Imaging Biomarkers for Adult Medulloblastomas: Genetic Entities May Be Identified by Their MR Imaging Radiophenotype.

PubMed

Keil, V C; Warmuth-Metz, M; Reh, C; Enkirch, S J; Reinert, C; Beier, D; Jones, D T W; Pietsch, T; Schild, H H; Hattingen, E; Hau, P

2017-10-01

The occurrence of medulloblastomas in adults is rare; nevertheless, these tumors can be subdivided into genetic and histologic entities each having distinct prognoses. This study aimed to identify MR imaging biomarkers to classify these entities and to uncover differences in MR imaging biomarkers identified in pediatric medulloblastomas. Eligible preoperative MRIs from 28 patients (11 women; 22-53 years of age) of the Multicenter Pilot-study for the Therapy of Medulloblastoma of Adults (NOA-7) cohort were assessed by 3 experienced neuroradiologists. Lesions and perifocal edema were volumetrized and multiparametrically evaluated for classic morphologic characteristics, location, hydrocephalus, and Chang criteria. To identify MR imaging biomarkers, we correlated genetic entities sonic hedgehog ( SHH ) TP53 wild type, wingless ( WNT ), and non -WNT/ non -SHH medulloblastomas (in adults, Group 4), and histologic entities were correlated with the imaging criteria. These MR imaging biomarkers were compared with corresponding data from a pediatric study. There were 19 SHH TP53 wild type (69%), 4 WNT -activated (14%), and 5 Group 4 (17%) medulloblastomas. Six potential MR imaging biomarkers were identified, 3 of which, hydrocephalus ( P = .03), intraventricular macrometastases ( P = .02), and hemorrhage ( P = .04), when combined, could identify WNT medulloblastoma with 100% sensitivity and 88.3% specificity (95% CI, 39.8%-100.0% and 62.6%-95.3%). WNT -activated nuclear β-catenin accumulating medulloblastomas were smaller than the other entities (95% CI, 5.2-22.3 cm 3 versus 35.1-47.6 cm 3 ; P = .03). Hemorrhage was exclusively present in non -WNT/ non -SHH medulloblastomas ( P = .04; n = 2/5). MR imaging biomarkers were all discordant from those identified in the pediatric cohort. Desmoplastic/nodular medulloblastomas were more rarely in contact with the fourth ventricle (4/15 versus 7/13; P = .04). MR imaging biomarkers can help distinguish histologic and genetic

A Resource for Discovering Specific and Universal Biomarkers for Distributed Stem Cells

PubMed Central

Noh, Minsoo; Smith, Janet L.; Huh, Yang Hoon; Sherley, James L.

2011-01-01

Specific and universal biomarkers for distributed stem cells (DSCs) have been elusive. A major barrier to discovery of such ideal DSC biomarkers is difficulty in obtaining DSCs in sufficient quantity and purity. To solve this problem, we used cell lines genetically engineered for conditional asymmetric self-renewal, the defining DSC property. In gene microarray analyses, we identified 85 genes whose expression is tightly asymmetric self-renewal associated (ASRA). The ASRA gene signature prescribed DSCs to undergo asymmetric self-renewal to a greater extent than committed progenitor cells, embryonic stem cells, or induced pluripotent stem cells. This delineation has several significant implications. These include: 1) providing experimental evidence that DSCs in vivo undergo asymmetric self-renewal as individual cells; 2) providing an explanation why earlier attempts to define a common gene expression signature for DSCs were unsuccessful; and 3) predicting that some ASRA proteins may be ideal biomarkers for DSCs. Indeed, two ASRA proteins, CXCR6 and BTG2, and two other related self-renewal pattern associated (SRPA) proteins identified in this gene resource, LGR5 and H2A.Z, display unique asymmetric patterns of expression that have a high potential for universal and specific DSC identification. PMID:21818293

Identifying cut points for biomarker defined subset effects in clinical trials with survival endpoints.

PubMed

He, Pei

2014-07-01

The advancements in biotechnology and genetics lead to an increasing research interest in personalized medicine, where a patient's genetic profile or biological traits contribute to choosing the most effective treatment for the patient. The process starts with finding a specific biomarker among all possible candidates that can best predict the treatment effect. After a biomarker is chosen, identifying a cut point of the biomarker value that splits the patients into treatment effective and non-effective subgroups becomes an important scientific problem. Numerous methods have been proposed to validate the predictive marker and select the appropriate cut points either prospectively or retrospectively using clinical trial data. In trials with survival outcomes, the current practice applies an interaction testing procedure and chooses the cut point that minimizes the p-values for the tests. Such method assumes independence between the baseline hazard and biomarker value. In reality, however, this assumption is often violated, as the chosen biomarker might also be prognostic in addition to its predictive nature for treatment effect. In this paper we propose a block-wise estimation and a sequential testing approach to identify the cut point in biomarkers that can group the patients into subsets based on their distinct treatment outcomes without assuming independence between the biomarker and baseline hazard. Numerical results based on simulated survival data show that the proposed method could pinpoint accurately the cut points in biomarker values that separate the patient subpopulations into subgroups with distinctive treatment outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.

Detailed comparison of amyloid PET and CSF biomarkers for identifying early Alzheimer disease

PubMed Central

Zetterberg, Henrik; Mattsson, Niklas; Johansson, Per; Minthon, Lennart; Blennow, Kaj; Olsson, Mattias

2015-01-01

Objective: To compare the diagnostic accuracy of CSF biomarkers and amyloid PET for diagnosing early-stage Alzheimer disease (AD). Methods: From the prospective, longitudinal BioFINDER study, we included 122 healthy elderly and 34 patients with mild cognitive impairment who developed AD dementia within 3 years (MCI-AD). β-Amyloid (Aβ) deposition in 9 brain regions was examined with [18F]-flutemetamol PET. CSF was analyzed with INNOTEST and EUROIMMUN ELISAs. The results were replicated in 146 controls and 64 patients with MCI-AD from the Alzheimer's Disease Neuroimaging Initiative study. Results: The best CSF measures for identifying MCI-AD were Aβ42/total tau (t-tau) and Aβ42/hyperphosphorylated tau (p-tau) (area under the curve [AUC] 0.93–0.94). The best PET measures performed similarly (AUC 0.92–0.93; anterior cingulate, posterior cingulate/precuneus, and global neocortical uptake). CSF Aβ42/t-tau and Aβ42/p-tau performed better than CSF Aβ42 and Aβ42/40 (AUC difference 0.03–0.12, p < 0.05). Using nonoptimized cutoffs, CSF Aβ42/t-tau had the highest accuracy of all CSF/PET biomarkers (sensitivity 97%, specificity 83%). The combination of CSF and PET was not better than using either biomarker separately. Conclusions: Amyloid PET and CSF biomarkers can identify early AD with high accuracy. There were no differences between the best CSF and PET measures and no improvement when combining them. Regional PET measures were not better than assessing the global Aβ deposition. The results were replicated in an independent cohort using another CSF assay and PET tracer. The choice between CSF and amyloid PET biomarkers for identifying early AD can be based on availability, costs, and doctor/patient preferences since both have equally high diagnostic accuracy. Classification of evidence: This study provides Class III evidence that amyloid PET and CSF biomarkers identify early-stage AD equally accurately. PMID:26354982

A protocol for identifying suitable biomarkers to assess fish health: A systematic review

PubMed Central

2017-01-01

Background Biomarkers have been used extensively to provide the connection between external levels of contaminant exposure, internal levels of tissue contamination, and early adverse effects in organisms. Objectives To present a three-step protocol for identifying suitable biomarkers to assess fish health in coastal and marine ecosystems, using Gladstone Harbour (Australia) as a case study. Methods Prior to applying our protocol, clear working definitions for biomarkers were developed to ensure consistency with the global literature on fish health assessment. First, contaminants of concern were identified based on the presence of point and diffuse sources of pollution and available monitoring data for the ecosystem of interest. Second, suitable fish species were identified using fisheries dependent and independent data, and prioritised based on potential pathways of exposure to the contaminants of concern. Finally, a systematic and critical literature review was conducted on the use of biomarkers to assess the health of fish exposed to the contaminants of concern. Results/Discussion We present clear working definitions for bioaccumulation markers, biomarkers of exposure, biomarkers of effect and biomarkers of susceptibility. Based on emission and concentration information, seven metals were identified as contaminants of concern for Gladstone Harbour. Twenty out of 232 fish species were abundant enough to be potentially suitable for biomarker studies; five of these were prioritised based on potential pathways of exposure and susceptibility to metals. The literature search on biomarkers yielded 5,035 articles, of which 151met the inclusion criteria. Based on our review, the most suitable biomarkers include bioaccumulation markers, biomarkers of exposure (CYP1A, EROD, SOD, LPOX, HSP, MT, DNA strand breaks, micronuclei, apoptosis), and biomarkers of effect (histopathology, TAG:ST). Conclusion Our protocol outlines a clear pathway to identify suitable biomarkers to

Identifying Thoracic Malignancies Through Pleural Fluid Biomarkers: A Predictive Multivariate Model.

PubMed

Porcel, José M; Esquerda, Aureli; Martínez-Alonso, Montserrat; Bielsa, Silvia; Salud, Antonieta

2016-03-01

The diagnosis of malignant pleural effusions may be challenging when cytological examination of aspirated pleural fluid is equivocal or noncontributory. The purpose of this study was to identify protein candidate biomarkers differentially expressed in the pleural fluid of patients with mesothelioma, lung adenocarcinoma, lymphoma, and tuberculosis (TB).A multiplex protein biochip comprising 120 biomarkers was used to determine the pleural fluid protein profile of 29 mesotheliomas, 29 lung adenocarcinomas, 12 lymphomas, and 35 tuberculosis. The relative abundance of these predetermined biomarkers among groups served to establish the differential diagnosis of: malignant versus benign (TB) effusions, lung adenocarcinoma versus mesothelioma, and lymphoma versus TB. The selected putative markers were validated using widely available commercial techniques in an independent sample of 102 patients.Significant differences were found in the protein expressions of metalloproteinase-9 (MMP-9), cathepsin-B, C-reactive protein, and chondroitin sulfate between malignant and TB effusions. When integrated into a scoring model, these proteins yielded 85% sensitivity, 100% specificity, and an area under the curve (AUC) of 0.98 for labeling malignancy in the verification sample. For lung adenocarcinoma-mesothelioma discrimination, combining CA19-9, CA15-3, and kallikrein-12 had maximal discriminatory capacity (65% sensitivity, 100% specificity, AUC 0.94); figures which also refer to the validation set. Last, cathepsin-B in isolation was only moderately useful (sensitivity 89%, specificity 62%, AUC 0.75) in separating lymphomatous and TB effusions. However, this last differentiation improved significantly when cathepsin-B was used with respect to the patient's age (sensitivity 72%, specificity 100%, AUC 0.94).In conclusion, panels of 4 (i.e., MMP-9, cathepsin-B, C-reactive protein, chondroitin sulfate), or 3 (i.e., CA19-9, CA15-3, kallikrein-12) different protein biomarkers on pleural

Biomarkers in Cardiology – Part 1 – In Heart Failure and Specific Cardiomyopathies

PubMed Central

2014-01-01

Cardiovascular diseases are the leading causes of mortality and morbidity in Brazil. The primary and secondary preventions of those diseases are a priority for the health system and require multiple approaches to increase their effectiveness. Biomarkers are tools used to more accurately identify high-risk individuals, to speed the diagnosis, and to aid in treatment and prognosis determination. This review aims to highlight the importance of biomarkers in clinical cardiology practice, and to raise relevant points of their use and the promises for the coming years. This document was divided into two parts, and this first one discusses the use of biomarkers in specific cardiomyopathies and heart failure. PMID:25590924

Lung cancer signature biomarkers: tissue specific semantic similarity based clustering of digital differential display (DDD) data.

PubMed

Srivastava, Mousami; Khurana, Pankaj; Sugadev, Ragumani

2012-11-02

The tissue-specific Unigene Sets derived from more than one million expressed sequence tags (ESTs) in the NCBI, GenBank database offers a platform for identifying significantly and differentially expressed tissue-specific genes by in-silico methods. Digital differential display (DDD) rapidly creates transcription profiles based on EST comparisons and numerically calculates, as a fraction of the pool of ESTs, the relative sequence abundance of known and novel genes. However, the process of identifying the most likely tissue for a specific disease in which to search for candidate genes from the pool of differentially expressed genes remains difficult. Therefore, we have used 'Gene Ontology semantic similarity score' to measure the GO similarity between gene products of lung tissue-specific candidate genes from control (normal) and disease (cancer) sets. This semantic similarity score matrix based on hierarchical clustering represents in the form of a dendrogram. The dendrogram cluster stability was assessed by multiple bootstrapping. Multiple bootstrapping also computes a p-value for each cluster and corrects the bias of the bootstrap probability. Subsequent hierarchical clustering by the multiple bootstrapping method (α = 0.95) identified seven clusters. The comparative, as well as subtractive, approach revealed a set of 38 biomarkers comprising four distinct lung cancer signature biomarker clusters (panel 1-4). Further gene enrichment analysis of the four panels revealed that each panel represents a set of lung cancer linked metastasis diagnostic biomarkers (panel 1), chemotherapy/drug resistance biomarkers (panel 2), hypoxia regulated biomarkers (panel 3) and lung extra cellular matrix biomarkers (panel 4). Expression analysis reveals that hypoxia induced lung cancer related biomarkers (panel 3), HIF and its modulating proteins (TGM2, CSNK1A1, CTNNA1, NAMPT/Visfatin, TNFRSF1A, ETS1, SRC-1, FN1, APLP2, DMBT1/SAG, AIB1 and AZIN1) are significantly down regulated

Isomer-specific profiling of N-glycans derived from human serum for potential biomarker discovery in pancreatic cancer.

PubMed

Liu, Yufei; Wang, Chang; Wang, Ran; Wu, Yike; Zhang, Liang; Liu, Bi-Feng; Cheng, Liming; Liu, Xin

2018-06-15

Glycosylation is one of the most important post-translational modifications of protein. Recently, global profiling of human serum glycomics has become a noninvasive method for cancer-related biomarker discovery and many studies have focused on compositional glycan profiling. In contrast, structure-specific glycan profiling may provide more potential biomarkers with higher specificity than compositional profiling. In this work, N-glycans released from human serum were neutralized with methylamine and reduced by ammonia-borane complex prior to profiling using nanoLC-ESI-MS with porous graphitized carbon (PGC) and relative abundances of over 280 isomers were compared between pancreatic cancer (PC) cases (n = 32) and healthy controls (n = 32). Statistical analysis identified 25 specific-isomeric biomarkers with significant differences (p-value < 0.05). ROC and PCA analysis were performed to assess the potential biomarkers which were identified as being significantly altered in cancer. The AUCs of the significantly changed specific-isomers were ranging from 0.712 to 0.949. In addition, with the combination of all potential biomarkers, a higher AUC of 0.976 with sensitivity (93.5%) and specificity (90.6%) was obtained. Overall, the proposed strategy coupled to relative quantitative analysis of isomeric glycans make it possible to discover new biomarkers for the diagnosis of PC. Pancreatic cancer (PC) has a poor prognosis with a five-year survival rate <5%. Therefore, a strategy for accurate diagnosis of PC is indeed required. In this paper, a dual-derivatized strategy for structure-specific glycan profiling has been used and according to our best knowledge, this is the first application of this strategy for PC biomarker discovery, in which the separation, identification and relative quantification of isomeric glycans can be simultaneously obtained. In addition, by in-depth analysis of isomeric glycans, the full description of the stereo- and region- diversity

Identifying DNA Methylation Biomarkers for Non-Endoscopic Detection of Barrett’s Esophagus

PubMed Central

Moinova, Helen R.; LaFramboise, Thomas; Lutterbaugh, James D.; Chandar, Apoorva Krishna; Dumot, John; Faulx, Ashley; Brock, Wendy; De la Cruz Cabrera, Omar; Guda, Kishore; Barnholtz-Sloan, Jill S.; Iyer, Prasad G.; Canto, Marcia I.; Wang, Jean S.; Shaheen, Nicholas J.; Thota, Prashanti N.; Willis, Joseph E.; Chak, Amitabh; Markowitz, Sanford D.

2018-01-01

We report a biomarker-based non-endoscopic method for detecting Barrett’s esophagus (BE), based on detecting methylated DNAs retrieved via a swallowable balloon-based esophageal sampling device. BE is the precursor of, and a major recognized risk factor for, developing esophageal adenocarcinoma (EAC). Endoscopy, the current standard for BE detection, is not cost-effective for population screening. We performed genome-wide screening to ascertain regions targeted for recurrent aberrant cytosine methylation in BE, identifying high-frequency methylation within the CCNA1 locus. We tested CCNA1 DNA methylation as a BE biomarker in cytology brushings of the distal esophagus from 173 individuals with or without BE. CCNA1 DNA methylation demonstrated an area under the curve (AUC)=0.95 for discriminating BE-related metaplasia and neoplasia cases versus normal individuals, performing identically to methylation of VIM DNA, an established BE biomarker. When combined, the resulting two biomarker panel was 95% sensitive and 91% specific. These results were replicated in an independent validation cohort of 149 individuals, who were assayed using the same cutoff values for test positivity established in the training population. To progress toward non-endoscopic esophageal screening, we engineered a well-tolerated, swallowable, encapsulated balloon device able to selectively sample the distal esophagus within 5 minutes. In balloon samples from 86 individuals, tests of CCNA1 plus VIM DNA methylation detected BE metaplasia with 90.3% sensitivity and 91.7% specificity. Combining the balloon sampling device with molecular assays of CCNA1 plus VIM DNA methylation enables an efficient, well-tolerated, sensitive, and specific method of screening at-risk populations for BE. PMID:29343623

Quantitative phase-digital holographic microscopy: a new imaging modality to identify original cellular biomarkers of diseases

NASA Astrophysics Data System (ADS)

Marquet, P.; Rothenfusser, K.; Rappaz, B.; Depeursinge, C.; Jourdain, P.; Magistretti, P. J.

2016-03-01

Quantitative phase microscopy (QPM) has recently emerged as a powerful label-free technique in the field of living cell imaging allowing to non-invasively measure with a nanometric axial sensitivity cell structure and dynamics. Since the phase retardation of a light wave when transmitted through the observed cells, namely the quantitative phase signal (QPS), is sensitive to both cellular thickness and intracellular refractive index related to the cellular content, its accurate analysis allows to derive various cell parameters and monitor specific cell processes, which are very likely to identify new cell biomarkers. Specifically, quantitative phase-digital holographic microscopy (QP-DHM), thanks to its numerical flexibility facilitating parallelization and automation processes, represents an appealing imaging modality to both identify original cellular biomarkers of diseases as well to explore the underlying pathophysiological processes.

Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence.

PubMed

Long, Qi; Xu, Jianpeng; Osunkoya, Adeboye O; Sannigrahi, Soma; Johnson, Brent A; Zhou, Wei; Gillespie, Theresa; Park, Jong Y; Nam, Robert K; Sugar, Linda; Stanimirovic, Aleksandra; Seth, Arun K; Petros, John A; Moreno, Carlos S

2014-06-15

Prostate cancer remains the second leading cause of cancer death in American men and there is an unmet need for biomarkers to identify patients with aggressive disease. In an effort to identify biomarkers of recurrence, we performed global RNA sequencing on 106 formalin-fixed, paraffin-embedded prostatectomy samples from 100 patients at three independent sites, defining a 24-gene signature panel. The 24 genes in this panel function in cell-cycle progression, angiogenesis, hypoxia, apoptosis, PI3K signaling, steroid metabolism, translation, chromatin modification, and transcription. Sixteen genes have been associated with cancer, with five specifically associated with prostate cancer (BTG2, IGFBP3, SIRT1, MXI1, and FDPS). Validation was performed on an independent publicly available dataset of 140 patients, where the new signature panel outperformed markers published previously in terms of predicting biochemical recurrence. Our work also identified differences in gene expression between Gleason pattern 4 + 3 and 3 + 4 tumors, including several genes involved in the epithelial-to-mesenchymal transition and developmental pathways. Overall, this study defines a novel biomarker panel that has the potential to improve the clinical management of prostate cancer. ©2014 American Association for Cancer Research.

Derivation and Validation of a Serum Biomarker Panel to Identify Infants With Acute Intracranial Hemorrhage.

PubMed

Berger, Rachel Pardes; Pak, Brian J; Kolesnikova, Mariya D; Fromkin, Janet; Saladino, Richard; Herman, Bruce E; Pierce, Mary Clyde; Englert, David; Smith, Paul T; Kochanek, Patrick M

2017-06-05

Abusive head trauma is the leading cause of death from physical abuse. Missing the diagnosis of abusive head trauma, particularly in its mild form, is common and contributes to increased morbidity and mortality. Serum biomarkers may have potential as quantitative point-of-care screening tools to alert physicians to the possibility of intracranial hemorrhage. To identify and validate a set of biomarkers that could be the basis of a multivariable model to identify intracranial hemorrhage in well-appearing infants using the Ziplex System. Binary logistic regression was used to develop a multivariable model incorporating 3 serum biomarkers (matrix metallopeptidase-9, neuron-specific enolase, and vascular cellular adhesion molecule-1) and 1 clinical variable (total hemoglobin). The model was then prospectively validated. Multiplex biomarker measurements were performed using Flow-Thru microarray technology on the Ziplex System, which has potential as a point-of-care system. The model was tested at 3 pediatric emergency departments in level I pediatric trauma centers (Children's Hospital of Pittsburgh of University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania; Primary Children's Hospital, Salt Lake City, Utah; and Lurie Children's Hospital, Chicago, Illinois) among well-appearing infants who presented for care owing to symptoms that placed them at increased risk of abusive head trauma. The study took place from November 2006 to April 2014 at Children's Hospital of Pittsburgh, June 2010 to August 2013 at Primary Children's Hospital, and January 2011 to August 2013 at Lurie Children's Hospital. A mathematical model that can predict acute intracranial hemorrhage in infants at increased risk of abusive head trauma. The multivariable model, Biomarkers for Infant Brain Injury Score, was applied prospectively to 599 patients. The mean (SD) age was 4.7 (3.1) months. Fifty-two percent were boys, 78% were white, and 8% were Hispanic. At a cutoff of 0.182, the model was 89

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.

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

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

PubMed

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

2013-08-26

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

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

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.

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

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.

Prostate Cancer Detection and Prognosis: From Prostate Specific Antigen (PSA) to Exosomal Biomarkers

PubMed Central

Filella, Xavier; Foj, Laura

2016-01-01

Prostate specific antigen (PSA) remains the most used biomarker in the management of early prostate cancer (PCa), in spite of the problems related to false positive results and overdiagnosis. New biomarkers have been proposed in recent years with the aim of increasing specificity and distinguishing aggressive from non-aggressive PCa. The emerging role of the prostate health index and the 4Kscore is reviewed in this article. Both are blood-based tests related to the aggressiveness of the tumor, which provide the risk of suffering PCa and avoiding negative biopsies. Furthermore, the use of urine has emerged as a non-invasive way to identify new biomarkers in recent years, including the PCA3 and TMPRSS2:ERG fusion gene. Available results about the PCA3 score showed its usefulness to decide the repetition of biopsy in patients with a previous negative result, although its relationship with the aggressiveness of the tumor is controversial. More recently, aberrant microRNA expression in PCa has been reported by different authors. Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of PCa. Although several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis. PMID:27792187

Prostate Cancer Detection and Prognosis: From Prostate Specific Antigen (PSA) to Exosomal Biomarkers.

PubMed

Filella, Xavier; Foj, Laura

2016-10-26

Prostate specific antigen (PSA) remains the most used biomarker in the management of early prostate cancer (PCa), in spite of the problems related to false positive results and overdiagnosis. New biomarkers have been proposed in recent years with the aim of increasing specificity and distinguishing aggressive from non-aggressive PCa. The emerging role of the prostate health index and the 4Kscore is reviewed in this article. Both are blood-based tests related to the aggressiveness of the tumor, which provide the risk of suffering PCa and avoiding negative biopsies. Furthermore, the use of urine has emerged as a non-invasive way to identify new biomarkers in recent years, including the PCA3 and TMPRSS2:ERG fusion gene. Available results about the PCA3 score showed its usefulness to decide the repetition of biopsy in patients with a previous negative result, although its relationship with the aggressiveness of the tumor is controversial. More recently, aberrant microRNA expression in PCa has been reported by different authors. Preliminary results suggest the utility of circulating and urinary microRNAs in the detection and prognosis of PCa. Although several of these new biomarkers have been recommended by different guidelines, large prospective and comparative studies are necessary to establish their value in PCa detection and prognosis.

Proteomic Profiling of Paraffin-Embedded Samples Identifies Metaplasia-Specific and Early-Stage Gastric Cancer Biomarkers

PubMed Central

Sousa, Josane F.; Ham, Amy-Joan L.; Whitwell, Corbin; Nam, Ki Taek; Lee, Hyuk-Joon; Yang, Han-Kwang; Kim, Woo Ho; Zhang, Bing; Li, Ming; LaFleur, Bonnie; Liebler, Daniel C.; Goldenring, James R.

