantitative trait locus marker (bnlg1702) and 47 protein-coding gene annotations. Eventually, five DM-resistance gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative reverse-transcription PCR (RT-PCR) without fine mapping of the bnlg1702 locus. Conclusions: The combined protocol with the spreader row technique, quantitative trait locus positional cloning, and quantitative RT-PCR was effective for identifying DM-resistance candidate genes. This cloning approach may be applied to other whole-genome-sequenced crops or resistance to other diseases. PMID:28224059

Comparing and combining biomarkers as principle surrogates for time-to-event clinical endpoints.

PubMed

Gabriel, Erin E; Sachs, Michael C; Gilbert, Peter B

2015-02-10

Principal surrogate endpoints are useful as targets for phase I and II trials. In many recent trials, multiple post-randomization biomarkers are measured. However, few statistical methods exist for comparison of or combination of biomarkers as principal surrogates, and none of these methods to our knowledge utilize time-to-event clinical endpoint information. We propose a Weibull model extension of the semi-parametric estimated maximum likelihood method that allows for the inclusion of multiple biomarkers in the same risk model as multivariate candidate principal surrogates. We propose several methods for comparing candidate principal surrogates and evaluating multivariate principal surrogates. These include the time-dependent and surrogate-dependent true and false positive fraction, the time-dependent and the integrated standardized total gain, and the cumulative distribution function of the risk difference. We illustrate the operating characteristics of our proposed methods in simulations and outline how these statistics can be used to evaluate and compare candidate principal surrogates. We use these methods to investigate candidate surrogates in the Diabetes Control and Complications Trial. Copyright © 2014 John Wiley & Sons, Ltd.

Biomarkers in Lysosomal Storage Diseases

PubMed Central

Bobillo Lobato, Joaquin; Jiménez Hidalgo, Maria; Jiménez Jiménez, Luis M.

2016-01-01

A biomarker is generally an analyte that indicates the presence and/or extent of a biological process, which is in itself usually directly linked to the clinical manifestations and outcome of a particular disease. The biomarkers in the field of lysosomal storage diseases (LSDs) have particular relevance where spectacular therapeutic initiatives have been achieved, most notably with the introduction of enzyme replacement therapy (ERT). There are two main types of biomarkers. The first group is comprised of those molecules whose accumulation is directly enhanced as a result of defective lysosomal function. These molecules represent the storage of the principal macro-molecular substrate(s) of a specific enzyme or protein, whose function is deficient in the given disease. In the second group of biomarkers, the relationship between the lysosomal defect and the biomarker is indirect. In this group, the biomarker reflects the effects of the primary lysosomal defect on cell, tissue, or organ functions. There is no “gold standard” among biomarkers used to diagnosis and/or monitor LSDs, but there are a number that exist that can be used to reasonably assess and monitor the state of certain organs or functions. A number of biomarkers have been proposed for the analysis of the most important LSDs. In this review, we will summarize the most promising biomarkers in major LSDs and discuss why these are the most promising candidates for screening systems. PMID:28933418

Development of Biomarkers for Screening Hepatocellular Carcinoma Using Global Data Mining and Multiple Reaction Monitoring

PubMed Central

Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases. PMID:23717429

Development of biomarkers for screening hepatocellular carcinoma using global data mining and multiple reaction monitoring.

PubMed

Kim, Hyunsoo; Kim, Kyunggon; Yu, Su Jong; Jang, Eun Sun; Yu, Jiyoung; Cho, Geunhee; Yoon, Jung-Hwan; Kim, Youngsoo

2013-01-01

Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction monitoring (MRM), based on triple quadrupole mass spectrometry, has been effective with regard to high-throughput verification, complementing antibody-based verification pipelines. In this study, global data mining was performed using 5 types of HCC data to screen for candidate biomarker proteins: cDNA microarray, copy number variation, somatic mutation, epigenetic, and quantitative proteomics data. Next, we applied MRM to verify HCC candidate biomarkers in individual serum samples from 3 groups: a healthy control group, patients who have been diagnosed with HCC (Before HCC treatment group), and HCC patients who underwent locoregional therapy (After HCC treatment group). After determining the relative quantities of the candidate proteins by MRM, we compared their expression levels between the 3 groups, identifying 4 potential biomarkers: the actin-binding protein anillin (ANLN), filamin-B (FLNB), complementary C4-A (C4A), and AFP. The combination of 2 markers (ANLN, FLNB) improved the discrimination of the before HCC treatment group from the healthy control group compared with AFP. We conclude that the combination of global data mining and MRM verification enhances the screening and verification of potential HCC biomarkers. This efficacious integrative strategy is applicable to the development of markers for cancer and other diseases.

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

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.

Cardiovascular disease biomarkers across autoimmune diseases.

PubMed

Ahearn, Joseph; Shields, Kelly J; Liu, Chau-Ching; Manzi, Susan

2015-11-01

Cardiovascular disease is increasingly recognized as a major cause of premature mortality among those with autoimmune disorders. There is an urgent need to identify those patients with autoimmune disease who are at risk for CVD so as to optimize therapeutic intervention and ultimately prevention. Accurate identification, monitoring and stratification of such patients will depend upon a panel of biomarkers of cardiovascular disease. This review will discuss some of the most recent biomarkers of cardiovascular diseases in autoimmune disease, including lipid oxidation, imaging biomarkers to characterize coronary calcium, plaque, and intima media thickness, biomarkers of inflammation and activated complement, genetic markers, endothelial biomarkers, and antiphospholipid antibodies. Clinical implementation of these biomarkers will not only enhance patient care but also likely accelerate the pharmaceutical pipeline for targeted intervention to reduce or eliminate cardiovascular disease in the setting of autoimmunity. Copyright © 2015 Elsevier Inc. All rights reserved.

Identification of candidate regions for a novel Usher syndrome type II locus.

PubMed

Ben Rebeh, Imen; Benzina, Zeineb; Dhouib, Houria; Hadjamor, Imen; Amyere, Mustapha; Ayadi, Leila; Turki, Khalil; Hammami, Bouthaina; Kmiha, Noureddine; Kammoun, Hassen; Hakim, Bochra; Charfedine, Ilhem; Vikkula, Miikka; Ghorbel, Abdelmonem; Ayadi, Hammadi; Masmoudi, Saber

2008-09-19

Chronic diseases affecting the inner ear and the retina cause severe impairments to our communication systems. In more than half of the cases, Usher syndrome (USH) is the origin of these double defects. Patients with USH type II (USH2) have retinitis pigmentosa (RP) that develops during puberty, moderate to severe hearing impairment with downsloping pure-tone audiogram, and normal vestibular function. Four loci and three genes are known for USH2. In this study, we proposed to localize the gene responsible for USH2 in a consanguineous family of Tunisian origin. Affected members underwent detailed ocular and audiologic characterization. One Tunisian family with USH2 and 45 healthy controls unrelated to the family were recruited. Two affected and six unaffected family members attended our study. DNA samples of eight family members were genotyped with polymorphic markers. Two-point and multipoint LOD scores were calculated using Genehunter software v2.1. Sequencing was used to investigate candidate genes. Haplotype analysis showed no significant linkage to any known USH gene or locus. A genome-wide screen, using microsatellite markers, was performed, allowing the identification of three homozygous regions in chromosomes 2, 4, and 15. We further confirmed and refined these three regions using microsatellite and single-nucleotide polymorphisms. With recessive mode of inheritance, the highest multipoint LOD score of 1.765 was identified for the candidate regions on chromosomes 4 and 15. The chromosome 15 locus is large (55 Mb), underscoring the limited number of meioses in the consanguineous pedigree. Moreover, the linked, homozygous chromosome 15q alleles, unlike those of the chromosome 2 and 4 loci, are infrequent in the local population. Thus, the data strongly suggest that the novel locus for USH2 is likely to reside on 15q. Our data provide a basis for the localization and the identification of a novel gene implicated in USH2, most likely localized on 15q.

Relative quantification of biomarkers using mixed-isotope labeling coupled with MS

PubMed Central

Chapman, Heidi M; Schutt, Katherine L; Dieter, Emily M; Lamos, Shane M

2013-01-01

The identification and quantification of important biomarkers is a critical first step in the elucidation of biological systems. Biomarkers take many forms as cellular responses to stimuli and can be manifested during transcription, translation, and/or metabolic processing. Increasingly, researchers have relied upon mixed-isotope labeling (MIL) coupled with MS to perform relative quantification of biomarkers between two or more biological samples. MIL effectively tags biomarkers of interest for ease of identification and quantification within the mass spectrometer by using isotopic labels that introduce a heavy and light form of the tag. In addition to MIL coupled with MS, a number of other approaches have been used to quantify biomarkers including protein gel staining, enzymatic labeling, metabolic labeling, and several label-free approaches that generate quantitative data from the MS signal response. This review focuses on MIL techniques coupled with MS for the quantification of protein and small-molecule biomarkers. PMID:23157360

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.

Is there Progress? An Overview of Selecting Biomarker Candidates for Major Depressive Disorder

PubMed Central

Young, Juan Joseph; Silber, Tim; Bruno, Davide; Galatzer-Levy, Isaac Robert; Pomara, Nunzio; Marmar, Charles Raymond

2016-01-01

Major depressive disorder (MDD) contributes to a significant worldwide disease burden, expected to be second only to heart disease by 2050. However, accurate diagnosis has been a historical weakness in clinical psychiatry. As a result, there is a demand for diagnostic modalities with greater objectivity that could improve on current psychiatric practice that relies mainly on self-reporting of symptoms and clinical interviews. Over the past two decades, literature on a growing number of putative biomarkers for MDD increasingly suggests that MDD patients have significantly different biological profiles compared to healthy controls. However, difficulty in elucidating their exact relationships within depression pathology renders individual markers inconsistent diagnostic tools. Consequently, further biomarker research could potentially improve our understanding of MDD pathophysiology as well as aid in interpreting response to treatment, narrow differential diagnoses, and help refine current MDD criteria. Representative of this, multiplex assays using multiple sources of biomarkers are reported to be more accurate options in comparison to individual markers that exhibit lower specificity and sensitivity, and are more prone to confounding factors. In the future, more sophisticated multiplex assays may hold promise for use in screening and diagnosing depression and determining clinical severity as an advance over relying solely on current subjective diagnostic criteria. A pervasive limitation in existing research is heterogeneity inherent in MDD studies, which impacts the validity of biomarker data. Additionally, small sample sizes of most studies limit statistical power. Yet, as the RDoC project evolves to decrease these limitations, and stronger studies with more generalizable data are developed, significant advances in the next decade are expected to yield important information in the development of MDD biomarkers for use in clinical settings. PMID:27199779

Modeling and Classification of Kinetic Patterns of Dynamic Metabolic Biomarkers in Physical Activity

PubMed Central

Breit, Marc; Netzer, Michael

2015-01-01

The objectives of this work were the classification of dynamic metabolic biomarker candidates and the modeling and characterization of kinetic regulatory mechanisms in human metabolism with response to external perturbations by physical activity. Longitudinal metabolic concentration data of 47 individuals from 4 different groups were examined, obtained from a cycle ergometry cohort study. In total, 110 metabolites (within the classes of acylcarnitines, amino acids, and sugars) were measured through a targeted metabolomics approach, combining tandem mass spectrometry (MS/MS) with the concept of stable isotope dilution (SID) for metabolite quantitation. Biomarker candidates were selected by combined analysis of maximum fold changes (MFCs) in concentrations and P-values resulting from statistical hypothesis testing. Characteristic kinetic signatures were identified through a mathematical modeling approach utilizing polynomial fitting. Modeled kinetic signatures were analyzed for groups with similar behavior by applying hierarchical cluster analysis. Kinetic shape templates were characterized, defining different forms of basic kinetic response patterns, such as sustained, early, late, and other forms, that can be used for metabolite classification. Acetylcarnitine (C2), showing a late response pattern and having the highest values in MFC and statistical significance, was classified as late marker and ranked as strong predictor (MFC = 1.97, P < 0.001). In the class of amino acids, highest values were shown for alanine (MFC = 1.42, P < 0.001), classified as late marker and strong predictor. Glucose yields a delayed response pattern, similar to a hockey stick function, being classified as delayed marker and ranked as moderate predictor (MFC = 1.32, P < 0.001). These findings coincide with existing knowledge on central metabolic pathways affected in exercise physiology, such as β-oxidation of fatty acids, glycolysis, and glycogenolysis. The presented modeling approach

Biomarkers for pediatric sepsis and septic shock

PubMed Central

Standage, Stephen W; Wong, Hector R

2011-01-01

Sepsis is a clinical syndrome defined by physiologic changes indicative of systemic inflammation, which are likely attributable to documented or suspected infection. Septic shock is the progression of those physiologic changes to the extent that delivery of oxygen and metabolic substrate to tissues is compromised. Biomarkers have the potential to diagnose, monitor, stratify and predict outcome in these syndromes. C-reactive protein is elevated in inflammatory and infectious conditions and has long been used as a biomarker indicating infection. Procalcitonin has more recently been shown to better distinguish infection from inflammation. Newer candidate biomarkers for infection include IL-18 and CD64. Lactate facilitates the diagnosis of septic shock and the monitoring of its progression. Multiple stratification biomarkers based on genome-wide expression profiling are under active investigation and present exciting future possibilities. PMID:21171879

De Novo Identification of Biomarker Proteins Using Tandem Mass Spectrometry

EPA Science Inventory

Many studies have shown that biological fluids contain an important number of biomarkers associated with various pathologies. For instance, there has been extensive research to identify effective biomarkers as prognostic indicators of breast cancer. An effective approach for biom...

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.

Blood biomarkers of kidney transplant rejection, an endless search?

PubMed

Jacquemont, Lola; Soulillou, Jean-Paul; Degauque, Nicolas

2017-07-01

The tailoring of immunosuppressive treatment is recognized as a promising strategy to improve long-term kidney graft outcome. To guide the standard care of transplant recipients, physicians need objective biomarkers that can identify an ongoing pathology with the graft or low intensity signals that will be later evolved to accelerated transplant rejection. The early identification of 'high-risk /low-risk' patients enables the adjustment of standard of caring, including managing the frequency of clinical visits and the immunosuppression dosing. Given their ease of availability and the compatibility with a large technical array, blood-based biomarkers have been widely scrutinized for use as potential predictive and diagnostic biomarkers. Areas covered: Here, the authors report on non-invasive biomarkers, such as modification of immune cell subsets and mRNA and miRNA profiles, identified in the blood of kidney transplant recipients collected before or after transplantation. Expert commentary: Combined with functional tests, the identification of biomarkers will improve our understanding of pathological processes and will contribute to a global improvement in clinical management.

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.

Biomarkers for AAA: Encouraging steps but clinical relevance still to be delivered.

PubMed

Htun, Nay Min; Peter, Karlheinz

2014-10-01

Potential biomarkers have been investigated using proteomic studies in a variety of diseases. Some biomarkers have central roles in both diagnosis and monitoring of various disorders in clinical medicine, such as troponins, brain natriuretic peptide, and C-reactive protein. Although several biomarkers have been suggested in human abdominal aortic aneurysm (AAA), reliable markers have been lacking. In this issue, Moxon et al. [Proteomics Clin Appl. 2014, 8, 762-772] undertook a broad and systematic proteomic approach toward identification of biomarkers in a commonly used AAA mouse model (AAA created by angiotensin-II infusion). In this mouse model, apolipoprotein C1 and matrix metalloproteinase-9 were identified as novel biomarkers of stable AAA. This finding represents an important step forward, toward a clinically relevant role of biomarkers in AAA. This also encourages for further studies toward the identification of biomarkers (or their combinations) that can predict AAA progression and rupture, which would represent a major progress in AAA management and would establish an AAA biomarker as a much anticipated clinical tool. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Identification of candidate genes affecting Δ9-tetrahydrocannabinol biosynthesis in Cannabis sativa

PubMed Central

Marks, M. David; Tian, Li; Wenger, Jonathan P.; Omburo, Stephanie N.; Soto-Fuentes, Wilfredo; He, Ji; Gang, David R.; Weiblen, George D.; Dixon, Richard A.

2009-01-01

RNA isolated from the glands of a Δ9-tetrahydrocannabinolic acid (THCA)-producing strain of Cannabis sativa was used to generate a cDNA library containing over 100 000 expressed sequence tags (ESTs). Sequencing of over 2000 clones from the library resulted in the identification of over 1000 unigenes. Candidate genes for almost every step in the biochemical pathways leading from primary metabolites to THCA were identified. Quantitative PCR analysis suggested that many of the pathway genes are preferentially expressed in the glands. Hexanoyl-CoA, one of the metabolites required for THCA synthesis, could be made via either de novo fatty acids synthesis or via the breakdown of existing lipids. qPCR analysis supported the de novo pathway. Many of the ESTs encode transcription factors and two putative MYB genes were identified that were preferentially expressed in glands. Given the similarity of the Cannabis MYB genes to those in other species with known functions, these Cannabis MYBs may play roles in regulating gland development and THCA synthesis. Three candidates for the polyketide synthase (PKS) gene responsible for the first committed step in the pathway to THCA were characterized in more detail. One of these was identical to a previously reported chalcone synthase (CHS) and was found to have CHS activity. All three could use malonyl-CoA and hexanoyl-CoA as substrates, including the CHS, but reaction conditions were not identified that allowed for the production of olivetolic acid (the proposed product of the PKS activity needed for THCA synthesis). One of the PKS candidates was highly and specifically expressed in glands (relative to whole leaves) and, on the basis of these expression data, it is proposed to be the most likely PKS responsible for olivetolic acid synthesis in Cannabis glands. PMID:19581347

Phage display for identification of serum biomarkers of traumatic brain injury.

PubMed

Ghoshal, Sarbani; Bondada, Vimala; Saatman, Kathryn E; Guttmann, Rodney P; Geddes, James W

2016-10-15

The extent and severity of traumatic brain injuries (TBIs) can be difficult to determine with current diagnostic methods. To address this, there has been increased interest in developing biomarkers to assist in the diagnosis, determination of injury severity, evaluation of recovery and therapeutic efficacy, and prediction of outcomes. Several promising serum TBI biomarkers have been identified using hypothesis-driven approaches, largely examining proteins that are abundant in neurons and non-neural cells in the CNS. An unbiased approach, phage display, was used to identify serum TBI biomarkers. In this proof-of-concept study, mice received a TBI using the controlled cortical impact model of TBI (1mm injury depth, 3.5m/s velocity) and phage display was utilized to identify putative serum biomarkers at 6h postinjury. An engineered phage which preferentially bound to injured serum was sequenced to identify the 12-mer 'recognizer' peptide expressed on the coat protein. Following synthesis of the recognizer peptide, pull down, and mass spectrometry analysis, the target protein was identified as glial fibrillary acidic protein (GFAP). GFAP has previously been identified as a promising TBI biomarker. The results provide proof of concept regarding the ability of phage display to identify TBI serum biomarkers. This methodology is currently being applied to serum biomarkers of mild TBI. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein biomarkers distinguish between high- and low-risk pediatric acute lymphoblastic leukemia in a tissue specific manner

PubMed Central

2013-01-01

The current study evaluated the differential expression detected in the proteomic profiles of low risk- and high risk- ALL pediatric patients to characterize candidate biomarkers related to diagnosis, prognosis and patient targeted therapy. Bone marrow and peripheral blood plasma and cell lysates samples were obtained from pediatric patients with low- (LR) and high-risk (HR) ALL at diagnosis. As controls, non-leukemic pediatric patients were studied. Cytogenetic analysis was carried out by G- banding and interphase fluorescent in situ hybridization. Differential proteomic analysis was performed using two-dimensional gel electrophoresis and protein identification by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The differential expression of certain proteins was confirmed by Western blot analysis. The obtained data revealed that CLUS, CERU, APOE, APOA4, APOA1, GELS, S10A9, AMBP, ACTB, CATA and AFAM proteins play a significant role in leukemia prognosis, potentially serving as distinctive biomarkers for leukemia aggressiveness, or as suppressor proteins in HR-ALL cases. In addition, vitronectin and plasminogen probably contributed to leukemogenesis, whilst bicaudal D-related protein 1 could afford a significant biomarker for pediatric ALL therapeutics. PMID:23849470

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

PubMed

Orsini, M; Travaglione, A; Capobianco, E

2013-07-01

Translational research in cancer genomics assigns a fundamental role to bioinformatics in support of candidate gene prioritization with regard to both biomarker discovery and target identification for drug development. Efforts in both such directions rely on the existence and constant update of large repositories of gene expression data and omics records obtained from a variety of experiments. Users who interactively interrogate such repositories may have problems in retrieving sample fields that present limited associated information, due for instance to incomplete entries or sometimes unusable files. Cancer-specific data sources present similar problems. Given that source integration usually improves data quality, one of the objectives is keeping the computational complexity sufficiently low to allow an optimal assimilation and mining of all the information. In particular, the scope of integrating intraomics data can be to improve the exploration of gene co-expression landscapes, while the scope of integrating interomics sources can be that of establishing genotype-phenotype associations. Both integrations are relevant to cancer biomarker meta-analysis, as the proposed study demonstrates. Our approach is based on re-annotating cancer-specific data available at the EBI's ArrayExpress repository and building a data warehouse aimed to biomarker discovery and validation studies. Cancer genes are organized by tissue with biomedical and clinical evidences combined to increase reproducibility and consistency of results. For better comparative evaluation, multiple queries have been designed to efficiently address all types of experiments and platforms, and allow for retrieval of sample-related information, such as cell line, disease state and clinical aspects. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Identification of biomarkers for the antiangiogenic and antitumour activity of the superoxide dismutase 1 (SOD1) inhibitor tetrathiomolybdate (ATN-224)

PubMed Central

Doñate, F; Juarez, J C; Burnett, M E; Manuia, M M; Guan, X; Shaw, D E; Smith, E L P; Timucin, C; Braunstein, M J; Batuman, O A; Mazar, A P

2008-01-01

Tetrathiomolybdate (choline salt; ATN-224), a specific, high-affinity copper binder, is currently being evaluated in several phase II cancer trials. ATN-224 inhibits CuZn superoxide dismutase 1 (SOD1) leading to antiangiogenic and antitumour effects. The pharmacodynamics of tetrathiomolybdate has been followed by tracking ceruloplasmin (Cp), a biomarker for systemic copper. However, at least in mice, the inhibition of angiogenesis occurs before a measurable decrease in systemic copper is observed. Thus, the identification and characterisation of other biomarkers to follow the activity of ATN-224 in the clinic is of great interest. Here, we present the preclinical evaluation of two potential biomarkers for the activity of ATN-224: (i) SOD activity measurements in blood cells in mice and (ii) levels of endothelial progenitor cells (EPCs) in bonnet macaques treated with ATN-224. The superoxide dismutase activity in blood cells in mice is rapidly inhibited by ATN-224 treatment at doses at which angiogenesis is maximally inhibited. Furthermore, ATN-224 dosing in bonnet macaques causes a profound and reversible decrease in EPCs without significant toxicity. Thus, both SOD activity measurements and levels of EPCs may be useful biomarkers of the antiangiogenic activity of ATN-224 to be used in its clinical development. PMID:18253124

Non-invasive identification of protein biomarkers for early pregnancy diagnosis in the cheetah (Acinonyx jubatus).

PubMed

Koester, Diana C; Wildt, David E; Maly, Morgan; Comizzoli, Pierre; Crosier, Adrienne E

2017-01-01

Approximately 80% of cheetahs living in typical zoological collections never reproduce. In more than 60% of breedings, the female is confirmed to ovulate, but parturition fails to occur. It is unknown if these non-pregnant intervals of elevated progesterone (deemed luteal phases) are conception failures or a pregnancy terminating in embryonic/fetal loss. There have been recent advances in metabolic profiling and proteome analyses in many species with mass spectrometry used to identify 'biomarkers' and mechanisms indicative of specific physiological states (including pregnancy). Here, we hypothesized that protein expression in voided cheetah feces varied depending on pregnancy status. We: 1) identified the expansive protein profile present in fecal material of females; and 2) isolated proteins that may be candidates playing a role in early pregnancy establishment and diagnosis. Five hundred and seventy unique proteins were discovered among samples from pregnant (n = 8), non-pregnant, luteal phase (n = 5), and non-ovulatory control (n = 5) cheetahs. Four protein candidates were isolated that were significantly up-regulated and two were down-regulated in samples from pregnant compared to non-pregnant or control counterparts. One up-regulated candidate, immunoglobulin J chain (IGJ; an important component of the secretory immune system) was detected using a commercially available antibody via immunoblotting. Findings revealed that increased IGJ abundance could be used to detect pregnancy successfully in >80% of 23 assessed females within 4 weeks after mating. The discovery of a novel fecal pregnancy marker improves the ability to determine reproductive, especially gestational, status in cheetahs managed in an ex situ insurance and source population.

Translational progress on tumor biomarkers

PubMed Central

Guo, Hongwei; Zhou, Xiaolin; Lu, Yi; Xie, Liye; Chen, Qian; Keller, Evan T; Liu, Qian; Zhou, Qinghua; Zhang, Jian

2015-01-01

There is an urgent need to apply basic research achievements to the clinic. In particular, mechanistic studies should be developed by bench researchers, depending upon clinical demands, in order to improve the survival and quality of life of cancer patients. To date, translational medicine has been addressed in cancer biology, particularly in the identification and characterization of novel tumor biomarkers. This review focuses on the recent achievements and clinical application prospects in tumor biomarkers based on translational medicine. PMID:26557902

The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications.

PubMed

de Graaf, Gimon; Postmus, Douwe; Westerink, Jan; Buskens, Erik

2018-01-01

Translating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study. We defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers. The most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more. It is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.

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

Cancer Transcriptome Dataset Analysis: Comparing Methods of Pathway and Gene Regulatory Network-Based Cluster Identification.

PubMed

Nam, Seungyoon

2017-04-01

Cancer transcriptome analysis is one of the leading areas of Big Data science, biomarker, and pharmaceutical discovery, not to forget personalized medicine. Yet, cancer transcriptomics and postgenomic medicine require innovation in bioinformatics as well as comparison of the performance of available algorithms. In this data analytics context, the value of network generation and algorithms has been widely underscored for addressing the salient questions in cancer pathogenesis. Analysis of cancer trancriptome often results in complicated networks where identification of network modularity remains critical, for example, in delineating the "druggable" molecular targets. Network clustering is useful, but depends on the network topology in and of itself. Notably, the performance of different network-generating tools for network cluster (NC) identification has been little investigated to date. Hence, using gastric cancer (GC) transcriptomic datasets, we compared two algorithms for generating pathway versus gene regulatory network-based NCs, showing that the pathway-based approach better agrees with a reference set of cancer-functional contexts. Finally, by applying pathway-based NC identification to GC transcriptome datasets, we describe cancer NCs that associate with candidate therapeutic targets and biomarkers in GC. These observations collectively inform future research on cancer transcriptomics, drug discovery, and rational development of new analysis tools for optimal harnessing of omics data.

Value of biomarkers in osteoarthritis: current status and perspectives

PubMed Central

Lotz, M; Martel-Pelletier, J; Christiansen, C; Brandi, M-L; Bruyère, O; Chapurlat, R; Collette, J; Cooper, C; Giacovelli, G; Kanis, J A; Karsdal, M A; Kraus, V; Lems, W F; Meulenbelt, I; Pelletier, J-P; Raynauld, J-P; Reiter-Niesert, S; Rizzoli, R; Sandell, L J; Van Spil, W E; Reginster, J-Y

2013-01-01

Osteoarthritis affects the whole joint structure with progressive changes in cartilage, menisci, ligaments and subchondral bone, and synovial inflammation. Biomarkers are being developed to quantify joint remodelling and disease progression. This article was prepared following a working meeting of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis convened to discuss the value of biochemical markers of matrix metabolism in drug development in osteoarthritis. The best candidates are generally molecules or molecular fragments present in cartilage, bone or synovium and may be specific to one type of joint tissue or common to them all. Many currently investigated biomarkers are associated with collagen metabolism in cartilage or bone, or aggrecan metabolism in cartilage. Other biomarkers are related to non-collagenous proteins, inflammation and/or fibrosis. Biomarkers in osteoarthritis can be categorised using the burden of disease, investigative, prognostic, efficacy of intervention, diagnostic and safety classification. There are a number of promising candidates, notably urinary C-terminal telopeptide of collagen type II and serum cartilage oligomeric protein, although none is sufficiently discriminating to differentiate between individual patients and controls (diagnostic) or between patients with different disease severities (burden of disease), predict prognosis in individuals with or without osteoarthritis (prognostic) or perform so consistently that it could function as a surrogate outcome in clinical trials (efficacy of intervention). Future avenues for research include exploration of underlying mechanisms of disease and development of new biomarkers; technological development; the ‘omics’ (genomics, metabolomics, proteomics and lipidomics); design of aggregate scores combining a panel of biomarkers and/or imaging markers into single diagnostic algorithms; and investigation into the relationship between biomarkers and

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

Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes.

PubMed

Xu, Hai-Ming; Kong, Xiang-Dong; Chen, Fei; Huang, Ji-Xiang; Lou, Xiang-Yang; Zhao, Jian-Yi

2015-10-24

Brassica napus is an important oilseed crop. Dissection of the genetic architecture underlying oil-related biological processes will greatly facilitates the genetic improvement of rapeseed. The differential gene expression during pod development offers a snapshot on the genes responsible for oil accumulation in. To identify candidate genes in the linkage peaks reported previously, we used RNA sequencing (RNA-Seq) technology to analyze the pod transcriptomes of German cultivar Sollux and Chinese inbred line Gaoyou. The RNA samples were collected for RNA-Seq at 5-7, 15-17 and 25-27 days after flowering (DAF). Bioinformatics analysis was performed to investigate differentially expressed genes (DEGs). Gene annotation analysis was integrated with QTL mapping and Brassica napus pod transcriptome profiling to detect potential candidate genes in oilseed. Four hundred sixty five and two thousand, one hundred fourteen candidate DEGs were identified, respectively, between two varieties at the same stages and across different periods of each variety. Then, 33 DEGs between Sollux and Gaoyou were identified as the candidate genes affecting seed oil content by combining those DEGs with the quantitative trait locus (QTL) mapping results, of which, one was found to be homologous to Arabidopsis thaliana lipid-related genes. Intervarietal DEGs of lipid pathways in QTL regions represent important candidate genes for oil-related traits. Integrated analysis of transcriptome profiling, QTL mapping and comparative genomics with other relative species leads to efficient identification of most plausible functional genes underlying oil-content related characters, offering valuable resources for bettering breeding program of Brassica napus. This study provided a comprehensive overview on the pod transcriptomes of two varieties with different oil-contents at the three developmental stages.

Blood Biomarkers in Idiopathic Pulmonary Fibrosis.

PubMed

Guiot, Julien; Moermans, Catherine; Henket, Monique; Corhay, Jean-Louis; Louis, Renaud

2017-06-01

Idiopathic pulmonary fibrosis (IPF) is a progressive and lethal lung disease of unknown origin whose incidence has been increasing over the latest decade partly as a consequence of population ageing. New anti-fibrotic therapy including pirfenidone and nintedanib have now proven efficacy in slowing down the disease. Nevertheless, diagnosis and follow-up of IPF remain challenging. This review examines the recent literature on potentially useful blood molecular and cellular biomarkers in IPF. Most of the proposed biomarkers belong to chemokines (IL-8, CCL18), proteases (MMP-1 and MMP-7), and growth factors (IGBPs) families. Circulating T cells and fibrocytes have also gained recent interest in that respect. Up to now, though several interesting candidates are profiling there has not been a single biomarker, which proved to be specific of the disease and predictive of the evolution (decline of pulmonary function test values, risk of acute exacerbation or mortality). Large scale multicentric studies are eagerly needed to confirm the utility of these biomarkers.

Identification of Biomarkers for Defense Response to Plasmopara viticola in a Resistant Grape Variety.

PubMed

Chitarrini, Giulia; Soini, Evelyn; Riccadonna, Samantha; Franceschi, Pietro; Zulini, Luca; Masuero, Domenico; Vecchione, Antonella; Stefanini, Marco; Di Gaspero, Gabriele; Mattivi, Fulvio; Vrhovsek, Urska

2017-01-01

Downy mildew ( Plasmopara viticola ) is one of the most destructive diseases of the cultivated species Vitis vinifera . The use of resistant varieties, originally derived from backcrosses of North American Vitis spp., is a promising solution to reduce disease damage in the vineyards. To shed light on the type and the timing of pathogen-triggered resistance, this work aimed at discovering biomarkers for the defense response in the resistant variety Bianca, using leaf discs after inoculation with a suspension of P. viticola . We investigated primary and secondary metabolism at 12, 24, 48, and 96 h post-inoculation (hpi). We used methods of identification and quantification for lipids (LC-MS/MS), phenols (LC-MS/MS), primary compounds (GC-MS), and semi-quantification for volatile compounds (GC-MS). We were able to identify and quantify or semi-quantify 176 metabolites, among which 53 were modulated in response to pathogen infection. The earliest changes occurred in primary metabolism at 24-48 hpi and involved lipid compounds, specifically unsaturated fatty acid and ceramide; amino acids, in particular proline; and some acids and sugars. At 48 hpi, we also found changes in volatile compounds and accumulation of benzaldehyde, a promoter of salicylic acid-mediated defense. Secondary metabolism was strongly induced only at later stages. The classes of compounds that increased at 96 hpi included phenylpropanoids, flavonols, stilbenes, and stilbenoids. Among stilbenoids we found an accumulation of ampelopsin H + vaticanol C, pallidol, ampelopsin D + quadrangularin A, Z -miyabenol C, and α-viniferin in inoculated samples. Some of these compounds are known as phytoalexins, while others are novel biomarkers for the defense response in Bianca. This work highlighted some important aspects of the host response to P. viticola in a commercial variety under controlled conditions, providing biomarkers for a better understanding of the mechanism of plant defense and a potential

Source identification analysis for the airborne bacteria and fungi using a biomarker approach

NASA Astrophysics Data System (ADS)

Lee, Alex K. Y.; Lau, Arthur P. S.; Cheng, Jessica Y. W.; Fang, Ming; Chan, Chak K.

Our recent studies have reported the feasibility of employing the 3-hydoxy fatty acids (3-OH FAs) and ergosterol as biomarkers to determine the loading of the airborne endotoxin from the Gram-negative bacteria and fungal biomass in atmospheric aerosols, respectively [Lee, A.K.Y., Chan, C.K., Fang, K., Lau, A.P.S., 2004. The 3-hydroxy fatty acids as biomarkers for quantification and characterization of endotoxins and Gram-negative bacteria in atmospheric aerosols in Hong Kong. Atmospheric Environment 38, 6807-6317; Lau, A.P.S., Lee, A.K.Y., Chan, C.K., Fang, K., 2006. Ergosterol as a biomarker for the quantification of the fungal biomass in atmospheric aerosols. Atmospheric Environment 40, 249-259]. These quantified biomarkers do not, however, provide information on their sources. In this study, the year-long dataset of the endotoxin and ergosterol measured in Hong Kong was integrated with the common water-soluble inorganic ions for source identification through the principal component analysis (PCA) and backward air mass trajectory analysis. In the coarse particles (PM 2.5-10), the bacterial endotoxin is loaded in the same factor group with Ca 2+ and accounted for about 20% of the total variance of the PCA. This implies the crustal origin for the airborne bacterial assemblage. The fungal ergosterol in the coarse particles (PM 2.5-10) had by itself loaded in a factor group of 10.8% of the total variance in one of the sampling sites with large area of natural vegetative coverage. This suggests the single entity nature of the fungal spores and their independent emission to the ambient air upon maturation of their vegetative growth. In the fine particles (

Proteome screening of pleural effusions identifies galectin 1 as a diagnostic biomarker and highlights several prognostic biomarkers for malignant mesothelioma.

PubMed

Mundt, Filip; Johansson, Henrik J; Forshed, Jenny; Arslan, Sertaç; Metintas, Muzaffer; Dobra, Katalin; Lehtiö, Janne; Hjerpe, Anders

2014-03-01

Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome

Biomarker Development for Intraductal Papillary Mucinous Neoplasms Using Multiple Reaction Monitoring Mass Spectrometry.

PubMed

Kim, Yikwon; Kang, MeeJoo; Han, Dohyun; Kim, Hyunsoo; Lee, KyoungBun; Kim, Sun-Whe; Kim, Yongkang; Park, Taesung; Jang, Jin-Young; Kim, Youngsoo

2016-01-04

Intraductal papillary mucinous neoplasm (IPMN) is a common precursor of pancreatic cancer (PC). Much clinical attention has been directed toward IPMNs due to the increase in the prevalence of PC. The diagnosis of IPMN depends primarily on a radiological examination, but the diagnostic accuracy of this tool is not satisfactory, necessitating the development of accurate diagnostic biomarkers for IPMN to prevent PC. Recently, high-throughput targeted proteomic quantification methods have accelerated the discovery of biomarkers, rendering them powerful platforms for the evolution of IPMN diagnostic biomarkers. In this study, a robust multiple reaction monitoring (MRM) pipeline was applied to discovery and verify IPMN biomarker candidates in a large cohort of plasma samples. Through highly reproducible MRM assays and a stringent statistical analysis, 11 proteins were selected as IPMN marker candidates with high confidence in 184 plasma samples, comprising a training (n = 84) and test set (n = 100). To improve the discriminatory power, we constructed a six-protein panel by combining marker candidates. The multimarker panel had high discriminatory power in distinguishing between IPMN and controls, including other benign diseases. Consequently, the diagnostic accuracy of IPMN can be improved dramatically with this novel plasma-based panel in combination with a radiological examination.

Protective effect of the Japanese traditional medicine juzentaihoto on myelosuppression induced by the anticancer drug TS-1 and identification of a potential biomarker of this effect.

PubMed

Ogawa, Kazuo; Omatsu, Tatsushi; Matsumoto, Chinami; Tsuchiya, Naoko; Yamamoto, Masahiro; Naito, Yuji; Yoshikawa, Toshikazu

2012-08-09

TS-1 is an oral anticancer drug containing a 5-fluorouracil derivative (Tegafur) that is widely used in Japan for the treatment of cancer, especially gastrointestinal tumors. Frequently, however, TS-1 therapy has to be discontinued because of leukopenia. If it were possible to predict the development of bone marrow suppression before the white blood cell (WBC) count had actually decreased, treatment could be improved by strict dosage control and/or the prophylactic administration of hematopoietic drugs. Juzentaihoto (JTT), a traditional Japanese medicine (Kampo), has been reported to activate hematopoiesis and reduce the side effects associated with chemotherapy and radiotherapy. Here, we 1) evaluate the efficacy of JTT in alleviating myelosuppression induced by TS-1 therapy in mice, and 2) explore biomarkers that reflect both induction by TS-1 and alleviation by JTT of bone marrow suppression using a proteomics approach. Ten mg/kg of TS-1 was administered to Balb/c mice with or without 1 g/kg of oral JTT for 3, 5 and 7 days. WBC count and ratio of CD34+ bone marrow cells (BMCs) were estimated by flow cytometry. Plasma samples were analyzed using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS). A biomarker candidate from SELDI profiling was identified using a combination of cation exchange spin column purification, SDS-PAGE, enzymatic digestion and LC-MS/MS. After administration of TS-1, a significant decrease in WBC count and CD34+ BMC ratio were observed at days 5 and 3, respectively. JTT treatment improved WBC count on day 7 and CD34+ BMC ratio on days 5 and 7. SELDI analysis highlighted three protein peaks that had increased on day 3 after treatment with TS-1 but remained unchanged in mice co-treated with JTT. One of the three peaks, m/z 4223.1, was further investigated and identified as a specific C-terminal fragment of albumin. This study indicates that bone marrow suppression by treatment with TS-1 in mice might

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.

Discovery and characterization of potential prognostic biomarkers for dengue hemorrhagic fever.

PubMed

Poole-Smith, B Katherine; Gilbert, Alexa; Gonzalez, Andrea L; Beltran, Manuela; Tomashek, Kay M; Ward, Brian J; Hunsperger, Elizabeth A; Ndao, Momar

2014-12-01

Half a million patients are hospitalized with severe dengue every year, many of whom would die without timely, appropriate clinical intervention. The majority of dengue cases are uncomplicated; however, 2-5% progress to severe dengue. Severe dengue cases have been reported with increasing frequency over the last 30 years. To discover biomarkers for severe dengue, we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to analyze dengue virus positive serum samples from the acute phase of infection. Using this method, 16 proteins were identified as candidate biomarkers for severe dengue. From these 16 biomarkers, three candidates were selected for confirmation by enzyme-linked immunosorbent assay and Western blot: vitronectin (Vtn, 55.1 kDa), hemopexin (Hx, 52.4 kDa), and serotransferrin (Tf, 79.2 kDa). Vitronectin, Hx, and Tf best differentiated between dengue and severe dengue. © The American Society of Tropical Medicine and Hygiene.

Discovery and Characterization of Potential Prognostic Biomarkers for Dengue Hemorrhagic Fever

PubMed Central

Poole-Smith, B. Katherine; Gilbert, Alexa; Gonzalez, Andrea L.; Beltran, Manuela; Tomashek, Kay M.; Ward, Brian J.; Hunsperger, Elizabeth A.; Ndao, Momar

2014-01-01

Half a million patients are hospitalized with severe dengue every year, many of whom would die without timely, appropriate clinical intervention. The majority of dengue cases are uncomplicated; however, 2–5% progress to severe dengue. Severe dengue cases have been reported with increasing frequency over the last 30 years. To discover biomarkers for severe dengue, we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry to analyze dengue virus positive serum samples from the acute phase of infection. Using this method, 16 proteins were identified as candidate biomarkers for severe dengue. From these 16 biomarkers, three candidates were selected for confirmation by enzyme-linked immunosorbent assay and Western blot: vitronectin (Vtn, 55.1 kDa), hemopexin (Hx, 52.4 kDa), and serotransferrin (Tf, 79.2 kDa). Vitronectin, Hx, and Tf best differentiated between dengue and severe dengue. PMID:25349378

Novel biomarkers for prediabetes, diabetes, and associated complications

PubMed Central

Dorcely, Brenda; Katz, Karin; Jagannathan, Ram; Chiang, Stephanie S; Oluwadare, Babajide; Goldberg, Ira J; Bergman, Michael

2017-01-01

The number of individuals with prediabetes is expected to grow substantially and estimated to globally affect 482 million people by 2040. Therefore, effective methods for diagnosing prediabetes will be required to reduce the risk of progressing to diabetes and its complications. The current biomarkers, glycated hemoglobin (HbA1c), fructosamine, and glycated albumin have limitations including moderate sensitivity and specificity and are inaccurate in certain clinical conditions. Therefore, identification of additional biomarkers is being explored recognizing that any single biomarker will also likely have inherent limitations. Therefore, combining several biomarkers may more precisely identify those at high risk for developing prediabetes and subsequent progression to diabetes. This review describes recently identified biomarkers and their potential utility for addressing the burgeoning epidemic of dysglycemic disorders. PMID:28860833

Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

PubMed

Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

2016-05-01

Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Genomic Biomarkers for Breast Cancer Risk

PubMed Central

Walsh, Michael F.; Nathanson, Katherine L.; Couch, Fergus J.

2016-01-01

Clinical risk assessment for cancer predisposition includes a three-generation pedigree and physical examination to identify inherited syndromes. Additionally genetic and genomic biomarkers may identify individuals with a constitutional basis for their disease that may not be evident clinically. Genomic biomarker testing may detect molecular variations in single genes, panels of genes, or entire genomes. The strength of evidence for the association of a genomic biomarker with disease risk may be weak or strong. The factors contributing to clinical validity and utility of genomic biomarkers include functional laboratory analyses and genetic epidemiologic evidence. Genomic biomarkers may be further classified as low, moderate or highly penetrant based on the likelihood of disease. Genomic biomarkers for breast cancer are comprised of rare highly penetrant mutations of genes such as BRCA1 or BRCA2, moderately penetrant mutations of genes such as CHEK2, as well as more common genomic variants, including single nucleotide polymorphisms, associated with modest effect sizes. When applied in the context of appropriate counseling and interpretation, identification of genomic biomarkers of inherited risk for breast cancer may decrease morbidity and mortality, allow for definitive prevention through assisted reproduction, and serve as a guide to targeted therapy. PMID:26987529

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.