2013-01-01

Early diagnosis and curative resection are the predominant factors associated with increased survival in patients with gastric cancer. However, most gastric cancer cases are still diagnosed at later stages. Since most pathologic specimens are archived as FFPE samples, the ability to use them to generate expression profiles can greatly improve cancer biomarker discovery. We sought to uncover new biomarkers for stomach preneoplastic metaplasias and neoplastic lesions by generating proteome profiles using FFPE samples. We combined peptide isoelectric focusing and liquid chromatography–tandem mass spectrometry analysis to generate proteomic profiles from FFPE samples of intestinal-type gastric cancer, metaplasia, and normal mucosa. The expression patterns of selected proteins were analyzed by immunostaining first in single tissue sections from normal stomach, metaplasia, and gastric cancer and later in larger tissue array cohorts. We detected 60 proteins up-regulated and 87 proteins down-regulated during the progression from normal mucosa to metaplasia to gastric cancer. Two of the up-regulated proteins, LTF and DMBT1, were validated as specific markers for spasmolytic polypeptide–expressing metaplasia and intestinal metaplasia, respectively. In cancers, significantly lower levels of DMBT1 or LTF correlated with more advanced disease and worse prognosis. Thus, proteomic profiling using FFPE samples has led to the identification of two novel markers for stomach metaplasias and gastric cancer prognosis. PMID:22944598

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

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

PubMed

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

2012-07-01

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

Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis

PubMed Central

Craig-Schapiro, Rebecca; Kuhn, Max; Xiong, Chengjie; Pickering, Eve H.; Liu, Jingxia; Misko, Thomas P.; Perrin, Richard J.; Bales, Kelly R.; Soares, Holly; Fagan, Anne M.; Holtzman, David M.

2011-01-01

Background Clinicopathological studies suggest that Alzheimer's disease (AD) pathology begins ∼10–15 years before the resulting cognitive impairment draws medical attention. Biomarkers that can detect AD pathology in its early stages and predict dementia onset would, therefore, be invaluable for patient care and efficient clinical trial design. We utilized a targeted proteomics approach to discover novel cerebrospinal fluid (CSF) biomarkers that can augment the diagnostic and prognostic accuracy of current leading CSF biomarkers (Aβ42, tau, p-tau181). Methods and Findings Using a multiplexed Luminex platform, 190 analytes were measured in 333 CSF samples from cognitively normal (Clinical Dementia Rating [CDR] 0), very mildly demented (CDR 0.5), and mildly demented (CDR 1) individuals. Mean levels of 37 analytes (12 after Bonferroni correction) were found to differ between CDR 0 and CDR>0 groups. Receiver-operating characteristic curve analyses revealed that small combinations of a subset of these markers (cystatin C, VEGF, TRAIL-R3, PAI-1, PP, NT-proBNP, MMP-10, MIF, GRO-α, fibrinogen, FAS, eotaxin-3) enhanced the ability of the best-performing established CSF biomarker, the tau/Aβ42 ratio, to discriminate CDR>0 from CDR 0 individuals. Multiple machine learning algorithms likewise showed that the novel biomarker panels improved the diagnostic performance of the current leading biomarkers. Importantly, most of the markers that best discriminated CDR 0 from CDR>0 individuals in the more targeted ROC analyses were also identified as top predictors in the machine learning models, reconfirming their potential as biomarkers for early-stage AD. Cox proportional hazards models demonstrated that an optimal panel of markers for predicting risk of developing cognitive impairment (CDR 0 to CDR>0 conversion) consisted of calbindin, Aβ42, and age. Conclusions/Significance Using a targeted proteomic screen, we identified novel candidate biomarkers that complement the best

A CONCISE PANEL OF BIOMARKERS IDENTIFIES NEUROCOGNITIVE FUNCTIONING CHANGES IN HIV-INFECTED INDIVIDUALS

PubMed Central

Marcotte, Thomas D.; Deutsch, Reena; Michael, Benedict Daniel; Franklin, Donald; Cookson, Debra Rosario; Bharti, Ajay R.; Grant, Igor; Letendre, Scott L.

2013-01-01

Background Neurocognitive (NC) impairment (NCI) occurs commonly in people living with HIV. Despite substantial effort, no biomarkers have been sufficiently validated for diagnosis and prognosis of NCI in the clinic. The goal of this project was to identify diagnostic or prognostic biomarkers for NCI in a comprehensively characterized HIV cohort. Methods Multidisciplinary case review selected 98 HIV-infected individuals and categorized them into four NC groups using normative data: stably normal (SN), stably impaired (SI), worsening (Wo), or improving (Im). All subjects underwent comprehensive NC testing, phlebotomy, and lumbar puncture at two timepoints separated by a median of 6.2 months. Eight biomarkers were measured in CSF and blood by immunoassay. Results were analyzed using mixed model linear regression and staged recursive partitioning. Results At the first visit, subjects were mostly middle-aged (median 45) white (58%) men (84%) who had AIDS (70%). Of the 73% who took antiretroviral therapy (ART), 54% had HIV RNA levels below 50 c/mL in plasma. Mixed model linear regression identified that only MCP-1 in CSF was associated with neurocognitive change group. Recursive partitioning models aimed at diagnosis (i.e., correctly classifying neurocognitive status at the first visit) were complex and required most biomarkers to achieve misclassification limits. In contrast, prognostic models were more efficient. A combination of three biomarkers (sCD14, MCP-1, SDF-1α) correctly classified 82% of Wo and SN subjects, including 88% of SN subjects. A combination of two biomarkers (MCP-1, TNF-α) correctly classified 81% of Im and SI subjects, including 100% of SI subjects. Conclusions This analysis of well-characterized individuals identified concise panels of biomarkers associated with NC change. Across all analyses, the two most frequently identified biomarkers were sCD14 and MCP-1, indicators of monocyte/macrophage activation. While the panels differed depending on

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.

HMGB1 and Its Hyperacetylated Isoform are Sensitive and Specific Serum Biomarkers to Detect Asbestos Exposure and to Identify Mesothelioma Patients.

PubMed

Napolitano, Andrea; Antoine, Daniel J; Pellegrini, Laura; Baumann, Francine; Pagano, Ian; Pastorino, Sandra; Goparaju, Chandra M; Prokrym, Kirill; Canino, Claudia; Pass, Harvey I; Carbone, Michele; Yang, Haining

2016-06-15

To determine whether serum levels of high mobility group box protein 1 (HMGB1) could differentiate malignant mesothelioma patients, asbestos-exposed individuals, and unexposed controls. Hyperacetylated and nonacetylated HMGB1 (together referred to as total HMGB1) were blindly measured in blood collected from malignant mesothelioma patients (n = 22), individuals with verified chronic asbestos exposure (n = 20), patients with benign pleural effusions (n = 13) or malignant pleural effusions not due to malignant mesothelioma (n = 25), and healthy controls (n = 20). Blood levels of previously proposed malignant mesothelioma biomarkers fibulin-3, mesothelin, and osteopontin were also measured in nonhealthy individuals. HMGB1 serum levels reliably distinguished malignant mesothelioma patients, asbestos-exposed individuals, and unexposed controls. Total HMGB1 was significantly higher in malignant mesothelioma patients and asbestos-exposed individuals compared with healthy controls. Hyperacetylated HMGB1 was significantly higher in malignant mesothelioma patients compared with asbestos-exposed individuals and healthy controls, and did not vary with tumor stage. At the cut-off value of 2.00 ng/mL, the sensitivity and specificity of serum hyperacetylated HMGB1 in differentiating malignant mesothelioma patients from asbestos-exposed individuals and healthy controls was 100%, outperforming other previously proposed biomarkers. Combining HMGB1 and fibulin-3 provided increased sensitivity and specificity in differentiating malignant mesothelioma patients from patients with cytologically benign or malignant non-mesothelioma pleural effusion. Our results are significant and clinically relevant as they provide the first biomarker of asbestos exposure and indicate that hyperacetylated HMGB1 is an accurate biomarker to differentiate malignant mesothelioma patients from individuals occupationally exposed to asbestos and unexposed controls. A trial to independently validate these

Global population-specific variation in miRNA associated with cancer risk and clinical biomarkers.

PubMed

Rawlings-Goss, Renata A; Campbell, Michael C; Tishkoff, Sarah A

2014-08-28

MiRNA expression profiling is being actively investigated as a clinical biomarker and diagnostic tool to detect multiple cancer types and stages as well as other complex diseases. Initial investigations, however, have not comprehensively taken into account genetic variability affecting miRNA expression and/or function in populations of different ethnic backgrounds. Therefore, more complete surveys of miRNA genetic variability are needed to assess global patterns of miRNA variation within and between diverse human populations and their effect on clinically relevant miRNA genes. Genetic variation in 1524 miRNA genes was examined using whole genome sequencing (60x coverage) in a panel of 69 unrelated individuals from 14 global populations, including European, Asian and African populations. We identified 33 previously undescribed miRNA variants, and 31 miRNA containing variants that are globally population-differentiated in frequency between African and non-African populations (PD-miRNA). The top 1% of PD-miRNA were significantly enriched for regulation of genes involved in glucose/insulin metabolism and cell division (p < 10(-7)), most significantly the mitosis pathway, which is strongly linked to cancer onset. Overall, we identify 7 PD-miRNAs that are currently implicated as cancer biomarkers or diagnostics: hsa-mir-202, hsa-mir-423, hsa-mir-196a-2, hsa-mir-520h, hsa-mir-647, hsa-mir-943, and hsa-mir-1908. Notably, hsa-mir-202, a potential breast cancer biomarker, was found to show significantly high allele frequency differentiation at SNP rs12355840, which is known to affect miRNA expression levels in vivo and subsequently breast cancer mortality. MiRNA expression profiles represent a promising new category of disease biomarkers. However, population specific genetic variation can affect the prevalence and baseline expression of these miRNAs in diverse populations. Consequently, miRNA genetic and expression level variation among ethnic groups may be contributing in

Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods.

PubMed

Lloyd, Amanda J; Favé, Gaëlle; Beckmann, Manfred; Lin, Wanchang; Tailliart, Kathleen; Xie, Long; Mathers, John C; Draper, John

2011-10-01

The lack of robust biological markers of dietary exposure hinders the quantitative understanding of causal relations between diet and health. We aimed to develop an efficient procedure to discover metabolites in urine that may have future potential as biomarkers of acute exposure to foods of high public health importance. Twenty-four participants were provided with a test breakfast in which the cereal component of a standardized breakfast was replaced by 1 of 4 foods of high public health importance; 1.5-, 3-, and 4.5-h postprandial urine samples were collected. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to discover signals resulting from consumption of each test food. Fasted-state urine samples provided a universal comparator for food biomarker lead discovery in postprandial urine. The filtering of data features associated with consumption of the common components of the standardized breakfast improved discrimination models and readily identified metabolites that showed consumption of specific test foods. A combination of trimethylamine-N-oxide and 1-methylhistidine was associated with salmon consumption. Novel ascorbate derivatives were discovered in urine after consumption of either broccoli or raspberries. Sulphonated caffeic acid and sulphonated methyl-epicatechin concentrations increased dramatically after consumption of raspberries. This biomarker lead discovery strategy can identify urinary metabolites associated with acute exposure to individual foods. Future studies are required to validate the specificity and utility of potential biomarkers in an epidemiologic context.

A cross sectional study of two independent cohorts identifies serum biomarkers for facioscapulohumeral muscular dystrophy (FSHD)

PubMed Central

Petek, Lisa M.; Rickard, Amanda M.; Budech, Christopher; Poliachik, Sandra L.; Shaw, Dennis; Ferguson, Mark R.; Tawil, Rabi; Friedman, Seth D.; Miller, Daniel G.

2016-01-01

Measuring the severity and progression of facioscapulohumeral muscular dystrophy (FSHD) is particularly challenging because muscle weakness progresses over long periods of time and can be sporadic. Biomarkers are essential for measuring disease burden and testing treatment strategies. We utilized the sensitive, specific, high-throughput SomaLogic proteomics platform of 1129 proteins to identify proteins with levels that correlate with FSHD severity in a cross-sectional study of two independent cohorts. We discovered biomarkers that correlate with clinical severity and disease burden measured by magnetic resonance imaging. Sixty-eight proteins in the Rochester cohort (n = 48) and 51 proteins in the Seattle cohort (n = 30) had significantly different levels in FSHD-affected individuals when compared with controls (p-value ≤ .005). A subset of these varied by at least 1.5 fold and four biomarkers were significantly elevated in both cohorts. Levels of creatine kinase MM and MB isoforms, carbonic anhydrase III, and troponin I type 2 reliably predicted the disease state and correlated with disease severity. Other novel biomarkers were also discovered that may reveal mechanisms of disease pathology. Assessing the levels of these biomarkers during clinical trials may add significance to other measures of quantifying disease progression or regression. PMID:27185459

Anti-anxiety drugs reduce conflict-specific "theta"--a possible human anxiety-specific biomarker.

PubMed

McNaughton, Neil; Swart, Charles; Neo, Phoebe; Bates, Vanessa; Glue, Paul

2013-05-15

Syndromes of fear/anxiety are currently ill-defined, with no accepted human biomarkers for anxiety-specific processes. A unique common neural action of different classes of anxiolytic drugs may provide such a biomarker. In rodents, a reduction in low frequency (4-12 Hz; "theta") brain rhythmicity is produced by all anxiolytics (even those lacking panicolytic or antidepressant action) and not by any non-anxiolytics. This rhythmicity is a key property of the Behavioural Inhibition System (BIS) postulated to be one neural substrate of anxiety. We sought homologous anxiolytic-sensitive changes in human surface EEG rhythmicity. Thirty-four healthy volunteers in parallel groups were administered double blind single doses of triazolam 0.25mg, buspirone 10mg or placebo 1 hour prior to completing the stop-signal task. Right frontal conflict-specific EEG power (previously shown to correlate with trait anxiety and neuroticism in this task) was extracted as a contrast between trials with balanced approach-avoidance (stop-go) conflict and the average of trials with net approach and net avoidance. Compared with placebo, both triazolam and buspirone decreased right-frontal, 9-10 Hz, conflict-specific-power. Only one dose of each of only two classes of anxiolytic and no non-anxiolytics were tested, so additional tests are needed to determine generality. There is a distinct rhythmic system in humans that is sensitive to both classical/GABAergic and novel/serotonergic anxiolytics. This conflict-specific rhythmicity should provide a biomarker, with a strong pre-clinical neuropsychology, for a novel approach to classifying anxiety disorders. Copyright © 2012 Elsevier B.V. All rights reserved.

Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome

DOE PAGES

Marino, Simeone; Gideon, Hannah P.; Gong, Chang; ...

2016-04-11

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identifiedmore » T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.« less

Computational and empirical studies predict Mycobacterium tuberculosis-specific T cells as a biomarker for infection outcome

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

Marino, Simeone; Gideon, Hannah P.; Gong, Chang

Identifying biomarkers for tuberculosis (TB) is an ongoing challenge in developing immunological correlates of infection outcome and protection. Biomarker discovery is also necessary for aiding design and testing of new treatments and vaccines. To effectively predict biomarkers for infection progression in any disease, including TB, large amounts of experimental data are required to reach statistical power and make accurate predictions. We took a two-pronged approach using both experimental and computational modeling to address this problem. We first collected 200 blood samples over a 2-year period from 28 non-human primates (NHP) infected with a low dose of Mycobacterium tuberculosis. We identifiedmore » T cells and the cytokines that they were producing (single and multiple) from each sample along with monkey status and infection progression data. Machine learning techniques were used to interrogate the experimental NHP datasets without identifying any potential TB biomarker. In parallel, we used our extensive novel NHP datasets to build and calibrate a multi-organ computational model that combines what is occurring at the site of infection (e.g., lung) at a single granuloma scale with blood level readouts that can be tracked in monkeys and humans. We then generated a large in silico repository of in silico granulomas coupled to lymph node and blood dynamics and developed an in silico tool to scale granuloma level results to a full host scale to identify what best predicts Mycobacterium tuberculosis (Mtb) infection outcomes. The analysis of in silico blood measures identifies Mtb-specific frequencies of effector T cell phenotypes at various time points post infection as promising indicators of infection outcome. As a result, we emphasize that pairing wetlab and computational approaches holds great promise to accelerate TB biomarker discovery.« less

A Serological Biopsy Using Five Stomach-Specific Circulating Biomarkers for Gastric Cancer Risk Assessment: A Multi-Phase Study.

PubMed

Tu, Huakang; Sun, Liping; Dong, Xiao; Gong, Yuehua; Xu, Qian; Jing, Jingjing; Bostick, Roberd M; Wu, Xifeng; Yuan, Yuan

2017-05-01

We aimed to assess a serological biopsy using five stomach-specific circulating biomarkers-pepsinogen I (PGI), PGII, PGI/II ratio, anti-Helicobacter pylori (H. pylori) antibody, and gastrin-17 (G-17)-for identifying high-risk individuals and predicting risk of developing gastric cancer (GC). Among 12,112 participants with prospective follow-up from an ongoing population-based screening program using both serology and gastroscopy in China, we conducted a multi-phase study involving a cross-sectional analysis, a follow-up analysis, and an integrative risk prediction modeling analysis. In the cross-sectional analysis, the five biomarkers (especially PGII, the PGI/II ratio, and H. pylori sero-positivity) were associated with the presence of precancerous gastric lesions or GC at enrollment. In the follow-up analysis, low PGI levels and PGI/II ratios were associated with higher risk of developing GC, and both low (<0.5 pmol/l) and high (>4.7 pmol/l) G-17 levels were associated with higher risk of developing GC, suggesting a J-shaped association. In the risk prediction modeling analysis, the five biomarkers combined yielded a C statistic of 0.803 (95% confidence interval (CI)=0.789-0.816) and improved prediction beyond traditional risk factors (C statistic from 0.580 to 0.811, P<0.001) for identifying precancerous lesions at enrollment, and higher serological biopsy scores based on the five biomarkers at enrollment were associated with higher risk of developing GC during follow-up (P for trend <0.001). A serological biopsy composed of the five stomach-specific circulating biomarkers could be used to identify high-risk individuals for further diagnostic gastroscopy, and to stratify individuals' risk of developing GC and thus to guide targeted screening and precision prevention.

CXCR6, a newly defined biomarker of tissue-specific stem cell asymmetric self-renewal, identifies more aggressive human melanoma cancer stem cells.

PubMed

Taghizadeh, Rouzbeh; Noh, Minsoo; Huh, Yang Hoon; Ciusani, Emilio; Sigalotti, Luca; Maio, Michele; Arosio, Beatrice; Nicotra, Maria R; Natali, PierGiorgio; Sherley, James L; La Porta, Caterina A M

2010-12-22

A fundamental problem in cancer research is identifying the cell type that is capable of sustaining neoplastic growth and its origin from normal tissue cells. Recent investigations of a variety of tumor types have shown that phenotypically identifiable and isolable subfractions of cells possess the tumor-forming ability. In the present paper, using two lineage-related human melanoma cell lines, primary melanoma line IGR39 and its metastatic derivative line IGR37, two main observations are reported. The first one is the first phenotypic evidence to support the origin of melanoma cancer stem cells (CSCs) from mutated tissue-specific stem cells; and the second one is the identification of a more aggressive subpopulation of CSCs in melanoma that are CXCR6+. We defined CXCR6 as a new biomarker for tissue-specific stem cell asymmetric self-renewal. Thus, the relationship between melanoma formation and ABCG2 and CXCR6 expression was investigated. Consistent with their non-metastatic character, unsorted IGR39 cells formed significantly smaller tumors than unsorted IGR37 cells. In addition, ABCG2+ cells produced tumors that had a 2-fold greater mass than tumors produced by unsorted cells or ABCG2- cells. CXCR6+ cells produced more aggressive tumors. CXCR6 identifies a more discrete subpopulation of cultured human melanoma cells with a more aggressive MCSC phenotype than cells selected on the basis of the ABCG2+ phenotype alone. The association of a more aggressive tumor phenotype with asymmetric self-renewal phenotype reveals a previously unrecognized aspect of tumor cell physiology. Namely, the retention of some tissue-specific stem cell attributes, like the ability to asymmetrically self-renew, impacts the natural history of human tumor development. Knowledge of this new aspect of tumor development and progression may provide new targets for cancer prevention and treatment.

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

PubMed

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

2013-10-01

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

Cardiovascular risk assessment of dyslipidemic children: analysis of biomarkers to identify monogenic dyslipidemia[S

PubMed Central

Medeiros, Ana Margarida; Alves, Ana Catarina; Aguiar, Pedro; Bourbon, Mafalda

2014-01-01

The distinction between a monogenic dyslipidemia and a polygenic/environmental dyslipidemia is important for the cardiovascular risk assessment, counseling, and treatment of these patients. The present work aims to perform the cardiovascular risk assessment of dyslipidemic children to identify useful biomarkers for clinical criteria improvement in clinical settings. Main cardiovascular risk factors were analyzed in a cohort of 237 unrelated children with clinical diagnosis of familial hypercholesterolemia (FH). About 40% carried at least two cardiovascular risk factors and 37.6% had FH, presenting mutations in LDLR and APOB. FH children showed significant elevated atherogenic markers and lower concentration of antiatherogenic particles. Children without a molecular diagnosis of FH had higher levels of TGs, apoC2, apoC3, and higher frequency of BMI and overweight/obesity, suggesting that environmental factors can be the underlying cause of their hypercholesterolem≥ia. An apoB/apoA1 ratio ≥0.68 was identified as the best biomarker (area under the curve = 0.835) to differentiate FH from other dyslipidemias. The inclusion in clinical criteria of a higher cut-off point for LDL cholesterol or an apoB/apoA1 ratio ≥0.68 optimized the criteria sensitivity and specificity. The correct identification, at an early age, of all children at-risk is of great importance so that specific interventions can be implemented. apoB/apoA1 can improve the identification of FH patients. PMID:24627126

Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action.

PubMed

Xuan, Jiekun; Pan, Guihua; Qiu, Yunping; Yang, Lun; Su, Mingming; Liu, Yumin; Chen, Jian; Feng, Guoyin; Fang, Yiru; Jia, Wei; Xing, Qinghe; He, Lin

2011-12-02

Despite recent advances in understanding the pathophysiology of schizophrenia and the mechanisms of antipsychotic drug action, the development of biomarkers for diagnosis and therapeutic monitoring in schizophrenia remains challenging. Metabolomics provides a powerful approach to discover diagnostic and therapeutic biomarkers by analyzing global changes in an individual's metabolic profile in response to pathophysiological stimuli or drug intervention. In this study, we performed gas chromatography-mass spectrometry based metabolomic profiling in serum of unmedicated schizophrenic patients before and after an 8-week risperidone monotherapy, to detect potential biomarkers associated with schizophrenia and risperidone treatment. Twenty-two marker metabolites contributing to the complete separation of schizophrenic patients from matched healthy controls were identified, with citrate, palmitic acid, myo-inositol, and allantoin exhibiting the best combined classification performance. Twenty marker metabolites contributing to the complete separation between posttreatment and pretreatment patients were identified, with myo-inositol, uric acid, and tryptophan showing the maximum combined classification performance. Metabolic pathways including energy metabolism, antioxidant defense systems, neurotransmitter metabolism, fatty acid biosynthesis, and phospholipid metabolism were found to be disturbed in schizophrenic patients and partially normalized following risperidone therapy. Further study of these metabolites may facilitate the development of noninvasive biomarkers and more efficient therapeutic strategies for schizophrenia.

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

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2016-10-01

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis PRINCIPAL...4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis 5b...Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad

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.

Nephron segment specific microRNA biomarkers of pre-clinical drug-induced renal toxicity: Opportunities and challenges

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

Nassirpour, Rounak, E-mail: Rounak.nassirpour@pfiz

Drug-induced nephrotoxicity is a common drug development complication for pharmaceutical companies. Sensitive, specific, translatable and non-invasive biomarkers of renal toxicity are urgently needed to diagnose nephron segment specific injury. The currently available gold standard biomarkers for nephrotoxicity are not kidney-specific, lack sensitivity for early detection, and are not suitable for renal damage localization (glomerular vs tubulointerstitial injury). MicroRNAs (miRNAs) are increasingly gaining momentum as promising biomarkers of various organ toxicities, including drug induced renal injury. This is mostly due to their stability in easily accessible biofluids, ease of developing nucleic acids detection compared to protein detection assays, as well asmore » their interspecies translatability. Increasing concordance of miRNA findings by standardizing methodology most suitable for their detection and quantitation, as well as characterization of their expression pattern in a cell type specific manner, will accelerate progress toward validation of these miRNAs as biomarkers in pre-clinical, and clinical settings. This review aims to highlight the current pre-clinical findings surrounding miRNAs as biomarkers in two important segments of the nephron, the glomerulus and tubules. - Highlights: • miRNAs are promising biomarkers of drug-induced kidney injury. • Summarized pre-clinical miRNA biomarkers of drug-induced nephrotoxicity. • Described the strengths and challenges associated with miRNAs as biomarkers.« less

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

Biomarker Discovery by Modeling Behçet's Disease with Patient-Specific Human Induced Pluripotent Stem Cells.

PubMed

Son, Mi-Young; Kim, Young-Dae; Seol, Binna; Lee, Mi-Ok; Na, Hee-Jun; Yoo, Bin; Chang, Jae-Suk; Cho, Yee Sook

2017-01-15

Behçet's disease (BD) is a chronic inflammatory and multisystemic autoimmune disease of unknown etiology. Due to the lack of a specific test for BD, its diagnosis is very difficult and therapeutic options are limited. Induced pluripotent stem cell (iPSC) technology, which provides inaccessible disease-relevant cell types, opens a new era for disease treatment. In this study, we generated BD iPSCs from patient somatic cells and differentiated them into hematopoietic precursor cells (BD iPSC-HPCs) as BD model cells. Based on comparative transcriptome analysis using our BD model cells, we identified eight novel BD-specific genes, AGTR2, CA9, CD44, CXCL1, HTN3, IL-2, PTGER4, and TSLP, which were differentially expressed in BD patients compared with healthy controls or patients with other immune diseases. The use of CXCL1 as a BD biomarker was further validated at the protein level using both a BD iPSC-HPC-based assay system and BD patient serum samples. Furthermore, we show that our BD iPSC-HPC-based drug screening system is highly effective for testing CXCL1 BD biomarkers, as determined by monitoring the efficacy of existing anti-inflammatory drugs. Our results shed new light on the usefulness of patient-specific iPSC technology in the development of a benchmarking platform for disease-specific biomarkers, phenotype- or target-driven drug discovery, and patient-tailored therapies.

Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury.

PubMed

Jones, Jace W; Jackson, Isabel L; Vujaskovic, Zeljko; Kaytor, Michael D; Kane, Maureen A

2017-12-01

Biomarkers serve a number of purposes during drug development including defining the natural history of injury/disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.

Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet's Disease by Gas Chromatography/Time-of-Flight-Mass Spectrometry.

PubMed

Ahn, Joong Kyong; Kim, Jungyeon; Hwang, Jiwon; Song, Juhwan; Kim, Kyoung Heon; Cha, Hoon-Suk

2017-11-02

Diagnosing Behcet's disease (BD) is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flight-mass spectrometry (GC/TOF-MS). Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC) were assessed using GC/TOF-MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF-MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA) model were R ² X of 0.231, R ² Y of 0.804, and Q ² of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974). OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%). We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF-MS.

Development of an Immunoassay for the Kidney Specific Protein myo-Inositol Oxygenase, a Potential Biomarker of Acute Kidney Injury

PubMed Central

Gaut, Joseph P.; Crimmins, Dan L.; Ohlendorf, Matt F.; Lockwood, Christina M.; Griest, Terry A.; Brada, Nancy A.; Hoshi, Masato; Sato, Bryan; Hotchkiss, Richard S.; Jain, Sanjay; Ladenson, Jack H.

2014-01-01

Background Acute kidney injury (AKI) affects 45% of critically ill patients resulting in increased morbidity and mortality. The diagnostic standard, serum creatinine (SCr), is non-specific and may not increase until days after injury. There is significant need for a renal specific AKI biomarker detectable early enough that there would be a potential window for therapeutic intervention. In this study, we sought to identify a renal specific biomarker of AKI. Methods Gene expression data was analyzed from normal mouse tissues to identify kidney specific genes, one of which was Miox. Monoclonal antibodies were generated to recombinant myo-inositol oxygenase (MIOX), and an immunoassay was developed to quantify MIOX in plasma. The immunoassay was tested in animals and retrospectively in patients with and without AKI. Results Kidney tissue specificity of MIOX was supported by Western blot. Immunohistochemistry localized MIOX to the proximal renal tubule. Plasma MIOX, undetectable at baseline, increased 24 hours following AKI in mice. Plasma MIOX was increased in critically ill patients with AKI (12.4 ± 4.3 ng/mL, n=42) compared with patients without AKI (0.5 ± 0.3 ng/mL, n=17) and was highest in patients with oliguric AKI (20.2 ± 7.5 ng/mL, n=23). Plasma MIOX increased 54.3 ± 3.8 hours before the increase in SCr. Conclusions MIOX is a renal specific, proximal tubule protein that is increased in plasma of animals and critically ill patients with AKI. MIOX preceded the elevation in SCr by approximately two days in human patients. Large-scale studies are warranted to further investigate MIOX as an AKI biomarker. PMID:24486646

Biomarkers for prostate cancer detection and progression: Beyond prostate-specific antigen.

PubMed

Berney, Daniel M

2010-04-01

Prostate cancer is a major health problem with an incompletely understood pathogenesis and etiology. The advent of the prostate-specific antigen (PSA) test in the 1980s caused a revolution in how the disease was detected, but the evidence for PSA as a screening test is deficient. Biomarkers have been investigated, both for detection and discrimination of indolent from aggressive cancers. Refinements to the PSA test have been proposed but for practical and evidence-based reasons none have translated through to widespread clinical use. Of the novel biomarkers, the most promising is the prostate cancer antigen 3 (PCA3) test. New biomarkers to predict aggressive disease are even more contentious. The pathological grade of tumor remains the most powerful biomarker of prognosis. Other proven variables include tumor extent on biopsy and serum PSA. Tissue biomarkers have proven unhelpful due to a variable and biased literature with multiple methodological flaws, but Ki-67 probably shows more promise than any other current tissue biomarker. The recent discovery of a family of fusion genes in the prostate has led to considerable discussion on their prognostic role. Dissection of the genetic basis of the disease may lead to discoveries that will enhance our understanding and aid the search for prognostically valuable biomarkers. Copyright 2010 Prous Science, S.A.U. or its licensors. All rights reserved.

T7 Phage Display Library a Promising Strategy to Detect Tuberculosis Specific Biomarkers.

PubMed

Talwar, Harvinder; Talreja, Jaya; Samavati, Lobelia

2016-06-01

One-third of the world's population is infected with tuberculosis, only 10% will develop active disease and the remaining 90% is considered to have latent TB (LTB). While active TB is contagious and can be lethal, the LTB can evolve to active TB. The diagnosis of TB can be challenging, especially in the early stages, due to the variability in presentation and nonspecific signs and symptoms. Currently, we have limited tools available to diagnose active TB, predict treatment efficacy and cure of active tuberculosis, the reactivation of latent tuberculosis infection, and the induction of protective immune responses through vaccination. Therefore, the identification of robust and accurate tuberculosis-specific biomarkers is crucial for the successful eradication of TB. In this commentary, we summarized the available methods for diagnosis and differentiation of active TB from LTB and their limitations. Additionally, we present a novel peptide microarray platform as promising strategy to identify TB biomarkers.

Biomarkers in localized prostate cancer

PubMed Central

Ferro, Matteo; Buonerba, Carlo; Terracciano, Daniela; Lucarelli, Giuseppe; Cosimato, Vincenzo; Bottero, Danilo; Deliu, Victor M; Ditonno, Pasquale; Perdonà, Sisto; Autorino, Riccardo; Coman, Ioman; De Placido, Sabino; Di Lorenzo, Giuseppe; De Cobelli, Ottavio

2016-01-01

Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer. PMID:26768791

New Biomarkers of Coffee Consumption Identified by the Non-Targeted Metabolomic Profiling of Cohort Study Subjects

PubMed Central

Martin, Jean-François; Lyan, Bernard; Pujos-Guillot, Estelle; Fezeu, Leopold; Hercberg, Serge; Comte, Blandine; Galan, Pilar; Touvier, Mathilde; Manach, Claudine

2014-01-01

Coffee contains various bioactives implicated with human health and disease risk. To accurately assess the effects of overall consumption upon health and disease, individual intake must be measured in large epidemiological studies. Metabolomics has emerged as a powerful approach to discover biomarkers of intake for a large range of foods. Here we report the profiling of the urinary metabolome of cohort study subjects to search for new biomarkers of coffee intake. Using repeated 24-hour dietary records and a food frequency questionnaire, 20 high coffee consumers (183–540 mL/d) and 19 low consumers were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject were profiled by high-resolution mass spectrometry. Partial least-square discriminant analysis of multidimensional liquid chromatography-mass spectrometry data clearly distinguished high consumers from low via 132 significant (p-value<0.05) discriminating features. Ion clusters whose intensities were most elevated in the high consumers were annotated using online and in-house databases and their identities checked using commercial standards and MS-MS fragmentation. The best discriminants, and thus potential markers of coffee consumption, were the glucuronide of the diterpenoid atractyligenin, the diketopiperazine cyclo(isoleucyl-prolyl), and the alkaloid trigonelline. Some caffeine metabolites, such as 1-methylxanthine, were also among the discriminants, however caffeine may be consumed from other sources and its metabolism is subject to inter-individual variation. Receiver operating characteristics curve analysis showed that the biomarkers identified could be used effectively in combination for increased sensitivity and specificity. Once validated in other cohorts or intervention studies, these specific single or combined biomarkers will become a valuable alternative to assessment of coffee intake by dietary survey and finally lead to a better understanding of the health

Composition of betel specific chemicals in saliva during betel chewing for the identification of biomarkers

PubMed Central

Franke, Adrian A.; Mendez, Ana Joy; Lai, Jennifer F.; Arat-Cabading, Celine; Li, Xingnan; Custer, Laurie J.

2015-01-01

Betel nut chewing causes cancer in humans including strong associations with head and neck cancer in Guam. In the search for biomarkers of betel chewing we sought to identify chemicals specific for the 3 most commonly consumed betel preparations in Guam: nut (‘BN’), nut + Piper betle leaf (‘BL’), and betel quid (‘BQ’) consisting of nut+lime+tobacco+Piper betle leaf. Chemicals were extracted from the chewing material and saliva of subjects chewing these betel preparations. Saliva analysis involved protein precipitation with acetonitrile, dilution with formic acid followed by LCMS analysis. Baseline and chewing saliva levels were compared using t-tests and differences between groups were compared by ANOVA; p<0.05 indicated significance. Predominant compounds in chewing material were guvacine, arecoline, guvacoline, arecaidine, chavibetol, and nicotine. In chewing saliva we found significant increases from baseline for guvacine (BN, BQ), arecoline (all groups), guvacoline (BN), arecaidine (all groups), nicotine (BQ), and chavibetol (BL, BQ) and significant differences between all groups for total areca- specific alkaloids, total tobacco-specific alkaloids and chavibetol. From this pilot study, we propose the following chemical patterns as biomarkers: areca alkaloids for BN use, areca alkaloids and chavibetol for BL use, and areca alkaloids plus chavibetol and tobacco-specific alkaloids for BQ use. PMID:25797484

Blood-based protein biomarkers for diagnosis of Alzheimer disease.

PubMed

Doecke, James D; Laws, Simon M; Faux, Noel G; Wilson, William; Burnham, Samantha C; Lam, Chiou-Peng; Mondal, Alinda; Bedo, Justin; Bush, Ashley I; Brown, Belinda; De Ruyck, Karl; Ellis, Kathryn A; Fowler, Christopher; Gupta, Veer B; Head, Richard; Macaulay, S Lance; Pertile, Kelly; Rowe, Christopher C; Rembach, Alan; Rodrigues, Mark; Rumble, Rebecca; Szoeke, Cassandra; Taddei, Kevin; Taddei, Tania; Trounson, Brett; Ames, David; Masters, Colin L; Martins, Ralph N

2012-10-01

To identify plasma biomarkers for the diagnosis of Alzheimer disease (AD). Baseline plasma screening of 151 multiplexed analytes combined with targeted biomarker and clinical pathology data. General community-based, prospective, longitudinal study of aging. A total of 754 healthy individuals serving as controls and 207 participants with AD from the Australian Imaging Biomarker and Lifestyle study (AIBL) cohort with identified biomarkers that were validated in 58 healthy controls and 112 individuals with AD from the Alzheimer Disease Neuroimaging Initiative (ADNI) cohort. A biomarker panel was identified that included markers significantly increased (cortisol, pancreatic polypeptide, insulinlike growth factor binding protein 2, β(2) microglobulin, vascular cell adhesion molecule 1, carcinoembryonic antigen, matrix metalloprotein 2, CD40, macrophage inflammatory protein 1α, superoxide dismutase, and homocysteine) and decreased (apolipoprotein E, epidermal growth factor receptor, hemoglobin, calcium, zinc, interleukin 17, and albumin) in AD. Cross-validated accuracy measures from the AIBL cohort reached a mean (SD) of 85% (3.0%) for sensitivity and specificity and 93% (3.0) for the area under the receiver operating characteristic curve. A second validation using the ADNI cohort attained accuracy measures of 80% (3.0%) for sensitivity and specificity and 85% (3.0) for area under the receiver operating characteristic curve. This study identified a panel of plasma biomarkers that distinguish individuals with AD from cognitively healthy control subjects with high sensitivity and specificity. Cross-validation within the AIBL cohort and further validation within the ADNI cohort provides strong evidence that the identified biomarkers are important for AD diagnosis.

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

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.

Use of Pathogen-Specific Antibody Biomarkers to Estimate Waterborne Infections in Population-Based Settings.

PubMed

Exum, Natalie G; Pisanic, Nora; Granger, Douglas A; Schwab, Kellogg J; Detrick, Barbara; Kosek, Margaret; Egorov, Andrey I; Griffin, Shannon M; Heaney, Christopher D

2016-09-01

This review discusses the utility of pathogen-specific antibody biomarkers for improving estimates of the population burden of waterborne infections, assessing the fraction of infections that can be prevented by specific water treatments, and understanding transmission routes and the natural history and ecology of disease in different populations (including asymptomatic infection rates). We review recent literature on the application of pathogen-specific antibody response data to estimate incidence and prevalence of acute infections and their utility to assess the contributions of waterborne transmission pathways. Advantages and technical challenges associated with the use of serum versus minimally invasive salivary antibody biomarkers in cross-sectional and prospective surveys are discussed. We highlight recent advances and challenges and outline future directions for research, development, and application of antibody-based and other immunological biomarkers of waterborne infections.

CANcer-specific Evaluation System (CANES): a high-accuracy platform, for preclinical single/multi-biomarker discovery

PubMed Central

Kwon, Min-Seok; Nam, Seungyoon; Lee, Sungyoung; Ahn, Young Zoo; Chang, Hae Ryung; Kim, Yon Hui; Park, Taesung

2017-01-01

The recent creation of enormous, cancer-related “Big Data” public depositories represents a powerful means for understanding tumorigenesis. However, a consistently accurate system for clinically evaluating single/multi-biomarkers remains lacking, and it has been asserted that oft-failed clinical advancement of biomarkers occurs within the very early stages of biomarker assessment. To address these challenges, we developed a clinically testable, web-based tool, CANcer-specific single/multi-biomarker Evaluation System (CANES), to evaluate biomarker effectiveness, across 2,134 whole transcriptome datasets, from 94,147 biological samples (from 18 tumor types). For user-provided single/multi-biomarkers, CANES evaluates the performance of single/multi-biomarker candidates, based on four classification methods, support vector machine, random forest, neural networks, and classification and regression trees. In addition, CANES offers several advantages over earlier analysis tools, including: 1) survival analysis; 2) evaluation of mature miRNAs as markers for user-defined diagnostic or prognostic purposes; and 3) provision of a “pan-cancer” summary view, based on each single marker. We believe that such “landscape” evaluation of single/multi-biomarkers, for diagnostic therapeutic/prognostic decision-making, will be highly valuable for the discovery and “repurposing” of existing biomarkers (and their specific targeted therapies), leading to improved patient therapeutic stratification, a key component of targeted therapy success for the avoidance of therapy resistance. PMID:29050243

Estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers.

PubMed

Li, Shanshan; Ning, Yang

2015-09-01

Covariate-specific time-dependent ROC curves are often used to evaluate the diagnostic accuracy of a biomarker with time-to-event outcomes, when certain covariates have an impact on the test accuracy. In many medical studies, measurements of biomarkers are subject to missingness due to high cost or limitation of technology. This article considers estimation of covariate-specific time-dependent ROC curves in the presence of missing biomarkers. To incorporate the covariate effect, we assume a proportional hazards model for the failure time given the biomarker and the covariates, and a semiparametric location model for the biomarker given the covariates. In the presence of missing biomarkers, we propose a simple weighted estimator for the ROC curves where the weights are inversely proportional to the selection probability. We also propose an augmented weighted estimator which utilizes information from the subjects with missing biomarkers. The augmented weighted estimator enjoys the double-robustness property in the sense that the estimator remains consistent if either the missing data process or the conditional distribution of the missing data given the observed data is correctly specified. We derive the large sample properties of the proposed estimators and evaluate their finite sample performance using numerical studies. The proposed approaches are illustrated using the US Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. © 2015, The International Biometric Society.

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.

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

PubMed Central

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

2014-01-01

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

Identification of sex-specific urinary biomarkers for major depressive disorder by combined application of NMR- and GC-MS-based metabonomics.

PubMed

Zheng, P; Chen, J-J; Zhou, C-J; Zeng, L; Li, K-W; Sun, L; Liu, M-L; Zhu, D; Liang, Z-H; Xie, P

2016-11-15

Women are more vulnerable to major depressive disorder (MDD) than men. However, molecular biomarkers of sex differences are limited. Here we combined gas chromatography-mass spectrometry (GC-MS)- and nuclear magnetic resonance (NMR)-based metabonomics to investigate sex differences of urinary metabolite markers in MDD, and further explore their potential of diagnosing MDD. Consequently, the metabolite signatures of women and men MDD subjects were significantly different from of that in their respective healthy controls (HCs). Twenty seven women and 36 men related differentially expressed metabolites were identified in MDD. Fourteen metabolites were changed in both women and men MDD subjects. Significantly, the women-specific (m-Hydroxyphenylacetate, malonate, glycolate, hypoxanthine, isobutyrate and azelaic acid) and men-specific (tyrosine, N-acetyl-d-glucosamine, N-methylnicotinamide, indoxyl sulfate, citrate and succinate) marker panels were further identified, which could differentiate men and women MDD patients from their respective HCs with higher accuracy than previously reported sex-nonspecific marker panels. Our findings demonstrate that men and women MDD patients have distinct metabonomic signatures and sex-specific biomarkers have promising values in diagnosing MDD.

Comparing human pancreatic cell secretomes by in vitro aptamer selection identifies cyclophilin B as a candidate pancreatic cancer biomarker

PubMed Central

Ray, Partha; Rialon-Guevara, Kristy L.; Veras, Emanuela; Sullenger, Bruce A.; White, Rebekah R.

2012-01-01

Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition–based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer. PMID:22484812

Comparing human pancreatic cell secretomes by in vitro aptamer selection identifies cyclophilin B as a candidate pancreatic cancer biomarker.

PubMed

Ray, Partha; Rialon-Guevara, Kristy L; Veras, Emanuela; Sullenger, Bruce A; White, Rebekah R

2012-05-01

Most cases of pancreatic cancer are not diagnosed until they are no longer curable with surgery. Therefore, it is critical to develop a sensitive, preferably noninvasive, method for detecting the disease at an earlier stage. In order to identify biomarkers for pancreatic cancer, we devised an in vitro positive/negative selection strategy to identify RNA ligands (aptamers) that could detect structural differences between the secretomes of pancreatic cancer and non-cancerous cells. Using this molecular recognition approach, we identified an aptamer (M9-5) that differentially bound conditioned media from cancerous and non-cancerous human pancreatic cell lines. This aptamer further discriminated between the sera of pancreatic cancer patients and healthy volunteers with high sensitivity and specificity. We utilized biochemical purification methods and mass-spectrometric analysis to identify the M9-5 target as cyclophilin B (CypB). This molecular recognition-based strategy simultaneously identified CypB as a serum biomarker and generated a new reagent to recognize it in body fluids. Moreover, this approach should be generalizable to other diseases and complementary to traditional approaches that focus on differences in expression level between samples. Finally, we suggest that the aptamer we identified has the potential to serve as a tool for the early detection of pancreatic cancer.

Use of Pathogen-Specific Antibody Biomarkers to Estimate Waterborne Infections in Population-Based Settings

PubMed Central

Exum, Natalie G.; Pisanic, Nora; Granger, Douglas A.; Schwab, Kellogg J.; Detrick, Barbara; Kosek, Margaret; Egorov, Andrey I.; Griffin, Shannon M.; Heaney, Christopher D.

2016-01-01

Purpose of review This review discusses the utility of pathogen-specific antibody biomarkers for improving estimates of the population burden of waterborne infections, assessing the fraction of infections that can be prevented by specific water treatments, and understanding transmission routes and the natural history and ecology of disease in different populations (including asymptomatic infection rates). Recent findings We review recent literature on the application of pathogen-specific antibody response data to estimate incidence and prevalence of acute infections and their utility to assess the contributions of waterborne transmission pathways. Advantages and technical challenges associated with the use of serum versus minimally invasive salivary antibody biomarkers in cross-sectional and prospective surveys are discussed. Summary We highlight recent advances and challenges and outline future directions for research, development, and application of antibody-based and other immunological biomarkers of waterborne infections. PMID:27352014

Urinary metabolomics analysis identifies key biomarkers of different stages of nonalcoholic fatty liver disease

PubMed Central

Dong, Shu; Zhan, Zong-Ying; Cao, Hong-Yan; Wu, Chao; Bian, Yan-Qin; Li, Jian-Yuan; Cheng, Gen-Hong; Liu, Ping; Sun, Ming-Yu

2017-01-01

AIM To identify a panel of biomarkers that can distinguish between non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH), and explore molecular mechanism involved in the process of developing NASH from NAFLD. METHODS Biomarkers may differ during stages of NAFLD. Urine and blood were obtained from non-diabetic subjects with NAFLD and steatosis, with normal liver function (n = 33), from patients with NASH, with abnormal liver function (n = 45), and from healthy age and sex-matched controls (n = 30). Samples were subjected to metabolomic analysis to identify potential non-invasive biomarkers. Differences in urinary metabolic profiles were analyzed using liquid chromatography tandem mass spectrometry with principal component analysis and partial least squares-discriminate analysis. RESULTS Compared with NAFLD patients, patients with NASH had abnormal liver function and high serum lipid concentrations. Urinary metabonomics found differences in 31 metabolites between these two groups, including differences in nucleic acids and amino acids. Pathway analysis based on overlapping metabolites showed that pathways of energy and amino acid metabolism, as well as the pentose phosphate pathway, were closely associated with pathological processes in NAFLD and NASH. CONCLUSION These findings suggested that a panel of biomarkers could distinguish between NAFLD and NASH, and could help to determine the molecular mechanism involved in the process of developing NASH from NAFLD. Urinary biomarkers may be diagnostic in these patients and could be used to assess responses to therapeutic interventions. PMID:28487615

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.

Composition of betel specific chemicals in saliva during betel chewing for the identification of biomarkers.

PubMed

Franke, Adrian A; Mendez, Ana Joy; Lai, Jennifer F; Arat-Cabading, Celine; Li, Xingnan; Custer, Laurie J

2015-06-01

Betel nut chewing causes cancer in humans, including strong associations with head and neck cancer in Guam. In the search for biomarkers of betel chewing we sought to identify chemicals specific for the 3 most commonly consumed betel preparations in Guam: nut ('BN'), nut + Piper betle leaf ('BL'), and betel quid ('BQ') consisting of nut + lime + tobacco + Piper betle leaf. Chemicals were extracted from the chewing material and saliva of subjects chewing these betel preparations. Saliva analysis involved protein precipitation with acetonitrile, dilution with formic acid followed by LCMS analysis. Baseline and chewing saliva levels were compared using t-tests and differences between groups were compared by ANOVA; p < 0.05 indicated significance. Predominant compounds in chewing material were guvacine, arecoline, guvacoline, arecaidine, chavibetol, and nicotine. In chewing saliva we found significant increases from baseline for guvacine (BN, BQ), arecoline (all groups), guvacoline (BN), arecaidine (all groups), nicotine (BQ), and chavibetol (BL, BQ), and significant differences between all groups for total areca-specific alkaloids, total tobacco-specific alkaloids and chavibetol. From this pilot study, we propose the following chemical patterns as biomarkers: areca alkaloids for BN use, areca alkaloids and chavibetol for BL use, and areca alkaloids plus chavibetol and tobacco-specific alkaloids for BQ use. Copyright © 2015 Elsevier Ltd. All rights reserved.

BluePen Biomarkers LLC: integrated biomarker solutions

PubMed Central

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

2016-01-01

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

Using bacterial biomarkers to identify early indicators of cystic fibrosis pulmonary exacerbation onset

PubMed Central

Rogers, Geraint B; Hoffman, Lucas R; Johnson, Matt W; Mayer-Hamblett, Nicole; Schwarze, Jürgen; Carroll, Mary P; Bruce, Kenneth D

2011-01-01

Acute periods of pulmonary exacerbation are the single most important cause of morbidity in cystic fibrosis patients, and may be associated with a loss of lung function. Intervening prior to the onset of a substantially increased inflammatory response may limit the associated damage to the airways. While a number of biomarker assays based on inflammatory markers have been developed, providing useful and important measures of disease during these periods, such factors are typically only elevated once the process of exacerbation has been initiated. Identifying biomarkers that can predict the onset of pulmonary exacerbation at an early stage would provide an opportunity to intervene before the establishment of a substantial immune response, with major implications for the advancement of cystic fibrosis care. The precise triggers of pulmonary exacerbation remain to be determined; however, the majority of models relate to the activity of microbes present in the patient's lower airways of cystic fibrosis. Advances in diagnostic microbiology now allow for the examination of these complex systems at a level likely to identify factors on which biomarker assays can be based. In this article, we discuss key considerations in the design and testing of assays that could predict pulmonary exacerbations. PMID:21405970

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

PubMed

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

2016-11-01

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

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

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

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

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

Urine protein profiling identified alpha-1-microglobulin and haptoglobin as biomarkers for early diagnosis of acute allograft rejection following kidney transplantation.