Identification of novel candidate maternal serum protein markers for Down syndrome by integrated proteomic and bioinformatic analysis.

PubMed

Kang, Yuan; Dong, Xinran; Zhou, Qiongjie; Zhang, Ying; Cheng, Yan; Hu, Rong; Su, Cuihong; Jin, Hong; Liu, Xiaohui; Ma, Duan; Tian, Weidong; Li, Xiaotian

2012-03-01

This study aimed to identify candidate protein biomarkers from maternal serum for Down syndrome (DS) by integrated proteomic and bioinformatics analysis. A pregnancy DS group of 18 women and a control group with the same number were prepared, and the maternal serum proteins were analyzed by isobaric tags for relative and absolute quantitation and mass spectrometry, to identify DS differentially expressed maternal serum proteins (DS-DEMSPs). Comprehensive bioinformatics analysis was then employed to analyze DS-DEMSPs both in this paper and seven related publications. Down syndrome differentially expressed maternal serum proteins from different studies are significantly enriched with common Gene Ontology functions, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, transcription factor binding sites, and Pfam protein domains, However, the DS-DEMSPs are less functionally related to known DS-related genes. These evidences suggest that common molecular mechanisms induced by secondary effects may be present upon DS carrying. A simple scoring scheme revealed Alpha-2-macroglobulin, Apolipoprotein A1, Apolipoprotein E, Complement C1s subcomponent, Complement component 5, Complement component 8, alpha polypeptide, Complement component 8, beta polypeptide and Fibronectin as potential DS biomarkers. The integration of proteomics and bioinformatics studies provides a novel approach to develop new prenatal screening methods for noninvasive yet accurate diagnosis of DS. Copyright © 2012 John Wiley & Sons, Ltd.

The search for drug-targetable diagnostic, prognostic and predictive biomarkers in chronic graft-versus-host disease.

PubMed

Ren, Hong-Gang; Adom, Djamilatou; Paczesny, Sophie

2018-05-01

Chronic graft-versus-host disease (cGVHD) continues to be the leading cause of late morbidity and mortality after allogeneic hematopoietic stem cell transplantation (allo-HSCT), which is an increasingly applied curative method for both benign and malignant hematologic disorders. Biomarker identification is crucial for the development of noninvasive and cost-effective cGVHD diagnostic, prognostic, and predictive test for use in clinic. Furthermore, biomarkers may help to gain a better insight on ongoing pathophysiological processes. The recent widespread application of omics technologies including genomics, transcriptomics, proteomics and cytomics provided opportunities to discover novel biomarkers. Areas covered: This review focuses on biomarkers identified through omics that play a critical role in target identification for drug development, and that were verified in at least two independent cohorts. It also summarizes the current status on omics tools used to identify these useful cGVHD targets. We briefly list the biomarkers identified and verified so far. We further address challenges associated to their exploitation and application in the management of cGVHD patients. Finally, insights on biomarkers that are drug targetable and represent potential therapeutic targets are discussed. Expert commentary: We focus on biomarkers that play an essential role in target identification.

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets.

PubMed

Auffret, Marc D; Stewart, Robert; Dewhurst, Richard J; Duthie, Carol-Anne; Rooke, John A; Wallace, Robert J; Freeman, Tom C; Snelling, Timothy J; Watson, Mick; Roehe, Rainer

2017-01-01

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH 4 ), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH 4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH 4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH 4 emissions and methanogens were the microbial populations most closely correlated with CH 4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH 4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH 4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH 4 , but these factors were not identified as robust enough for predictive purposes

Identification, Comparison, and Validation of Robust Rumen Microbial Biomarkers for Methane Emissions Using Diverse Bos Taurus Breeds and Basal Diets

PubMed Central

Auffret, Marc D.; Stewart, Robert; Dewhurst, Richard J.; Duthie, Carol-Anne; Rooke, John A.; Wallace, Robert J.; Freeman, Tom C.; Snelling, Timothy J.; Watson, Mick; Roehe, Rainer

2018-01-01

Previous shotgun metagenomic analyses of ruminal digesta identified some microbial information that might be useful as biomarkers to select cattle that emit less methane (CH4), which is a potent greenhouse gas. It is known that methane production (g/kgDMI) and to an extent the microbial community is heritable and therefore biomarkers can offer a method of selecting cattle for low methane emitting phenotypes. In this study a wider range of Bos Taurus cattle, varying in breed and diet, was investigated to determine microbial communities and genetic markers associated with high/low CH4 emissions. Digesta samples were taken from 50 beef cattle, comprising four cattle breeds, receiving two basal diets containing different proportions of concentrate and also including feed additives (nitrate or lipid), that may influence methane emissions. A combination of partial least square analysis and network analysis enabled the identification of the most significant and robust biomarkers of CH4 emissions (VIP > 0.8) across diets and breeds when comparing all potential biomarkers together. Genes associated with the hydrogenotrophic methanogenesis pathway converting carbon dioxide to methane, provided the dominant biomarkers of CH4 emissions and methanogens were the microbial populations most closely correlated with CH4 emissions and identified by metagenomics. Moreover, these genes grouped together as confirmed by network analysis for each independent experiment and when combined. Finally, the genes involved in the methane synthesis pathway explained a higher proportion of variation in CH4 emissions by PLS analysis compared to phylogenetic parameters or functional genes. These results confirmed the reproducibility of the analysis and the advantage to use these genes as robust biomarkers of CH4 emissions. Volatile fatty acid concentrations and ratios were significantly correlated with CH4, but these factors were not identified as robust enough for predictive purposes. Moreover, the

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.

Biomarkers and Genetics in Peripheral Artery Disease

PubMed Central

Hazarika, Surovi; Annex, Brian H.

2017-01-01

BACKGROUND Peripheral artery disease (PAD) is highly prevalent and there is considerable diversity in the initial clinical manifestation and disease progression among individuals. Currently, there is no ideal biomarker to screen for PAD, to risk stratify patients with PAD, or to monitor therapeutic response to revascularization procedures. Advances in human genetics have markedly enhanced the ability to develop novel diagnostic and therapeutic approaches across a host of human diseases, but such developments in the field of PAD are lagging. CONTENT In this article, we will discuss the epidemiology, traditional risk factors for, and clinical presentations of PAD. We will discuss the possible role of genetic factors and gene–environment interactions in the development and/or progression of PAD. We will further explore future avenues through which genetic advances can be used to better our understanding of the pathophysiology of PAD and potentially find newer therapeutic targets. We will discuss the potential role of biomarkers in identifying patients at risk for PAD and for risk stratifying patients with PAD, and novel approaches to identification of reliable biomarkers in PAD. SUMMARY The exponential growth of genetic tools and newer technologies provides opportunities to investigate and identify newer pathways in the development and progression of PAD, and thereby in the identification of newer biomarkers and therapies. PMID:27872083

Identification of Candidate Genes Responsible for Stem Pith Production Using Expression Analysis in Solid-Stemmed Wheat.

PubMed

Oiestad, A J; Martin, J M; Cook, J; Varella, A C; Giroux, M J

2017-07-01

The wheat stem sawfly (WSS) is an economically important pest of wheat in the Northern Great Plains. The primary means of WSS control is resistance associated with the single quantitative trait locus (QTL) , which controls most stem solidness variation. The goal of this study was to identify stem solidness candidate genes via RNA-seq. This study made use of 28 single nucleotide polymorphism (SNP) makers derived from expressed sequence tags (ESTs) linked to contained within a 5.13 cM region. Allele specific expression of EST markers was examined in stem tissue for solid and hollow-stemmed pairs of two spring wheat near isogenic lines (NILs) differing for the QTL. Of the 28 ESTs, 13 were located within annotated genes and 10 had detectable stem expression. Annotated genes corresponding to four of the ESTs were differentially expressed between solid and hollow-stemmed NILs and represent possible stem solidness gene candidates. Further examination of the 5.13 cM region containing the 28 EST markers identified 260 annotated genes. Twenty of the 260 linked genes were up-regulated in hollow NIL stems, while only seven genes were up-regulated in solid NIL stems. An -methyltransferase within the region of interest was identified as a candidate based on differential expression between solid and hollow-stemmed NILs and putative function. Further study of these candidate genes may lead to the identification of the gene(s) controlling stem solidness and an increased ability to select for wheat stem solidness and manage WSS. Copyright © 2017 Crop Science Society of America.

Molecular biomarkers in idiopathic pulmonary fibrosis

PubMed Central

Ley, Brett; Brown, Kevin K.

2014-01-01

Molecular biomarkers are highly desired in idiopathic pulmonary fibrosis (IPF), where they hold the potential to elucidate underlying disease mechanisms, accelerated drug development, and advance clinical management. Currently, there are no molecular biomarkers in widespread clinical use for IPF, and the search for potential markers remains in its infancy. Proposed core mechanisms in the pathogenesis of IPF for which candidate markers have been offered include alveolar epithelial cell dysfunction, immune dysregulation, and fibrogenesis. Useful markers reflect important pathological pathways, are practically and accurately measured, have undergone extensive validation, and are an improvement upon the current approach for their intended use. The successful development of useful molecular biomarkers is a central challenge for the future of translational research in IPF and will require collaborative efforts among those parties invested in advancing the care of patients with IPF. PMID:25260757

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

PubMed Central

Clementz, Brett A.; Sweeney, John A.; Hamm, Jordan P.; Ivleva, Elena I.; Ethridge, Lauren E.; Pearlson, Godfrey D.; Keshavan, Matcheri S.; Tamminga, Carol A.

2017-01-01

Objective Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. Method A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. Results Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. Conclusions These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when

Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers.

PubMed

Clementz, Brett A; Sweeney, John A; Hamm, Jordan P; Ivleva, Elena I; Ethridge, Lauren E; Pearlson, Godfrey D; Keshavan, Matcheri S; Tamminga, Carol A

2016-04-01

Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold

Use of biomarkers for assessing radiation injury and efficacy of countermeasures

PubMed Central

Singh, Vijay K; Newman, Victoria L; Romaine, Patricia LP; Hauer-Jensen, Martin; Pollard, Harvey B

2016-01-01

Several candidate drugs for acute radiation syndrome (ARS) have been identified that have low toxicity and significant radioprotective and radiomitigative efficacy. Inasmuch as exposing healthy human volunteers to injurious levels of radiation is unethical, development and approval of new radiation countermeasures for ARS are therefore presently based on animal studies and Phase I safety study in healthy volunteers. The Animal Efficacy Rule, which underlies the Food and Drug Administration approval pathway, requires a sound understanding of the mechanisms of injury, drug efficacy, and efficacy biomarkers. In this context, it is important to identify biomarkers for radiation injury and drug efficacy that can extrapolate animal efficacy results, and can be used to convert drug doses deduced from animal studies to those that can be efficacious when used in humans. Here, we summarize the progress of studies to identify candidate biomarkers for the extent of radiation injury and for evaluation of countermeasure efficacy. PMID:26568096

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.

Oral biomarkers in exercise-induced neuroplasticity in Parkinson's disease.

PubMed

Mougeot, J-Lc; Hirsch, M A; Stevens, C B; Mougeot, Fkb

2016-11-01

In this article, we review candidate biomarkers for Parkinson's disease (PD) in oral cavity, potential of oral biomarkers as markers of neuroplasticity, and literature on the effects of exercise on oral cavity biomarkers in PD. We first describe how pathophysiological pathways of PD may be transduced from brain stem and ganglia to oral cavity through the autonomic nervous system or transduced by a reverse path. Next we describe the effects of exercise in PD and potential impact on oral cavity. We propose that biomarkers in oral cavity may be useful targets for describing exercise-induced brain neuroplasticity in PD. Nevertheless, much research remains to be carried out before applying these biomarkers for the determination of disease state and therapeutic response to develop strategies to mitigate motor or non-motor symptoms in PD. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Emerging biomarkers in breast cancer care.

PubMed

Napieralski, Rudolf; Brünner, Nils; Mengele, Karin; Schmitt, Manfred

2010-08-01

Currently, decision-making for breast cancer treatment in the clinical setting is mainly based on clinical data, histomorphological features of the tumor tissue and a few cancer biomarkers such as steroid hormone receptor status (estrogen and progesterone receptors) and oncoprotein HER2 status. Although various therapeutic options were introduced into the clinic in recent decades, with the objective of improving surgery, radiotherapy, biochemotherapy and chemotherapy, varying response of individual patients to certain types of therapy and therapy resistance is still a challenge in breast cancer care. Therefore, since breast cancer treatment should be based on individual features of the patient and her tumor, tailored therapy should be an option by integrating cancer biomarkers to define patients at risk and to reliably predict their course of the disease and/or response to cancer therapy. Recently, candidate-marker approaches and genome-wide transcriptomic and epigenetic screening of different breast cancer tissues and bodily fluids resulted in new promising biomarker panels, allowing breast cancer prognosis, prediction of therapy response and monitoring of therapy efficacy. These biomarkers are now subject of validation in prospective clinical trials.

Quantitative label-free proteomic analysis of human urine to identify novel candidate protein biomarkers for schistosomiasis.

PubMed

Onile, Olugbenga Samson; Calder, Bridget; Soares, Nelson C; Anumudu, Chiaka I; Blackburn, Jonathan M

2017-11-01

Schistosomiasis is a chronic neglected tropical disease that is characterized by continued inflammatory challenges to the exposed population and it has been established as a possible risk factor in the aetiology of bladder cancer. Improved diagnosis of schistosomiasis and its associated pathology is possible through mass spectrometry to identify biomarkers among the infected population, which will influence early detection of the disease and its subtle morbidity. A high-throughput proteomic approach was used to analyse human urine samples for 49 volunteers from Eggua, a schistosomiasis endemic community in South-West, Nigeria. The individuals were previously screened for Schistosoma haematobium and structural bladder pathologies via microscopy and ultrasonography respectively. Samples were categorised into schistosomiasis, schistosomiasis with bladder pathology, bladder pathology, and a normal healthy control group. These samples were analysed to identify potential protein biomarkers. A total of 1306 proteins and 9701 unique peptides were observed in this study (FDR = 0.01). Fifty-four human proteins were found to be potential biomarkers for schistosomiasis and bladder pathologies due to schistosomiasis by label-free quantitative comparison between groups. Thirty-six (36) parasite-derived potential biomarkers were also identified, which include some existing putative schistosomiasis biomarkers that have been previously reported. Some of these proteins include Elongation factor 1 alpha, phosphopyruvate hydratase, histone H4 and heat shock proteins (HSP 60, HSP 70). These findings provide an in-depth analysis of potential schistosoma and human host protein biomarkers for diagnosis of chronic schistosomiasis caused by Schistosoma haematobium and its pathogenesis.

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

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.

Biomarkers for Cystic Fibrosis Drug Development

PubMed Central

Muhlebach, Marianne S.; Clancy, JP; Heltshe, Sonya L.; Ziady, Assem; Kelley, Tom; Accurso, Frank; Pilewski, Joseph; Mayer-Hamblett, Nicole; Joseloff, Elizabeth; Sagel, Scott D.

2016-01-01

Purpose To provide a review of the status of biomarkers in cystic fibrosis drug development, including regulatory definitions and considerations, a summary of biomarkers in current use with supportive data, current gaps, and future needs. Methods Biomarkers are considered across several areas of CF drug development, including cystic fibrosis transmembrane conductance regulator modulation, infection, and inflammation. Results Sweat chloride, nasal potential difference, and intestinal current measurements have been standardized and examined in the context of multicenter trials to quantify CFTR function. Detection and quantification of pathogenic bacteria in CF respiratory cultures (e.g.: Pseudomonas aeruginosa) is commonly used in early phase antimicrobial clinical trials, and to monitor safety of therapeutic interventions. Sputum (e.g.: neutrophil elastase, myeloperoxidase, calprotectin) and blood biomarkers (e.g.: C reactive protein, calprotectin, serum amyloid A) have had variable success in detecting response to inflammatory treatments. Conclusions Biomarkers are used throughout the drug development process in CF, and many have been used in early phase clinical trials to provide proof of concept, detect drug bioactivity, and inform dosing for later-phase studies. Advances in the precision of current biomarkers, and the identification of new biomarkers with ‘omics-based technologies, are needed to accelerate CF drug development. PMID:28215711

Biomarker discovery and development in pediatric critical care medicine

PubMed Central

Kaplan, Jennifer M.; Wong, Hector R.

2010-01-01

Objective To frame the general process of biomarker discovery and development, and to describe a proposal for the development of a multi-biomarker based risk model for pediatric septic shock. Data Source Narrative literature review and author generated data. Main Results Biomarkers can be grouped into four broad classes, based on the intended function: diagnostic, monitoring, surrogate, and stratification. Biomarker discovery and development requires a rigorous process, which is frequently not well followed in the critical care medicine literature. Very few biomarkers have successfully transitioned from the candidate stage to the true biomarker stage. There is great interest in developing diagnostic and stratification biomarkers for sepsis. Procalcitonin is currently the most promising diagnostic biomarker for sepsis. Recent evidence suggests that interleukin-8 can be used to stratify children with septic shock having a high likelihood of survival with standard care. Currently, there is a multi-institutional effort to develop a multi-biomarker based sepsis risk model intended to predict outcome and illness severity for individual children with septic shock. Conclusions Biomarker discovery and development is an important portion of the pediatric critical care medicine translational research agenda. This effort will require collaboration across multiple institutions and investigators. Rigorous conduct of biomarker-focused research holds the promise of transforming our ability to care for individual patients and our ability to conduct clinical trials in a more effective manner. PMID:20473243

Target biomarker profile for the clinical management of paracetamol overdose

PubMed Central

Vliegenthart, A D Bastiaan; Antoine, Daniel J; Dear, James W

2015-01-01

Paracetamol (acetaminophen) overdose is one of the most common causes of acute liver injury in the Western world. To improve patient care and reduce pressure on already stretched health care providers new biomarkers are needed that identify or exclude liver injury soon after an overdose of paracetamol is ingested. This review highlights the current state of paracetamol poisoning management and how novel biomarkers could improve patient care and save healthcare providers money. Based on the widely used concept of defining a target product profile, a target biomarker profile is proposed that identifies desirable and acceptable key properties for a biomarker in development to enable the improved treatment of this patient population. The current biomarker candidates, with improved hepatic specificity and based on the fundamental mechanistic basis of paracetamol-induced liver injury, are reviewed and their performance compared with our target profile. PMID:26076366

[Cellular microparticles, potential useful biomarkers in the identification of cerebrovascular accidents].

PubMed

Anglés-Cano, Eduardo; Vivien, Denis

2009-10-01

The clinical utility of biomarkers depends on their ability to identify high-risk individuals in order to establish preventive, diagnostic or therapeutic measures. Currently, no practical, rapid and sensitive test is available for the diagnosis of acute ischemic stroke. A number of soluble molecules have been identified that are merely associated to these cerebrovascular accidents. Despite this association not a single molecule has the characteristics of a true biomarker directly involved in the pathophysiology of ischemic stroke-none of them is organ-specific and may therefore be elevated in the context of medical comorbidities. When explored as a combination of biomarkers, e.g. matrix metalloproteinase 9, brain natriuretic protein, D-dimer, protein S100B, the question still remains whether serial biomarker analysis provides additional prognostic information. Even S100B, a glial activation protein, has a low specificity for acute ischemic stroke because it may originate from extracranial sources. Current knowledge from the field of cell-derived microparticles suggests that these membrane fragments may represent reliable biomarkers as they are cell-specific and are released early in the pathophysiological cascade of a disease. These microparticles can be found not only in the cerebrospinal fluid but also in tears and circulating blood in case of blood-brain barrier dysfunction. They represent a new challenge in stroke diagnosis and management.

Calcium-deficiency assessment and biomarker identification by an integrated urinary metabonomics analysis

PubMed Central

2013-01-01

Background Calcium deficiency is a global public-health problem. Although the initial stage of calcium deficiency can lead to metabolic alterations or potential pathological changes, calcium deficiency is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of calcium deficiency remain somewhat elusive. To accurately assess and provide appropriate nutritional intervention, we carried out a global analysis of metabolic alterations in response to calcium deficiency. Methods The metabolic alterations associated with calcium deficiency were first investigated in a rat model, using urinary metabonomics based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. Correlations between dietary calcium intake and the biomarkers identified from the rat model were further analyzed to confirm the potential application of these biomarkers in humans. Results Urinary metabolic-profiling analysis could preliminarily distinguish between calcium-deficient and non-deficient rats after a 2-week low-calcium diet. We established an integrated metabonomics strategy for identifying reliable biomarkers of calcium deficiency using a time-course analysis of discriminating metabolites in a low-calcium diet experiment, repeating the low-calcium diet experiment and performing a calcium-supplement experiment. In total, 27 biomarkers were identified, including glycine, oxoglutaric acid, pyrophosphoric acid, sebacic acid, pseudouridine, indoxyl sulfate, taurine, and phenylacetylglycine. The integrated urinary metabonomics analysis, which combined biomarkers with regular trends of change (types A, B, and C), could accurately assess calcium-deficient rats at different stages and clarify the dynamic pathophysiological changes and molecular mechanism of calcium deficiency in detail. Significant correlations between calcium intake and two biomarkers, pseudouridine (Pearson

Gastric biomarkers: a global review.

PubMed

Baniak, Nick; Senger, Jenna-Lynn; Ahmed, Shahid; Kanthan, S C; Kanthan, Rani

2016-08-11

Gastric cancer is an aggressive disease with a poor 5-year survival and large global burden of disease. The disease is biologically and genetically heterogeneous with a poorly understood carcinogenesis at the molecular level. Despite the many prognostic, predictive, and therapeutic biomarkers investigated to date, gastric cancer continues to be detected at an advanced stage with resultant poor clinical outcomes. This is a global review of gastric biomarkers with an emphasis on HER2, E-cadherin, fibroblast growth factor receptor, mammalian target of rapamycin, and hepatocyte growth factor receptor as well as sections on microRNAs, long noncoding RNAs, matrix metalloproteinases, PD-L1, TP53, and microsatellite instability. A deeper understanding of the pathogenesis and biological features of gastric cancer, including the identification and characterization of diagnostic, prognostic, predictive, and therapeutic biomarkers, hopefully will provide improved clinical outcomes.