PubMed

Stubendorff, Beatrice; Finke, Stephanie; Walter, Martina; Kniemeyer, Olaf; von Eggeling, Ferdinand; Gruschwitz, Torsten; Steiner, Thomas; Ott, Undine; Wolf, Gunter; Wunderlich, Heiko; Junker, Kerstin

2014-12-01

Early diagnosis of acute rejection and effective immunosuppressive therapy lead to improvement in graft survival following kidney transplantation. In this study, we aimed to establish a urinary protein profile suitable to distinguish between patients with rejection and stable graft function and to predict acute rejection based on postoperatively collected urine samples. A further objective was to identify candidate proteins for the use as biomarkers in clinical practice. Urine samples of 116 kidney recipients were included. Rejection was proven by biopsy (n = 58), and stable transplant function was monitored for at least 2 years (n = 58). Postoperative urine samples were collected between 3rd and 10th day following transplantation. Urinary protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Protein identification and validation were performed using multiplex fluorescence 2DE, peptide mass fingerprinting and enzyme-linked immunosorbent assay. A protein profile including four mass peaks differentiated acute rejection from stable transplants at the time point of rejection and at the postoperative state with 73 % sensitivity and 88 % specificity. Alpha-1-microglobulin (A1MG) and Haptoglobin (Hp) were identified as putative rejection biomarkers. Protein levels were significantly higher in postoperative urine from patients with rejection (A1MG 29.13 vs. 22.06 μg/ml, p = 0.001; Hp 628.34 vs. 248.57 ng/ml, p = 0.003). The combination of both proteins enabled the diagnosis of early rejection with 85 % sensitivity and 80 % specificity. Protein profiling using mass spectrometry is suitable for noninvasive detection of rejection-specific changes following kidney transplantation. A specific protein profile enables the prediction of early acute allograft rejection in the immediate postoperative period. A1MG and Hp appear to be reliable rejection biomarkers.

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

The ethnicity-specific association of biomarkers with the angiographic severity of coronary artery disease.

PubMed

Gijsberts, C M; Seneviratna, A; Bank, I E M; den Ruijter, H M; Asselbergs, F W; Agostoni, P; Remijn, J A; Pasterkamp, G; Kiat, H C; Roest, M; Richards, A M; Chan, M Y; de Kleijn, D P V; Hoefer, I E

2016-03-01

Risk factor burden and clinical characteristics of patients with coronary artery disease (CAD) differ among ethnic groups. We related biomarkers to CAD severity in Caucasians, Chinese, Indians and Malays. In the Dutch-Singaporean UNICORN coronary angiography cohort (n = 2033) we compared levels of five cardiovascular biomarkers: N-terminal pro-brain natriuretic peptide (NTproBNP), high-sensitivity C-reactive protein (hsCRP), cystatin C (CysC), myeloperoxidase (MPO) and high-sensitivity troponin I (hsTnI). We assessed ethnicity-specific associations of biomarkers with CAD severity, quantified by the SYNTAX score. Adjusted for baseline differences, NTproBNP levels were significantly higher in Malays than in Chinese and Caucasians (72.1 vs. 34.4 and 41.1 pmol/l, p < 0.001 and p = 0.005, respectively). MPO levels were higher in Caucasians than in Indians (32.8 vs. 27.2 ng/ml, p = 0.026), hsTnI levels were higher in Malays than in Caucasians and Indians (33.3 vs. 16.4 and 17.8 ng/l, p < 0.001 and p = 0.029) and hsTnI levels were higher in Chinese than in Caucasians (23.3 vs. 16.4, p = 0.031). We found modifying effects of ethnicity on the association of biomarkers with SYNTAX score. NTproBNP associated more strongly with the SYNTAX score in Malays than Caucasians (β 0.132 vs. β 0.020 per 100 pmol/l increase in NTproBNP, p = 0.032). For MPO levels the association was stronger in Malays than Caucasians (β 1.146 vs. β 0.016 per 10 ng/ml increase, p = 0.017). Differing biomarker cut-off levels were found for the ethnic groups. When corrected for possible confounders we observe ethnicity-specific differences in biomarker levels. Moreover, biomarkers associated differently with CAD severity, suggesting that ethnicity-specific cut-off values should be considered.

A Systematic Strategy for Screening and Application of Specific Biomarkers in Hepatotoxicity Using Metabolomics Combined With ROC Curves and SVMs.

PubMed

Li, Yubo; Wang, Lei; Ju, Liang; Deng, Haoyue; Zhang, Zhenzhu; Hou, Zhiguo; Xie, Jiabin; Wang, Yuming; Zhang, Yanjun

2016-04-01

Current studies that evaluate toxicity based on metabolomics have primarily focused on the screening of biomarkers while largely neglecting further verification and biomarker applications. For this reason, we used drug-induced hepatotoxicity as an example to establish a systematic strategy for screening specific biomarkers and applied these biomarkers to evaluate whether the drugs have potential hepatotoxicity toxicity. Carbon tetrachloride (5 ml/kg), acetaminophen (1500 mg/kg), and atorvastatin (5 mg/kg) are established as rat hepatotoxicity models. Fifteen common biomarkers were screened by multivariate statistical analysis and integration analysis-based metabolomics data. The receiver operating characteristic curve was used to evaluate the sensitivity and specificity of the biomarkers. We obtained 10 specific biomarker candidates with an area under the curve greater than 0.7. Then, a support vector machine model was established by extracting specific biomarker candidate data from the hepatotoxic drugs and nonhepatotoxic drugs; the accuracy of the model was 94.90% (92.86% sensitivity and 92.59% specificity) and the results demonstrated that those ten biomarkers are specific. 6 drugs were used to predict the hepatotoxicity by the support vector machines model; the prediction results were consistent with the biochemical and histopathological results, demonstrating that the model was reliable. Thus, this support vector machine model can be applied to discriminate the between the hepatic or nonhepatic toxicity of drugs. This approach not only presents a new strategy for screening-specific biomarkers with greater diagnostic significance but also provides a new evaluation pattern for hepatotoxicity, and it will be a highly useful tool in toxicity estimation and disease diagnoses. © The Author 2016. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Discriminant biomarkers of acute respiratory distress syndrome associated to H1N1 influenza identified by metabolomics HPLC-QTOF-MS/MS platform.

PubMed

Ferrarini, Alessia; Righetti, Laura; Martínez, Ma Paz; Fernández-López, Mariano; Mastrangelo, Annalaura; Horcajada, Juan P; Betbesé, Antoni; Esteban, Andrés; Ordóñez, Jordi; Gea, Joaquín; Cabello, Jesús Ruiz; Pellati, Federica; Lorente, José A; Nin, Nicolás; Rupérez, Francisco J

2017-09-01

Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC-MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC-MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty-three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Circulating Organ-Specific MicroRNAs Serve as Biomarkers in Organ-Specific Diseases: Implications for Organ Allo- and Xeno-Transplantation

PubMed Central

Zhou, Ming; Hara, Hidetaka; Dai, Yifan; Mou, Lisha; Cooper, David K. C.; Wu, Changyou; Cai, Zhiming

2016-01-01

Different cell types possess different miRNA expression profiles, and cell/tissue/organ-specific miRNAs (or profiles) indicate different diseases. Circulating miRNA is either actively secreted by living cells or passively released during cell death. Circulating cell/tissue/organ-specific miRNA may serve as a non-invasive biomarker for allo- or xeno-transplantation to monitor organ survival and immune rejection. In this review, we summarize the proof of concept that circulating organ-specific miRNAs serve as non-invasive biomarkers for a wide spectrum of clinical organ-specific manifestations such as liver-related disease, heart-related disease, kidney-related disease, and lung-related disease. Furthermore, we summarize how circulating organ-specific miRNAs may have advantages over conventional methods for monitoring immune rejection in organ transplantation. Finally, we discuss the implications and challenges of applying miRNA to monitor organ survival and immune rejection in allo- or xeno-transplantation. PMID:27490531

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

Identifying disease-related subnetwork connectome biomarkers by sparse hypergraph learning.

PubMed

Zu, Chen; Gao, Yue; Munsell, Brent; Kim, Minjeong; Peng, Ziwen; Cohen, Jessica R; Zhang, Daoqiang; Wu, Guorong

2018-06-14

The functional brain network has gained increased attention in the neuroscience community because of its ability to reveal the underlying architecture of human brain. In general, majority work of functional network connectivity is built based on the correlations between discrete-time-series signals that link only two different brain regions. However, these simple region-to-region connectivity models do not capture complex connectivity patterns between three or more brain regions that form a connectivity subnetwork, or subnetwork for short. To overcome this current limitation, a hypergraph learning-based method is proposed to identify subnetwork differences between two different cohorts. To achieve our goal, a hypergraph is constructed, where each vertex represents a subject and also a hyperedge encodes a subnetwork with similar functional connectivity patterns between different subjects. Unlike previous learning-based methods, our approach is designed to jointly optimize the weights for all hyperedges such that the learned representation is in consensus with the distribution of phenotype data, i.e. clinical labels. In order to suppress the spurious subnetwork biomarkers, we further enforce a sparsity constraint on the hyperedge weights, where a larger hyperedge weight indicates the subnetwork with the capability of identifying the disorder condition. We apply our hypergraph learning-based method to identify subnetwork biomarkers in Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD). A comprehensive quantitative and qualitative analysis is performed, and the results show that our approach can correctly classify ASD and ADHD subjects from normal controls with 87.65 and 65.08% accuracies, respectively.

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 specific metabolites in culture supernatant of Mycobacterium tuberculosis using metabolomics: exploration of potential biomarkers

PubMed Central

Lau, Susanna KP; Lam, Ching-Wan; Curreem, Shirly OT; Lee, Kim-Chung; Lau, Candy CY; Chow, Wang-Ngai; Ngan, Antonio HY; To, Kelvin KW; Chan, Jasper FW; Hung, Ivan FN; Yam, Wing-Cheong; Yuen, Kwok-Yung; Woo, Patrick CY

2015-01-01

Although previous studies have reported the use of metabolomics for Mycobacterium species differentiation, little is known about the potential of extracellular metabolites of Mycobacterium tuberculosis (MTB) as specific biomarkers. Using an optimized ultrahigh performance liquid chromatography–electrospray ionization–quadruple time of flight–mass spectrometry (UHPLC–ESI–Q–TOF–MS) platform, we characterized the extracellular metabolomes of culture supernatant of nine MTB strains and nine non-tuberculous Mycobacterium (NTM) strains (four M. avium complex, one M. bovis Bacillus Calmette–Guérin (BCG), one M. chelonae, one M. fortuitum and two M. kansasii). Principal component analysis readily distinguished the metabolomes between MTB and NTM. Using multivariate and univariate analysis, 24 metabolites with significantly higher levels in MTB were identified. While seven metabolites were identified by tandem mass spectrometry (MS/MS), the other 17 metabolites were unidentified by MS/MS against database matching, suggesting that they may be potentially novel compounds. One metabolite was identified as dexpanthenol, the alcohol analog of pantothenic acid (vitamin B5), which was not known to be produced by bacteria previously. Four metabolites were identified as 1-tuberculosinyladenosine (1-TbAd), a product of the virulence-associated enzyme Rv3378c, and three previously undescribed derivatives of 1-TbAd. Two derivatives differ from 1-TbAd by the ribose group of the nucleoside while the other likely differs by the base. The remaining two metabolites were identified as a tetrapeptide, Val-His-Glu-His, and a monoacylglycerophosphoglycerol, phosphatidylglycerol (PG) (16∶0/0∶0), respectively. Further studies on the chemical structure and biosynthetic pathway of these MTB-specific metabolites would help understand their biological functions. Studies on clinical samples from tuberculosis patients are required to explore for their potential role as diagnostic

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome—a prospective multicentre biomarker study conducted in the Netherlands

PubMed Central

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-01-01

Purpose Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such ‘vulnerable periods’. Participants BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. Methods and analysis We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate ‘vulnerable periods’ during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case–cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Future plans and dissemination Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and

Gene expression profiling combined with bioinformatics analysis identify biomarkers for Parkinson disease.

PubMed

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result.

Gene Expression Profiling Combined with Bioinformatics Analysis Identify Biomarkers for Parkinson Disease

PubMed Central

Diao, Hongyu; Li, Xinxing; Hu, Sheng; Liu, Yunhui

2012-01-01

Parkinson disease (PD) progresses relentlessly and affects approximately 4% of the population aged over 80 years old. It is difficult to diagnose in its early stages. The purpose of our study is to identify molecular biomarkers for PD initiation using a computational bioinformatics analysis of gene expression. We downloaded the gene expression profile of PD from Gene Expression Omnibus and identified differentially coexpressed genes (DCGs) and dysfunctional pathways in PD patients compared to controls. Besides, we built a regulatory network by mapping the DCGs to known regulatory data between transcription factors (TFs) and target genes and calculated the regulatory impact factor of each transcription factor. As the results, a total of 1004 genes associated with PD initiation were identified. Pathway enrichment of these genes suggests that biological processes of protein turnover were impaired in PD. In the regulatory network, HLF, E2F1 and STAT4 were found have altered expression levels in PD patients. The expression levels of other transcription factors, NKX3-1, TAL1, RFX1 and EGR3, were not found altered. However, they regulated differentially expressed genes. In conclusion, we suggest that HLF, E2F1 and STAT4 may be used as molecular biomarkers for PD; however, more work is needed to validate our result. PMID:23284986

Biomarker progressions explain higher variability in stage-specific cognitive decline than baseline values in Alzheimer disease.

PubMed

Dodge, Hiroko H; Zhu, Jian; Harvey, Danielle; Saito, Naomi; Silbert, Lisa C; Kaye, Jeffrey A; Koeppe, Robert A; Albin, Roger L

2014-11-01

It is unknown which commonly used Alzheimer disease (AD) biomarker values-baseline or progression-best predict longitudinal cognitive decline. 526 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). ADNI composite memory and executive scores were the primary outcomes. Individual-specific slope of the longitudinal trajectory of each biomarker was first estimated. These estimates and observed baseline biomarker values were used as predictors of cognitive declines. Variability in cognitive declines explained by baseline biomarker values was compared with variability explained by biomarker progression values. About 40% of variability in memory and executive function declines was explained by ventricular volume progression among mild cognitive impairment patients. A total of 84% of memory and 65% of executive function declines were explained by fluorodeoxyglucose positron emission tomography (FDG-PET) score progression and ventricular volume progression, respectively, among AD patients. For most biomarkers, biomarker progressions explained higher variability in cognitive decline than biomarker baseline values. This has important implications for clinical trials targeted to modify AD biomarkers. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Biomarkers of response and resistance to antiangiogenic therapy

PubMed Central

Jain, Rakesh K.; Duda, Dan G.; Willett, Christopher G.; Sahani, Dushyant V.; Zhu, Andrew X.; Loeffler, Jay S.; Batchelor, Tracy T.; Sorensen, A. Gregory

2011-01-01

No validated biological markers (or biomarkers) currently exist for appropriately selecting patients with cancer for antiangiogenic therapy. Nor are there biomarkers identifying escape pathways that should be targeted after tumors develop resistance to a given antiangiogenic agent. A number of potential systemic, circulating, tissue and imaging biomarkers have emerged from recently completed phase I–III studies. Some of these are measured at baseline (for example VEGF polymorphisms), others are measured during treatment (such as hypertension, MRI-measured Ktrans, circulating angiogenic molecules or collagen IV), and all are mechanistically based. Some of these biomarkers might be pharmacodynamic (for example, increase in circulating VEGF, placental growth factor) while others have potential for predicting clinical benefit or identifying the escape pathways (for example, stromal-cell-derived factor 1α, interleukin-6). Most biomarkers are disease and/or agent specific and all of them need to be validated prospectively. We discuss the current challenges in establishing biomarkers of antiangiogenic therapy, define systemic, circulating, tissue and imaging biomarkers and their advantages and disadvantages, and comment on the future opportunities for validating biomarkers of antiangiogenic therapy. PMID:19483739

All fats are not equal: Considerations when using fatty acid biomarkers in compound-specific stable isotope soil and sediment tracing

NASA Astrophysics Data System (ADS)

Reiffarth, Dominic; Petticrew, Ellen; Owens, Philip; Lobb, David

2013-04-01

The development of cost-effective, convenient and reliable methods for tracing sediment movement will help establish water security. The use of compound-specific stable isotopes (CSSIs) has seen limited, small-scale applications, often in watersheds exhibiting exotic and highly diverse vegetation types. The CSSI tracing technique relies on the detection and transport of naturally occurring organics of plant origin (biomarkers); the biomarkers of interest are produced by flora, deposited on the soil and potentially mobilized along with soil particles. In part, the uniqueness of a biomarker is dependent on its biological pathway. As a plant fixes CO2-its primary source of carbon for building larger organic molecules-discrimination against the heavier 13C isotope leads to an enrichment of 12C. The more complex the biological pathway the biomarker has been subjected to, the more discrimination and unique isotopic signature the biomarker exhibits. Successfully implementing CSSI tracing requires recognizing: (i) factors contributing to the natural variability of the isotopic signature (ii) the suitability of a biomarker and (iii) factors affecting sensitivity during analysis. Considering the relatively low input of suitable organic biomarkers into the soil and degree of signal dispersion, care must be taken to isolate and correctly identify biomarkers, particularly where vegetation types show low variability and where long-range transport occurs. Research is currently being conducted in the Horsefly River (British Columbia, Canada) and South Tobacco Creek (Manitoba, Canada) watersheds; the research seeks to address some of these concerns, particularly in a temperate climate where exotic vegetation types are not common and variability is expected to be low.

SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

PubMed

Li, Jun; Roebuck, Paul; Grünewald, Stefan; Liang, Han

2012-07-01

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.

Pharmacogenetics Biomarkers and Their Specific Role in Neoadjuvant Chemoradiotherapy Treatments: An Exploratory Study on Rectal Cancer Patients

PubMed Central

Dreussi, Eva; Cecchin, Erika; Polesel, Jerry; Canzonieri, Vincenzo; Agostini, Marco; Boso, Caterina; Belluco, Claudio; Buonadonna, Angela; Lonardi, Sara; Bergamo, Francesca; Gagno, Sara; De Mattia, Elena; Pucciarelli, Salvatore; De Paoli, Antonino; Toffoli, Giuseppe

2016-01-01

Background: Pathological complete response (pCR) to neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC) is still ascribed to a minority of patients. A pathway based-approach could highlight the predictive role of germline single nucleotide polymorphisms (SNPs). The primary aim of this study was to define new predictive biomarkers considering treatment specificities. Secondary aim was to determine new potential predictive biomarkers independent from radiotherapy (RT) dosage and cotreatment with oxaliplatin. Methods: Thirty germ-line SNPs in twenty-one genes were selected according to a pathway-based approach. Genetic analyses were performed on 280 LARC patients who underwent fluoropyrimidine-based CRT. The potential predictive role of these SNPs in determining pathological tumor response was tested in Group 1 (94 patients undergoing also oxaliplatin), Group 2 (73 patients treated with high RT dosage), Group 3 (113 patients treated with standard RT dosage), and in the pooled population (280 patients). Results: Nine new predictive biomarkers were identified in the three groups. The most promising one was rs3136228-MSH6 (p = 0.004) arising from Group 3. In the pooled population, rs1801133-MTHFR showed only a trend (p = 0.073). Conclusion: This exploratory study highlighted new potential predictive biomarkers of neoadjuvant CRT and underlined the importance to strictly define treatment peculiarities in pharmacogenetic analyses. PMID:27608007

Pharmacogenomic biomarkers in dermatologic drugs.

PubMed

Greenfield, Nava Pincus; Maibach, Howard

2013-12-01

Biomarkers are becoming increasingly important when considering the efficacy, toxicology, mechanism of action, and risk of adverse events in certain drugs. As availability of bio-genomic information increases, more treatments can be tailored to specific individuals, with a net effect of improved health outcomes. Many dermatology drugs have pharmacogenomic information on their labels. Knowing the risks and benefits associated with genomic biomarkers can aid physicians to make more knowledgeable decisions when identifying treatments for their patients.

Cohort profile of BIOMArCS: the BIOMarker study to identify the Acute risk of a Coronary Syndrome-a prospective multicentre biomarker study conducted in the Netherlands.

PubMed

Oemrawsingh, Rohit M; Akkerhuis, K Martijn; Umans, Victor A; Kietselaer, Bas; Schotborgh, Carl; Ronner, Eelko; Lenderink, Timo; Liem, Anho; Haitsma, David; van der Harst, Pim; Asselbergs, Folkert W; Maas, Arthur; Oude Ophuis, Anton J; Ilmer, Ben; Dijkgraaf, Rene; de Winter, Robbert-Jan; The, S Hong Kie; Wardeh, Alexander J; Hermans, Walter; Cramer, Etienne; van Schaik, Ron H; Hoefer, Imo E; Doevendans, Pieter A; Simoons, Maarten L; Boersma, Eric

2016-12-23

Progression of stable coronary artery disease (CAD) towards acute coronary syndrome (ACS) is a dynamic and heterogeneous process with many intertwined constituents, in which a plaque destabilising sequence could lead to ACS within short time frames. Current CAD risk assessment models, however, are not designed to identify increased vulnerability for the occurrence of coronary events within a precise, short time frame at the individual patient level. The BIOMarker study to identify the Acute risk of a Coronary Syndrome (BIOMArCS) was designed to evaluate whether repeated measurements of multiple biomarkers can predict such 'vulnerable periods'. BIOMArCS is a multicentre, prospective, observational study of 844 patients presenting with ACS, either with or without ST-elevation and at least one additional cardiovascular risk factor. We hypothesised that patterns of circulating biomarkers that reflect the various pathophysiological components of CAD, such as distorted lipid metabolism, vascular inflammation, endothelial dysfunction, increased thrombogenicity and ischaemia, diverge in the days to weeks before a coronary event. Divergent biomarker patterns, identified by serial biomarker measurements during 1-year follow-up might then indicate 'vulnerable periods' during which patients with CAD are at high short-term risk of developing an ACS. Venepuncture was performed every fortnight during the first half-year and monthly thereafter. As prespecified, patient enrolment was terminated after the primary end point of cardiovascular death or hospital admission for non-fatal ACS had occurred in 50 patients. A case-cohort design will explore differences in temporal patterns of circulating biomarkers prior to the repeat ACS. Follow-up and event adjudication have been completed. Prespecified biomarker analyses are currently being performed and dissemination through peer-reviewed publications and conference presentations is expected from the third quarter of 2016. Should

Use of Pathogen-Specific Antibody Biomarkers to Estimate Waterborne Infections in Population-Based Settings

EPA Science Inventory

Purpose of reviewThis review discusses the utility of pathogen-specific antibody biomarkers for improving estimates of the population burden of waterborne infections, assessing the fraction of infections that can be prevented by specific water treatments, and understanding transm...

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

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

Normalization of Patient-Identified Plasma Biomarkers in SMNΔ7 Mice following Postnatal SMN Restoration

PubMed Central

Arnold, W. David; Duque, Sandra; Iyer, Chitra C.; Zaworski, Phillip; McGovern, Vicki L.; Taylor, Shannon J.; von Herrmann, Katharine M.; Kobayashi, Dione T.; Chen, Karen S.; Kolb, Stephen J.; Paushkin, Sergey V.; Burghes, Arthur H. M.

2016-01-01

Introduction and Objective Spinal muscular atrophy (SMA) is an autosomal recessive motor neuron disorder. SMA is caused by homozygous loss of the SMN1 gene and retention of the SMN2 gene resulting in reduced levels of full length SMN protein that are insufficient for motor neuron function. Various treatments that restore levels of SMN are currently in clinical trials and biomarkers are needed to determine the response to treatment. Here, we sought to investigate in SMA mice a set of plasma analytes, previously identified in patients with SMA to correlate with motor function. The goal was to determine whether levels of plasma markers were altered in the SMNΔ7 mouse model of SMA and whether postnatal SMN restoration resulted in normalization of the biomarkers. Methods SMNΔ7 and control mice were treated with antisense oligonucleotides (ASO) targeting ISS-N1 to increase SMN protein from SMN2 or scramble ASO (sham treatment) via intracerebroventricular injection on postnatal day 1 (P1). Brain, spinal cord, quadriceps muscle, and liver were analyzed for SMN protein levels at P12 and P90. Ten plasma biomarkers (a subset of biomarkers in the SMA-MAP panel available for analysis in mice) were analyzed in plasma obtained at P12, P30, and P90. Results Of the eight plasma biomarkers assessed, 5 were significantly changed in sham treated SMNΔ7 mice compared to control mice and were normalized in SMNΔ7 mice treated with ASO. Conclusion This study defines a subset of the SMA-MAP plasma biomarker panel that is abnormal in the most commonly used mouse model of SMA. Furthermore, some of these markers are responsive to postnatal SMN restoration. These findings support continued clinical development of these potential prognostic and pharmacodynamic biomarkers. PMID:27907033

Biomarkers identified for prostate cancer patients through genome-scale screening.

PubMed

Wang, Lei-Yun; Cui, Jia-Jia; Zhu, Tao; Shao, Wei-Hua; Zhao, Yi; Wang, Sai; Zhang, Yu-Peng; Wu, Ji-Chu; Zhang, Le

2017-11-03

Prostate cancer is a threat to men and usually occurs in aged males. Though prostate specific antigen level and Gleason score are utilized for evaluation of the prostate cancer in clinic, the biomarkers for this malignancy have not been widely recognized. Furthermore, the outcome varies across individuals receiving comparable treatment regimens and the underlying mechanism is still unclear. We supposed that genetic feature may be responsible for, at least in part, this process and conducted a two-cohort study to compare the genetic difference in tumorous and normal tissues of prostate cancer patients. The Gene Expression Omnibus dataset were used and a total of 41 genes were found significantly differently expressed in tumor tissues as compared with normal prostate tissues. Four genes (SPOCK3, SPON1, PTN and TGFB3) were selected for further evaluation after Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis and clinical association analysis. MIR1908 was also found decreased expression level in prostate cancer whose target genes were found expressing in both prostate tumor and normal tissues. These results indicated that these potential biomarkers deserve attention in prostate cancer patients and the underlying mechanism should be further investigated.

Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents

DTIC Science & Technology

1997-11-01

status can sometimes be reflected in the infectious potential or drug resistance of those pathogens. For example, in Mycobacterium tuberculosis ... Mycobacterium tuberculosis , its antibiotic resistance and prediction of pathogenicity amongst Mycobacterium spp. based on signature lipid biomarkers ...TITLE AND SUBTITLE Rapid, Potentially Automatable, Method Extract Biomarkers for HPLC/ESI/MS/MS to Detect and Identify BW Agents 5a. CONTRACT NUMBER 5b

Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening

PubMed Central

Phillips, Michael; Bauer, Thomas L.; Cataneo, Renee N.; Lebauer, Cassie; Mundada, Mayur; Pass, Harvey I.; Ramakrishna, Naren; Rom, William N.; Vallières, Eric

2015-01-01

Background Breath volatile organic compounds (VOCs) have been reported as biomarkers of lung cancer, but it is not known if biomarkers identified in one group can identify disease in a separate independent cohort. Also, it is not known if combining breath biomarkers with chest CT has the potential to improve the sensitivity and specificity of lung cancer screening. Methods Model-building phase (unblinded): Breath VOCs were analyzed with gas chromatography mass spectrometry in 82 asymptomatic smokers having screening chest CT, 84 symptomatic high-risk subjects with a tissue diagnosis, 100 without a tissue diagnosis, and 35 healthy subjects. Multiple Monte Carlo simulations identified breath VOC mass ions with greater than random diagnostic accuracy for lung cancer, and these were combined in a multivariate predictive algorithm. Model-testing phase (blinded validation): We analyzed breath VOCs in an independent cohort of similar subjects (n = 70, 51, 75 and 19 respectively). The algorithm predicted discriminant function (DF) values in blinded replicate breath VOC samples analyzed independently at two laboratories (A and B). Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening. Results Unblinded model-building phase. The algorithm identified lung cancer with sensitivity 74.0%, specificity 70.7% and C-statistic 0.78. Blinded model-testing phase: The algorithm identified lung cancer at Laboratory A with sensitivity 68.0%, specificity 68.4%, C-statistic 0.71; and at Laboratory B with sensitivity 70.1%, specificity 68.0%, C-statistic 0.70, with linear correlation between replicates (r = 0.88). In a projected outcome model, breath biomarkers increased the sensitivity, specificity, and positive and negative predictive values of chest CT for lung cancer when the tests were combined in series or parallel. Conclusions Breath VOC mass ion biomarkers identified lung cancer in a

Rationale of the FIBROTARGETS study designed to identify novel biomarkers of myocardial fibrosis

PubMed Central

Ferreira, João Pedro; Machu, Jean‐Loup; Girerd, Nicolas; Jaisser, Frederic; Thum, Thomas; Butler, Javed; González, Arantxa; Diez, Javier; Heymans, Stephane; McDonald, Kenneth; Gyöngyösi, Mariann; Firat, Hueseyin; Rossignol, Patrick; Pizard, Anne

2017-01-01

Abstract Aims Myocardial fibrosis alters the cardiac architecture favouring the development of cardiac dysfunction, including arrhythmias and heart failure. Reducing myocardial fibrosis may improve outcomes through the targeted diagnosis and treatment of emerging fibrotic pathways. The European‐Commission‐funded ‘FIBROTARGETS’ is a multinational academic and industrial consortium with the main aims of (i) characterizing novel key mechanistic pathways involved in the metabolism of fibrillary collagen that may serve as biotargets, (ii) evaluating the potential anti‐fibrotic properties of novel or repurposed molecules interfering with the newly identified biotargets, and (iii) characterizing bioprofiles based on distinct mechanistic phenotypes involving the aforementioned biotargets. These pathways will be explored by performing a systematic and collaborative search for mechanisms and targets of myocardial fibrosis. These mechanisms will then be translated into individualized diagnostic tools and specific therapeutic pharmacological options for heart failure. Methods and results The FIBROTARGETS consortium has merged data from 12 patient cohorts in a common database available to individual consortium partners. The database consists of >12 000 patients with a large spectrum of cardiovascular clinical phenotypes. It integrates community‐based population cohorts, cardiovascular risk cohorts, and heart failure cohorts. Conclusions The FIBROTARGETS biomarker programme is aimed at exploring fibrotic pathways allowing the bioprofiling of patients into specific ‘fibrotic’ phenotypes and identifying new therapeutic targets that will potentially enable the development of novel and tailored anti‐fibrotic therapies for heart failure. PMID:28988439

Post-translationally modified muscle-specific ubiquitin ligases as circulating biomarkers in experimental cancer cachexia

PubMed Central

Mota, Roberto; Rodríguez, Jessica E; Bonetto, Andrea; O’Connell, Thomas M; Asher, Scott A; Parry, Traci L; Lockyer, Pamela; McCudden, Christopher R; Couch, Marion E; Willis, Monte S

2017-01-01

Cancer cachexia is a severe wasting syndrome characterized by the progressive loss of lean body mass and systemic inflammation. Up to 80% of cancer patients experience cachexia, with 20-30% of cancer-related deaths directly linked to cachexia. Despite efforts to identify early cachexia and cancer relapse, clinically useful markers are lacking. Recently, we identified the role of muscle-specific ubiquitin ligases Atrogin-1 (MAFbx, FBXO32) and Muscle Ring Finger-1 in the pathogenesis of cardiac atrophy and hypertrophy. We hypothesized that during cachexia, the Atrogin-1 and MuRF1 ubiquitin ligases are released from muscle and migrate to the circulation where they could be detected and serve as a cachexia biomarker. To test this, we induced cachexia in mice using the C26 adenocarcinoma cells or vehicle (control). Body weight, tumor volume, and food consumption were measured from inoculation until ~day 14 to document cachexia. Western blot analysis of serum identified the presence of Atrogin-1 and MuRF1 with unique post-translational modifications consistent with mono- and poly- ubiquitination of Atrogin-1 and MuRF1 found only in cachectic serum. These findings suggest that both increased Atrogin-1 and the presence of unique post-translational modifications may serve as a surrogate marker specific for cachexia. PMID:28979816

Biomarkers associated with obstructive sleep apnea: A scoping review

PubMed Central

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

2014-01-01

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

In Vivo Fluorescence Lifetime Imaging Monitors Binding of Specific Probes to Cancer Biomarkers

PubMed Central

Ardeshirpour, Yasaman; Chernomordik, Victor; Zielinski, Rafal; Capala, Jacek; Griffiths, Gary; Vasalatiy, Olga; Smirnov, Aleksandr V.; Knutson, Jay R.; Lyakhov, Ilya; Achilefu, Samuel; Gandjbakhche, Amir; Hassan, Moinuddin

2012-01-01

One of the most important factors in choosing a treatment strategy for cancer is characterization of biomarkers in cancer cells. Particularly, recent advances in Monoclonal Antibodies (MAB) as primary-specific drugs targeting tumor receptors show that their efficacy depends strongly on characterization of tumor biomarkers. Assessment of their status in individual patients would facilitate selection of an optimal treatment strategy, and the continuous monitoring of those biomarkers and their binding process to the therapy would provide a means for early evaluation of the efficacy of therapeutic intervention. In this study we have demonstrated for the first time in live animals that the fluorescence lifetime can be used to detect the binding of targeted optical probes to the extracellular receptors on tumor cells in vivo. The rationale was that fluorescence lifetime of a specific probe is sensitive to local environment and/or affinity to other molecules. We attached Near-InfraRed (NIR) fluorescent probes to Human Epidermal Growth Factor 2 (HER2/neu)-specific Affibody molecules and used our time-resolved optical system to compare the fluorescence lifetime of the optical probes that were bound and unbound to tumor cells in live mice. Our results show that the fluorescence lifetime changes in our model system delineate HER2 receptor bound from the unbound probe in vivo. Thus, this method is useful as a specific marker of the receptor binding process, which can open a new paradigm in the “image and treat” concept, especially for early evaluation of the efficacy of the therapy. PMID:22384092

Proteomic analysis of first trimester maternal serum to identify candidate biomarkers potentially predictive of spontaneous preterm birth.

PubMed

D'Silva, Arlene M; Hyett, Jon A; Coorssen, Jens R

2018-04-30

Spontaneous preterm birth (sPTB) remains a major clinical dilemma; current diagnostics and interventions have not reduced the rate of this serious healthcare burden. This study characterizes differential protein profiles and post-translational modifications (PTMs) in first trimester maternal serum using a refined top-down approach coupling two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) to directly compare subsequent term and preterm labour events and identify marked protein differences. 30 proteoforms were found to be significantly increased or decreased in the sPTB group including 9 phosphoproteins and 11 glycoproteins. Changes occurred in proteins associated with immune and defence responses. We identified protein species that are associated with several clinically relevant biological processes, including interrelated biological networks linked to regulation of the complement cascade and coagulation pathways, immune modulation, metabolic processes and cell signalling. The finding of altered proteoforms in maternal serum from pregnancies that delivered preterm suggests these as potential early biomarkers of sPTB and also possible mediators of the disorder. Identifying changes in protein profiles is critical in the study of cell biology, and disease treatment and prevention. Identifying consistent changes in the maternal serum proteome during early pregnancy, including specific protein PTMs (e.g. phosphorylation, glycosylation), is likely to provide better opportunities for prediction, intervention and prevention of preterm birth. This is the first study to examine first trimester maternal serum using a highly refined top-down proteomic analytical approach based on high resolution 2DE coupled with mass spectrometry to directly compare preterm (<37 weeks) and preterm (≥37 weeks) events and identify select protein differences between these conditions. As such, the data present a promising avenue for translation of biomarker discovery to a

Tissue-specific exosome biomarkers for noninvasively monitoring immunologic rejection of transplanted tissue

PubMed Central

Korutla, Laxminarayana; Habertheuer, Andreas; Yu, Ming; Rostami, Susan; Yuan, Chao-Xing; Reddy, Sanjana; Korutla, Varun; Koeberlein, Brigitte; Trofe-Clark, Jennifer; Rickels, Michael R.; Naji, Ali

2017-01-01

In transplantation, there is a critical need for noninvasive biomarker platforms for monitoring immunologic rejection. We hypothesized that transplanted tissues release donor-specific exosomes into recipient circulation and that the quantitation and profiling of donor intra-exosomal cargoes may constitute a biomarker platform for monitoring rejection. Here, we have tested this hypothesis in a human-into-mouse xenogeneic islet transplant model and validated the concept in clinical settings of islet and renal transplantation. In the xenogeneic model, we quantified islet transplant exosomes in recipient blood over long-term follow-up using anti-HLA antibody, which was detectable only in xenoislet recipients of human islets. Transplant islet exosomes were purified using anti-HLA antibody–conjugated beads, and their cargoes contained the islet endocrine hormone markers insulin, glucagon, and somatostatin. Rejection led to a marked decrease in transplant islet exosome signal along with distinct changes in exosomal microRNA and proteomic profiles prior to appearance of hyperglycemia. In the clinical settings of islet and renal transplantation, donor exosomes with respective tissue specificity for islet β cells and renal epithelial cells were reliably characterized in recipient plasma over follow-up periods of up to 5 years. Collectively, these findings demonstrate the biomarker potential of transplant exosome characterization for providing a noninvasive window into the conditional state of transplant tissue. PMID:28319051

Hypersaline Microbial Mat Lipid Biomarkers

NASA Technical Reports Server (NTRS)

Jahnke, Linda L.; Embaye, Tsegereda; Turk, Kendra A.; Summons, Roger E.

2002-01-01

Lipid biomarkers and compound specific isotopic abundances are powerful tools for studies of contemporary microbial ecosystems. Knowledge of the relationship of biomarkers to microbial physiology and community structure creates important links for understanding the nature of early organisms and paleoenvironments. Our recent work has focused on the hypersaline microbial mats in evaporation ponds at Guerrero Negro, Baja California Sur, Mexico. Specific biomarkers for diatoms, cyanobacteria, archaea, green nonsulfur (GNS), sulfate reducing, sulfur oxidizing 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. The delta C-13 of cyanobacterial biomarkers such as the monomethylalkanes and hopanoids are consistent with the delta C-13 measured for bulk mat (-10%o), while a GNS biomarker, wax esters (WXE), suggests a more depleted delta C-13 for GNS biomass (-16%o). This isotopic relationship is different than that observed in mats at Octopus Spring, Yellowstone National Park (YSNP) where GNS appear to grow photoheterotrophic ally. WXE abundance, while relatively low, is most pronounced in an anaerobic zone just below the cyanobacterial layer. The WXE isotope composition at GN suggests that these bacteria utilize photoautotrophy incorporating dissolved inorganic carbon (DIC) via the 3-hydroxypropionate pathway using H2S or H2.

Biomarkers of adverse drug reactions.

PubMed

Carr, Daniel F; Pirmohamed, Munir

2018-02-01

Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue

Biomarker discovery and transcriptomic responses in Daphnia magna exposed to munitions constituents.

PubMed

Garcia-Reyero, Natalia; Poynton, Helen C; Kennedy, Alan J; Guan, Xin; Escalon, B Lynn; Chang, Bonnie; Varshavsky, Julia; Loguinov, Alex V; Vulpe, Chris D; Perkins, Edward J

2009-06-01

Ecotoxicogenomic approaches are emerging as alternative methods in environmental monitoring because they allow insight into pollutant modes of action and help assess the causal agents and potential toxicity beyond the traditional end points of death, growth, and reproduction. Gene expression analysis has shown particular promise for identifying gene expression biomarkers of chemical exposure that can be further used to monitor specific chemical exposures in the environment. We focused on the development of gene expression markers to detect and discriminate between chemical exposures. Using a custom cDNA microarray for Daphnia magna, we identified distinct expression fingerprints in response to exposure at sublethal concentrations of Cu, Zn, Pb, and munitions constituents. Using the results obtained from microarray analysis, we chose a suite of potential biomarkers for each of the specific exposures. The selected potential biomarkers were tested in independent chemical exposures for specificity using quantitative reverse transcription polymerase chain reaction. Six genes were confirmed as differentially regulated bythe selected chemical exposures. Furthermore, each exposure was identified by response of a unique combination (suite) of individual gene expression biomarkers. These results demonstrate the potential for discovery and validation of novel biomarkers of chemical exposures using gene expression analysis, which could have broad applicability in environmental monitoring.

Do classic blood biomarkers of JSLE identify active lupus nephritis? Evidence from the UK JSLE Cohort Study.

PubMed

Smith, E M D; Jorgensen, A L; Beresford, M W

2017-10-01

Background Lupus nephritis (LN) affects up to 80% of juvenile-onset systemic lupus erythematosus (JSLE) patients. The value of commonly available biomarkers, such as anti-dsDNA antibodies, complement (C3/C4), ESR and full blood count parameters in the identification of active LN remains uncertain. Methods Participants from the UK JSLE Cohort Study, aged <16 years at diagnosis, were categorized as having active or inactive LN according to the renal domain of the British Isles Lupus Assessment Group score. Classic biomarkers: anti-dsDNA, C3, C4, ESR, CRP, haemoglobin, total white cells, neutrophils, lymphocytes, platelets and immunoglobulins were assessed for their ability to identify active LN using binary logistic regression modeling, with stepAIC function applied to select a final model. Receiver-operating curve analysis was used to assess diagnostic accuracy. Results A total of 370 patients were recruited; 191 (52%) had active LN and 179 (48%) had inactive LN. Binary logistic regression modeling demonstrated a combination of ESR, C3, white cell count, neutrophils, lymphocytes and IgG to be best for the identification of active LN (area under the curve 0.724). Conclusions At best, combining common classic blood biomarkers of lupus activity using multivariate analysis provides a 'fair' ability to identify active LN. Urine biomarkers were not included in these analyses. These results add to the concern that classic blood biomarkers are limited in monitoring discrete JSLE manifestations such as LN.

The use of plant-specific pyrolysis products as biomarkers in peat deposits

NASA Astrophysics Data System (ADS)

Schellekens, Judith; Bradley, Jonathan A.; Kuyper, Thomas W.; Fraga, Isabel; Pontevedra-Pombal, Xabier; Vidal-Torrado, Pablo; Abbott, Geoffrey D.; Buurman, Peter

2015-09-01

Peatlands are archives of environmental change that can be driven by climate and human activity. Proxies for peatland vegetation composition provide records of (local) environmental conditions that can be linked to both autogenic and allogenic factors. Analytical pyrolysis offers a molecular fingerprint of peat, and thereby a suite of environmental proxies. Here we investigate analytical pyrolysis as a method for biomarker analysis. Pyrolysates of 48 peatland plant species were compared, comprising seventeen lichens, three Sphagnum species, four non-Sphagnum mosses, eleven graminoids (Cyperaceae, Juncaceae, Poaceae), five Ericaceae and six species from other families. This resulted in twenty-one potential biomarkers, including new markers for lichens (3-methoxy-5-methylphenol) and graminoids (ferulic acid methyl ester). The potential of the identified biomarkers to reconstruct vegetation composition is discussed according to their depth records in cores from six peatlands from boreal, temperate and tropical biomes. The occurrence of markers for Sphagnum, graminoids and lichens in all six studied peat deposits indicates that they persist in peat of thousands of years old, in different vegetation types and under different conditions. In order to facilitate the quantification of biomarkers from pyrolysates, typically expressed as proportion (%) of the total quantified pyrolysis products, an internal standard (5-α-androstane) was introduced. Depth records of the Sphagnum marker 4-isopropenylphenol from the upper 3 m of a Sphagnum-dominated peat, from samples analysed with and without internal standard showed a strong positive correlation (r2 = 0.72, P < 0.0005, n = 12). This indicates that application of an internal standard is a reliable method to assess biomarker depth records, which enormously facilitates the use of analytical pyrolysis in biomarker research by avoiding quantification of a high number of products.

Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis

DTIC Science & Technology

2017-10-13

AWARD NUMBER: W81XWH-15-2-0032 TITLE: Identifying Subgroups of Tinnitus Using Novel Resting State fMRI Biomarkers and Cluster Analysis...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-15-2-0032 5b. GRANT NUMBER Identifying Subgroups of Tinnitus Using Novel Resting State fMRI...Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The subject of the project is FY14 PRMRP Topic Area – Tinnitus . The broad goal is

SWATH-based proteomics identified carbonic anhydrase 2 as a potential diagnosis biomarker for nasopharyngeal carcinoma

PubMed Central

Luo, Yanzhang; Mok, Tin Seak; Lin, Xiuxian; Zhang, Wanling; Cui, Yizhi; Guo, Jiahui; Chen, Xing; Zhang, Tao; Wang, Tong

2017-01-01

Nasopharyngeal carcinoma (NPC) is a serious threat to public health, and the biomarker discovery is of urgent needs. The data-independent mode (DIA) based sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry (MS) has been proved to be precise in protein quantitation and efficient for cancer biomarker researches. In this study, we performed the first SWATH-MS analysis comparing the NPC and normal tissues. Spike-in stable isotope labeling by amino acids in cell culture (super-SILAC) MS was used as a shotgun reference. We identified and quantified 1414 proteins across all SWATH-MS analyses. We found that SWATH-MS had a unique feature to preferentially detect proteins with smaller molecular weights than either super-SILAC MS or human proteome background. With SWATH-MS, 29 significant differentially express proteins (DEPs) were identified. Among them, carbonic anhydrase 2 (CA2) was selected for further validation per novelty, MS quality and other supporting rationale. With the tissue microarray analysis, we found that CA2 had an AUC of 0.94 in differentiating NPC from normal tissue samples. In conclusion, SWATH-MS has unique features in proteome analysis, and it leads to the identification of CA2 as a potentially new diagnostic biomarker for NPC. PMID:28117408

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.

Biomarkers of nanomaterial exposure and effect: current status

NASA Astrophysics Data System (ADS)

Iavicoli, Ivo; Leso, Veruscka; Manno, Maurizio; Schulte, Paul A.

2014-03-01

Recent advances in nanotechnology have induced a widespread production and application of nanomaterials. As a consequence, an increasing number of workers are expected to undergo exposure to these xenobiotics, while the possible hazards to their health remain not being completely understood. In this context, biological monitoring may play a key role not only to identify potential hazards from and to evaluate occupational exposure to nanomaterials, but also to detect their early biological effects to better assess and manage risks of exposure in respect of the health of workers. Therefore, the aim of this review is to provide a critical evaluation of potential biomarkers of nanomaterial exposure and effect investigated in human and animal studies. Concerning exposure biomarkers, internal dose of metallic or metal oxide nanoparticle exposure may be assessed measuring the elemental metallic content in blood or urine or other biological materials, whereas specific molecules may be carefully evaluated in target tissues as possible biomarkers of biologically effective dose. Oxidative stress biomarkers, such as 8-hydroxy-deoxy-guanosine, genotoxicity biomarkers, and inflammatory response indicators may also be useful, although not specific, as biomarkers of nanomaterial early adverse health effects. Finally, potential biomarkers from "omic" technologies appear to be quite innovative and greatly relevant, although mechanistic, ethical, and practical issues should all be resolved before their routine application in occupational settings could be implemented. Although all these findings are interesting, they point out the need for further research to identify and possibly validate sensitive and specific biomarkers of exposure and effect, suitable for future use in occupational biomonitoring programs. A valuable contribution may derive from the studies investigating the biological behavior of nanomaterials and the factors influencing their toxicokinetics and reactivity. In

Biomarker Analysis of Samples Visually Identified as Microbial in the Eocene Green River Formation: An Analogue for Mars.

PubMed

Olcott Marshall, Alison; Cestari, Nicholas A

2015-09-01

One of the major exploration targets for current and future Mars missions are lithofacies suggestive of biotic activity. Although such lithofacies are not confirmation of biotic activity, they provide a way to identify samples for further analyses. To test the efficacy of this approach, we identified carbonate samples from the Eocene Green River Formation as "microbial" or "non-microbial" based on the macroscale morphology of their laminations. These samples were then crushed and analyzed by gas chromatography/mass spectroscopy (GC/MS) to determine their lipid biomarker composition. GC/MS analysis revealed that carbonates visually identified as "microbial" contained a higher concentration of more diverse biomarkers than those identified as "non-microbial," suggesting that this could be a viable detection strategy for selecting samples for further analysis or caching on Mars.

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.

A novel workflow combining plaque imaging, plaque and plasma proteomics identifies biomarkers of human coronary atherosclerotic plaque disruption.

PubMed

Lee, Regent; Fischer, Roman; Charles, Philip D; Adlam, David; Valli, Alessandro; Di Gleria, Katalin; Kharbanda, Rajesh K; Choudhury, Robin P; Antoniades, Charalambos; Kessler, Benedikt M; Channon, Keith M

2017-01-01

Atherosclerotic plaque rupture is the culprit event which underpins most acute vascular syndromes such as acute myocardial infarction. Novel biomarkers of plaque rupture could improve biological understanding and clinical management of patients presenting with possible acute vascular syndromes but such biomarker(s) remain elusive. Investigation of biomarkers in the context of de novo plaque rupture in humans is confounded by the inability to attribute the plaque rupture as the source of biomarker release, as plaque ruptures are typically associated with prompt down-stream events of myocardial necrosis and systemic inflammation. We developed a novel approach to identify potential biomarkers of plaque rupture by integrating plaque imaging, using optical coherence tomography, with both plaque and plasma proteomic analysis in a human model of angioplasty-induced plaque disruption. We compared two pairs of coronary plaque debris, captured by a FilterWire Device, and their corresponding control samples and found matrix metalloproteinase 9 (MMP9) to be significantly enriched in plaque. Plaque contents, as defined by optical coherence tomography, affect the systemic changes of MMP9. Disruption of lipid-rich plaque led to prompt elevation of plasma MMP9, whereas disruption of non-lipid-rich plaque resulted in delayed elevation of plasma MMP9. Systemic MMP9 elevation is independent of the associated myocardial necrosis and systemic inflammation (measured by Troponin I and C-reactive protein, respectively). This information guided the selection of a subset of subjects of for further label free proteomics analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). We discovered five novel, plaque-enriched proteins (lipopolysaccharide binding protein, Annexin A5, eukaryotic translocation initiation factor, syntaxin 11, cytochrome B5 reductase 3) to be significantly elevated in systemic circulation at 5 min after plaque disruption. This novel approach for biomarker

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

Characterization of Foodborne Strains of Staphylococcus aureus by Shotgun Proteomics: Functional Networks, Virulence Factors and Species-Specific Peptide Biomarkers

PubMed Central

Carrera, Mónica; Böhme, Karola; Gallardo, José M.; Barros-Velázquez, Jorge; Cañas, Benito; Calo-Mata, Pilar

2017-01-01

In the present work, we applied a shotgun proteomics approach for the fast and easy characterization of 20 different foodborne strains of Staphylococcus aureus (S. aureus), one of the most recognized foodborne pathogenic bacteria. A total of 644 non-redundant proteins were identified and analyzed via an easy and rapid protein sample preparation procedure. The results allowed the differentiation of several proteome datasets from the different strains (common, accessory, and unique datasets), which were used to determine relevant functional pathways and differentiate the strains into different Euclidean hierarchical clusters. Moreover, a predicted protein-protein interaction network of the foodborne S. aureus strains was created. The whole confidence network contains 77 nodes and 769 interactions. Most of the identified proteins were surface-associated proteins that were related to pathways and networks of energy, lipid metabolism and virulence. Twenty-seven virulence factors were identified, and most of them corresponded to autolysins, N-acetylmuramoyl-L-alanine amidases, phenol-soluble modulins, extracellular fibrinogen-binding proteins and virulence factor EsxA. Potential species-specific peptide biomarkers were screened. Twenty-one species-specific peptide biomarkers, belonging to eight different proteins (nickel-ABC transporter, N-acetylmuramoyl-L-alanine amidase, autolysin, clumping factor A, gram-positive signal peptide YSIRK, cysteine protease/staphopain, transcriptional regulator MarR, and transcriptional regulator Sar-A), were proposed to identify S. aureus. These results constitute the first major dataset of peptides and proteins of foodborne S. aureus strains. This repository may be useful for further studies, for the development of new therapeutic treatments for S. aureus food intoxications and for microbial source-tracking in foodstuffs. PMID:29312172

Determination of thermal stability of specific biomarker lipids of the freshwater fern Azolla through hydrous pyrolysis

NASA Astrophysics Data System (ADS)

Sap, Merel; Speelman, Eveline N.; Lewan, Michael D.; Sinninghe Damsté, Jaap S.; Reichart, Gert-Jan

2010-05-01

Enormous blooms of the free-floating freshwater fern Azolla occurred within the Arctic Basin during an extended period of ~1.2 Ma during the middle Eocene (Brinkhuis et al. 2006; Speelman et al., GB, 2009). The sustained growth of Azolla, currently ranking among the fastest growing plants on Earth, in a major anoxic basin may have substantially contributed to decreasing atmospheric CO2 levels by burial of Azolla-derived organic matter. Speelman et al. (OG, 2009) reported biomarkers for Azolla (1,w20 C32 - C36 diols, structurally related C29 ω20,ω21 diols, C29 1,20,21 triols, C29 dihydroxy fatty acids as well as a series of wax esters containing these mono- and dihydroxy lipids), which can be used to reconstruct palaeo-environmental conditions. Here we assess the thermal stability of these compounds, to extend their biomarker potential. We specifically focused on the thermal stability of the Azolla biomarkers using hydrous pyrolysis in order to determine which burial conditions allow reconstruction of past occurrences of Azolla. In addition, hydrous pyrolysis was also performed on samples from the Eocene Arctic Ocean (ACEX core), to test if and how the biomarkers change under higher temperatures and pressures in situ. During hydrous pyrolysis, the biomass was heated under high pressure at temperatures ranging between 220 and 365°C for 72 hours. Four experiments were also run using different durations to explore the kinetics of biomarker degradation at specific temperatures. First results indicate that the Azolla specific diols are still present at 220°C, while the corresponding wax esters are already absent. At 300°C all Azolla specific biomarkers are destroyed. More specific determination of the different biomarkers' stability and kinetics would potentially allow the reconstruction of the temperature and pressure history of Azolla deposits. Literature: • Brinkhuis, H., Schouten, S., Collinson, M. E., Sluijs, A., Sinninghe Damste, J. S., Dickens, G. R., Huber

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.