The current status of biomarkers for predicting toxicity

PubMed Central

Campion, Sarah; Aubrecht, Jiri; Boekelheide, Kim; Brewster, David W; Vaidya, Vishal S; Anderson, Linnea; Burt, Deborah; Dere, Edward; Hwang, Kathleen; Pacheco, Sara; Saikumar, Janani; Schomaker, Shelli; Sigman, Mark; Goodsaid, Federico

2013-01-01

Introduction There are significant rates of attrition in drug development. A number of compounds fail to progress past preclinical development due to limited tools that accurately monitor toxicity in preclinical studies and in the clinic. Research has focused on improving tools for the detection of organ-specific toxicity through the identification and characterization of biomarkers of toxicity. Areas covered This article reviews what we know about emerging biomarkers in toxicology, with a focus on the 2012 Northeast Society of Toxicology meeting titled ‘Translational Biomarkers in Toxicology.’ The areas covered in this meeting are summarized and include biomarkers of testicular injury and dysfunction, emerging biomarkers of kidney injury and translation of emerging biomarkers from preclinical species to human populations. The authors also provide a discussion about the biomarker qualification process and possible improvements to this process. Expert opinion There is currently a gap between the scientific work in the development and qualification of novel biomarkers for nonclinical drug safety assessment and how these biomarkers are actually used in drug safety assessment. A clear and efficient path to regulatory acceptance is needed so that breakthroughs in the biomarker toolkit for nonclinical drug safety assessment can be utilized to aid in the drug development process. PMID:23961847

Biomarkers for wound healing and their evaluation.

PubMed

Patel, S; Maheshwari, A; Chandra, A

2016-01-01

A biological marker (biomarker) is a substance used as an indicator of biological state. Advances in genomics, proteomics and molecular pathology have generated many candidate biomarkers with potential clinical value. Research has identified several cellular events and mediators associated with wound healing that can serve as biomarkers. Macrophages, neutrophils, fibroblasts and platelets release cytokines molecules including TNF-α, interleukins (ILs) and growth factors, of which platelet-derived growth factor (PDGF) holds the greatest importance. As a result, various white cells and connective tissue cells release both matrix metalloproteinases (MMPs) and the tissue inhibitors of metalloproteinases (TIMPs). Studies have demonstrated that IL-1, IL-6, and MMPs, levels above normal, and an abnormally high MMP/TIMP ratio are often present in non-healing wounds. Clinical examination of wounds for these mediators could predict which wounds will heal and which will not, suggesting use of these chemicals as biomarkers of wound healing. There is also evidence that the application of growth factors like PDGF will alleviate the recuperating process of chronic, non-healing wounds. Finding a specific biomarker for wound healing status would be a breakthrough in this field and helping treat impaired wound healing.

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

An integrated workflow for multiplex CSF proteomics and peptidomics-identification of candidate cerebrospinal fluid biomarkers of Alzheimer's disease.

PubMed

Hölttä, Mikko; Minthon, Lennart; Hansson, Oskar; Holmén-Larsson, Jessica; Pike, Ian; Ward, Malcolm; Kuhn, Karsten; Rüetschi, Ulla; Zetterberg, Henrik; Blennow, Kaj; Gobom, Johan

2015-02-06

Many disease processes in the brain are reflected in the protein composition of the cerebrospinal fluid (CSF). In addition to proteins, CSF also contains a large number of endogenous peptides whose potential as disease biomarkers largely remains to be explored. We have developed a novel workflow in which multiplex isobaric labeling is used for simultaneous quantification of endogenous CSF peptides and proteins by liquid chromatography coupled with mass spectrometry. After the labeling of CSF samples, endogenous peptides are separated from proteins by ultrafiltration. The proteins retained on the filters are trypsinized, and the tryptic peptides are collected separately. We evaluated this technique in a comparative pilot study of CSF peptide and protein profiles in eight patients with Alzheimer's disease (AD) and eight nondemented controls. We identified several differences between the AD and control group among endogenous peptides derived from proteins known to be associated with AD, including neurosecretory protein VGF (ratios AD/controls 0.45-0.81), integral membrane protein 2B (ratios AD/controls 0.72-0.84), and metallothionein-3 (ratios AD/controls 0.51-0.61). Analysis of tryptic peptides identified several proteins that were altered in the AD group, some of which have previously been reported as changed in AD, for example, VGF (ratio AD/controls 0.70).

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 genes from the Treacher Collins candidate region

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

Dixon, M.; Dixon, J.; Edwards, S.

Treacher Collins syndrome (TCOF1) is an autosomal dominant disorder of craniofacial development. The TCOF1 locus has previously been mapped to chromosome 5q32-33. The candidate gene region has been defined as being between two flanking markers, ribosomal protein S14 (RPS14) and Annexin 6 (ANX6), by analyzing recombination events in affected individuals. It is estimated that the distance between these flanking markers is 500 kb by three separate analysis methods: (1) radiation hybrid mapping; (2) genetic linkage; and (3) YAC contig analysis. A cosmid contig which spans the candidate gene region for TCOF1 has been constructed by screening the Los Alamos Nationalmore » Laboratory flow-sorted chromosome 5 cosmid library. Cosmids were obtained by using a combination of probes generated from YAC end clones, Alu-PCR fragments from YACs, and asymmetric PCR fragments from both T7 and T3 cosmid ends. Exon amplifications, the selection of genomic coding sequences based upon the presence of functional splice acceptor and donor sites, was used to identify potential exon sequences. Sequences found to be conserved between species were then used to screen cDNA libraries in order to identify candidate genes. To date, four different cDNAs have been isolated from this region and are being analyzed as potential candidate genes for TCOF1. These include the genes encoding plasma glutathione peroxidase (GPX3), heparin sulfate sulfotransferase (HSST), a gene with homology to the ETS family of proteins and one which shows no homology to any known genes. Work is also in progress to identify and characterize additional cDNAs from the candidate gene region.« less

AACR-FDA-NCI Cancer Biomarkers Collaborative consensus report: advancing the use of biomarkers in cancer drug development.

PubMed

Khleif, Samir N; Doroshow, James H; Hait, William N

2010-07-01

Recent discoveries in cancer biology have greatly increased our understanding of cancer at the molecular and cellular level, but translating this knowledge into safe and effective therapies for cancer patients has proved to be challenging. There is a growing imperative to modernize the drug development process by incorporating new techniques that can predict the safety and effectiveness of new drugs faster, with more certainty, and at lower cost. Biomarkers are central to accelerating the identification and adoption of new therapies, but currently, many barriers impede their use in drug development and clinical practice. In 2007, the AACR-FDA-NCI Cancer Biomarkers Collaborative stepped into the national effort to bring together disparate stakeholders to clearly delineate these barriers, to develop recommendations for integrating biomarkers into the cancer drug development enterprise, and to set in motion the necessary action plans and collaborations to see the promise of biomarkers come to fruition, efficiently delivering quality cancer care to patients.

Identification of serum angiopoietin-2 as a biomarker for clinical outcome of colorectal cancer patients treated with bevacizumab-containing therapy.

PubMed

Goede, V; Coutelle, O; Neuneier, J; Reinacher-Schick, A; Schnell, R; Koslowsky, T C; Weihrauch, M R; Cremer, B; Kashkar, H; Odenthal, M; Augustin, H G; Schmiegel, W; Hallek, M; Hacker, U T

2010-10-26

The combination of chemotherapy with the vascular endothelial growth factor (VEGF) antibody bevacizumab is a standard of care in advanced colorectal cancer (CRC). However, biomarkers predicting outcome of bevacizumab-containing treatment are lacking. As angiopoietin-2 (Ang-2) is a key regulator of vascular remodelling in concert with VEGF, we investigated its role as a biomarker in metastatic CRC. Serum Ang-2 levels were measured in 33 healthy volunteers and 90 patients with CRC. Of these, 34 had metastatic disease and received bevacizumab-containing therapy. To determine the tissue of origin of Ang-2, quantitative real-time PCR was performed on microdissected cryosections of human CRC and in a murine xenograft model of CRC using species-specific amplification. Ang-2 originated from the stromal compartment of CRC tissues. Serum Ang-2 levels were significantly elevated in patients with metastatic CRC compared with healthy controls. Amongst patients receiving bevacizumab-containing treatment, low pre-therapeutic serum Ang-2 levels were associated with a significant better response rate (82 vs 31%; P<0.01), a prolonged median progression-free survival (14.1 vs 8.5 months; P<0.01) and a reduction of 91% in the hazard of death (P<0.05). Serum Ang-2 is a candidate biomarker for outcome of patients with metastatic CRC treated with bevacizumab-containing therapy, and it should be further validated to customise combined chemotherapeutic and anti-angiogenic treatment.

Biomarkers in acute heart failure.

PubMed

Mallick, Aditi; Januzzi, James L

2015-06-01

The care of patients with acutely decompensated heart failure is being reshaped by the availability and understanding of several novel and emerging heart failure biomarkers. The gold standard biomarkers in heart failure are B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide, which play an important role in the diagnosis, prognosis, and management of acute decompensated heart failure. Novel biomarkers that are increasingly involved in the processes of myocardial injury, neurohormonal activation, and ventricular remodeling are showing promise in improving diagnosis and prognosis among patients with acute decompensated heart failure. These include midregional proatrial natriuretic peptide, soluble ST2, galectin-3, highly-sensitive troponin, and midregional proadrenomedullin. There has also been an emergence of biomarkers for evaluation of acute decompensated heart failure that assist in the differential diagnosis of dyspnea, such as procalcitonin (for identification of acute pneumonia), as well as markers that predict complications of acute decompensated heart failure, such as renal injury markers. In this article, we will review the pathophysiology and usefulness of established and emerging biomarkers for the clinical diagnosis, prognosis, and management of acute decompensated heart failure. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Identifying module biomarkers from gastric cancer by differential correlation network

PubMed Central

Liu, Xiaoping; Chang, Xiao

2016-01-01

Gastric cancer (stomach cancer) is a severe disease caused by dysregulation of many functionally correlated genes or pathways instead of the mutation of individual genes. Systematic identification of gastric cancer biomarkers can provide insights into the mechanisms underlying this deadly disease and help in the development of new drugs. In this paper, we present a novel network-based approach to predict module biomarkers of gastric cancer that can effectively distinguish the disease from normal samples. Specifically, by assuming that gastric cancer has mainly resulted from dysfunction of biomolecular networks rather than individual genes in an organism, the genes in the module biomarkers are potentially related to gastric cancer. Finally, we identified a module biomarker with 27 genes, and by comparing the module biomarker with known gastric cancer biomarkers, we found that our module biomarker exhibited a greater ability to diagnose the samples with gastric cancer. PMID:27703371

Case-Control Study of Candidate Gene Methylation and Adenomatous Polyp Formation

PubMed Central

M, Alexander; JB, Burch; SE, Steck; C-F, Chen; TG, Hurley; P, Cavicchia; N, Shivappa; J, Guess; H, Zhang; SD, Youngstedt; KE, Creek; S, Lloyd; K, Jones; JR, Hébert

2016-01-01

Purpose Colorectal cancer (CRC) is one of the most common and preventable forms of cancer, but remains the second leading cause of cancer-related death. Colorectal adenomas are precursor lesions that develop in 70–90% of CRC cases. Identification of peripheral biomarkers for adenomas would help to enhance screening efforts. This exploratory study examined the methylation status of 20 candidate markers in peripheral blood leukocytes and their association with adenoma formation. Methods Patients recruited from a local endoscopy clinic provided informed consent, and completed an interview to ascertain demographic, lifestyle, and adenoma risk factors. Cases were individuals with a histopathologically confirmed adenoma, and controls included patients with a normal colonoscopy, or those with histopathological findings not requiring heightened surveillance (normal biopsy, hyperplastic polyp). Methylation-specific polymerase chain reaction was used to characterize candidate gene promoter methylation. Odds ratios and 95% confidence intervals (OR, 95% CI) were calculated using unconditional multivariable logistic regression to test the hypothesis that candidate gene methylation differed between cases and controls, after adjustment for confounders. Results Complete data were available for 107 participants; 36% had adenomas (men: 40%, women: 31%). Hypomethylation of the MINT1 locus (OR: 5.3, 95% CI: 1.0–28.2), and the PER1 (OR: 2.9, 95% CI: 1.1–7.7) and PER3 (OR: 11.6, 95% CI: 1.6–78.5) clock gene promoters was more common among adenoma cases. While specificity was moderate to high for the three markers (71–97%), sensitivity was relatively low (18–45%). Conclusion Follow-up of these epigenetic markers is suggested to further evaluate their utility for adenoma screening or surveillance. PMID:27771773

In Silico Identification of Candidate Genes for Fertility Restoration in Cytoplasmic Male Sterile Perennial Ryegrass (Lolium perenne L.)

PubMed Central

Sykes, Timothy; Yates, Steven; Nagy, Istvan; Asp, Torben; Small, Ian

2017-01-01

Perennial ryegrass (Lolium perenne L.) is widely used for forage production in both permanent and temporary grassland systems. To increase yields in perennial ryegrass, recent breeding efforts have been focused on strategies to more efficiently exploit heterosis by hybrid breeding. Cytoplasmic male sterility (CMS) is a widely applied mechanism to control pollination for commercial hybrid seed production and although CMS systems have been identified in perennial ryegrass, they are yet to be fully characterized. Here, we present a bioinformatics pipeline for efficient identification of candidate restorer of fertility (Rf) genes for CMS. From a high-quality draft of the perennial ryegrass genome, 373 pentatricopeptide repeat (PPR) genes were identified and classified, further identifying 25 restorer of fertility-like PPR (RFL) genes through a combination of DNA sequence clustering and comparison to known Rf genes. This extensive gene family was targeted as the majority of Rf genes in higher plants are RFL genes. These RFL genes were further investigated by phylogenetic analyses, identifying three groups of perennial ryegrass RFLs. These three groups likely represent genomic regions of active RFL generation and identify the probable location of perennial ryegrass PPR-Rf genes. This pipeline allows for the identification of candidate PPR-Rf genes from genomic sequence data and can be used in any plant species. Functional markers for PPR-Rf genes will facilitate map-based cloning of Rf genes and enable the use of CMS as an efficient tool to control pollination for hybrid crop production. PMID:26951780

[Collaborative projects with academia for regulatory science studies on biomarkers].

PubMed

Saito, Yoshiro; Nakamura, Ryosuke; Maekawa, Keiko

2014-01-01

Biomarkers are useful tools to be utilized as indicators/predictors of disease severity and drug responsiveness/safety, and thus are expected to promote efficient drug development and to accelerate proper use of approved drugs. Many academic achievements have been reported, but only a small number of biomarkers are used in clinical trials and drug treatments. Regulatory sciences on biomarkers for their secure development and proper qualification are necessary to facilitate their practical application. We started to collaborate with Tohoku University and Nagoya City University for sample quality, biomarker identification, evaluation of their usage, and making guidances. In this short review, scheme and progress of these projects are introduced.

Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

PubMed

Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

2016-01-01

Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

Enrichment of low-molecular-weight proteins from biofluids for biomarker discovery.

PubMed

Chertov, Oleg; Simpson, John T; Biragyn, Arya; Conrads, Thomas P; Veenstra, Timothy D; Fisher, Robert J

2005-01-01

The dramatic progress in mass spectrometry-based methods of protein identification has triggered a new quest for disease-associated biomarkers. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and its variant surface-enhanced laser desorption/ionization mass spectrometry, provide effective means to explore the less studied information slice of the human serum proteome -- low-molecular-weight proteins and peptides. These low-molecular-weight proteins and peptides are promising for the detection of important biomarkers. Due to the significant experimental problems imposed by high-abundance and high-molecular-weight proteins, it is important to effectively remove these species prior to mass spectrometry analysis of the low-molecular-weight serum and plasma proteomes. In this review, the advantages afforded by recently introduced methods for prefractionation of serum, as they pertain to the detection and identification of biomarkers, will be discussed.

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.

The Role of Biomarkers in Detection of Cardio-toxicity.

PubMed

Shah, Kevin S; Yang, Eric H; Maisel, Alan S; Fonarow, Gregg C

2017-06-01

The goal of this paper is to review the current literature on the role of biomarkers in the detection and management of patients with cardio-oncologic disease. The role of biomarker surveillance in patients with known cardiac disease, as a result of chemotherapy or with the potential to develop cardio-toxicity, will be discussed. In addition, the studies surrounding sub-clinical cardiac toxicity monitoring during therapy, identification of high-risk patients prior to therapy, and tailoring oncologic therapies to potential biomarker risk profiles are reviewed. Based on evidence, to date, troponin and natriuretic peptides have the greatest potential to detect sub-clinical cardiac dysfunction and even tailor therapy to prevent progression based on biomarker profiles. Finally, future directions for potential utilization of novel biomarkers for the improvement of care of patients in the field of cardio-oncology are discussed.

Emerging infection and sepsis biomarkers: will they change current therapies?

PubMed Central

Jacobs, Lauren

2016-01-01

Introduction Sepsis is a heterogeneous syndrome characterized by both immune hyperactivity and relative immune suppression. Biomarkers have the potential to improve recognition and management of sepsis through three main applications: diagnosis, monitoring response to treatment, and stratifying patients based on prognosis or underlying biological response. Areas Covered This review focuses on specific examples of well-studied, evidence-supported biomarkers, and discusses their role in clinical practice with special attention to antibiotic stewardship and cost-effectiveness. Biomarkers were selected based on availability of robust prospective trials and meta-analyses which supported their role as emerging tools to improve the clinical management of sepsis. Expert Commentary Great strides have been made in candidate sepsis biomarker discovery and testing, with the biomarkers in this review showing promise. Yet sepsis remains a dynamic illness with a great degree of biological heterogeneity – heterogeneity which may be further resolved by recently discovered gene expression-based endotypes in septic shock. PMID:27533847

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

PubMed Central

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

2010-01-01

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

[Biomarkers of radiation-induced DNA repair processes].

PubMed

Vallard, Alexis; Rancoule, Chloé; Guy, Jean-Baptiste; Espenel, Sophie; Sauvaigo, Sylvie; Rodriguez-Lafrasse, Claire; Magné, Nicolas

2017-11-01

The identification of DNA repair biomarkers is of paramount importance. Indeed, it is the first step in the process of modulating radiosensitivity and radioresistance. Unlike tools of detection and measurement of DNA damage, DNA repair biomarkers highlight the variations of DNA damage responses, depending on the dose and the dose rate. The aim of the present review is to describe the main biomarkers of radiation-induced DNA repair. We will focus on double strand breaks (DSB), because of their major role in radiation-induced cell death. The most important DNA repair biomarkers are DNA damage signaling proteins, with ATM, DNA-PKcs, 53BP1 and γ-H2AX. They can be analyzed either using immunostaining, or using lived cell imaging. However, to date, these techniques are still time and money consuming. The development of "omics" technologies should lead the way to new (and usable in daily routine) DNA repair biomarkers. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Epigenetic Biomarkers of Preterm Birth and Its Risk Factors

PubMed Central

Knight, Anna K.; Smith, Alicia K.

2016-01-01

A biomarker is a biological measure predictive of a normal or pathogenic process or response. Biomarkers are often useful for making clinical decisions and determining treatment course. One area where such biomarkers would be particularly useful is in identifying women at risk for preterm delivery and related pregnancy complications. Neonates born preterm have significant morbidity and mortality, both in the perinatal period and throughout the life course, and identifying women at risk of delivering preterm may allow for targeted interventions to prevent or delay preterm birth (PTB). In addition to identifying those at increased risk for preterm birth, biomarkers may be able to distinguish neonates at particular risk for future complications due to modifiable environmental factors, such as maternal smoking or alcohol use during pregnancy. Currently, there are no such biomarkers available, though candidate gene and epigenome-wide association studies have identified DNA methylation differences associated with PTB, its risk factors and its long-term outcomes. Further biomarker development is crucial to reducing the health burden associated with adverse intrauterine conditions and preterm birth, and the results of recent DNA methylation studies may advance that goal. PMID:27089367

Biomarkers in the Diagnosis and Prognosis of Alzheimer's Disease.

PubMed

Schaffer, Cole; Sarad, Nakia; DeCrumpe, Ashton; Goswami, Disha; Herrmann, Sara; Morales, Jose; Patel, Parth; Osborne, Jim

2015-10-01

Alzheimer's disease (AD) is a neurodegenerative disease that inhibits cognitive functions and has no cure. This report reviews the current diagnostic standards for AD with an emphasis on early diagnosis using the cerebrospinal fluid (CSF) biomarkers amyloid-beta, t-tau, and p-tau and fluorodeoxyglucose positron emission tomography imaging. Abnormal levels of these CSF biomarkers and decreased cerebral uptake of glucose have recently been used in the early diagnosis of AD in experimental studies. These promising biomarkers can be measured using immunoassays performed in singleplex or multiplex formats. Although presently, there are no Food and Drug Administration-approved in vitro diagnostics (IVDs) for early detection of AD, a multiplex immunoassay measuring a panel of promising AD biomarkers in CSF may be a likely IVD candidate for the clinical AD diagnostic market. Specifically, the INNO-BIA AlzBio3 immunoassay kit, performed using bead arrays on the xMAP Luminex analyzer, allows simultaneous quantification of amyloid-beta, t-tau, and p-tau biomarkers. AD biomarkers can also be screened using enzyme-linked immunosorbent assays that are offered as laboratory-developed tests. © 2014 Society for Laboratory Automation and Screening.

Identification of ovarian cancer-associated proteins in symptomatic women: A novel method for semi-quantitative plasma proteomics.