Disease-specific dynamic biomarkers selected by integrating inflammatory mediators with clinical informatics in ARDS patients with severe pneumonia.

PubMed

Chen, Chengshui; Shi, Lin; Li, Yuping; Wang, Xiangdong; Yang, Shuanying

2016-06-01

Acute respiratory distress syndrome (ARDS) is a heterogeneous syndrome that occurs as a result of various risk factors, including either direct or indirect lung injury, and systemic inflammation triggered also by severe pneumonia (SP). SP-ARDS-associated morbidity and mortality remains high also due to the lack of disease-specific biomarkers. The present study aimed at identifying disease-specific biomarkers in SP or SP-ARDS by integrating proteomic profiles of inflammatory mediators with clinical informatics. Plasma was sampled from the healthy as controls or patients with SP infected with bacteria or infection-associated SP-ARDS on the day of admission, day 3, and day 7. About 15 or 52 cytokines showed significant difference between SP and SP-ARDS patients with controls or 13 between SP-ARDS with SP alone and controls, including bone morphogenetic protein-15 (BMP-15), chemokine (C-X-C motif) ligand 16 (CXCL16), chemokine (C-X-C motif) receptor 3 (CXCR3), interleukin-6 (IL-6), protein NOV homolog (NOV/CCN3), glypican 3, insulin-like growth factor binding protein 4 (IGFBP-4), IL-5, IL-5 R alpha, IL-22 BP, leptin, MIP-1d, and orexin B with a significant correlation with Digital Evaluation Score System (DESS) scores. ARDS patients with overexpressed IL-6, CXCL16, or IGFBP-4 had significantly longer hospital stay and higher incidence of secondary infection. We also found higher levels of those mediators were associated with poor survival rates in patients with lung cancer and involved in the process of the epithelial mesenchymal transition of alveolar epithelial cells. Our preliminary study suggested that integration of proteomic profiles with clinical informatics as part of clinical bioinformatics is important to validate and optimize disease-specific and disease-staged biomarkers.

Utility of salivary biomarkers for demonstrating acute myocardial infarction.

PubMed

Miller, C S; Foley, J D; Floriano, P N; Christodoulides, N; Ebersole, J L; Campbell, C L; Bailey, A L; Rose, B G; Kinane, D F; Novak, M J; McDevitt, J T; Ding, X; Kryscio, R J

2014-07-01

The comparative utility of serum and saliva as diagnostic fluids for identifying biomarkers of acute myocardial infarction (AMI) was investigated. The goal was to determine if salivary biomarkers could facilitate a screening diagnosis of AMI, especially in cases of non-ST elevation MI (NSTEMI), since these cases are not readily identified by electrocardiogram (ECG). Serum and unstimulated whole saliva (UWS) collected from 92 AMI patients within 48 hours of chest pain onset and 105 asymptomatic healthy control individuals were assayed for 13 proteins relevant to cardiovascular disease, by Beadlyte technology (Luminex(®)) and enzyme immunoassays. Data were analyzed with concentration cut-points, ECG findings, logistic regression (LR) (adjusted for matching for age, gender, race, smoking, number of teeth, and oral health status), and classification and regression tree (CART) analysis. A sensitivity analysis was conducted by repetition of the CART analysis in 58 cases and 58 controls, each matched by age and gender. Serum biomarkers demonstrated AMI sensitivity and specificity superior to that of saliva, as determined by LR and CART. The predominant discriminators in serum by LR were troponin I (TnI), B-type natriuretic peptide (BNP), and creatine kinase-MB (CK-MB), and TnI and BNP by CART. In saliva, LR identified C-reactive protein (CRP) as the biomarker most predictive of AMI. A combination of smoking tobacco, UWS CRP, CK-MB, sCD40 ligand, gender, and number of teeth identified AMI in the CART decision trees. When ECG findings, salivary biomarkers, and confounders were included, AMI was predicted with 80.0% sensitivity and 100% specificity. These analyses support the potential utility of salivary biomarker measurements used with ECG for the identification of AMI. Thus, saliva-based tests may provide additional diagnostic screening information in the clinical course for patients suspected of having an AMI. © International & American Associations for Dental Research.

Biomarkers in psoriasis and psoriatic arthritis.

PubMed

Villanova, Federica; Di Meglio, Paola; Nestle, Frank O

2013-04-01

Psoriasis is a common immune-mediated disease of the skin, which associates in 20-30% of patients with psoriatic arthritis (PsA). The immunopathogenesis of both conditions is not fully understood as it is the result of a complex interaction between genetic, environmental and immunological factors. At present there is no cure for psoriasis and there are no specific markers that can accurately predict disease progression and therapeutic response. Therefore, biomarkers for disease prognosis and response to treatment are urgently needed to help clinicians with objective indications to improve patient management and outcomes. Although many efforts have been made to identify psoriasis/PsA biomarkers none of them has yet been translated into routine clinical practice. In this review we summarise the different classes of possible biomarkers explored in psoriasis and PsA so far and discuss novel strategies for biomarker discovery.

Global microRNA expression profiling of microdissected tissues identifies miR-135b as a novel biomarker for pancreatic ductal adenocarcinoma.

PubMed

Munding, Johanna B; Adai, Alex T; Maghnouj, Abdelouahid; Urbanik, Aleksandra; Zöllner, Hannah; Liffers, Sven T; Chromik, Ansgar M; Uhl, Waldemar; Szafranska-Schwarzbach, Anna E; Tannapfel, Andrea; Hahn, Stephan A

2012-07-15

Pancreatic ductal adenocarcinoma (PDAC) is known for its poor prognosis resulting from being diagnosed at an advanced stage. Accurate early diagnosis and new therapeutic modalities are therefore urgently needed. MicroRNAs (miRNAs), considered a new class of biomarkers and therapeutic targets, may be able to fulfill those needs. Combining tissue microdissection with global miRNA array analyses, cell type-specific miRNA expression profiles were generated for normal pancreatic ductal cells, acinar cells, PDAC cells derived from xenografts and also from macrodissected chronic pancreatitis (CP) tissues. We identified 78 miRNAs differentially expressed between ND and PDAC cells providing new insights into the miRNA-driven pathophysiological mechanisms involved in PDAC development. Having filtered miRNAs which are upregulated in the three pairwise comparisons of PDAC vs. ND, PDAC vs. AZ and PDAC vs. CP, we identified 15 miRNA biomarker candidates including miR-135b. Using relative qRT-PCR to measure miR-135b normalized to miR-24 in 75 FFPE specimens (42 PDAC and 33 CP) covering a broad range of tumor content, we discriminated CP from PDAC with a sensitivity and specificity of 92.9% [95% CI=(80.5, 98.5)] and 93.4% [95% CI=(79.8, 99.3)], respectively. Furthermore, the area under the curve (AUC) value reached of 0.97 was accompanied by positive and negative predictive values of 95% and 91%, respectively. In conclusion, we report pancreatic cell-specific global miRNA profiles, which offer new candidate miRNAs to be exploited for functional studies in PDAC. Furthermore, we provide evidence that miRNAs are well-suited analytes for development of sensitive and specific aid-in-diagnosis tests for PDAC. Copyright © 2011 UICC.

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

PubMed Central

Sandquist, Mary; Wong, Hector R

2015-01-01

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

Proteoglycan 4 is a diagnostic biomarker for COPD.

PubMed

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

2015-01-01

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

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.

A review of biomarkers for predicting clinical reactivity to foods with a focus on specific immunoglobulin E antibodies.

PubMed

Sato, Sakura; Yanagida, Noriyuki; Ohtani, Kiyotaka; Koike, Yumi; Ebisawa, Motohiro

2015-06-01

The purpose of this study is to assess the latest studies that focus on specific immunoglobulin (Ig)E antibodies for predicting clinical reactivity to foods. Persistent hen's egg and cow's milk allergy patients have higher antigen-specific IgE levels at all ages than those who have outgrown these allergies. Recent studies on the natural histories of hen's egg and cow's milk allergies suggested that baseline antigen-specific IgEs are the most important predictors of tolerance. Oral immunotherapy (OIT), which is a novel therapeutic approach for food allergy, requires biomarkers for predicting outcomes after therapy. Several studies indicate that the initial antigen-specific IgE level may be a useful biomarker for the prognosis of OIT. Recently, component-resolved diagnostics (CRD) has been used for food allergy diagnosis. Current studies have suggested that Ara h 2, omega-5 gliadin and ovomucoid are good diagnostic markers for peanut, wheat and egg allergies, respectively. Antigen-specific IgE can be a useful biomarker for predicting clinical reactivity to food allergies. Monitoring hen's egg and cow's milk-specific IgE is useful for predicting prognosis, and baseline specific IgE levels may be associated with the outcome of OIT. The use of CRD provides us with a better tool for diagnosing food allergy.

Application of “omics” to Prion Biomarker Discovery

PubMed Central

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

2010-01-01

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

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

Comprehensive and integrative analysis identifies microRNA-106 as a novel non-invasive biomarker for detection of gastric cancer.

PubMed

Peng, Qiliang; Shen, Yi; Lin, Kaisu; Zou, Li; Shen, Yuntian; Zhu, Yaqun

2018-05-15

Recently, accumulating evidences have revealed that microRNA-106 (miR-106) may serve as a non-invasive and cost-effective biomarker in gastric cancer (GC) detection. However, inconsistent results have prevented its application to clinical practice. As a result of this, a comprehensive meta-analysis was conducted to evaluate the diagnostic performance of miR-106 alone and miR-106-related combination markers for GC detection. Meanwhile, an integrative bioinformatics analysis was performed to explore the function of miR-106 at the systems biology level. The results in our work showed that sensitivity of 0.71 (95% CI 0.65-0.76) and specificity of 0.82 (0.72-0.88), with the under area AUC (area under the curve) value of 0.80 (0.76-0.83) for miR-106 alone. Prospectively, miR-106-related combination markers improved the combined sensitivity, specificity and AUC, describing the discriminatory ability of 0.78 (0.65-0.87), 0.83 (0.77-0.89) and 0.88 (0.85-0.90) in the present analysis. Furthermore, targets of miR-106 were obtained and enriched by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, revealing their associations with the occurrence and development of GC. Hub genes and significant modules were identified from the protein-protein interaction networks constructed by miR-106 targets and found closely associated with the initiation and progression of GC again. Our comprehensive and integrative analysis revealed that miR-106 may be suitable as a diagnostic biomarker for GC while microRNA combination biomarkers may provide a new alternative for clinical application. However, it is necessary to conduct large-scale population-based studies and biological experiments to further investigate the diagnostic value of miR-106.

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

Identifying Group-Specific Sequences for Microbial Communities Using Long k-mer Sequence Signatures

PubMed Central

Wang, Ying; Fu, Lei; Ren, Jie; Yu, Zhaoxia; Chen, Ting; Sun, Fengzhu

2018-01-01

Comparing metagenomic samples is crucial for understanding microbial communities. For different groups of microbial communities, such as human gut metagenomic samples from patients with a certain disease and healthy controls, identifying group-specific sequences offers essential information for potential biomarker discovery. A sequence that is present, or rich, in one group, but absent, or scarce, in another group is considered “group-specific” in our study. Our main purpose is to discover group-specific sequence regions between control and case groups as disease-associated markers. We developed a long k-mer (k ≥ 30 bps)-based computational pipeline to detect group-specific sequences at strain resolution free from reference sequences, sequence alignments, and metagenome-wide de novo assembly. We called our method MetaGO: Group-specific oligonucleotide analysis for metagenomic samples. An open-source pipeline on Apache Spark was developed with parallel computing. We applied MetaGO to one simulated and three real metagenomic datasets to evaluate the discriminative capability of identified group-specific markers. In the simulated dataset, 99.11% of group-specific logical 40-mers covered 98.89% disease-specific regions from the disease-associated strain. In addition, 97.90% of group-specific numerical 40-mers covered 99.61 and 96.39% of differentially abundant genome and regions between two groups, respectively. For a large-scale metagenomic liver cirrhosis (LC)-associated dataset, we identified 37,647 group-specific 40-mer features. Any one of the features can predict disease status of the training samples with the average of sensitivity and specificity higher than 0.8. The random forests classification using the top 10 group-specific features yielded a higher AUC (from ∼0.8 to ∼0.9) than that of previous studies. All group-specific 40-mers were present in LC patients, but not healthy controls. All the assembled 11 LC-specific sequences can be mapped to two

[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.

PD-1 identifies the patient-specific CD8+ tumor-reactive repertoire infiltrating human tumors

PubMed Central

Gros, Alena; Robbins, Paul F.; Yao, Xin; Li, Yong F.; Turcotte, Simon; Tran, Eric; Wunderlich, John R.; Mixon, Arnold; Farid, Shawn; Dudley, Mark E.; Hanada, Ken-ichi; Almeida, Jorge R.; Darko, Sam; Douek, Daniel C.; Yang, James C.; Rosenberg, Steven A.

2014-01-01

Adoptive transfer of tumor-infiltrating lymphocytes (TILs) can mediate regression of metastatic melanoma; however, TILs are a heterogeneous population, and there are no effective markers to specifically identify and select the repertoire of tumor-reactive and mutation-specific CD8+ lymphocytes. The lack of biomarkers limits the ability to study these cells and develop strategies to enhance clinical efficacy and extend this therapy to other malignancies. Here, we evaluated unique phenotypic traits of CD8+ TILs and TCR β chain (TCRβ) clonotypic frequency in melanoma tumors to identify patient-specific repertoires of tumor-reactive CD8+ lymphocytes. In all 6 tumors studied, expression of the inhibitory receptors programmed cell death 1 (PD-1; also known as CD279), lymphocyte-activation gene 3 (LAG-3; also known as CD223), and T cell immunoglobulin and mucin domain 3 (TIM-3) on CD8+ TILs identified the autologous tumor-reactive repertoire, including mutated neoantigen-specific CD8+ lymphocytes, whereas only a fraction of the tumor-reactive population expressed the costimulatory receptor 4-1BB (also known as CD137). TCRβ deep sequencing revealed oligoclonal expansion of specific TCRβ clonotypes in CD8+PD-1+ compared with CD8+PD-1– TIL populations. Furthermore, the most highly expanded TCRβ clonotypes in the CD8+ and the CD8+PD-1+ populations recognized the autologous tumor and included clonotypes targeting mutated antigens. Thus, in addition to the well-documented negative regulatory role of PD-1 in T cells, our findings demonstrate that PD-1 expression on CD8+ TILs also accurately identifies the repertoire of clonally expanded tumor-reactive cells and reveal a dual importance of PD-1 expression in the tumor microenvironment. PMID:24667641

Is modern climate variability reflected in compund specific hydrogen isotope ratios of sedimentary biomarkers?

NASA Astrophysics Data System (ADS)

Sachse, D.; Radke, J.; Gleixner, G.

2003-04-01

Compound specific hydrogen isotope ratios are emerging as a new palaeoclimatic and palaeohydrological proxy. First reconstructions of palaeoclimate using D/H ratios from n-alkanes are available (Andersen et al. 2001, Sauer et al. 2001, Sachse et al. 2003). However, a systematic approach comparing recent sedimentary biomarkers with climate data is still lacking. We are establishing an ecosystem study of small, ground water fed lakes with known limnology. Nearly all lakes are close to a long-term climate-monitoring site (CARBOEUROPE flux tower site, IAEA precipitation monitoring) delivering ecophysiological and climatic data as temperature, precipitation, evapotranspiration etc. Water, primary biomass, plant, soil and sediment were sampled from lakes and the surrounding ecosystem along a climatic and isotopic gradient in meteoric waters from northern Finland (deltaD: -130 permil vs. VSMOW) to southern Italy (deltaD: -30 permil vs. VSMOW, IAEA 2001). Biomarkers were extracted from the samples to test if climatic variability is reflected in their D/H ratios. First results of the factors influencing the hydrogen isotope composition of sedimentary biomarkers and their use as palaeoclimatic and palaeohydrological proxy will be presented. Andersen N, Paul HA, Bernasconi SM, McKenzie JA, Behrens A, Schaeffer P, Albrecht P (2001) Large and rapid climate variability during the Messinian salinity crisis: Evidence from deuterium concentrations of individual biomarkers. Geology 29:799-802 IAEA (2001) GNIP Maps and Animations. International Atomic Energy Agency, Vienna. Accessible at http://isohis.iaea.org Sachse D, Radke J, Gaupp R, Schwark L, Lüniger G, Gleixner G (2003) Reconstruction of palaeohydrological conditions in a lagoon during the 2nd Zechstein cycle through simultaneous use of deltaD values of individual n-alkanes and delta18O and delta13C values of carbonates. International Journal of Earth Sciences, submitted Sauer PE, Eglington TI, Hayes JM, Schimmelman A

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

PubMed Central

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

2014-01-01

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

MD-miniRNA could be a more accurate biomarker for prostate cancer screening compared with serum prostate-specific antigen level.

PubMed

Xue, Dong; Zhou, Cui-Xing; Shi, Yun-Bo; Lu, Hao; He, Xiao-Zhou

2015-05-01

Prostate cancer and prostatic hyperplasia detection remains a great challenge, lacking of effective non-invasive and specific diagnostic biomarkers. In the current study, we aimed to identify the relative expression of plasma MD-miniRNA and its diagnostic performance in differentiating prostate cancer and prostatic hyperplasia patients from healthy controls, compared with serum prostate-specific antigen (PSA) level. All of the clinical participants (63 prostate cancer patients, 32 prostatic hyperplasia patients, and 50 healthy controls) were obtained from the Third Affiliated Hospital of Suzhou University in China between January 2013 and April 2014. Clinical characteristics were well matched. Plasma samples were extracted to test the relative expression of MD-miniRNA using the method of qRT-PCR. SPSS 22.0 statistical software package was used to analyze the data and GraphPad Prism 6.0 was used to generate the graphs. Relativity expression of plasma MD-miniRNA was significantly upregulated in prostate cancer, compared with prostatic hyperplasia patients and healthy controls. Serum PSA level revealed similar differences among these groups. MD-miniRNA presented a relatively high diagnostic accuracy with AUC of 0.86 (95 % CI 0.80-0.93) in differentiating prostate cancer patients from healthy controls. Simultaneously, MD-miniRNA was able to discriminate prostate cancer patients from prostatic hyperplasia controls with AUC of 0.79 (95 % CI 0.70-0.88). In addition, MD-miniRNA displayed a better diagnostic performance than PSA level. However, the panel of these two biomarkers revealed the best diagnostic performance, compared with either single biomarker. Results of this study showed that plasma MD-miniRNA could serve as a promising and noninvasive biomarker for diagnosing prostate cancer. Further large-scale studies are needed to confirm its clinical diagnosis accuracy.

Proteomic Analysis of Saliva Identifies Potential Biomarkers for Orthodontic Tooth Movement

PubMed Central

Ellias, Mohd Faiz; Zainal Ariffin, Shahrul Hisham; Karsani, Saiful Anuar; Abdul Rahman, Mariati; Senafi, Shahidan; Megat Abdul Wahab, Rohaya

2012-01-01

Orthodontic treatment has been shown to induce inflammation, followed by bone remodelling in the periodontium. These processes trigger the secretion of various proteins and enzymes into the saliva. This study aims to identify salivary proteins that change in expression during orthodontic tooth movement. These differentially expressed proteins can potentially serve as protein biomarkers for the monitoring of orthodontic treatment and tooth movement. Whole saliva from three healthy female subjects were collected before force application using fixed appliance and at 14 days after 0.014′′ Niti wire was applied. Salivary proteins were resolved using two-dimensional gel electrophoresis (2DE) over a pH range of 3–10, and the resulting proteome profiles were compared. Differentially expressed protein spots were then identified by MALDI-TOF/TOF tandem mass spectrometry. Nine proteins were found to be differentially expressed; however, only eight were identified by MALDI-TOF/TOF. Four of these proteins—Protein S100-A9, immunoglobulin J chain, Ig alpha-1 chain C region, and CRISP-3—have known roles in inflammation and bone resorption. PMID:22919344

A Paleoevaporation Proxy Using Compound Specific Stable Isotope Measurements from Peatland Biomarkers

NASA Astrophysics Data System (ADS)

Wang, J.; Nichols, J. E.; Huang, Y.

2009-12-01

It is important to understand how evaporation from wetlands changes with climate. To do this, we have developed a paleoevaporation proxy for use in ombrotrophic peatland sediments. Using compound specific hydrogen isotopic ratios of vascular plant and Sphagnum biomarkers, we can quantitatively reconstruct past changes in evaporation. The contrast in H isotopic ratios of water available to living Sphagnum and water in the acrotelm can be used to estimate “f”—the fraction of water remaining after evaporation. Vascular plant leaf waxes record H isotopic ratios of precipitation which is little affected by evaporation, whereas the Sphagnum biomarker, C23 n-alkane, records H isotopic ratios of the water inside its cells and between its leaves, which is strongly affected by evaporation at the bog surface. Evaporation changes can then be calculated with the H-isotopic ratios of the two types of biomarkers. We calibrated the apparent fractionation of D/H ratios from source water to C23 n-alkane with lab-grown Sphagnum. We also present several reconstructions of paleoevaporation from peatlands throughout eastern North America. By comparison with overall hydrologic balance, we are able to understand the varying role of evaporation in the hydrologic system in both time and space.

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

PubMed Central

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

2017-01-01

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

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

PubMed

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

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.

A single-index threshold Cox proportional hazard model for identifying a treatment-sensitive subset based on multiple biomarkers.

PubMed

He, Ye; Lin, Huazhen; Tu, Dongsheng

2018-06-04

In this paper, we introduce a single-index threshold Cox proportional hazard model to select and combine biomarkers to identify patients who may be sensitive to a specific treatment. A penalized smoothed partial likelihood is proposed to estimate the parameters in the model. A simple, efficient, and unified algorithm is presented to maximize this likelihood function. The estimators based on this likelihood function are shown to be consistent and asymptotically normal. Under mild conditions, the proposed estimators also achieve the oracle property. The proposed approach is evaluated through simulation analyses and application to the analysis of data from two clinical trials, one involving patients with locally advanced or metastatic pancreatic cancer and one involving patients with resectable lung cancer. Copyright © 2018 John Wiley & Sons, Ltd.

Predictive Biomarkers for Asthma Therapy.

PubMed

Medrek, Sarah K; Parulekar, Amit D; Hanania, Nicola A

2017-09-19

Asthma is a heterogeneous disease characterized by multiple phenotypes. Treatment of patients with severe disease can be challenging. Predictive biomarkers are measurable characteristics that reflect the underlying pathophysiology of asthma and can identify patients that are likely to respond to a given therapy. This review discusses current knowledge regarding predictive biomarkers in asthma. Recent trials evaluating biologic therapies targeting IgE, IL-5, IL-13, and IL-4 have utilized predictive biomarkers to identify patients who might benefit from treatment. Other work has suggested that using composite biomarkers may offer enhanced predictive capabilities in tailoring asthma therapy. Multiple biomarkers including sputum eosinophil count, blood eosinophil count, fractional concentration of nitric oxide in exhaled breath (FeNO), and serum periostin have been used to identify which patients will respond to targeted asthma medications. Further work is needed to integrate predictive biomarkers into clinical practice.