PubMed

Shield-Artin, Kristy L; Bailey, Mark J; Oliva, Karen; Liovic, Ana K; Barker, Gillian; Dellios, Nicole L; Reisman, Simone; Ayhan, Mustafa; Rice, Gregory E

2012-04-01

To evaluate the utility of an enhanced biomarker discovery approach in order to identify potential biomarkers relevant to ovarian cancer detection. We combined immuno-depletion, liquid-phase IEF, 1D-DIGE, MALDI-TOF/MS and LC-MS/MS to identify differentially expressed proteins in the plasma of symptomatic ovarian cancer patients, stratified by stage, compared to samples obtained from normal subjects. We demonstrate that this approach is a practical alternative to traditional 2D gel techniques and that it has some advantages, most notably increased protein capacity. Proteins were identified in all 76 bands excised from the gels in this project and confirmed the cancer-associated expression of several well-established biomarkers of ovarian cancer. These included C-reactive protein (CRP), haptoglobin, alpha-2 macroglobulin and A1A2. We also identified new ovarian cancer candidate biomarkers, Protein S100-A9 (S100A9) and multimerin-2. The cancer-associated differential expression of CRP and S100A9 was further confirmed by Western blot and ELISA. The methods developed in this study allow for the increased loading of plasma proteins into the analytical stream when compared to traditional 2D-DIGE. This increased protein identification sensitivity allowed us to identify new putative ovarian cancer biomarkers. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomarkers for monitoring clinical efficacy of allergen immunotherapy for allergic rhinoconjunctivitis and allergic asthma: an EAACI Position Paper.

PubMed

Shamji, M H; Kappen, J H; Akdis, M; Jensen-Jarolim, E; Knol, E F; Kleine-Tebbe, J; Bohle, B; Chaker, A M; Till, S J; Valenta, R; Poulsen, L K; Calderon, M A; Demoly, P; Pfaar, O; Jacobsen, L; Durham, S R; Schmidt-Weber, C B

2017-08-01

Allergen immunotherapy (AIT) is an effective treatment for allergic rhinoconjunctivitis (AR) with or without asthma. It is important to note that due to the complex interaction between patient, allergy triggers, symptomatology and vaccines used for AIT, some patients do not respond optimally to the treatment. Furthermore, there are no validated or generally accepted candidate biomarkers that are predictive of the clinical response to AIT. Clinical management of patients receiving AIT and efficacy in randomised controlled trials for drug development could be enhanced by predictive biomarkers. The EAACI taskforce reviewed all candidate biomarkers used in clinical trials of AR patients with/without asthma in a literature review. Biomarkers were grouped into seven domains: (i) IgE (total IgE, specific IgE and sIgE/Total IgE ratio), (ii) IgG-subclasses (sIgG1, sIgG4 including SIgE/IgG4 ratio), (iii) Serum inhibitory activity for IgE (IgE-FAB and IgE-BF), (iv) Basophil activation, (v) Cytokines and Chemokines, (vi) Cellular markers (T regulatory cells, B regulatory cells and dendritic cells) and (vii) In vivo biomarkers (including provocation tests?). All biomarkers were reviewed in the light of their potential advantages as well as their respective drawbacks. Unmet needs and specific recommendations on all seven domains were addressed. It is recommended to explore the use of allergen-specific IgG4 as a biomarker for compliance. sIgE/tIgE and IgE-FAB are considered as potential surrogate candidate biomarkers. Cytokine/chemokines and cellular reponses provided insight into the mechanisms of AIT. More studies for confirmation and interpretation of the possible association with the clinical response to AIT are needed. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network.

PubMed

Zhang, Guangle; Pian, Cong; Chen, Zhi; Zhang, Jin; Xu, Mingmin; Zhang, Liangyun; Chen, Yuanyuan

2018-01-01

LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

Identification of a potential biomarker for FABP4 inhibition: the power of lipidomics in preclinical drug testing.

PubMed

Suhre, Karsten; Römisch-Margl, Werner; de Angelis, Martin Hrabé; Adamski, Jerzy; Luippold, Gerd; Augustin, Robert

2011-06-01

The fatty acid binding protein 4 (FABP4) belongs to the family of lipid chaperones that control intracellular fluxes and compartmentalization of their respective ligands (e.g., fatty acids). FABP4, which is almost exclusively expressed in adipocytes and macrophages, contributes to the development of insulin resistance and atherosclerosis in mice. Lack of FABP4 protects against the development of insulin resistance associated with genetic or diet-induced obesity in mice. Furthermore, total or macrophage-specific FABP4 deficiency is protective against atherosclerosis in apolipoprotein E-deficient mice. The FABP4 small-molecule inhibitor BMS309403 has demonstrated efficacy in mouse models for type 2 diabetes mellitus and atherosclerosis, resembling phenotypes of mice with FABP4 deficiency. However, despite the therapeutically attractive long-term effects of FABP4 inhibition, an acute biomarker for drug action is lacking. The authors applied mass spectrometry lipidomics analysis to in vitro and in vivo (plasma and adipose tissue) samples upon inhibitor treatment. They report the identification of a potential biomarker for acute in vivo FABP4 inhibition that is applicable for further investigations and can be implemented in simple and fast-flow injection mass spectrometry assays. In addition, this approach can be considered a proof-of-principle study that can be applied to other lipid-pathway targeting mechanisms.

In Vivo Cancer Biomarkers of Esophageal Neoplasia

PubMed Central

Lu, Shaoying; Wang, Thomas D

2011-01-01

Summary The emergence of in vivo cancer biomarkers is promising tool for early detection, risk stratification, and therapeutic intervention in the esophagus, where adenocarcinoma is increasing at a rate that is faster than any other in industrialized nations. Exciting advances in target identification, probe development, and optical instrumentation are creating tremendous new opportunities for advancing techniques of molecular imaging. Progress in these areas is being made with small animal models of esophageal cancer using surgical approaches to induce reflux of acid and bile, and these findings are beginning to be evaluated in the clinic. Further identification of relevant targets, characterization of specific probes, and development of endoscopic imaging technologies are needed to further this direction in the field of molecular medicine. In the future, new methods that use in vivo cancer biomarkers for the early detection of neoplastic changes in the setting of Barrett's esophagus will become available. PMID:19126962

Biomarkers for the management of pre-eclampsia in pregnant women

PubMed Central

Petla, Lakshmi Tanuja; Chikkala, Rosy; Ratnakar, K.S.; Kodati, Vijayalakshmi; Sritharan, V.

2013-01-01

Pre-eclampsia (PE) is a pregnancy related disorder characterized by hypertension and proteinuria noticeable after 20 wk of gestation. It is a leading cause of maternal and foetal mortality and morbidity worldwide. The aetiology of the disease is unknown, but recent studies have revealed that this disorder appears to originate in placenta and is characterized by widespread maternal endothelial dysfunction. Till date, delivery of placenta is the only cure for the disease. So, there is a need for the identification of highly specific and sensitive biochemical markers that would allow early identification of patients at risk and thus help in providing proper prenatal care. Several promising biomarkers have been proposed, alone or in combination, that may help in predicting women who are likely to develop PE. Maternal serum concentrations of these biomarkers either increase or decrease in PE during gestation. This review focuses on the various biomarkers available and their utility in predicting pre-eclampsia. PMID:24056556

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.

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.

Identification of candidate infection genes from the model entomopathogenic nematode Heterorhabditis bacteriophora.

PubMed

Vadnal, Jonathan; Ratnappan, Ramesh; Keaney, Melissa; Kenney, Eric; Eleftherianos, Ioannis; O'Halloran, Damien; Hawdon, John M

2017-01-03

Despite important progress in the field of innate immunity, our understanding of host immune responses to parasitic nematode infections lags behind that of responses to microbes. A limiting factor has been the obligate requirement for a vertebrate host which has hindered investigation of the parasitic nematode infective process. The nematode parasite Heterorhabditis bacteriophora offers great potential as a model to genetically dissect the process of infection. With its mutualistic Photorhabdus luminescens bacteria, H. bacteriophora invades multiple species of insects, which it kills and exploits as a food source for the development of several nematode generations. The ability to culture the life cycle of H. bacteriophora on plates growing the bacterial symbiont makes it a very exciting model of parasitic infection that can be used to unlock the molecular events occurring during infection of a host that are inaccessible using vertebrate hosts. To profile the transcriptional response of an infective nematode during the early stage of infection, we performed next generation RNA sequencing on H. bacteriophora IJs incubated in Manduca sexta hemolymph plasma for 9 h. A subset of up-regulated and down-regulated genes were validated using qRT-PCR. Comparative analysis of the transcriptome with untreated controls found a number of differentially expressed genes (DEGs) which cover a number of different functional categories. A subset of DEGs is conserved across Clade V parasitic nematodes revealing an array of candidate parasitic genes. Our analysis reveals transcriptional changes in the regulation of a large number of genes, most of which have not been shown previously to play a role in the process of infection. A significant proportion of these genes are unique to parasitic nematodes, suggesting the identification of a group of parasitism factors within nematodes. Future studies using these candidates may provide functional insight into the process of nematode parasitism

Biology and Biomarkers for Wound Healing.

PubMed

Lindley, Linsey E; Stojadinovic, Olivera; Pastar, Irena; Tomic-Canic, Marjana

2016-09-01

As the population grows older, the incidence and prevalence of conditions that lead to a predisposition for poor wound healing also increase. Ultimately, this increase in nonhealing wounds has led to significant morbidity and mortality with subsequent huge economic ramifications. Therefore, understanding specific molecular mechanisms underlying aberrant wound healing is of great importance. It has and will continue to be the leading pathway to the discovery of therapeutic targets, as well as diagnostic molecular biomarkers. Biomarkers may help identify and stratify subsets of nonhealing patients for whom biomarker-guided approaches may aid in healing. A series of literature searches were performed using Medline, PubMed, Cochrane Library, and Internet searches. Currently, biomarkers are being identified using biomaterials sourced locally from human wounds and/or systemically using high-throughput "omics" modalities (genomic, proteomic, lipidomic, and metabolomic analysis). In this review, we highlight the current status of clinically applicable biomarkers and propose multiple steps in validation and implementation spectrum, including those measured in tissue specimens, for example, β-catenin and c-myc, wound fluid, matrix metalloproteinases and interleukins, swabs, wound microbiota, and serum, for example, procalcitonin and matrix metalloproteinases. Identification of numerous potential biomarkers using different avenues of sample collection and molecular approaches is currently underway. A focus on simplicity and consistent implementation of these biomarkers, as well as an emphasis on efficacious follow-up therapeutics, is necessary for transition of this technology to clinically feasible point-of-care applications.

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer.

PubMed

Chang, Hae Ryung; Nam, Seungyoon; Lee, Jinhyuk; Kim, Jin-Hee; Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-12-06

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer "Big Data" has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of "hit" compounds.

Biomarkers of aging in Drosophila.

PubMed

Jacobson, Jake; Lambert, Adrian J; Portero-Otín, Manuel; Pamplona, Reinald; Magwere, Tapiwanashe; Miwa, Satomi; Driege, Yasmine; Brand, Martin D; Partridge, Linda

2010-08-01

Low environmental temperature and dietary restriction (DR) extend lifespan in diverse organisms. In the fruit fly Drosophila, switching flies between temperatures alters the rate at which mortality subsequently increases with age but does not reverse mortality rate. In contrast, DR acts acutely to lower mortality risk; flies switched between control feeding and DR show a rapid reversal of mortality rate. Dietary restriction thus does not slow accumulation of aging-related damage. Molecular species that track the effects of temperatures on mortality but are unaltered with switches in diet are therefore potential biomarkers of aging-related damage. However, molecular species that switch upon instigation or withdrawal of DR are thus potential biomarkers of mechanisms underlying risk of mortality, but not of aging-related damage. Using this approach, we assessed several commonly used biomarkers of aging-related damage. Accumulation of fluorescent advanced glycation end products (AGEs) correlated strongly with mortality rate of flies at different temperatures but was independent of diet. Hence, fluorescent AGEs are biomarkers of aging-related damage in flies. In contrast, five oxidized and glycated protein adducts accumulated with age, but were reversible with both temperature and diet, and are therefore not markers either of acute risk of dying or of aging-related damage. Our approach provides a powerful method for identification of biomarkers of aging.

Biomarkers of ageing in Drosophila

PubMed Central

Jacobson, Jake; Portero-Otín, Manuel; Pamplona, Reinald; Magwere, Tapiwanashe; Miwa, Satomi; Driege, Yasmine; Brand, Martin D.; Partridge, Linda

2015-01-01

Summary Low environmental temperature and dietary restriction (DR) extend lifespan in diverse organisms. In the fruit fly Drosophila, switching flies between temperatures alters the rate at which mortality subsequently increases with age but does not reverse mortality rate. In contrast, DR acts acutely to lower mortality risk; flies switched between control feeding and DR show a rapid reversal of mortality rate. DR thus does not slow accumulation of ageing-related damage. Molecular species that track the effects of temperatures on mortality but are unaltered with switches in diet are therefore potential biomarkers of ageing-related damage. However, molecular species that switch upon instigation or withdrawal of DR are thus potential biomarkers of mechanisms underlying risk of mortality, but not of ageing-related damage. Using this approach, we assessed several commonly used biomarkers of ageing-related damage. Accumulation of fluorescent advanced glycation end products (AGEs) correlated strongly with mortality rate of flies at different temperatures but was independent of diet. Hence fluorescent AGEs are biomarkers of ageing-related damage in flies. In contrast, five oxidised and glycated protein adducts accumulated with age, but were reversible with both temperature and diet, and are therefore not markers either of acute risk of dying or of ageing-related damage. Our approach provides a powerful method for identification of biomarkers of ageing. PMID:20367621

Biomarkers predicting sepsis in polytrauma patients: Current evidence.

PubMed

Ciriello, Vincenzo; Gudipati, Suribabu; Stavrou, Petros Z; Kanakaris, Nikolaos K; Bellamy, Mark C; Giannoudis, Peter V

2013-12-01

Major trauma still represents one of the leading causes of death in the first four decades of life. Septic complications represent the predominant causes of late death (45% of overall mortality) in polytrauma patients. The ability of clinicians to early differentiate between systemic inflammatory response syndrome (SIRS) and sepsis is demonstrated to improve clinical outcome and mortality. The identification of an "ideal" biomarker able to early recognize incoming septic complications in trauma patients is still a challenge for researchers. To evaluate the existing evidence regarding the role of biomarkers to predict or facilitate early diagnosis of sepsis in trauma patients, trying to compile some recommendations for the clinical setting. An Internet-based search of the MEDLINE, EMBASE and Cochrane Library databases was performed using the search terms: "Biomarkers", "Sepsis" and "Trauma" in various combinations. The methodological quality of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies Checklist (QUADAS). After data extraction, the level of evidence available for each bio-marker was rated and presented using the "best-evidence synthesis" method, in line with the US Agency for Healthcare Research and Quality. Thirty studies were eligible for the final analysis: 13 case-control studies and 17 cohort studies. The "strong evidence" available demonstrated the potential use of procalcitonin as an early indicator of post-traumatic septic complications and reported the inability of c-reactive protein (CRP) to specifically identify infective complications. Moderate, conflicting and limited evidence are available for the other 31 biomarkers. Several biomarkers have been evaluated for predicting or making early diagnosis of sepsis in trauma patients. Current evidence does not support the use of a single biomarker in diagnosing sepsis. However, procalcitonin trend was found to be useful in early identification of post

Potential biomarkers in psychiatry: focus on the cholesterol system

PubMed Central

Woods, Alisa G; Sokolowska, Izabela; Taurines, Regina; Gerlach, Manfred; Dudley, Edward; Thome, Johannes; Darie, Costel C

2012-01-01

Abstract Measuring biomarkers to identify and assess illness is a strategy growing in popularity and relevance. Although already in clinical use for treating and predicting cancer, no biological measurement is used clinically for any psychiatric disorder. Biomarkers could predict the course of a medical problem, and aid in determining how and when to treat. Several studies have indicated that of candidate psychiatric biomarkers detected using proteomic techniques, cholesterol and associated proteins, specifically apolipoproteins (Apos), may be of interest. Cholesterol is necessary for brain development and its synthesis continues at a lower rate in the adult brain. Apos are the protein component of lipoproteins responsible for lipid transport. There is extensive evidence that the levels of cholesterol and Apos may be disturbed in psychiatric disorders, including autistic spectrum disorders (ASD). Here, we describe putative serum biomarkers for psychiatric disorders, and the role of cholesterol and Apos in central nervous system (CNS) disorders. PMID:22304330

Comparative genomics study for the identification of drug and vaccine targets in Staphylococcus aureus: MurA ligase enzyme as a proposed candidate.

PubMed

Ghosh, Soma; Prava, Jyoti; Samal, Himanshu Bhusan; Suar, Mrutyunjay; Mahapatra, Rajani Kanta

2014-06-01

Now-a-days increasing emergence of antibiotic-resistant pathogenic microorganisms is one of the biggest challenges for management of disease. In the present study comparative genomics, metabolic pathways analysis and additional parameters were defined for the identification of 94 non-homologous essential proteins in Staphylococcus aureus genome. Further study prioritized 19 proteins as vaccine candidates where as druggability study reports 34 proteins suitable as drug targets. Enzymes from peptidoglycan biosynthesis, folate biosynthesis were identified as candidates for drug development. Furthermore, bacterial secretory proteins and few hypothetical proteins identified in our analysis fulfill the criteria of vaccine candidates. As a case study, we built a homology model of one of the potential drug target, MurA ligase, using MODELLER (9v12) software. The model has been further selected for in silico docking study with inhibitors from the DrugBank database. Results from this study could facilitate selection of proteins for entry into drug design and vaccine production pipelines. Copyright © 2014 Elsevier B.V. All rights reserved.

Differential blood-based biomarkers of psychopathological dimensions of schizophrenia.

PubMed

Garcia-Alvarez, Leticia; Garcia-Portilla, Maria Paz; Gonzalez-Blanco, Leticia; Saiz Martinez, Pilar Alejandra; de la Fuente-Tomas, Lorena; Menendez-Miranda, Isabel; Iglesias, Celso; Bobes, Julio

Symptomatology of schizophrenia is heterogeneous, there is not any pathognomonic symptom. Moreover, the diagnosis is difficult, since it is based on subjective information, instead of markers. The purpose of this study is to provide a review of the current status of blood-based biomarkers of psychopathological dimensions of schizophrenia. Inflammatory, hormonal or metabolic dysfunctions have been identified in patients with schizophrenia and it has attempted to establish biomarkers responsible for these dysfunctions. The identification of these biomarkers could contribute to the diagnosis and treatment of schizophrenia. Copyright © 2016 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Physiological and molecular characterization of drought responses and identification of candidate tolerance genes in cassava

PubMed Central

Turyagyenda, Laban F.; Kizito, Elizabeth B.; Ferguson, Morag; Baguma, Yona; Agaba, Morris; Harvey, Jagger J. W.; Osiru, David S. O.

2013-01-01

Cassava is an important root crop to resource-poor farmers in marginal areas, where its production faces drought stress constraints. Given the difficulties associated with cassava breeding, a molecular understanding of drought tolerance in cassava will help in the identification of markers for use in marker-assisted selection and genes for transgenic improvement of drought tolerance. This study was carried out to identify candidate drought-tolerance genes and expression-based markers of drought stress in cassava. One drought-tolerant (improved variety) and one drought-susceptible (farmer-preferred) cassava landrace were grown in the glasshouse under well-watered and water-stressed conditions. Their morphological, physiological and molecular responses to drought were characterized. Morphological and physiological measurements indicate that the tolerance of the improved variety is based on drought avoidance, through reduction of water loss via partial stomatal closure. Ten genes that have previously been biologically validated as conferring or being associated with drought tolerance in other plant species were confirmed as being drought responsive in cassava. Four genes (MeALDH, MeZFP, MeMSD and MeRD28) were identified as candidate cassava drought-tolerance genes, as they were exclusively up-regulated in the drought-tolerant genotype to comparable levels known to confer drought tolerance in other species. Based on these genes, we hypothesize that the basis of the tolerance at the cellular level is probably through mitigation of the oxidative burst and osmotic adjustment. This study provides an initial characterization of the molecular response of cassava to drought stress resembling field conditions. The drought-responsive genes can now be used as expression-based markers of drought stress tolerance in cassava, and the candidate tolerance genes tested in the context of breeding (as possible quantitative trait loci) and engineering drought tolerance in transgenics

Galactic SNR Candidates in the ROSAT All-Sky Survey

NASA Technical Reports Server (NTRS)

Schaudel, Daniel; Becker, Werner; Voges, Wolfgand; Reich, Wolfgang; Weisskopf, Martin; Six, N. Frank (Technical Monitor)

2001-01-01

Identified radio supernova remnants (SNRS) in the Galaxy comprise an incomplete sample of the SNR population due to various selection effects. ROSAT performed the first all-sky survey with an imaging X-ray telescope, and thus provides another window for finding SNRS and compact objects that may reside within them. Performing a search for extended X-ray sources in the ROSAT all-sky survey database about 350 objects were identified as SNR candidates in recent years. Continuing this systematic search, we have reanalyzed the ROSAT all-sky survey (BASS) data of these candidates and correlated the results with radio surveys like NVSS, ATNF, Molonglo, and Effelsberg. A further correlation with SIMBAD and NED were used for subsequent identification purpose. About 50 of the 350 candidates turned out to be likely galaxies or clusters of galaxies. We found 14 RASS sources which are very promising SNR candidates and are currently subject of further follow-up studies. We will provide the details of the identification campaign and present first results.

Omics-based biomarkers: current status and potential use in the clinic.