Identifying biomarkers of dietary patterns by using metabolomics123

PubMed Central

Derkach, Andriy; Reedy, Jill; Subar, Amy F; Sampson, Joshua N; Albanes, Demetrius; Gu, Fangyi; Kontto, Jukka; Lassale, Camille; Liao, Linda M; Männistö, Satu; Mondul, Alison M; Weinstein, Stephanie J; Irwin, Melinda L; Mayne, Susan T; Stolzenberg-Solomon, Rachael

2017-01-01

Background: Healthy dietary patterns that conform to national dietary guidelines are related to lower chronic disease incidence and longer life span. However, the precise mechanisms involved are unclear. Identifying biomarkers of dietary patterns may provide tools to validate diet quality measurement and determine underlying metabolic pathways influenced by diet quality. Objective: The objective of this study was to examine the correlation of 4 diet quality indexes [the Healthy Eating Index (HEI) 2010, the Alternate Mediterranean Diet Score (aMED), the WHO Healthy Diet Indicator (HDI), and the Baltic Sea Diet (BSD)] with serum metabolites. Design: We evaluated dietary patterns and metabolites in male Finnish smokers (n = 1336) from 5 nested case-control studies within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort. Participants completed a validated food-frequency questionnaire and provided a fasting serum sample before study randomization (1985–1988). Metabolites were measured with the use of mass spectrometry. We analyzed cross-sectional partial correlations of 1316 metabolites with 4 diet quality indexes, adjusting for age, body mass index, smoking, energy intake, education, and physical activity. We pooled estimates across studies with the use of fixed-effects meta-analysis with Bonferroni correction for multiple comparisons, and conducted metabolic pathway analyses. Results: The HEI-2010, aMED, HDI, and BSD were associated with 23, 46, 23, and 33 metabolites, respectively (17, 21, 11, and 10 metabolites, respectively, were chemically identified; r-range: −0.30 to 0.20; P = 6 × 10−15 to 8 × 10−6). Food-based diet indexes (HEI-2010, aMED, and BSD) were associated with metabolites correlated with most components used to score adherence (e.g., fruit, vegetables, whole grains, fish, and unsaturated fat). HDI correlated with metabolites related to polyunsaturated fat and fiber components, but not other macro- or micronutrients (e

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

Rationale in diagnosis and screening of atrophic gastritis with stomach-specific plasma biomarkers

PubMed Central

Agréus, Lars; Kuipers, Ernst J; Kupcinskas, Limas; Malfertheiner, Peter; Di Mario, Francesco; Leja, Marcis; Mahachai, Varocha; Yaron, Niv; Van Oijen, Martijn; Perez, Guillermo Perez; Rugge, Massimo; Ronkainen, Jukka; Salaspuro, Mikko; Sipponen, Pentti; Sugano, Kentaro; Sung, Joseph

2012-01-01

Background and aims Atrophic gastritis (AG) results most often from Helicobacter pylori (H. pylori) infection. AG is the most important single risk condition for gastric cancer that often leads to an acid-free or hypochlorhydric stomach. In the present paper, we suggest a rationale for noninvasive screening of AG with stomach-specific biomarkers. Methods The paper summarizes a set of data on application of the biomarkers and describes how the test results could be interpreted in practice. Results In AG of the gastric corpus and fundus, the plasma levels of pepsinogen I and/or the pepsinogen I/pepsinogen II ratio are always low. The fasting level of gastrin-17 is high in AG limited to the corpus and fundus, but low or non-elevated if the AG occurs in both antrum and corpus. A low fasting level of G-17 is a sign of antral AG or indicates high intragastric acidity. Differentiation between antral AG and high intragastric acidity can be done by assaying the plasma G-17 before and after protein stimulation, or before and after administration of the proton pump inhibitors (PPI). Amidated G-17 will rise if the antral mucosa is normal in structure. H. pylori antibodies are a reliable indicator of helicobacter infection, even in patients with AG and hypochlorhydria. Conclusions Stomach-specific biomarkers provide information about the stomach health and about the function of stomach mucosa and are a noninvasive tool for diagnosis and screening of AG and acid-free stomach. PMID:22242613

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

Integrated analysis of numerous heterogeneous gene expression profiles for detecting robust disease-specific biomarkers and proposing drug targets.

PubMed

Amar, David; Hait, Tom; Izraeli, Shai; Shamir, Ron

2015-09-18

Genome-wide expression profiling has revolutionized biomedical research; vast amounts of expression data from numerous studies of many diseases are now available. Making the best use of this resource in order to better understand disease processes and treatment remains an open challenge. In particular, disease biomarkers detected in case-control studies suffer from low reliability and are only weakly reproducible. Here, we present a systematic integrative analysis methodology to overcome these shortcomings. We assembled and manually curated more than 14,000 expression profiles spanning 48 diseases and 18 expression platforms. We show that when studying a particular disease, judicious utilization of profiles from other diseases and information on disease hierarchy improves classification quality, avoids overoptimistic evaluation of that quality, and enhances disease-specific biomarker discovery. This approach yielded specific biomarkers for 24 of the analyzed diseases. We demonstrate how to combine these biomarkers with large-scale interaction, mutation and drug target data, forming a highly valuable disease summary that suggests novel directions in disease understanding and drug repurposing. Our analysis also estimates the number of samples required to reach a desired level of biomarker stability. This methodology can greatly improve the exploitation of the mountain of expression profiles for better disease analysis. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Computational Gene Expression Modeling Identifies Salivary Biomarker Analysis that Predict Oral Feeding Readiness in the Newborn

PubMed Central

Maron, Jill L.; Hwang, Jooyeon S.; Pathak, Subash; Ruthazer, Robin; Russell, Ruby L.; Alterovitz, Gil

2014-01-01

Objective To combine mathematical modeling of salivary gene expression microarray data and systems biology annotation with RT-qPCR amplification to identify (phase I) and validate (phase II) salivary biomarker analysis for the prediction of oral feeding readiness in preterm infants. Study design Comparative whole transcriptome microarray analysis from 12 preterm newborns pre- and post-oral feeding success was used for computational modeling and systems biology analysis to identify potential salivary transcripts associated with oral feeding success (phase I). Selected gene expression biomarkers (15 from computational modeling; 6 evidence-based; and 3 reference) were evaluated by RT-qPCR amplification on 400 salivary samples from successful (n=200) and unsuccessful (n=200) oral feeders (phase II). Genes, alone and in combination, were evaluated by a multivariate analysis controlling for sex and post-conceptional age (PCA) to determine the probability that newborns achieved successful oral feeding. Results Advancing post-conceptional age (p < 0.001) and female sex (p = 0.05) positively predicted an infant’s ability to feed orally. A combination of five genes, NPY2R (hunger signaling), AMPK (energy homeostasis), PLXNA1 (olfactory neurogenesis), NPHP4 (visual behavior) and WNT3 (facial development), in addition to PCA and sex, demonstrated good accuracy for determining feeding success (AUROC = 0.78). Conclusions We have identified objective and biologically relevant salivary biomarkers that noninvasively assess a newborn’s developing brain, sensory and facial development as they relate to oral feeding success. Understanding the mechanisms that underlie the development of oral feeding readiness through translational and computational methods may improve clinical decision making while decreasing morbidities and health care costs. PMID:25620512

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

PubMed

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

2012-09-01

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

Stable Isotope Ratios as Biomarkers of Diet for Health Research

PubMed Central

O’Brien, Diane M.

2016-01-01

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

The role of biomarkers in the management of epithelial ovarian cancer.

PubMed

Yang, Wei-Lei; Lu, Zhen; Bast, Robert C

2017-06-01

Despite advances in surgery and chemotherapy for ovarian cancer, 70% of women still succumb to the disease. Biomarkers have contributed to the management of ovarian cancer by monitoring response to treatment, detecting recurrence, distinguishing benign from malignant pelvic masses and attempting to detect disease at an earlier stage. Areas covered: This review focuses on recent advances in biomarkers and imaging for management of ovarian cancer with particular emphasis on early detection. Relevant literature has been reviewed and analyzed. Expert commentary: Rising or persistent CA125 blood levels provide a highly specific biomarker for epithelial ovarian cancer, but not an optimally sensitive biomarker. Addition of HE4, CA 72.4, anti-TP53 autoantibodies and other biomarkers can increase sensitivity for detecting early stage or recurrent disease. Detecting disease recurrence will become more important as more effective therapy is developed. Early detection will require the development not only of biomarker panels, but also of more sensitive and specific imaging strategies. Effective biomarker strategies are already available for distinguishing benign from malignant pelvic masses, but their use in identifying and referring patients with probable ovarian cancer to gynecologic oncologists for cytoreductive operations must be encouraged.

MicroRNA Biomarkers of Toxicity in Biological Matrices ...

EPA Pesticide Factsheets

Biomarker measurements that reliably correlate with tissue injury and can be measured from sampling accessible biofluids offer enormous benefits in terms of cost, time, and convenience when assessing environmental and drug-induced toxicity in model systems or human cohorts. MicroRNAs (miRNAs) have emerged in recent years as a promising new type of biomarker for monitoring toxicity. Recent enthusiasm for miRNA biomarker research has been fueled by discoveries that certain miRNA species are cell-type specific and released during injury, thus raising the possibility of using biofluid-based miRNAs as a “liquid biopsy” that may be obtained by sampling extracellular fluids. As biomarkers, miRNAs demonstrate improved stability as compared to many protein markers and sequences are largely conserved across species, simplifying analytical techniques. Recent efforts have sought to identify miRNAs that are released into accessible biofluids following xenobiotic exposure, using compounds that target specific organs. While still early in the discovery phase, miRNA biomarkers will have an increasingly important role in the assessment of adverse effects of both environmental chemicals and pharmaceutical drugs. Here, we review the current findings of biofluid-based miRNAs, as well as highlight technical challenges in assessing toxicologic pathology using these biomarkers. MicroRNAs (miRNAs) are small, non-coding RNA species that selectively bind mRNA molecules and alter thei

Novel heart failure biomarkers: why do we fail to exploit their potential?

PubMed

Piek, Arnold; Du, Weijie; de Boer, Rudolf A; Silljé, Herman H W

2018-06-01

Plasma biomarkers are useful tools in the diagnosis and prognosis of heart failure (HF). In the last decade, numerous studies have aimed to identify novel HF biomarkers that would provide superior and/or additional diagnostic, prognostic, or stratification utility. Although numerous biomarkers have been identified, their implementation in clinical practice has so far remained largely unsuccessful. Whereas cardiac-specific biomarkers, including natriuretic peptides (ANP and BNP) and high sensitivity troponins (hsTn), are widely used in clinical practice, other biomarkers have not yet proven their utility. Galectin-3 (Gal-3) and soluble suppression of tumorigenicity 2 (sST2) are the only novel HF biomarkers that are included in the ACC/AHA HF guidelines, but their clinical utility still needs to be demonstrated. In this review, we will describe natriuretic peptides, hsTn, and novel HF biomarkers, including Gal-3, sST2, human epididymis protein 4 (HE4), insulin-like growth factor-binding protein 7 (IGFBP-7), heart fatty acid-binding protein (H-FABP), soluble CD146 (sCD146), interleukin-6 (IL-6), growth differentiation factor 15 (GDF-15), procalcitonin (PCT), adrenomedullin (ADM), microRNAs (miRNAs), and metabolites like 5-oxoproline. We will discuss the biology of these HF biomarkers and conclude that most of them are markers of general pathological processes like fibrosis, cell death, and inflammation, and are not cardiac- or HF-specific. These characteristics explain to a large degree why it has been difficult to relate these biomarkers to a single disease. We propose that, in addition to clinical investigations, it will be pivotal to perform comprehensive preclinical biomarker investigations in animal models of HF in order to fully reveal the potential of these novel HF biomarkers.

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 use of biomarkers to trace carbon transformations and input in soils

NASA Astrophysics Data System (ADS)

Jansen, Boris; Kalbitz, Karsten

2015-04-01

Tracing the origin of soil organic matter is an important tool to unravel mechanisms that lead to (de)stabilization of organic carbon in soil systems. To this end biomarkers, i.e. (groups of) specific molecules that can be linked to (groups of) specific plant species or plant parts are often used. A good example is the use of suberin and cutin as biomarkers to distinguish organic matter with a root origin from organic matter with a leaf origin. However, the use of biomarkers to trace the origin of soil organic matter is also subject of fierce scientific debate. On the one extreme end there are those colleagues who see biomarkers as a cure-all solution to all organic matter tracing problems. On the other end of the spectrum there are experts who claim that the concept of biomarkers is so intrinsically flawed that it can never yield meaningful information about carbon transformations except in the most specific cases. We believe that neither vision is correct. In our presentation we discuss the merits and drawbacks of using biomarkers to trace root versus leaf derived organic matter in soils. For this we use a 1-year incubation experiment with fine root and leaf material of six temperate tree species as a case study. We discuss the abundance, or lack thereof, of root and leaf derived biomarkers and the development of their concentration over time. Specifically, we found that the specificity of root and leaf specific biomarkers depended strongly on the amount and diversity of studied species. For instance, four molecules were identified to be leaf biomarkers for some species, while serving as root biomarkers for others. This could result in serious misjudgment of root and leaf specific biomarkers if the boundary conditions, including species of interest, are not well known. On the other hand, our results show that cutin and suberin derived biomarkers can indeed be successfully used to distinguish root from leaf input in certain situations, such as an ecosystem

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

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

PubMed Central

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

2017-01-01

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

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.

Neuroproteomics and Systems Biology Approach to Identify Temporal Biomarker Changes Post Experimental Traumatic Brain Injury in Rats.

PubMed

Kobeissy, Firas H; Guingab-Cagmat, Joy D; Zhang, Zhiqun; Moghieb, Ahmed; Glushakova, Olena Y; Mondello, Stefania; Boutté, Angela M; Anagli, John; Rubenstein, Richard; Bahmad, Hisham; Wagner, Amy K; Hayes, Ronald L; Wang, Kevin K W

2016-01-01

Traumatic brain injury (TBI) represents a critical health problem of which diagnosis, management, and treatment remain challenging. TBI is a contributing factor in approximately one-third of all injury-related deaths in the United States. The Centers for Disease Control and Prevention estimate that 1.7 million people suffer a TBI in the United States annually. Efforts continue to focus on elucidating the complex molecular mechanisms underlying TBI pathophysiology and defining sensitive and specific biomarkers that can aid in improving patient management and care. Recently, the area of neuroproteomics-systems biology is proving to be a prominent tool in biomarker discovery for central nervous system injury and other neurological diseases. In this work, we employed the controlled cortical impact (CCI) model of experimental TBI in rat model to assess the temporal-global proteome changes after acute (1 day) and for the first time, subacute (7 days), post-injury time frame using the established cation-anion exchange chromatography-1D SDS gel electrophoresis LC-MS/MS platform for protein separation combined with discrete systems biology analyses to identify temporal biomarker changes related to this rat TBI model. Rather than focusing on any one individual molecular entity, we used in silico systems biology approach to understand the global dynamics that govern proteins that are differentially altered post-injury. In addition, gene ontology analysis of the proteomic data was conducted in order to categorize the proteins by molecular function, biological process, and cellular localization. Results show alterations in several proteins related to inflammatory responses and oxidative stress in both acute (1 day) and subacute (7 days) periods post-TBI. Moreover, results suggest a differential upregulation of neuroprotective proteins at 7 days post-CCI involved in cellular functions such as neurite growth, regeneration, and axonal guidance. Our study is among the

Searching for ‘omic’ biomarkers

PubMed Central

Lin, David; Hollander, Zsuzsanna; Meredith, Anna; McManus, Bruce M

2009-01-01

Cardiovascular diseases impose enormous social and economic burdens on both individual citizens and on society as a whole. Clinical indicators such as high blood pressure, blood cholesterol and obesity have had some utility in identifying those who are at increased risk of cardiovascular events. However, there remains an urgent need for sensitive and specific indicators, preferably acquired through minimally invasive means, to help stratify patients for more personalized health care. As such, there has been a steadily growing interest in searching for ‘omic’ biomarkers of cardiovascular diseases. Historically, the transition of cardiac biomarker discovery to implementation has been a lengthy and somewhat unregulated process. Recent technological advancements, as well as concurrent efforts by regulatory agencies such as the Food and Drug Administration (United States) and Health Canada to establish policies and guidelines in the ‘omic’ arena, have helped propel the discovery and validation of biomarkers forward. The present paper provides perspective on current strategies in the bio-marker development pathway, as well as the potential limitations associated with each step from discovery to clinical uptake. Canadian biomarker studies now underway illustrate the possibilities for assessment of risk, diagnosis, prognosis and response to therapy, and for the drug discovery process. PMID:19521568

Diatom-specific highly branched isoprenoids as biomarkers in Antarctic consumers.

PubMed

Goutte, Aurélie; Cherel, Yves; Houssais, Marie-Noëlle; Klein, Vincent; Ozouf-Costaz, Catherine; Raccurt, Mireille; Robineau, Camille; Massé, Guillaume

2013-01-01

The structure, functioning and dynamics of polar marine ecosystems are strongly influenced by the extent of sea ice. Ice algae and pelagic phytoplankton represent the primary sources of nutrition for higher trophic-level organisms in seasonally ice-covered areas, but their relative contributions to polar marine consumers remain largely unexplored. Here, we investigated the potential of diatom-specific lipid markers and highly branched isoprenoids (HBIs) for estimating the importance of these two carbon pools in an Antarctic pelagic ecosystem. Using GC-MS analysis, we studied HBI biomarkers in key marine species over three years in Adélie Land, Antarctica: euphausiids (ice krill Euphausia crystallorophias and Antarctic krill E. superba), fish (bald notothens Pagothenia borchgrevinki and Antarctic silverfish Pleuragramma antarcticum) and seabirds (Adélie penguins Pygoscelis adeliae, snow petrels Pagodroma nivea and cape petrels Daption capense). This study provides the first evidence of the incorporation of HBI lipids in Antarctic pelagic consumers. Specifically, a di-unsaturated HBI (diene) of sea ice origin was more abundant in ice-associated species than in pelagic species, whereas a tri-unsaturated HBI (triene) of phytoplanktonic origin was more abundant in pelagic species than in ice-associated species. Moreover, the relative abundances of diene and triene in seabird tissues and eggs were higher during a year of good sea ice conditions than in a year of poor ice conditions. In turn, the higher contribution of ice algal derived organic matter to the diet of seabirds was related to earlier breeding and higher breeding success. HBI biomarkers are a promising tool for estimating the contribution of organic matter derived from ice algae in pelagic consumers from Antarctica.

Applications of Nutritional Biomarkers in Global Health Settings.

PubMed

Prentice, Andrew M

2016-01-01

In global health settings, there are three generic areas that require reliable biomarkers of nutritional status and function. Population surveillance needs to identify key nutrient deficiencies (or excesses) to monitor progress towards elimination of nutritional imbalances and to stratify populations into groups especially 'at risk' to whom public health resources can be focused. Clinical interventions need biomarkers to help identify disease pathways, to assist in targeting nutrient prescriptions, and to avoid potential harm (e.g. in the case of iron). Discovery science requires biomarkers in many domains, but especially in the study of nutrient-gene interactions and regarding the effects of nutritional status on the epigenome. Each of these applications imposes different constraints on the methodology though in all cases the optimum biomarker would have high sensitivity and specificity, would capture variation of functional significance, and would be cheap and easy to apply. These attributes are hard to achieve, and recent progress towards next-generation biomarkers, though holding much promise, has not yet delivered significant breakthroughs in the global health setting. Recent efforts to overcome these problems by two initiatives (BOND and INSPIRE) are highlighted as exemplars of a route map to progress. © 2016 Nestec Ltd., Vevey/S. Karger AG, Basel.

Validation of biomarkers of food intake-critical assessment of candidate biomarkers.

PubMed

Dragsted, L O; Gao, Q; Scalbert, A; Vergères, G; Kolehmainen, M; Manach, C; Brennan, L; Afman, L A; Wishart, D S; Andres Lacueva, C; Garcia-Aloy, M; Verhagen, H; Feskens, E J M; Praticò, G

2018-01-01

Biomarkers of food intake (BFIs) are a promising tool for limiting misclassification in nutrition research where more subjective dietary assessment instruments are used. They may also be used to assess compliance to dietary guidelines or to a dietary intervention. Biomarkers therefore hold promise for direct and objective measurement of food intake. However, the number of comprehensively validated biomarkers of food intake is limited to just a few. Many new candidate biomarkers emerge from metabolic profiling studies and from advances in food chemistry. Furthermore, candidate food intake biomarkers may also be identified based on extensive literature reviews such as described in the guidelines for Biomarker of Food Intake Reviews (BFIRev). To systematically and critically assess the validity of candidate biomarkers of food intake, it is necessary to outline and streamline an optimal and reproducible validation process. A consensus-based procedure was used to provide and evaluate a set of the most important criteria for systematic validation of BFIs. As a result, a validation procedure was developed including eight criteria, plausibility, dose-response, time-response, robustness, reliability, stability, analytical performance, and inter-laboratory reproducibility. The validation has a dual purpose: (1) to estimate the current level of validation of candidate biomarkers of food intake based on an objective and systematic approach and (2) to pinpoint which additional studies are needed to provide full validation of each candidate biomarker of food intake. This position paper on biomarker of food intake validation outlines the second step of the BFIRev procedure but may also be used as such for validation of new candidate biomarkers identified, e.g., in food metabolomic studies.

Growth dynamics of specific spoilage organisms and associated spoilage biomarkers in chicken breast stored aerobically

USDA-ARS?s Scientific Manuscript database

This study was performed to identify and quantify selected volatile spoilage biomarkers in a headspace over chicken breast using solid phase microextraction (SPME) combined with gas chromatography-mass spectrometry-flame ionization detectors (GC-MS/FID). The chicken breast samples were aerobically s...

Inflammatory cytokine biomarkers to identify women with asymptomatic sexually transmitted infections and bacterial vaginosis who are at high risk of HIV infection.

PubMed

Masson, Lindi; Arnold, Kelly B; Little, Francesca; Mlisana, Koleka; Lewis, David A; Mkhize, Nonhlanhla; Gamieldien, Hoyam; Ngcapu, Sinaye; Johnson, Leigh; Lauffenburger, Douglas A; Abdool Karim, Quarraisha; Abdool Karim, Salim S; Passmore, Jo-Ann S

2016-05-01

Untreated sexually transmitted infections (STIs) and bacterial vaginosis (BV) cause genital inflammation and increase the risk of HIV infection. WHO-recommended syndromic STI and BV management is severely limited as many women with asymptomatic infections go untreated. The purpose of this cross-sectional study was to evaluate genital cytokine profiles as a biomarker of STIs and BV to identify women with asymptomatic, treatable infections. Concentrations of 42 cytokines in cervicovaginal lavages from 227 HIV-uninfected women were measured using Luminex. All women were screened for BV by microscopy and STIs using molecular assays. Multivariate analyses were used to identify cytokine profiles associated with STIs/BV. A multivariate profile of seven cytokines (interleukin (IL)-1α, IL-1β, tumour necrosis factor-β, IL-4, fractalkine, macrophage-derived chemokine, and interferon-γ) most accurately predicted the presence of a treatable genital condition, with 77% classification accuracy and 75% cross-validation accuracy (sensitivity 72%; specificity 81%, positive predictive value (PPV) 86%, negative predictive value (NPV) 64%). Concomitant increased IL-1β and decreased IP-10 concentrations predicted the presence of a treatable genital condition without a substantial reduction in predictive value (sensitivity 77%, specificity 72%, PPV 82% and NPV 65%), correctly classifying 75% of the women. This approach performed substantially better than clinical signs (sensitivity 19%, specificity 92%, PPV 79% and NPV 40%). Supplementing syndromic management with an assessment of IL-1β and IP-10 as biomarkers of genital inflammation may improve STI/BV management for women, enabling more effective treatment of asymptomatic infections and potentially reducing their risk of HIV infection. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Biomarkers of exposure and dose: state of the art.

PubMed

Brooks, A L

2001-01-01

Biomarkers provide methods to measure changes in biological systems and to relate them to environmental insults and disease processes. Biomarkers can be classified as markers of exposure and dose, markers of sensitivity, and markers of disease. It is important that the differences and applications of the various types of biomarkers be clearly understood. The military is primarily interested in early biomarkers of exposure and dose that do not require high levels of sensitivity but can be used to rapidly triage war fighters under combat or terrorist conditions and determine which, if any, require medical attention. Biomarkers of long-term radiation risk represent the second area of interest for the military. Biomarkers of risk require high sensitivity and specificity for the disease and insult but do not require rapid data turnaround. Biomarkers will help provide information for quick command decisions in the field, characterise long-term troop risks and identify early stages of radiation-induced diseases. This information provides major positive reassurances about individual exposures and risk that will minimise the physical and psychological impact of wartime radiation exposures.

Colorectal cancer tumour markers and biomarkers: Recent therapeutic advances.