PubMed

Quezada, Héctor; Guzmán-Ortiz, Ana Laura; Díaz-Sánchez, Hugo; Valle-Rios, Ricardo; Aguirre-Hernández, Jesús

In recent years, the use of high-throughput omics technologies has led to the rapid discovery of many candidate biomarkers. However, few of them have made the transition to the clinic. In this review, the promise of omics technologies to contribute to the process of biomarker development is described. An overview of the current state in this area is presented with examples of genomics, proteomics, transcriptomics, metabolomics and microbiomics biomarkers in the field of oncology, along with some proposed strategies to accelerate their validation and translation to improve the care of patients with neoplasms. The inherent complexity underlying neoplasms combined with the requirement of developing well-designed biomarker discovery processes based on omics technologies present a challenge for the effective development of biomarkers that may be useful in guiding therapies, addressing disease risks, and predicting clinical outcomes. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Evidence for Post-Translational Processing of Vascular Endothelial (VE)-Cadherin in Brain Tumors: Towards a Candidate Biomarker

PubMed Central

Vilgrain, Isabelle; Sidibé, Adama; Polena, Helena; Cand, Francine; Mannic, Tiphaine; Arboleas, Mélanie; Boccard, Sandra; Baudet, Antoine; Gulino-Debrac, Danielle; Bouillet, Laurence; Quesada, Jean-Louis; Mendoza, Christophe; Lebas, Jean-François; Pelletier, Laurent; Berger, François

2013-01-01

Vessel abnormalities are among the most important features in malignant glioma. Vascular endothelial (VE)-cadherin is of major importance for vascular integrity. Upon cytokine challenge, VE-cadherin structural modifications have been described including tyrosine phosphorylation and cleavage. The goal of this study was to examine whether these events occurred in human glioma vessels. We demonstrated that VE-cadherin is highly expressed in human glioma tissue and tyrosine phosphorylated at site Y685, a site previously found phosphorylated upon VEGF challenge, via Src activation. In vitro experiments showed that VEGF-induced VE-cadherin phosphorylation, preceded the cleavage of its extracellular adhesive domain (sVE, 90 kDa). Interestingly, metalloproteases (MMPs) secreted by glioma cell lines were responsible for sVE release. Because VEGF and MMPs are important components of tumor microenvironment, we hypothesized that VE-cadherin proteolysis might occur in human brain tumors. Analysis of glioma patient sera prior treatment confirmed the presence of sVE in bloodstream. Furthermore, sVE levels studied in a cohort of 53 glioma patients were significantly predictive of the overall survival at three years (HR 0.13 [0.04; 0.40] p≤0.001), irrespective to histopathological grade of tumors. Altogether, these results suggest that VE-cadherin structural modifications should be examined as candidate biomarkers of tumor vessel abnormalities, with promising applications in oncology. PMID:24358106

Lipid Biomarkers for a Hypersaline Microbial Mat Community

NASA Technical Reports Server (NTRS)

Jahnke, Linda L.; Embaye, Tsege; Turk, Kendra A.

2003-01-01

The use of lipid biomarkers and their carbon isotopic compositions are valuable tools for establishing links to ancient microbial ecosystems. As witnessed by the stromatolite record, benthic microbial mats grew in shallow water lagoonal environments where microorganisms had virtually no competition apart from the harsh conditions of hypersalinity, desiccation and intense light. Today, the modern counterparts of these microbial ecosystems find appropriate niches in only a few places where extremes eliminate eukaryotic grazers. Answers to many outstanding questions about the evolution of microorganisms and their environments on early Earth are best answered through study of these extant analogs. Lipids associated with various groups of bacteria can be valuable biomarkers for identification of specific groups of microorganisms both in ancient organic-rich sedimentary rocks (geolipids) and contemporary microbial communities (membrane lipids). Use of compound specific isotope analysis adds additional refinement to the identification of biomarker source, so that it is possible to take advantage of the 3C-depletions associated with various functional groups of organisms (i.e. autotrophs, heterotrophs, methanotrophs, methanogens) responsible for the cycling of carbon within a microbial community. Our recent work has focused on a set of hypersaline evaporation ponds at Guerrero Negro, Baja California Sur, Mexico which support the abundant growth of Microcoleus-dominated microbial mats. Specific biomarkers for diatoms, cyanobacteria, archaea, green nonsulfur (GNS), sulfate reducing, and methanotrophic bacteria have been identified. Analyses of the ester-bound fatty acids indicate a highly diverse microbial community, dominated by photosynthetic organisms at the surface.

Biomarkers of Rheumatoid Arthritis–Associated Interstitial Lung Disease

PubMed Central

Chen, Juan; Doyle, Tracy J.; Liu, Yongliang; Aggarwal, Rohit; Wang, Xiaoping; Shi, Yonghong; Ge, Sheng Xiang; Huang, Heqing; Lin, Qingyan; Liu, Wen; Cai, Yongjin; Koontz, Diane; Fuhrman, Carl R.; Golzarri, Maria F.; Liu, Yushi; Hatabu, Hiroto; Nishino, Mizuki; Araki, Tetsuro; Dellaripa, Paul F.; Oddis, Chester V.; Rosas, Ivan O.; Ascherman, Dana P.

2015-01-01

Objective Interstitial lung disease (ILD) is a relatively common extraarticular manifestation of rheumatoid arthritis (RA) that contributes significantly to disease burden and excess mortality. The purpose of this study was to identify peripheral blood markers of RA-associated ILD that can facilitate earlier diagnosis and provide insight regarding the pathogenesis of this potentially devastating disease complication. Methods Patients with RA who were enrolled in a well-characterized Chinese identification cohort or a US replication cohort were subclassified as having RA–no ILD, RA–mild ILD, or RA–advanced ILD, based on high-resolution computed tomography scans of the chest. Multiplex enzyme-linked immunosorbent assays (ELISAs) and Luminex xMAP technology were used to assess 36 cytokines/chemokines, matrix metalloproteinases (MMPs), and acute-phase proteins in the identification cohort. Unadjusted and adjusted logistic regression models were used to quantify the strength of association between RA-ILD and biomarkers of interest. Results MMP-7 and interferon-γ–inducible protein 10 (IP-10)/CXCL10 were identified by multiplex ELISA as potential biomarkers for RA-ILD in 133 RA patients comprising the Chinese identification cohort (50 RA–no ILD, 41 RA-ILD, 42 RA–indeterminate ILD). The findings were confirmed by standard solid-phase sandwich ELISA in the Chinese identification cohort as well as an independent cohort of US patients with RA and different stages of ILD (22 RA–no ILD, 49 RA-ILD, 15 RA–indeterminate ILD), with statistically significant associations in both unadjusted and adjusted logistic regression analyses. Conclusion Levels of MMP-7 and IP-10/CXCL10 are elevated in the serum of RA patients with ILD, whether mild or advanced, supporting their value as pathogenically relevant biomarkers that can contribute to noninvasive detection of this extraarticular disease complication. PMID:25302945

Advances in the design of nanomaterial-based electrochemical affinity and enzymatic biosensors for metabolic biomarkers: A review.

PubMed

Farzin, Leila; Shamsipur, Mojtaba; Samandari, Leila; Sheibani, Shahab

2018-05-02

This review (with 340 refs) focuses on methods for specific and sensitive detection of metabolites for diagnostic purposes, with particular emphasis on electrochemical nanomaterial-based sensors. It also covers novel candidate metabolites as potential biomarkers for diseases such as neurodegenerative diseases, autism spectrum disorder and hepatitis. Following an introduction into the field of metabolic biomarkers, a first major section classifies electrochemical biosensors according to the bioreceptor type (enzymatic, immuno, apta and peptide based sensors). A next section covers applications of nanomaterials in electrochemical biosensing (with subsections on the classification of nanomaterials, electrochemical approaches for signal generation and amplification using nanomaterials, and on nanomaterials as tags). A next large sections treats candidate metabolic biomarkers for diagnosis of diseases (in the context with metabolomics), with subsections on biomarkers for neurodegenerative diseases, autism spectrum disorder and hepatitis. The Conclusion addresses current challenges and future perspectives. Graphical abstract This review focuses on the recent developments in electrochemical biosensors based on the use of nanomaterials for the detection of metabolic biomarkers. It covers the critical metabolites for some diseases such as neurodegenerative diseases, autism spectrum disorder and hepatitis.

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.

Risk Factors and Biomarkers of Age-Related Macular Degeneration

PubMed Central

Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

2016-01-01

A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

Biology and Biomarkers for Wound Healing

PubMed Central

Lindley, Linsey E.; Stojadinovic, Olivera; Pastar, Irena; Tomic-Canic, Marjana

2016-01-01

Background As the population grows older, the incidence and prevalence of conditions which lead to a predisposition for poor wound healing also increases. Ultimately, this increase in non-healing wounds has led to significant morbidity and mortality with subsequent huge economic ramifications. Therefore, understanding specific molecular mechanisms underlying aberrant wound healing is of great importance. It has, and will continue to be the leading pathway to the discovery of therapeutic targets as well as diagnostic molecular biomarkers. Biomarkers may help identify and stratify subsets of non-healing patients for whom biomarker-guided approaches may aid in healing. Methods A series of literature searches were performed using Medline, PubMed, Cochrane Library, and Internet searches. Results Currently, biomarkers are being identified using biomaterials sourced locally, from human wounds and/or systemically using systematic high-throughput “omics” modalities (genomic, proteomic, lipidomic, metabolomic analysis). In this review we highlight the current status of clinically applicable biomarkers and propose multiple steps in validation and implementation spectrum including those measured in tissue specimens e.g. β-catenin and c-myc, wound fluid e.g. MMP’s and interleukins, swabs e.g. wound microbiota and serum e.g. procalcitonin and MMP’s. Conclusions Identification of numerous potential biomarkers utilizing different avenues of sample collection and molecular approaches is currently underway. A focus on simplicity, and consistent implementation of these biomarkers as well as an emphasis on efficacious follow-up therapeutics is necessary for transition of this technology to clinically feasible point-of-care applications. PMID:27556760

Cardiac transplantation: candidate identification, evaluation, and management.

PubMed

McCalmont, Vicki; Ohler, Linda

2008-01-01

For more than 40 years, cardiac transplantation has been a treatment option for patients with severe heart failure in whom optimal medical management is no longer effective. Critical care nurses are integrally involved in the care of patients with severe heart failure who may benefit from cardiac transplantation and are in a special position to recognize potential candidates for transplantation. Understanding patient selection criteria, the evaluation process, and how patients are managed while awaiting transplantation is key to the knowledge and skills required. It is also important to understand the allocation of donor hearts as part of this process. The waiting period for a suitable donor heart can be long and a patient's condition may deteriorate, requiring an increase in pharmacologic bridges with intravenous inotropic agents or mechanical bridges with circulatory assist devices. Critical care nurses become important as a personal bridge to transplantation through their education of patients and families and helping them cope with their fears during the waiting period. Critical care nurses who possess knowledge of patient selection and organ allocation processes along with the skills of caring for this complex patient population can contribute to better outcomes for patients with heart failure who may be candidates for cardiac transplantation.

Impact of biomarker development on drug safety assessment

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

Marrer, Estelle, E-mail: estelle.marrer@novartis.co; Dieterle, Frank

2010-03-01

Drug safety has always been a key aspect of drug development. Recently, the Vioxx case and several cases of serious adverse events being linked to high-profile products have increased the importance of drug safety, especially in the eyes of drug development companies and global regulatory agencies. Safety biomarkers are increasingly being seen as helping to provide the clarity, predictability, and certainty needed to gain confidence in decision making: early-stage projects can be stopped quicker, late-stage projects become less risky. Public and private organizations are investing heavily in terms of time, money and manpower on safety biomarker development. An illustrative andmore » 'door opening' safety biomarker success story is the recent recognition of kidney safety biomarkers for pre-clinical and limited translational contexts by FDA and EMEA. This milestone achieved for kidney biomarkers and the 'know how' acquired is being transferred to other organ toxicities, namely liver, heart, vascular system. New technologies and molecular-based approaches, i.e., molecular pathology as a complement to the classical toolbox, allow promising discoveries in the safety biomarker field. This review will focus on the utility and use of safety biomarkers all along drug development, highlighting the present gaps and opportunities identified in organ toxicity monitoring. A last part will be dedicated to safety biomarker development in general, from identification to diagnostic tests, using the kidney safety biomarkers success as an illustrative example.« less

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification.

PubMed

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus .

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

Salivary Biomarkers in Cancer Detection

PubMed Central

Wang, Xiaoqian; Kaczor-Urbanowicz, Karolina Elżbieta; Wong, David T.W.

2017-01-01

Cancer is the second most common cause of death in the United States. Its symptoms are often not specific and absent, until the tumors have already metastasized. Therefore, there is an urgent demand for developing rapid, highly accurate and non-invasive tools for cancer screening, early detection, diagnostics, staging and prognostics. Saliva as a multi-constituent oral fluid, comprises secretions from the major and minor salivary glands, extensively supplied by blood. Molecules such as DNAs, RNAs, proteins, metabolites, and microbiota, present in blood, could be also found in saliva. Recently, salivary diagnostics has drawn significant attention for the detection of specific biomarkers, since the sample collection and processing are simple, cost-effective, precise and do not cause patient discomfort. Here, we review recent salivary candidate biomarkers for systemic cancers by dividing them according to their origin into: genomic, transcriptomic, proteomic, metabolomic and microbial types. PMID:27943101

Triton stellar occultation candidates - 1992-1994

NASA Technical Reports Server (NTRS)

Mcdonald, S. W.; Elliot, J. T.

1992-01-01

A search for Triton stellar occultation candidates for the period 1992-1994 has been completed with CCD strip-scanning observations. The search reached an R magnitude of about 17.4 and found 129 candidates within 1.5 arcsec of Triton's ephemeris during this period. Of these events, around 30 occultations are expected to be visible from the earth, indicating that a number of Triton occultation events should be visible from major observatories. Even the faintest of the present candidate events could produce useful occultation data if observed with a large enough telescope. The present astrometric accuracy is inadequate to identify which of these appulse events will produce occultations on the earth; further astrometry is needed to refine the predictions for positive occultation identification. To aid in selecting candidates for additional astrometric and photometric studies, finder charts and earth-based visibility charts for each event are included.

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

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

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.

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

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

PubMed

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

2015-01-01

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

Biomarker development in the precision medicine era: lung cancer as a case study.

PubMed

Vargas, Ashley J; Harris, Curtis C

2016-08-01

Precision medicine relies on validated biomarkers with which to better classify patients by their probable disease risk, prognosis and/or response to treatment. Although affordable 'omics'-based technology has enabled faster identification of putative biomarkers, the validation of biomarkers is still stymied by low statistical power and poor reproducibility of results. This Review summarizes the successes and challenges of using different types of molecule as biomarkers, using lung cancer as a key illustrative example. Efforts at the national level of several countries to tie molecular measurement of samples to patient data via electronic medical records are the future of precision medicine research.

Charting a Roadmap for Heart Failure Biomarker Studies

PubMed Central

Ahmad, Tariq; Fiuzat, Mona; Pencina, Michael J.; Geller, Nancy L.; Zannad, Faiez; Cleland, John G. F.; Snider, James V.; Blankenberg, Stephan; Adams, Kirkwood F.; Redberg, Rita F.; Kim, Jae B.; Mascette, Alice; Mentz, Robert J.; O'Connor, Christopher M.; Felker, G. Michael; Januzzi, James L.

2014-01-01

Heart failure is a syndrome with a pathophysiological basis that can be traced to dysfunction in several interconnected molecular pathways. Identification of biomarkers of heart failure that allow measurement of the disease on a molecular level has resulted in enthusiasm for their use in prognostication and selection of appropriate therapies. However, despite considerable amounts of information available on numerous biomarkers, inconsistent research methodologies and lack of clinical correlations have made bench-to-bedside translations rare and left the literature with countless publications of varied quality. There is a need for a systematic and collaborative approach aimed at definitively studying the clinical benefits of novel biomarkers. In this review, on the basis of input from academia, industry, and governmental agencies, we propose a systematized approach based on adherence to specific quality measures for studies looking to augment current prediction model or use biomarkers to tailor therapeutics. We suggest that study quality, rather than results, should determine publication and propose a system for grading biomarker studies. We outline the need for collaboration between clinical investigators and statisticians to introduce more advanced statistical methodologies into the field of biomarkers that would allow for data from a large number of variables to be distilled into clinically actionable information. Lastly, we propose the creation of a heart failure biomarker consortium that would allow for a comprehensive list of biomarkers to be concomitantly analyzed in a pooled sample of randomized clinical trials and hypotheses to be generated for testing in biomarker-guided trials. Such a consortium could collaborate in sharing samples to identify biomarkers, undertake meta- analyses on completed trials, and spearhead clinical trials to test the clinical utility of new biomarkers. PMID:24929535

Biomarker identification and pathway analysis of preeclampsia based on serum metabolomics.

PubMed

Chen, Tingting; He, Ping; Tan, Yong; Xu, Dongying

2017-03-25

Preeclampsia presents serious risk of both maternal and fetal morbidity and mortality. Biomarkers for the detection of preeclampsia are critical for risk assessment and targeted intervention. The goal of this study is to screen potential biomarkers for the diagnosis of preeclampsia and to illuminate the pathogenesis of preeclampsia development based on the differential expression network. Two groups of subjects, including healthy pregnant women, subjects with preeclampsia, were recruited for this study. The metabolic profiles of all of the subjects' serum were obtained by liquid chromatography quadruple time-of-flight mass spectrometry. Correlation between metabolites was analyzed by bioinformatics technique. Results showed that the PC(14:0/00), proline betaine and proline were potential sensitive and specific biomarkers for preeclampsia diagnosis and prognosis. Perturbation of corresponding biological pathways, such as iNOS signaling, nitric oxide signaling in the cardiovascular system, mitochondrial dysfunction were responsible for the pathogenesis of preeclampsia. This study indicated that the metabolic profiling had a good clinical significance in the diagnosis of preeclampsia as well as in the study of its pathogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictive Biomarkers for Linking Disease Pathology and Drug Effect.

PubMed

Mayer, Bernd; Heinzel, Andreas; Lukas, Arno; Perco, Paul

2017-01-01

Productivity in drug R&D continues seeing significant attrition in clinical stage testing. Approval of new molecular entities proceeds with slow pace specifically when it comes to chronic, age-related diseases, calling for new conceptual approaches, methodological implementation and organizational adoption in drug development. Detailed phenotyping of disease presentation together with comprehensive representation of drug mechanism of action is considered as a path forward, and a big data spectrum has become available covering behavioral, clinical and molecular characteristics, the latter combining reductionist and explorative strategies. On this basis integrative analytics in the realm of Systems Biology has emerged, essentially aiming at traversing associations into causal relationships for bridging molecular disease specifics and clinical phenotype surrogates and finally explaining drug response and outcome. From a conceptual perspective bottom-up modeling approaches are available, with dynamical hierarchies as formalism capable of describing clinical findings as emergent properties of an underlying molecular process network comprehensively resembling disease pathology. In such representation biomarker candidates serve as proxy of a molecular process set, at the interface of a corresponding representation of drug mechanism of action allowing patient stratification and prediction of drug response. In practical implementation network analytics on a protein coding gene level has provided a number of example cases for matching disease presentation and drug molecular effect, and workflows combining computational hypothesis generation and experimental evaluation have become available for systematically optimizing biomarker candidate selection. With biomarker-based enrichment strategies in adaptive clinical trials, implementation routes for tackling development attrition are provided. Predictive biomarkers add precision in drug development and as companion diagnostics

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.

Strategic regulatory approaches for the qualification of a biomarker assay for safety use.

PubMed

Valeri, Anna P; Beharry, Michelle; Jones, David R

2013-02-01

Biomarkers can be defined as key molecular or cellular events that link a specific biological event to a health outcome. As such, biomarkers play an important role in understanding the relationships between exposure to a xenobiotic, the development of chronic human diseases, and the identification of subgroups that are at increased risk of disease. Much progress has been made in identifying and validating new biomarkers to be used in population-based studies. The increasing availability and use of biomarkers to aid informed decision-making in risk-benefit decisions highlights the need for careful assessment of the validity of such models. In particular, models involving new biomarkers require careful validation and regulatory acceptance.

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

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.

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.

EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628

Biomarkers for the early diagnosis of hepatocellular carcinoma

PubMed Central

Tsuchiya, Nobuhiro; Sawada, Yu; Endo, Itaru; Saito, Keigo; Uemura, Yasushi; Nakatsura, Tetsuya

2015-01-01

Hepatocellular carcinoma (HCC) is the fifth most common cancer and the second leading cause of cancer-related deaths worldwide. Although the prognosis of patients with HCC is generally poor, the 5-year survival rate is > 70% if patients are diagnosed at an early stage. However, early diagnosis of HCC is complicated by the coexistence of inflammation and cirrhosis. Thus, novel biomarkers for the early diagnosis of HCC are required. Currently, the diagnosis of HCC without pathological correlation is achieved by analyzing serum α-fetoprotein levels combined with imaging techniques. Advances in genomics and proteomics platforms and biomarker assay techniques over the last decade have resulted in the identification of numerous novel biomarkers and have improved the diagnosis of HCC. The most promising biomarkers, such as glypican-3, osteopontin, Golgi protein-73 and nucleic acids including microRNAs, are most likely to become clinically validated in the near future. These biomarkers are not only useful for early diagnosis of HCC, but also provide insight into the mechanisms driving oncogenesis. In addition, such molecular insight creates the basis for the development of potentially more effective treatment strategies. In this article, we provide an overview of the biomarkers that are currently used for the early diagnosis of HCC. PMID:26457017

Clinical biomarkers of angiogenesis inhibition

PubMed Central

Brown, Aaron P.; Citrin, Deborah E.; Camphausen, Kevin A.

2009-01-01

Introduction An expanding understanding of the importance of angiogenesis in oncology and the development of numerous angiogenesis inhibitors are driving the search for biomarkers of angiogenesis. We review currently available candidate biomarkers and surrogate markers of anti-angiogenic agent effect. Discussion A number of invasive, minimally invasive, and non-invasive tools are described with their potential benefits and limitations. Diverse markers can evaluate tumor tissue or biological fluids, or specialized imaging modalities. Conclusions The inclusion of these markers into clinical trials may provide insight into appropriate dosing for desired biological effects, appropriate timing of additional therapy, prediction of individual response to an agent, insight into the interaction of chemotherapy and radiation following exposure to these agents, and perhaps most importantly, a better understanding of the complex nature of angiogenesis in human tumors. While many markers have potential for clinical use, it is not yet clear which marker or combination of markers will prove most useful. PMID:18414993

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

Genome-wide association study of CSF biomarkers Abeta1-42, t-tau, and p-tau181p in the ADNI cohort.

PubMed

Kim, S; Swaminathan, S; Shen, L; Risacher, S L; Nho, K; Foroud, T; Shaw, L M; Trojanowski, J Q; Potkin, S G; Huentelman, M J; Craig, D W; DeChairo, B M; Aisen, P S; Petersen, R C; Weiner, M W; Saykin, A J

2011-01-04

CSF levels of Aβ1-42, t-tau, and p-tau181p are potential early diagnostic markers for probable Alzheimer disease (AD). The influence of genetic variation on these markers has been investigated for candidate genes but not on a genome-wide basis. We report a genome-wide association study (GWAS) of CSF biomarkers (Aβ1-42, t-tau, p-tau181p, p-tau181p/Aβ1-42, and t-tau/Aβ1-42). A total of 374 non-Hispanic Caucasian participants in the Alzheimer's Disease Neuroimaging Initiative cohort with quality-controlled CSF and genotype data were included in this analysis. The main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed on each of 5 CSF biomarkers. The p values of all SNPs for each CSF biomarker were adjusted for multiple comparisons by the Bonferroni method. We focused on SNPs with corrected p<0.01 (uncorrected p<3.10×10(-8)) and secondarily examined SNPs with uncorrected p values less than 10(-5) to identify potential candidates. Four SNPs in the regions of the APOE, LOC100129500, TOMM40, and EPC2 genes reached genome-wide significance for associations with one or more CSF biomarkers. SNPs in CCDC134, ABCG2, SREBF2, and NFATC4, although not reaching genome-wide significance, were identified as potential candidates. In addition to known candidate genes, APOE, TOMM40, and one hypothetical gene LOC100129500 partially overlapping APOE; one novel gene, EPC2, and several other interesting genes were associated with CSF biomarkers that are related to AD. These findings, especially the new EPC2 results, require replication in independent cohorts.

A Biophysical Basis for Mucus Solids Concentration as a Candidate Biomarker for Airways Disease

PubMed Central

Hill, David B.; Vasquez, Paula A.; Mellnik, John; McKinley, Scott A.; Vose, Aaron; Mu, Frank; Henderson, Ashley G.; Donaldson, Scott H.; Alexis, Neil E.; Boucher, Richard C.; Forest, M. Gregory

2014-01-01

In human airways diseases, including cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD), host defense is compromised and airways inflammation and infection often result. Mucus clearance and trapping of inhaled pathogens constitute key elements of host defense. Clearance rates are governed by mucus viscous and elastic moduli at physiological driving frequencies, whereas transport of trapped pathogens in mucus layers is governed by diffusivity. There is a clear need for simple and effective clinical biomarkers of airways disease that correlate with these properties. We tested the hypothesis that mucus solids concentration, indexed as weight percent solids (wt%), is such a biomarker. Passive microbead rheology was employed to determine both diffusive and viscoelastic properties of mucus harvested from human bronchial epithelial (HBE) cultures. Guided by sputum from healthy (1.5–2.5 wt%) and diseased (COPD, CF; 5 wt%) subjects, mucus samples were generated in vitro to mimic in vivo physiology, including intermediate range wt% to represent disease progression. Analyses of microbead datasets showed mucus diffusive properties and viscoelastic moduli scale robustly with wt%. Importantly, prominent changes in both biophysical properties arose at ∼4 wt%, consistent with a gel transition (from a more viscous-dominated solution to a more elastic-dominated gel). These findings have significant implications for: (1) penetration of cilia into the mucus layer and effectiveness of mucus transport; and (2) diffusion vs. immobilization of micro-scale particles relevant to mucus barrier properties. These data provide compelling evidence for mucus solids concentration as a baseline clinical biomarker of mucus barrier and clearance functions. PMID:24558372

Systematic approach identifies RHOA as a potential biomarker therapeutic target for Asian gastric cancer

PubMed Central

Jung, Hae Rim; Park, Hee Seo; Park, Sungjin; Ahn, Young Zoo; Huh, Iksoo; Balch, Curt; Ku, Ja-Lok; Powis, Garth; Park, Taesung; Jeong, Jin-Hyun; Kim, Yon Hui

2016-01-01

Gastric cancer (GC) is a highly heterogeneous disease, in dire need of specific, biomarker-driven cancer therapies. While the accumulation of cancer “Big Data” has propelled the search for novel molecular targets for GC, its specific subpathway and cellular functions vary from patient to patient. In particular, mutations in the small GTPase gene RHOA have been identified in recent genome-wide sequencing of GC tumors. Moreover, protein overexpression of RHOA was reported in Chinese populations, while RHOA mutations were found in Caucasian GC tumors. To develop evidence-based precision medicine for heterogeneous cancers, we established a systematic approach to integrate transcriptomic and genomic data. Predicted signaling subpathways were then laboratory-validated both in vitro and in vivo, resulting in the identification of new candidate therapeutic targets. Here, we show: i) differences in RHOA expression patterns, and its pathway activity, between Asian and Caucasian GC tumors; ii) in vitro and in vivo perturbed RHOA expression inhibits GC cell growth in high RHOA-expressing cell lines; iii) inverse correlation between RHOA and RHOB expression; and iv) an innovative small molecule design strategy for RHOA inhibitors. In summary, RHOA, and its oncogenic signaling pathway, represent a strong biomarker-driven therapeutic target for Asian GC. This comprehensive strategy represents a promising approach for the development of “hit” compounds. PMID:27806312

Recent Advances in Resting-State Electroencephalography Biomarkers for Autism Spectrum Disorder-A Review of Methodological and Clinical Challenges.

PubMed

Heunis, Tosca-Marie; Aldrich, Chris; de Vries, Petrus J

2016-08-01

Electroencephalography (EEG) has been used for almost a century to identify seizure-related disorders in humans, typically through expert interpretation of multichannel recordings. Attempts have been made to quantify EEG through frequency analyses and graphic representations. These "traditional" quantitative EEG analysis methods were limited in their ability to analyze complex and multivariate data and have not been generally accepted in clinical settings. There has been growing interest in identification of novel EEG biomarkers to detect early risk of autism spectrum disorder, to identify clinically meaningful subgroups, and to monitor targeted intervention strategies. Most studies to date have, however, used quantitative EEG approaches, and little is known about the emerging multivariate analytical methods or the robustness of candidate biomarkers in the context of the variability of autism spectrum disorder. Here, we present a targeted review of methodological and clinical challenges in the search for novel resting-state EEG biomarkers for autism spectrum disorder. Three primary novel methodologies are discussed: (1) modified multiscale entropy, (2) coherence analysis, and (3) recurrence quantification analysis. Results suggest that these methods may be able to classify resting-state EEG as "autism spectrum disorder" or "typically developing", but many signal processing questions remain unanswered. We suggest that the move to novel EEG analysis methods is akin to the progress in neuroimaging from visual inspection, through region-of-interest analysis, to whole-brain computational analysis. Novel resting-state EEG biomarkers will have to evaluate a range of potential demographic, clinical, and technical confounders including age, gender, intellectual ability, comorbidity, and medication, before these approaches can be translated into the clinical setting. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-05-02

Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualization toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.

Osteoarthritis Year in Review 2016: biomarkers (biochemical markers).

PubMed

Mobasheri, A; Bay-Jensen, A-C; van Spil, W E; Larkin, J; Levesque, M C

2017-02-01

The aim of this "Year in Review" article is to summarize and discuss the implications of biochemical marker related articles published between the Osteoarthritis Research Society International (OARSI) 2015 Congress in Seattle and the OARSI 2016 Congress in Amsterdam. The PubMed/MEDLINE bibliographic database was searched using the combined keywords: 'biomarker' and 'osteoarthritis'. The PubMed/MEDLINE literature search was conducted using the Advanced Search Builder function (http://www.ncbi.nlm.nih.gov/pubmed/advanced). Over two hundred new biomarker-related papers were published during the literature search period. Some papers identified new biomarkers whereas others explored the biological properties and clinical utility of existing markers. There were specific references to several adipocytokines including leptin and adiponectin. ADAM Metallopeptidase with Thrombospondin Type 1 motif 4 (ADAMTS-4) and aggrecan ARGS neo-epitope fragment (ARGS) in synovial fluid (SF) and plasma chemokine (CeC motif) ligand 3 (CCL3) were reported as potential new knee biomarkers. New and refined proteomic technologies and novel assays including a fluoro-microbead guiding chip (FMGC) for measuring C-telopeptide of type II collagen (CTX-II) in serum and urine and a novel magnetic nanoparticle-based technology (termed magnetic capture) for collecting and concentrating CTX-II, were described this past year. There has been steady progress in osteoarthritis (OA) biomarker research in 2016. Several novel biomarkers were identified and new technologies have been developed for measuring existing biomarkers. However, there has been no "quantum leap" this past year and identification of novel early OA biomarkers remains challenging. During the past year, OARSI published a set of recommendations for the use of soluble biomarkers in clinical trials, which is a major step forward in the clinical use of OA biomarkers and bodes well for future OA biomarker development. Copyright © 2016 The

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.

Sepsis biomarkers.

PubMed

Prucha, Miroslav; Bellingan, Geoff; Zazula, Roman

2015-02-02

Sepsis is the most frequent cause of death in non-coronary intensive care units (ICUs). In the past 10 years, progress has been made in the early identification of septic patients and in their treatment and these improvements in support and therapy mean that the mortality is gradually decreasing but it still remains unacceptably high. Leaving clinical diagnosis aside, the laboratory diagnostics represent a complex range of investigations that can place significant demands on the system given the speed of response required. There are hundreds of biomarkers which could be potentially used for diagnosis and prognosis in septic patients. The main attributes of successful markers would be high sensitivity, specificity, possibility of bed-side monitoring, and financial accessibility. Only a fraction is used in routine clinical practice because many lack sufficient sensitivity or specificity. The following review gives a short overview of the current epidemiology of sepsis, its pathogenesis and state-of-the-art knowledge on the use of specific biochemical, hematological and immunological parameters in its diagnostics. Prospective approaches towards discovery of new diagnostic biomarkers have been shortly mentioned. Copyright © 2014 Elsevier B.V. All rights reserved.

Verification of Ribosomal Proteins of Aspergillus fumigatus for Use as Biomarkers in MALDI-TOF MS Identification

PubMed Central

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Yaguchi, Takashi

2016-01-01

We have previously proposed a rapid identification method for bacterial strains based on the profiles of their ribosomal subunit proteins (RSPs), observed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). This method can perform phylogenetic characterization based on the mass of housekeeping RSP biomarkers, ideally calculated from amino acid sequence information registered in public protein databases. With the aim of extending its field of application to medical mycology, this study investigates the actual state of information of RSPs of eukaryotic fungi registered in public protein databases through the characterization of ribosomal protein fractions extracted from genome-sequenced Aspergillus fumigatus strains Af293 and A1163 as a model. In this process, we have found that the public protein databases harbor problems. The RSP names are in confusion, so we have provisionally unified them using the yeast naming system. The most serious problem is that many incorrect sequences are registered in the public protein databases. Surprisingly, more than half of the sequences are incorrect, due chiefly to mis-annotation of exon/intron structures. These errors could be corrected by a combination of in silico inspection by sequence homology analysis and MALDI-TOF MS measurements. We were also able to confirm conserved post-translational modifications in eleven RSPs. After these verifications, the masses of 31 expressed RSPs under 20,000 Da could be accurately confirmed. These RSPs have a potential to be useful biomarkers for identifying clinical isolates of A. fumigatus. PMID:27843740

Application of multi-target phytotherapeutic concept in malaria drug discovery: a systems biology approach in biomarker identification.

PubMed

Tarkang, Protus Arrey; Appiah-Opong, Regina; Ofori, Michael F; Ayong, Lawrence S; Nyarko, Alexander K

2016-01-01

There is an urgent need for new anti-malaria drugs with broad therapeutic potential and novel mode of action, for effective treatment and to overcome emerging drug resistance. Plant-derived anti-malarials remain a significant source of bioactive molecules in this regard. The multicomponent formulation forms the basis of phytotherapy. Mechanistic reasons for the poly-pharmacological effects of plants constitute increased bioavailability, interference with cellular transport processes, activation of pro-drugs/deactivation of active compounds to inactive metabolites and action of synergistic partners at different points of the same signaling cascade. These effects are known as the multi-target concept. However, due to the intrinsic complexity of natural products-based drug discovery, there is need to rethink the approaches toward understanding their therapeutic effect. This review discusses the multi-target phytotherapeutic concept and its application in biomarker identification using the modified reverse pharmacology - systems biology approach. Considerations include the generation of a product library, high throughput screening (HTS) techniques for efficacy and interaction assessment, High Performance Liquid Chromatography (HPLC)-based anti-malarial profiling and animal pharmacology. This approach is an integrated interdisciplinary implementation of tailored technology platforms coupled to miniaturized biological assays, to track and characterize the multi-target bioactive components of botanicals as well as identify potential biomarkers. While preserving biodiversity, this will serve as a primary step towards the development of standardized phytomedicines, as well as facilitate lead discovery for chemical prioritization and downstream clinical development.

Identification of Quantitative Trait Loci (QTL) and Candidate Genes for Cadmium Tolerance in Populus

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

Induri, Brahma R; Ellis, Danielle R; Slavov, Gancho

2012-01-01

Knowledge of genetic variation in response of Populus to heavy metals like cadmium (Cd) is an important step in understanding the underlying mechanisms of tolerance. In this study, a pseudo-backcross pedigree of Populus trichocarpa and Populus deltoides was characterized for Cd exposure. The pedigree showed significant variation for Cd tolerance thus enabling the identification of relatively tolerant and susceptible genotypes for intensive characterization. A total of 16 QTLs at logarithm of odds (LOD) ratio > 2.5, were found to be associated with total dry weight, its components, and root volume. Four major QTLs for total dry weight were mapped tomore » different linkage groups in control (LG III) and Cd conditions (LG XVI) and had opposite allelic effects on Cd tolerance, suggesting that these genomic regions were differentially controlled. The phenotypic variation explained by Cd QTL for all traits under study varied from 5.9% to 11.6% and averaged 8.2% across all QTL. Leaf Cd contents also showed significant variation suggesting the phytoextraction potential of Populus genotypes, though heritability of this trait was low (0.22). A whole-genome microarray study was conducted by using two genotypes with extreme responses for Cd tolerance in the above study and differentially expressed genes were identified. Candidate genes including CAD2 (CADMIUM SENSITIVE 2), HMA5 (HEAVY METAL ATPase5), ATGTST1 (Arabidopsis thaliana Glutathione S-Transferase1), ATGPX6 (Glutathione peroxidase 6), and ATMRP 14 (Arabidopsis thaliana Multidrug Resistance associated Protein 14) were identified from QTL intervals and microarray study. Functional characterization of these candidate genes could enhance phytoremediation capabilities of Populus.« less

Transcriptome Sequencing of Codonopsis pilosula and Identification of Candidate Genes Involved in Polysaccharide Biosynthesis

PubMed Central

Gao, Jian Ping; Wang, Dong; Cao, Ling Ya; Sun, Hai Feng

2015-01-01

Background Codonopsis pilosula (Franch.) Nannf. is one of the most widely used medicinal plants. Although chemical and pharmacological studies have shown that codonopsis polysaccharides (CPPs) are bioactive compounds and that their composition is variable, their biosynthetic pathways remain largely unknown. Next-generation sequencing is an efficient and high-throughput technique that allows the identification of candidate genes involved in secondary metabolism. Principal Findings To identify the components involved in CPP biosynthesis, a transcriptome library, prepared using root and other tissues, was assembled with the help of Illumina sequencing. A total of 9.2 Gb of clean nucleotides was obtained comprising 91,175,044 clean reads, 102,125 contigs, and 45,511 unigenes. After aligning the sequences to the public protein databases, 76.1% of the unigenes were annotated. Among these annotated unigenes, 26,189 were assigned to Gene Ontology categories, 11,415 to Clusters of Orthologous Groups, and 18,848 to Kyoto Encyclopedia of Genes and Genomes pathways. Analysis of abundance of transcripts in the library showed that genes, including those encoding metallothionein, aquaporin, and cysteine protease that are related to stress responses, were in the top list. Among genes involved in the biosynthesis of CPP, those responsible for the synthesis of UDP-L-arabinose and UDP-xylose were highly expressed. Significance To our knowledge, this is the first study to provide a public transcriptome dataset prepared from C. pilosula and an outline of the biosynthetic pathway of polysaccharides in a medicinal plant. Identified candidate genes involved in CPP biosynthesis provide understanding of the biosynthesis and regulation of CPP at the molecular level. PMID:25719364

Inflammatory biomarkers in heart failure revisited: much more than innocent bystanders.

PubMed

von Haehling, Stephan; Schefold, Joerg C; Lainscak, Mitja; Doehner, Wolfram; Anker, Stefan D

2009-10-01

Chronic heart failure is viewed as a state of chronic inflammation. Many inflammatory markers have been shown to be up-regulated in patients who have this condition, but the markers' roles in clinical decision making have not yet been fully elucidated. A panel of biomarkers is likely to have a strong impact on patient management. Inflammatory biomarkers are interesting candidates that could answer specific clinical questions on their own or complement a multi-marker approach. This article provides a broad overview of several inflammatory biomarkers, including the pro-inflammatory cytokines tumor necrosis factor-alpha, interleukin (IL)-6, IL-1, IL-18, and the soluble receptors TNFR-1, TNFR-2, IL-6R, and gp130. In addition to these acute phase reactants, several adhesion molecules, and lipopolysaccharide-signaling pathways are discussed.

The Present and Future of Prostate Cancer Urine Biomarkers

PubMed Central

Rigau, Marina; Olivan, Mireia; Garcia, Marta; Sequeiros, Tamara; Montes, Melania; Colás, Eva; Llauradó, Marta; Planas, Jacques; de Torres, Inés; Morote, Juan; Cooper, Colin; Reventós, Jaume; Clark, Jeremy; Doll, Andreas

2013-01-01

In order to successfully cure patients with prostate cancer (PCa), it is important to detect the disease at an early stage. The existing clinical biomarkers for PCa are not ideal, since they cannot specifically differentiate between those patients who should be treated immediately and those who should avoid over-treatment. Current screening techniques lack specificity, and a decisive diagnosis of PCa is based on prostate biopsy. Although PCa screening is widely utilized nowadays, two thirds of the biopsies performed are still unnecessary. Thus the discovery of non-invasive PCa biomarkers remains urgent. In recent years, the utilization of urine has emerged as an attractive option for the non-invasive detection of PCa. Moreover, a great improvement in high-throughput “omic” techniques has presented considerable opportunities for the identification of new biomarkers. Herein, we will review the most significant urine biomarkers described in recent years, as well as some future prospects in that field. PMID:23774836

Current and Prospective Protein Biomarkers of Lung Cancer

PubMed Central

Zamay, Tatiana N.; Zamay, Galina S.; Kolovskaya, Olga S.; Zukov, Ruslan A.; Petrova, Marina M.; Gargaun, Ana; Berezovski, Maxim V.

2017-01-01

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate. PMID:29137182

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

PubMed

Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

2016-09-01

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

Identification of Tengfu Jiangya Tablet Target Biomarkers with Quantitative Proteomic Technique

PubMed Central

Xu, Jingwen; Zhang, Shijun; Jiang, Haiqiang; Wang, Nan; Lin, Haiqing

2017-01-01

Tengfu Jiangya Tablet (TJT) is a well accepted antihypertension drug in China and its major active components were Uncaria total alkaloids and Semen Raphani soluble alkaloid. To further explore treatment effects mechanism of TJT on essential hypertension, a serum proteomic study was performed. Potential biomarkers were quantified in serum of hypertension individuals before and after taking TJT with isobaric tags for relative and absolute quantitation (iTRAQ) coupled two-dimensional liquid chromatography followed electrospray ionization-tandem mass spectrometry (2D LC-MS/MS) proteomics technique. Among 391 identified proteins with high confidence, 70 proteins were differentially expressed (fold variation criteria, >1.2 or <0.83) between two groups (39 upregulated and 31 downregulated). Combining with Gene Ontology annotation, KEGG pathway analysis, and literature retrieval, 5 proteins were chosen as key target biomarkers during TJT therapeutic process. And the alteration profiles of these 5 proteins were verified by ELISA and Western Blot. Proteins Kininogen 1 and Keratin 1 are members of Kallikrein system, while Myeloperoxidase, Serum Amyloid protein A, and Retinol binding protein 4 had been reported closely related to vascular endothelial injury. Our study discovered 5 target biomarkers of the compound Chinese medicine TJT. Secondly, this research initially revealed the antihypertension therapeutic mechanism of this drug from a brand-new aspect. PMID:28408942

Optimization of Imidazo[4,5-b]pyridine-Based Kinase Inhibitors: Identification of a Dual FLT3/Aurora Kinase Inhibitor as an Orally Bioavailable Preclinical Development Candidate for the Treatment of Acute Myeloid Leukemia

PubMed Central

2012-01-01

Optimization of the imidazo[4,5-b]pyridine-based series of Aurora kinase inhibitors led to the identification of 6-chloro-7-(4-(4-chlorobenzyl)piperazin-1-yl)-2-(1,3-dimethyl-1H-pyrazol-4-yl)-3H-imidazo[4,5-b]pyridine (27e), a potent inhibitor of Aurora kinases (Aurora-A Kd = 7.5 nM, Aurora-B Kd = 48 nM), FLT3 kinase (Kd = 6.2 nM), and FLT3 mutants including FLT3-ITD (Kd = 38 nM) and FLT3(D835Y) (Kd = 14 nM). FLT3-ITD causes constitutive FLT3 kinase activation and is detected in 20–35% of adults and 15% of children with acute myeloid leukemia (AML), conferring a poor prognosis in both age groups. In an in vivo setting, 27e strongly inhibited the growth of a FLT3-ITD-positive AML human tumor xenograft (MV4–11) following oral administration, with in vivo biomarker modulation and plasma free drug exposures consistent with dual FLT3 and Aurora kinase inhibition. Compound 27e, an orally bioavailable dual FLT3 and Aurora kinase inhibitor, was selected as a preclinical development candidate for the treatment of human malignancies, in particular AML, in adults and children. PMID:23043539

Identification of aldo-keto reductase (AKR7A1) and glutathione S-transferase pi (GSTP1) as novel renal damage biomarkers following exposure to mercury.

PubMed

Shin, Y-J; Kim, K-A; Kim, E-S; Kim, J-H; Kim, H-S; Ha, M; Bae, O-N

2017-01-01

The kidney is one of the main targets for toxicity induced by xenobiotics. Sensitive detection of early impairment is critical to assess chemical-associated renal toxicity. The aim of this study was to identify potential nephrotoxic biomarkers in rat kidney tissues after exposure to mercury (Hg), a representative nephrotoxicant, and to evaluate these new biomarkers employing in vivo and in vitro systems. Mercuric chloride was administered orally to Sprague-Dawley rats for 2 weeks. Proteomic analysis revealed that aldo-keto reductase (AKR7A1) and glutathione S-transferase pi (GSTP1) were significantly elevated in kidney after Hg exposure. While the levels of conventional nephrotoxic clinical markers including blood urea nitrogen and serum creatinine were not elevated, the mRNA and protein levels of AKR7A1 and GSTP1 were increased upon Hg exposure in a dose-dependent manner. The increases in AKR7A1 and GSTP1 were also observed in rat kidneys after an extended exposure for 6 weeks to low-dose Hg. In in vitro rat kidney proximal tubular cells, changes in AKR7A1 and GSTP1 levels correlated well with the extent of cytotoxicity induced by Hg, cadmium, or cisplatin. AKR7A1 and GSTP1 were identified as new candidates for Hg-induced nephrotoxicity, suggesting that these biomarkers have potential for evaluating or predicting nephrotoxicity.

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

Evaluation of six candidate DNA barcode loci for identification of five important invasive grasses in eastern Australia

PubMed Central

Wang, Aisuo; Gopurenko, David; Wu, Hanwen; Lepschi, Brendan

2017-01-01

Invasive grass weeds reduce farm productivity, threaten biodiversity, and increase weed control costs. Identification of invasive grasses from native grasses has generally relied on the morphological examination of grass floral material. DNA barcoding may provide an alternative means to identify co-occurring native and invasive grasses, particularly during early growth stages when floral characters are unavailable for analysis. However, there are no universal loci available for grass barcoding. We herein evaluated the utility of six candidate loci (atpF intron, matK, ndhK-ndhC, psbE—petL, ETS and ITS) for barcode identification of several economically important invasive grass species frequently found among native grasses in eastern Australia. We evaluated these loci in 66 specimens representing five invasive grass species (Chloris gayana, Eragrostis curvula, Hyparrhenia hirta, Nassella neesiana, Nassella trichotoma) and seven native grass species. Our results indicated that, while no single locus can be universally used as a DNA barcode for distinguishing the grass species examined in this study, two plastid loci (atpF and matK) showed good distinguishing power to separate most of the taxa examined, and could be used as a dual locus to distinguish several of the invasive from the native species. Low PCR success rates were evidenced among two nuclear loci (ETS and ITS), and few species were amplified at these loci, however ETS was able to genetically distinguish the two important invasive Nassella species. Multiple loci analyses also suggested that ETS played a crucial role in allowing identification of the two Nassella species in the multiple loci combinations. PMID:28399170

Evaluation of six candidate DNA barcode loci for identification of five important invasive grasses in eastern Australia.

PubMed

Wang, Aisuo; Gopurenko, David; Wu, Hanwen; Lepschi, Brendan

2017-01-01

Invasive grass weeds reduce farm productivity, threaten biodiversity, and increase weed control costs. Identification of invasive grasses from native grasses has generally relied on the morphological examination of grass floral material. DNA barcoding may provide an alternative means to identify co-occurring native and invasive grasses, particularly during early growth stages when floral characters are unavailable for analysis. However, there are no universal loci available for grass barcoding. We herein evaluated the utility of six candidate loci (atpF intron, matK, ndhK-ndhC, psbE-petL, ETS and ITS) for barcode identification of several economically important invasive grass species frequently found among native grasses in eastern Australia. We evaluated these loci in 66 specimens representing five invasive grass species (Chloris gayana, Eragrostis curvula, Hyparrhenia hirta, Nassella neesiana, Nassella trichotoma) and seven native grass species. Our results indicated that, while no single locus can be universally used as a DNA barcode for distinguishing the grass species examined in this study, two plastid loci (atpF and matK) showed good distinguishing power to separate most of the taxa examined, and could be used as a dual locus to distinguish several of the invasive from the native species. Low PCR success rates were evidenced among two nuclear loci (ETS and ITS), and few species were amplified at these loci, however ETS was able to genetically distinguish the two important invasive Nassella species. Multiple loci analyses also suggested that ETS played a crucial role in allowing identification of the two Nassella species in the multiple loci combinations.

Metabolomics for Biomarker Discovery: Moving to the Clinic

PubMed Central

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

2015-01-01

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

Identification of MicroRNA as Sepsis Biomarker Based on miRNAs Regulatory Network Analysis

PubMed Central

Huang, Jie; Sun, Zhandong; Yan, Wenying; Zhu, Yujie; Lin, Yuxin; Chen, Jiajai; Shen, Bairong

2014-01-01

Sepsis is regarded as arising from an unusual systemic response to infection but the physiopathology of sepsis remains elusive. At present, sepsis is still a fatal condition with delayed diagnosis and a poor outcome. Many biomarkers have been reported in clinical application for patients with sepsis, and claimed to improve the diagnosis and treatment. Because of the difficulty in the interpreting of clinical features of sepsis, some biomarkers do not show high sensitivity and specificity. MicroRNAs (miRNAs) are small noncoding RNAs which pair the sites in mRNAs to regulate gene expression in eukaryotes. They play a key role in inflammatory response, and have been validated to be potential sepsis biomarker recently. In the present work, we apply a miRNA regulatory network based method to identify novel microRNA biomarkers associated with the early diagnosis of sepsis. By analyzing the miRNA expression profiles and the miRNA regulatory network, we obtained novel miRNAs associated with sepsis. Pathways analysis, disease ontology analysis, and protein-protein interaction network (PIN) analysis, as well as ROC curve, were exploited to testify the reliability of the predicted miRNAs. We finally identified 8 novel miRNAs which have the potential to be sepsis biomarkers. PMID:24809055

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

Peptide identification

DOEpatents

Jarman, Kristin H [Richland, WA; Cannon, William R [Richland, WA; Jarman, Kenneth D [Richland, WA; Heredia-Langner, Alejandro [Richland, WA

2011-07-12

Peptides are identified from a list of candidates using collision-induced dissociation tandem mass spectrometry data. A probabilistic model for the occurrence of spectral peaks corresponding to frequently observed partial peptide fragment ions is applied. As part of the identification procedure, a probability score is produced that indicates the likelihood of any given candidate being the correct match. The statistical significance of the score is known without necessarily having reference to the actual identity of the peptide. In one form of the invention, a genetic algorithm is applied to candidate peptides using an objective function that takes into account the number of shifted peaks appearing in the candidate spectrum relative to the test spectrum.

*Biomarkers of acute respiratory allergen exposure: Screening for sensitization potential

EPA Science Inventory

Effective hazard screening will require the development of high-throughput or in vitro assays for the identification of potential sensitizers. The goal of this preliminary study was to identify potential biomarkers that differentiate the response to allergens vs non-allergens fol...

Identification and Accessioning of Individuals for the Officer Candidate School (OCS)

DTIC Science & Technology

2011-02-01

OSOs ). OSOs complete an interview with U. S. Marine Corps (USMC) OCs. Upon completing a satisfactory interview, the candidate goes on to the next step...accepted by the board review. The USMC officer selection review board only reviews those candidates that are passed forward by OSOs . The board votes to...for each AFSC as outlined in the Air Force Officer Classification Directory. 2 Upon completing a satisfactory interview, the OSO then makes the

Non-invasive detection of candidate pregnancy protein biomarkers in the feces of captive polar bears (Ursus maritimus).

PubMed

Curry, E; Stoops, M A; Roth, T L

2012-07-15

Currently, there is no method of accurately and non-invasively diagnosing pregnancy in polar bears. Specific proteins may exhibit altered profiles in the feces of pregnant bears, but predicting appropriate candidate proteins to investigate is speculative at best. The objective of this study was to identify potential pregnancy biomarker proteins based on their increased abundance in the feces of pregnant polar bears compared to pseudopregnant females (controls) using two-dimensional in-gel electrophoresis (2D-DIGE) and mass spectrometry (MS). Three 2D-DIGE gels were performed to evaluate fecal protein profiles from controls (n=3) and pregnant polar bears (n=3). There were 2224.67±52.39 (mean±SEM) spots resolved per gel. Of these, only five proteins were elevated in the pregnant group (P<0.05), and seven additional spots tended to be higher (0.0599.9% confidence interval. The 11 spots represented seven distinct proteins, five of which were significantly more abundant in the pregnant group: IgGFc-binding protein, filamin-C, carboxypeptidase B, transthyretin, and immunoglobulin heavy chain variable region. To our knowledge, this was the first study that employed 2D-DIGE to identify differentially expressed proteins in fecal samples to characterize a physiological condition other than those related to gastrointestinal disorders. These promising results provided a strong foundation for ensuing efforts to develop a non-invasive pregnancy assay for use in both captive and wild polar bears. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

Increasing the predictive accuracy of amyloid-β blood-borne biomarkers in Alzheimer's disease.

PubMed

Watt, Andrew D; Perez, Keyla A; Faux, Noel G; Pike, Kerryn E; Rowe, Christopher C; Bourgeat, Pierrick; Salvado, Olivier; Masters, Colin L; Villemagne, Victor L; Barnham, Kevin J

2011-01-01

Diagnostic measures for Alzheimer's disease (AD) commonly rely on evaluating the levels of amyloid-β (Aβ) peptides within the cerebrospinal fluid (CSF) of affected individuals. These levels are often combined with levels of an additional non-Aβ marker to increase predictive accuracy. Recent efforts to overcome the invasive nature of CSF collection led to the observation of Aβ species within the blood cellular fraction, however, little is known of what additional biomarkers may be found in this membranous fraction. The current study aimed to undertake a discovery-based proteomic investigation of the blood cellular fraction from AD patients (n = 18) and healthy controls (HC; n = 15) using copper immobilized metal affinity capture and Surface Enhanced Laser Desorption/Ionisation Time-Of-Flight Mass Spectrometry. Three candidate biomarkers were observed which could differentiate AD patients from HC (ROC AUC > 0.8). Bivariate pairwise comparisons revealed significant correlations between these markers and measures of AD severity including; MMSE, composite memory, brain amyloid burden, and hippocampal volume. A partial least squares regression model was generated using the three candidate markers along with blood levels of Aβ. This model was able to distinguish AD from HC with high specificity (90%) and sensitivity (77%) and was able to separate individuals with mild cognitive impairment (MCI) who converted to AD from MCI non-converters. While requiring further characterization, these candidate biomarkers reaffirm the potential efficacy of blood-based investigations into neurodegenerative conditions. Furthermore, the findings indicate that the incorporation of non-amyloid markers into predictive models, function to increase the accuracy of the diagnostic potential of Aβ.

A HPLC-Q-TOF-MS-based urinary metabolomic approach to identification of potential biomarkers of metabolic syndrome.

PubMed

Yu, Zhi-rui; Ning, Yu; Yu, Hao; Tang, Nai-jun

2014-04-01

Metabolic syndrome (MetS) is a serious threat to public health worldwide with an increased risk of developing type 2 diabetes, cardiovascular diseases and all-cause morbidity and mortality. In this study, a urinary metabolomic approach was performed on high performance liquid chromatography quadrupole time-of-flight mass spectrometry to discriminate 36 male MetS patients and 36 sex and age matched healthy controls. Pattern recognition analyses (principal component analysis and orthogonal projections to latent structures discriminate analysis) commonly demonstrated the difference between MetS patients and no-MetS subjects. This study found 8 metabolites that showed significant changes in patients with MetS, including branch-chain and aromatic amino acids (leucine, tyrosine, phenylalanine and tryptophan), short-chain acylcanitine (tiglylcarnitine), tricarboxylic acid (TCA) cycle intermediate (cis-aconitic acid) and glucuronidated products (cortolone-3-glucuronide and tetrahydroaldosterone-3-glucuronide). The candidate biomarkers revealed in this study could be useful in providing clues for further research focusing on the in-depth investigation of the cause of and cure for MetS.

Identification of candidate mimicry proteins involved in parasite-driven phenotypic changes.

PubMed

Hebert, Francois Olivier; Phelps, Luke; Samonte, Irene; Panchal, Mahesh; Grambauer, Stephan; Barber, Iain; Kalbe, Martin; Landry, Christian R; Aubin-Horth, Nadia

2015-04-15

Endoparasites with complex life cycles are faced with several biological challenges, as they need to occupy various ecological niches throughout their development. Host phenotypes that increase the parasite's transmission rate to the next host have been extensively described, but few mechanistic explanations have been proposed to describe their proximate causes. In this study we explore the possibility that host phenotypic changes are triggered by the production of mimicry proteins from the parasite by using an ecological model system consisting of the infection of the threespine stickleback (Gasterosteus aculeatus) by the cestode Schistocephalus solidus. Using RNA-seq data, we assembled 9,093 protein-coding genes from which ORFs were predicted to generate a reference proteome. Based on a previously published method, we built two complementary analysis pipelines to i) establish a general classification of protein similarity among various species (pipeline A) and ii) identify candidate mimicry proteins showing specific host-parasite similarities (pipeline B), a key feature underlying the possibility of molecular mimicry. Ninety-four tapeworm proteins showed high local sequence homology with stickleback proteins. Four of these candidates correspond to secreted or membrane proteins that could be produced by the parasite and eventually be released in or be in contact with the host to modulate physiological pathways involved in various phenotypes (e.g. behaviors). One of these candidates belongs to the Wnt family, a large group of signaling molecules involved in cell-to-cell interactions and various developmental pathways. The three other candidates are involved in ion transport and post-translational protein modifications. We further confirmed that these four candidates are expressed in three different developmental stages of the cestode by RT-PCR, including the stages found in the host. In this study, we identified mimicry candidate peptides from a behavior

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

Messenger RNA biomarker signatures for forensic body fluid identification revealed by targeted RNA sequencing.

PubMed

Hanson, E; Ingold, S; Haas, C; Ballantyne, J

2018-05-01

The recovery of a DNA profile from the perpetrator or victim in criminal investigations can provide valuable 'source level' information for investigators. However, a DNA profile does not reveal the circumstances by which biological material was transferred. Some contextual information can be obtained by a determination of the tissue or fluid source of origin of the biological material as it is potentially indicative of some behavioral activity on behalf of the individual that resulted in its transfer from the body. Here, we sought to improve upon established RNA based methods for body fluid identification by developing a targeted multiplexed next generation mRNA sequencing assay comprising a panel of approximately equal sized gene amplicons. The multiplexed biomarker panel includes several highly specific gene targets with the necessary specificity to definitively identify most forensically relevant biological fluids and tissues (blood, semen, saliva, vaginal secretions, menstrual blood and skin). In developing the biomarker panel we evaluated 66 gene targets, with a progressive iteration of testing target combinations that exhibited optimal sensitivity and specificity using a training set of forensically relevant body fluid samples. The current assay comprises 33 targets: 6 blood, 6 semen, 6 saliva, 4 vaginal secretions, 5 menstrual blood and 6 skin markers. We demonstrate the sensitivity and specificity of the assay and the ability to identify body fluids in single source and admixed stains. A 16 sample blind test was carried out by one lab with samples provided by the other participating lab. The blinded lab correctly identified the body fluids present in 15 of the samples with the major component identified in the 16th. Various classification methods are being investigated to permit inference of the body fluid/tissue in dried physiological stains. These include the percentage of reads in a sample that are due to each of the 6 tissues/body fluids tested and

Identification of prostate cancer biomarkers in urinary exosomes

PubMed Central

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

2015-01-01

Exosomes have recently appeared as a novel source of non-invasive cancer biomarkers since tumour-specific molecules can be found in exosomes isolated from biological fluids. We have here investigated the proteome of urinary exosomes by using mass spectrometry to identify proteins differentially expressed in prostate cancer patients compared to healthy male controls. In total, 15 control and 16 prostate cancer samples of urinary exosomes were analyzed. Importantly, 246 proteins were differentially expressed in the two groups. The majority of these proteins (221) were up-regulated in exosomes from prostate cancer patients. These proteins were analyzed according to specific criteria to create a focus list that contained 37 proteins. At 100% specificity, 17 of these proteins displayed individual sensitivities above 60%. Even though several of these proteins showed high sensitivity and specificity for prostate cancer as individual biomarkers, combining them in a multi-panel test has the potential for full differentiation of prostate cancer from non-disease controls. The highest sensitivity, 94%, was observed for transmembrane protein 256 (TM256; chromosome 17 open reading frame 61). LAMTOR proteins were also distinctly enriched with very high specificity for patient samples. TM256 and LAMTOR1 could be used to augment the sensitivity to 100%. Other prominent proteins were V-type proton ATPase 16 kDa proteolipid subunit (VATL), adipogenesis regulatory factor (ADIRF), and several Rab-class members and proteasomal proteins. In conclusion, this study clearly shows the potential of using urinary exosomes in the diagnosis and clinical management of prostate cancer. PMID:26196085

Identification of prostate cancer biomarkers in urinary exosomes.

PubMed

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

2015-10-06

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

Identification of candidate genes in Populus cell wall biosynthesis using text-mining, co-expression network and comparative genomics

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

Yang, Xiaohan; Ye, Chuyu; Bisaria, Anjali

2011-01-01

Populus is an important bioenergy crop for bioethanol production. A greater understanding of cell wall biosynthesis processes is critical in reducing biomass recalcitrance, a major hindrance in efficient generation of ethanol from lignocellulosic biomass. Here, we report the identification of candidate cell wall biosynthesis genes through the development and application of a novel bioinformatics pipeline. As a first step, via text-mining of PubMed publications, we obtained 121 Arabidopsis genes that had the experimental evidences supporting their involvement in cell wall biosynthesis or remodeling. The 121 genes were then used as bait genes to query an Arabidopsis co-expression database and additionalmore » genes were identified as neighbors of the bait genes in the network, increasing the number of genes to 548. The 548 Arabidopsis genes were then used to re-query the Arabidopsis co-expression database and re-construct a network that captured additional network neighbors, expanding to a total of 694 genes. The 694 Arabidopsis genes were computationally divided into 22 clusters. Queries of the Populus genome using the Arabidopsis genes revealed 817 Populus orthologs. Functional analysis of gene ontology and tissue-specific gene expression indicated that these Arabidopsis and Populus genes are high likelihood candidates for functional genomics in relation to cell wall biosynthesis.« less

Kidney Injury Molecule-1 Outperforms Traditional Biomarkers of Kidney Injury in Multi-site Preclinical Biomarker Qualification Studies

PubMed Central

Vaidya, Vishal S.; Ozer, Josef S.; Frank, Dieterle; Collings, Fitz B.; Ramirez, Victoria; Troth, Sean; Muniappa, Nagaraja; Thudium, Douglas; Gerhold, David; Holder, Daniel J.; Bobadilla, Norma A.; Marrer, Estelle; Perentes, Elias; Cordier, André; Vonderscher, Jacky; Maurer, Gérard; Goering, Peter L.; Sistare, Frank D.; Bonventre, Joseph V.

2010-01-01

Kidney toxicity accounts for a significant percentage of morbidity and drug candidate failure. Serum creatinine (SCr) and blood urea nitrogen (BUN) have been used to monitor kidney dysfunction for over a century but these markers are insensitive and non-specific. In multi-site preclinical rat toxicology studies the diagnostic performance of urinary kidney injury molecule-1 (Kim-1) was compared to traditional biomarkers as predictors of kidney tubular histopathologic changes, currently considered the “gold standard” of nephrotoxicity. In multiple models of kidney injury, urinary Kim-1 significantly outperformed SCr and BUN. The area under the receiver operating characteristic curve for Kim-1 was between 0.91 and 0.99 as compared to 0.79 to 0.9 for BUN and 0.73 to 0.85 for SCr. Thus urinary Kim-1 is the first injury biomarker of kidney toxicity qualified by the FDA and EMEA and is expected to significantly improve kidney safety monitoring. PMID:20458318

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

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

Temporal Patterns of Novel Circulating Biomarkers in IL-2-mediated Vascular Injury in the Rat.

PubMed

Keirstead, Natalie D; Bertinetti-Lapatki, Cristina; Knapp, Denise; Albassam, Mudher; Hughes, Valerie; Hong, Feng; Roth, Adrian B; Mikaelian, Igor

2015-10-01

Recombinant interleukin-2 (rIL-2) administration in oncology indications is hampered by vascular toxicity, which presents as a vascular leak syndrome. We used this aspect of the toxicity of rIL-2 to evaluate candidate biomarkers of drug-induced vascular injury (DIVI) in rats given 0.36 mg/kg rIL-2 daily. Groups of rats were given either 2 or 5 doses of rIL-2 or 5 doses of rIL-2 followed by a 7-day recovery. The histomorphologic lexicon and grading scheme developed by the Vascular Injury Working Group of the Predictive Safety Testing Consortium of the Critical Path Institute were utilized to enable semiquantitative integration with circulating biomarker levels. The administration of rIL-2 was associated with time-dependent endothelial cell hyperplasia and hypertrophy and perivascular inflammation that correlated with increases in circulating angiopoietin-2, lipocalin-2, monocyte chemotactic protein-1, tissue inhibitor of metalloproteinase-1, vascular endothelial growth factor A, E-selectin, and chemokine (C-X-C motif) ligand-1, and the microRNAs miR-21, miR-132, and miR-155. The dose groups were differentially identified by panels comprising novel candidate biomarkers and traditional hematologic parameters. These results identify biomarkers of the early stages of DIVI prior to the onset of vascular smooth muscle necrosis. © 2015 by The Author(s).

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.

Evaluation of androgen receptor gene as a candidate gene in female androgenetic alopecia.