PubMed

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

2016-02-07

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

Repeated significance tests of linear combinations of sensitivity and specificity of a diagnostic biomarker

PubMed Central

Wu, Mixia; Shu, Yu; Li, Zhaohai; Liu, Aiyi

2016-01-01

A sequential design is proposed to test whether the accuracy of a binary diagnostic biomarker meets the minimal level of acceptance. The accuracy of a binary diagnostic biomarker is a linear combination of the marker’s sensitivity and specificity. The objective of the sequential method is to minimize the maximum expected sample size under the null hypothesis that the marker’s accuracy is below the minimal level of acceptance. The exact results of two-stage designs based on Youden’s index and efficiency indicate that the maximum expected sample sizes are smaller than the sample sizes of the fixed designs. Exact methods are also developed for estimation, confidence interval and p-value concerning the proposed accuracy index upon termination of the sequential testing. PMID:26947768

Increased liver-specific proteins in circulating extracellular vesicles as potential biomarkers for drug- and alcohol-induced liver injury

PubMed Central

Cho, Young-Eun; Im, Eun-Ju; Moon, Pyong-Gon; Mezey, Esteban; Song, Byoung-Joon; Baek, Moon-Chang

2017-01-01

Drug- and alcohol-induced liver injury are a leading cause of liver failure and transplantation. Emerging evidence suggests that extracellular vesicles (EVs) are a source of biomarkers because they contain unique proteins reflecting the identity and tissue-specific origin of the EV proteins. This study aimed to determine whether potentially hepatotoxic agents, such as acetaminophen (APAP) and binge alcohol, can increase the amounts of circulating EVs and evaluate liver-specific EV proteins as potential biomarkers for liver injury. The circulating EVs, isolated from plasma of APAP-exposed, ethanol-fed mice, or alcoholic hepatitis patients versus normal control counterparts, were characterized by proteomics and biochemical methods. Liver specific EV proteins were analyzed by immunoblots and ELISA. The amounts of total and liver-specific proteins in circulating EVs from APAP-treated mice significantly increased in a dose- and time-dependent manner. Proteomic analysis of EVs from APAP-exposed mice revealed that the amounts of liver-specific and/or hepatotoxic proteins were increased compared to those of controls. Additionally, the increased protein amounts in EVs following APAP exposure returned to basal levels when mice were treated with N-acetylcysteine or glutathione. Similar results of increased amounts and liver-specific proteins in circulating EVs were also observed in mice exposed to hepatotoxic doses of thioacetamide or d-galactosamine but not by non-hepatotoxic penicillin or myotoxic bupivacaine. Additionally, binge ethanol exposure significantly elevated liver-specific proteins in circulating EVs from mice and alcoholics with alcoholic hepatitis, compared to control counterparts. These results indicate that circulating EVs in drug- and alcohol-mediated hepatic injury contain liver-specific proteins that could serve as specific biomarkers for hepatotoxicity. PMID:28225807

Protocol for Biomarker Ratio Imaging Microscopy with Specific Application to Ductal Carcinoma In situ of the Breast

PubMed Central

Clark, Andrea J.; Petty, Howard R.

2016-01-01

This protocol describes the methods and steps involved in performing biomarker ratio imaging microscopy (BRIM) using formalin fixed paraffin-embedded (FFPE) samples of human breast tissue. The technique is based on the acquisition of two fluorescence images of the same microscopic field using two biomarkers and immunohistochemical tools. The biomarkers are selected such that one biomarker correlates with breast cancer aggressiveness while the second biomarker anti-correlates with aggressiveness. When the former image is divided by the latter image, a computed ratio image is formed that reflects the aggressiveness of tumor cells while increasing contrast and eliminating path-length and other artifacts from the image. For example, the aggressiveness of epithelial cells may be assessed by computing ratio images of N-cadherin and E-cadherin images or CD44 and CD24 images, which specifically reflect the mesenchymal or stem cell nature of the constituent cells, respectively. This methodology is illustrated for tissue samples of ductal carcinoma in situ (DCIS) and invasive breast cancer. This tool should be useful in tissue studies of experimental cancer as well as the management of cancer patients. PMID:27857940

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

Precision Oncology Medicine: The Clinical Relevance of Patient-Specific Biomarkers Used to Optimize Cancer Treatment.

PubMed

Schmidt, Keith T; Chau, Cindy H; Price, Douglas K; Figg, William D

2016-12-01

Precision medicine in oncology is the result of an increasing awareness of patient-specific clinical features coupled with the development of genomic-based diagnostics and targeted therapeutics. Companion diagnostics designed for specific drug-target pairs were the first to widely utilize clinically applicable tumor biomarkers (eg, HER2, EGFR), directing treatment for patients whose tumors exhibit a mutation susceptible to an FDA-approved targeted therapy (eg, trastuzumab, erlotinib). Clinically relevant germline mutations in drug-metabolizing enzymes and transporters (eg, TPMT, DPYD) have been shown to impact drug response, providing a rationale for individualized dosing to optimize treatment. The use of multigene expression-based assays to analyze an array of prognostic biomarkers has been shown to help direct treatment decisions, especially in breast cancer (eg, Oncotype DX). More recently, the use of next-generation sequencing to detect many potential "actionable" cancer molecular alterations is further shifting the 1 gene-1 drug paradigm toward a more comprehensive, multigene approach. Currently, many clinical trials (eg, NCI-MATCH, NCI-MPACT) are assessing novel diagnostic tools with a combination of different targeted therapeutics while also examining tumor biomarkers that were previously unexplored in a variety of cancer histologies. Results from ongoing trials such as the NCI-MATCH will help determine the clinical utility and future development of the precision-medicine approach. © 2016, The American College of Clinical Pharmacology.

USE OF qRTPCR TO IDENTIFY POTENTIAL BIOMARKERS OF BROMATE EXPOSURE IN F344 MALE RAT KIDNEYS

EPA Science Inventory

Potassium bromate (KBrO3) is a drinking water disinfection by-product that is nephrotoxic and carcinogenic. To identify potential biomarkers of carcinogenicity, male F344 rats were chronically exposed to a carcinogenic dose (400mg/l) of KBrO3 in their drinking water. Kidneys were...

Exosomal microRNA profiling to identify hypoxia-related biomarkers in prostate cancer

PubMed Central

Panigrahi, Gati K.; Ramteke, Anand; Birks, Diane; Abouzeid Ali, Hamdy E.; Venkataraman, Sujatha; Agarwal, Chapla; Vibhakar, Rajeev; Miller, Lance D.; Agarwal, Rajesh; Abd Elmageed, Zakaria Y.; Deep, Gagan

2018-01-01

Hypoxia and expression of hypoxia-related biomarkers are associated with disease progression and treatment failure in prostate cancer (PCa). We have reported that exosomes (nanovesicles of 30-150 nm in diameter) secreted by human PCa cells under hypoxia promote invasiveness and stemness in naïve PCa cells. Here, we identified the unique microRNAs (miRNAs) loaded in exosomes secreted by PCa cells under hypoxia. Using TaqMan® array microRNA cards, we analyzed the miRNA profile in exosomes secreted by human PCa LNCaP cells under hypoxic (ExoHypoxic) and normoxic (ExoNormoxic) conditions. We identified 292 miRNAs loaded in both ExoHypoxic and ExoNormoxic. The top 11 miRNAs with significantly higher level in ExoHypoxic compared to ExoNormoxic were miR-517a, miR-204, miR-885, miR-143, miR-335, miR-127, miR-542, miR-433, miR-451, miR-92a and miR-181a; and top nine miRNA with significantly lower expression level in ExoHypoxic compared to ExoNormoxic were miR-521, miR-27a, miR-324, miR-579, miR-502, miR-222, miR-135b, miR-146a and miR-491. Importantly, the two differentially expressed miRNAs miR-885 (increased expression) and miR-521 (decreased expression) showed similar expression pattern in exosomes isolated from the serum of PCa patients compared to healthy individuals. Additionally, miR-204 and miR-222 displayed correlated expression patterns in prostate tumors (Pearson R = 0.66, p < 0.0001) by The Cancer Genome Atlas (TCGA) prostate adenocarcinoma (PRAD) genomic dataset analysis. Overall, the present study identified unique miRNAs with differential expression in exosomes secreted from hypoxic PCa cells and suggests their potential usefulness as a biomarker of hypoxia in PCa patients. PMID:29568403

Biomarkers of exposure to new and emerging tobacco delivery products.

PubMed

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

2017-09-01

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

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

PubMed

Rodriguez, M; Siwko, S; Liu, M

2016-01-01

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

New serum biomarkers for prostate cancer diagnosis

PubMed Central

Chadha, Kailash C.; Miller, Austin; Nair, Bindukumar B.; Schwartz, Stanley A.; Trump, Donald L.; Underwood, Willie

2014-01-01

Background Prostate-specific antigen (PSA) is currently used as a biomarker for diagnosis and management of prostate cancer (CaP). However, PSA typically lacks the sensitivity and specificity desired of a diagnostic marker. Objective The goal of this study was to identify an additional biomarker or a panel of biomarkers that is more sensitive and specific than PSA in differentiating benign versus malignant prostate disease and/or localized CaP versus metastatic CaP. Methods Concurrent measurements of circulating interleukin-8 (IL-8), Tumor necrosis factor-α (TNF-α) and soluble tumor necrosis factor-α receptors 1 (sTNFR1) were obtained from four groups of men: (1) Controls (2) with elevated prostate-specific antigen with a negative prostate biopsy (elPSA_negBx) (3) with clinically localized CaP and (4) with castration resistant prostate cancer. Results TNF-α Area under the receiver operating characteristic curve (AUC = 0.93) and sTNFR1 (AUC = 0.97) were strong predictors of elPSA_negBx (vs. CaP). The best predictor of elPSA_negBx vs CaP was sTNFR1 and IL-8 combined (AUC = 0.997). The strongest single predictors of localized versus metastatic CaP were TNF-α (AUC = 0.992) and PSA (AUC = 0.963) levels. Conclusions The specificity and sensitivity of a PSA-based CaP diagnosis can be significantly enhanced by concurrent serum measurements of IL-8, TNF-α and sTNFR1. In view of the concerns about the ability of PSA to distinguish clinically relevant CaP from indolent disease, assessment of these biomarkers in the larger cohort is warranted. PMID:25593898

Drug Induced Liver Injury: Can Biomarkers Assist RUCAM in Causality Assessment?

PubMed Central

Teschke, Rolf; Schulze, Johannes; Eickhoff, Axel; Danan, Gaby

2017-01-01

Drug induced liver injury (DILI) is a potentially serious adverse reaction in a few susceptible individuals under therapy by various drugs. Health care professionals facing DILI are confronted with a wealth of drug-unrelated liver diseases with high incidence and prevalence rates, which can confound the DILI diagnosis. Searching for alternative causes is a key element of RUCAM (Roussel Uclaf Causality Assessment Method) to assess rigorously causality in suspected DILI cases. Diagnostic biomarkers as blood tests would be a great help to clinicians, regulators, and pharmaceutical industry would be more comfortable if, in addition to RUCAM, causality of DILI can be confirmed. High specificity and sensitivity are required for any diagnostic biomarker. Although some risk factors are available to evaluate liver safety of drugs in patients, no valid diagnostic or prognostic biomarker exists currently for idiosyncratic DILI when a liver injury occurred. Identifying a biomarker in idiosyncratic DILI requires detailed knowledge of cellular and biochemical disturbances leading to apoptosis or cell necrosis and causing leakage of specific products in blood. As idiosyncratic DILI is typically a human disease and hardly reproducible in animals, pathogenetic events and resulting possible biomarkers remain largely undisclosed. Potential new diagnostic biomarkers should be evaluated in patients with DILI and RUCAM-based established causality. In conclusion, causality assessment in cases of suspected idiosyncratic DILI is still best achieved using RUCAM since specific biomarkers as diagnostic blood tests that could enhance RUCAM results are not yet available. PMID:28398242

Biomarkers for non-human primate type-I hypersensitivity: antigen-specific immunoglobulin E assays.

PubMed

Clark, Darcey; Shiota, Faith; Forte, Carla; Narayanan, Padma; Mytych, Daniel T; Hock, M Benjamin

2013-06-28

Immunoglobulin E (IgE) is the least abundant immunoglobulin in serum. However, development of an IgE immune response can induce IgE receptor-expressing cells to carry out potent effector functions. A reliable antigen-specific IgE biomarker method for use in non-human primate studies would facilitate (i) confirmation of Type-I hypersensitivity reactions during safety toxicology testing, and (ii) a better understanding of non-human primate models of allergic disease. We cloned and expressed a recombinant cynomolgus monkey IgE molecule in order to screen a panel of commercially available detection reagents raised against human IgE for cross-reactivity. The reagent most reactive to cynomolgus IgE was confirmed to be specific for IgE and did not bind recombinant cynomolgus monkey IgG1-4. A drug-specific IgE assay was developed on the MSD electrochemiluminescent (ECL) platform. The assay is capable of detecting 10 ng/mL drug-specific IgE. Importantly, the assay is able to detect IgE in the presence of excess IgG, the scenario likely to be present in a safety toxicology study. Using our ECL assay, we were able to confirm that serum from cynomolgus monkeys that had experienced clinical symptoms consistent with hypersensitivity responses contained IgE specific for a candidate therapeutic antibody. In addition, a bioassay for mast cell activation was developed using CD34(+)-derived cynomolgus monkey mast cells. This assay confirmed that plasma from animals identified as positive in the drug-specific IgE immunoassay contained biologically active IgE (i.e. could sensitize cultured mast cells), resulting in histamine release after exposure to the therapeutic antibody. These sensitive assays for Type-I hypersensitivity in the NHP can confirm that secondary events are downstream of immunogenicity. Copyright © 2013 Elsevier B.V. All rights reserved.

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches.

PubMed

Checkley, William; Deza, Maria P; Klawitter, Jost; Romero, Karina M; Klawitter, Jelena; Pollard, Suzanne L; Wise, Robert A; Christians, Uwe; Hansel, Nadia N

2016-12-01

The diagnosis of asthma in children is challenging and relies on a combination of clinical factors and biomarkers including methacholine challenge, lung function, bronchodilator responsiveness, and presence of airway inflammation. No single test is diagnostic. We sought to identify a pattern of inflammatory biomarkers that was unique to asthma using a targeted metabolomics approach combined with data science methods. We conducted a nested case-control study of 100 children living in a peri-urban community in Lima, Peru. We defined cases as children with current asthma, and controls as children with no prior history of asthma and normal lung function. We further categorized enrollment following a factorial design to enroll equal numbers of children as either overweight or not. We obtained a fasting venous blood sample to characterize a comprehensive panel of targeted markers using a metabolomics approach based on high performance liquid chromatography-mass spectrometry. A statistical comparison of targeted metabolites between children with asthma (n = 50) and healthy controls (n = 49) revealed distinct patterns in relative concentrations of several metabolites: children with asthma had approximately 40-50% lower relative concentrations of ascorbic acid, 2-isopropylmalic acid, shikimate-3-phosphate, and 6-phospho-d-gluconate when compared to children without asthma, and 70% lower relative concentrations of reduced glutathione (all p < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 13 077 normalized counts/second and betaine ≤ 16 47 121 normalized counts/second). By using a metabolomics approach applied to serum, we were able to discriminate between children with and without asthma by revealing different metabolic patterns. These results suggest that

Biomarkers of PTSD: military applications and considerations.

PubMed

Lehrner, Amy; Yehuda, Rachel

2014-01-01

Although there are no established biomarkers for posttraumatic stress disorder (PTSD) as yet, biological investigations of PTSD have made progress identifying the pathophysiology of PTSD. Given the biological and clinical complexity of PTSD, it is increasingly unlikely that a single biomarker of disease will be identified. Rather, investigations will more likely identify different biomarkers that indicate the presence of clinically significant PTSD symptoms, associate with risk for PTSD following trauma exposure, and predict or identify recovery. While there has been much interest in PTSD biomarkers, there has been less discussion of their potential clinical applications, and of the social, legal, and ethical implications of such biomarkers. This article will discuss possible applications of PTSD biomarkers, including the social, legal, and ethical implications of such biomarkers, with an emphasis on military applications. Literature on applications of PTSD biomarkers and on potential ethical and legal implications will be reviewed. Biologically informed research findings hold promise for prevention, assessment, treatment planning, and the development of prophylactic and treatment interventions. As with any biological indicator of disorder, there are potentially positive and negative clinical, social, legal, and ethical consequences of using such biomarkers. Potential clinical applications of PTSD biomarkers hold promise for clinicians, patients, and employers. The search for biomarkers of PTSD should occur in tandem with an interdisciplinary discussion regarding the potential implications of applying biological findings in clinical and employment settings.

Biomarkers of glomerular dysfunction in pre-eclampsia - A systematic review.

PubMed

Kerley, Robert N; McCarthy, Cathal

2018-03-10

Early detection of pre-eclampsia remains one of the major focuses of antenatal obstetric care. There is often a delay in the diagnosis, mainly due to the non-specific nature of the condition. Podocytes which play a pivotal role in glomerular function become injured in pre-eclampsia leading to subsequent proteinuria. Our aim was to review available studies to determine the clinical utility of biomarkers of podocyte injury in pre-eclampsia. We used QUADAS (Quality Assessment of Diagnostic Accuracy Studies) criteria to perform a systematic review of the literature to determine the clinical utility of podocyte injury biomarkers in predicting pre-eclampsia. This study identified five potential renal biomarkers including podocytes, nephrin, synaptopodin, podocin and podocalyxin. The pooled sensitivity of all biomarkers was 0.78 (95% CI 0.74-0.82) with a specificity of 0.82 (95% CI 0.79-0.85). The area under the Summary of Receiver Operating Characteristics Curve (SROC) was 0.926 (SE 0.30). Urinary nephrin achieved the highest diagnostic values with a sensitivity of 0.81 (95% CI 0.72-0.88) and specificity of 0.84 (95% CI 0.79-0.84). Biomarkers of glomerular injury show promise as diagnostic aids in pre-eclampsia. A large-scale prospective cohort study is warranted before these biomarkers can be recommended for routine clinical care. Copyright © 2018 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.

Preliminary use of compound-specific stable isotope (CSSI) technique to identify and apportion sediment origin in a small Austrian catchment

NASA Astrophysics Data System (ADS)

Mabit, Lionel; Gibbs, Max; Chen, Xu; Meusburger, Katrin; Toloza, Arsenio; Resch, Christian; Klik, Andreas; Eder, Alexander; Strauss, Peter; Alewell, Christine

2015-04-01

The overall impacts of climate change on agriculture are expected to be negative, threatening global food security. In the agricultural areas of the European Union, water erosion risk is expected to increase by about 80% by the year 2050. Reducing soil erosion and sedimentation-related environmental problems represent a key requirement for mitigating the impact of climate change. A new forensic stable isotope technique, using the compound specific stable isotope (CSSI) signatures of inherent soil organic biomarkers, can discriminate and apportion the source soil contribution from different land uses. Plant communities label the soil where they grow by exuding organic biomarkers. Although all plants produce the same biomarkers, the stable isotopic signature of those biomarkers is different for each plant species. For agri-environmental investigation, the CSSI technique is based on the measurement of carbon-13 (13-C) natural abundance signatures of specific organic compounds such as natural fatty acids (FAs) in the soil. By linking fingerprints of land use to the sediment in deposition zones, this approach has been shown to be a useful technique for determining the source of eroded soil and thereby identifying areas prone to soil degradation. The authors have tested this innovative stable isotopic approach in a small Austrian agricultural catchment located 60 km north of Vienna. A previous fallout radionuclide (i.e. 137-Cs) based investigation established a sedimentation rate of 4 mm/yr in the lowest part of the study site. To gain knowledge about the origin of these sediments, the CSSI technique was then tested using representative samples from the different land-uses of the catchment as source material. Values of 13-C signatures of specific FAs (i.e. C22:0 = Behenic Acid ; C24:0 = Lignoceric Acid) and the bulk 13-C of the sediment mixture and potential landscape sources were analyzed with the mixing models IsoSource and CSSIAR v1.00. Using both mixing models

Fluid Biomarkers of Traumatic Brain Injury and Intended Context of Use

PubMed Central

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

2016-01-01

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

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

PubMed Central

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

2015-01-01

STUDY QUESTION Do any proteomic biomarkers previously identified for pre-eclampsia (PE) overlap with those identified in women with polycystic ovary syndrome (PCOS). SUMMARY ANSWER Five previously identified proteomic biomarkers were found to be common in women with PE and PCOS when compared with controls. WHAT IS KNOWN ALREADY Various studies have indicated an association between PCOS and PE; however, the pathophysiological mechanisms supporting this association are not known. STUDY DESIGN, SIZE, DURATION A systematic review and update of our PCOS proteomic biomarker database was performed, along with a parallel review of PE biomarkers. The study included papers from 1980 to December 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS In all the studies analysed, there were a total of 1423 patients and controls. The number of proteomic biomarkers that were catalogued for PE was 192. MAIN RESULTS AND THE ROLE OF CHANCE Five proteomic biomarkers were shown to be differentially expressed in women with PE and PCOS when compared with controls: transferrin, fibrinogen α, β and γ chain variants, kininogen-1, annexin 2 and peroxiredoxin 2. In PE, the biomarkers were identified in serum, plasma and placenta and in PCOS, the biomarkers were identified in serum, follicular fluid, and ovarian and omental biopsies. LIMITATIONS, REASONS FOR CAUTION The techniques employed to detect proteomics have limited ability in identifying proteins that are of low abundance, some of which may have a diagnostic potential. The sample sizes and number of biomarkers identified from these studies do not exclude the risk of false positives, a limitation of all biomarker studies. The biomarkers common to PE and PCOS were identified from proteomic analyses of different tissues. WIDER IMPLICATIONS OF THE FINDINGS This data amalgamation of the proteomic studies in PE and in PCOS, for the first time, discovered a panel of five biomarkers for PE which are common to women with PCOS, including transferrin

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.

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

PubMed

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

2018-06-01

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

Use of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection

PubMed Central

Nachamkin, Irving; Coffin, Susan E.; Gerber, Jeffrey S.; Fuchs, Barry; Garrigan, Charles; Han, Xiaoyan; Bilker, Warren B.; Wise, Jacqueleen; Tolomeo, Pam; Lautenbach, Ebbing

2015-01-01

Sepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting. PMID:26239984

Dietary biomarkers: advances, limitations and future directions

PubMed Central

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

PubMed

Zhang, Bo; Chen, Zhen; Albert, Paul S

2012-01-01

High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

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

USDA-ARS?s Scientific Manuscript database

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

Autoantibody signatures as biomarkers to distinguish prostate cancer from benign prostatic hyperplasia in patients with increased serum prostate specific antigen.

PubMed

O'Rourke, Dennis J; DiJohnson, Daniel A; Caiazzo, Robert J; Nelson, James C; Ure, David; O'Leary, Michael P; Richie, Jerome P; Liu, Brian C-S

2012-03-22

Serum prostate specific antigen (PSA) concentrations lack the specificity to differentiate prostate cancer from benign prostate hyperplasia (BPH), resulting in unnecessary biopsies. We identified 5 autoantibody signatures to specific cancer targets which might be able to differentiate prostate cancer from BPH in patients with increased serum PSA. To identify autoantibody signatures as biomarkers, a native antigen reverse capture microarray platform was used. Briefly, well-characterized monoclonal antibodies were arrayed onto nanoparticle slides to capture native antigens from prostate cancer cells. Prostate cancer patient serum samples (n=41) and BPH patient samples (collected starting at the time of initial diagnosis) with a mean follow-up of 6.56 y without the diagnosis of cancer (n=39) were obtained. One hundred micrograms of IgGs were purified and labeled with a Cy3 dye and incubated on the arrays. The arrays were scanned for fluorescence and the intensity was quantified. Receiver operating characteristic curves were produced and the area under the curve (AUC) was determined. Using our microarray platform, we identified autoantibody signatures capable of distinguishing between prostate cancer and BPH. The top 5 autoantibody signatures were TARDBP, TLN1, PARK7, LEDGF/PSIP1, and CALD1. Combining these signatures resulted in an AUC of 0.95 (sensitivity of 95% at 80% specificity) compared to AUC of 0.5 for serum concentration PSA (sensitivity of 12.2% at 80% specificity). Our preliminary results showed that we were able to identify specific autoantibody signatures that can differentiate prostate cancer from BPH, and may result in the reduction of unnecessary biopsies in patients with increased serum PSA. Copyright © 2011 Elsevier B.V. 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.

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.

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

PubMed

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

2012-12-01

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

Proteomic profiling identifies the inorganic pyrophosphatase (PPA1) protein as a potential biomarker of metastasis in laryngeal squamous cell carcinoma.

PubMed

Bodnar, Magdalena; Luczak, Magdalena; Bednarek, Kinga; Szylberg, Lukasz; Marszalek, Andrzej; Grenman, Reidar; Szyfter, Krzysztof; Jarmuz-Szymczak, Malgorzata; Giefing, Maciej

2016-06-01

Relapse and metastasis are the main causes of unfavorable outcome in head and neck cancers. Whereas, understanding of the molecular background of these processes is far from being complete. Therefore, in this study we aimed to identify potential biomarker candidates of relapse and metastasis in laryngeal squamous cell carcinoma (LSCC) by combining the 2D electrophoresis based protein screen and immunohistochemical analysis of candidate proteins. We screened three groups of LSCC cell lines derived from primary tumors, recurrent tumors and metastases and identified seven proteins that differed significantly in relative abundance between the analyzed groups. Among the identified proteins were the heat shock proteins HSP60 and HSP70 that were significantly downregulated both in recurrences- and metastases-derived cell lines but not in primary tumor-derived cell lines. Moreover, we identified significant upregulation of the annexin V, calreticulin and the inorganic pyrophosphatase (PPA1) exclusively in the metastases-derived cell lines. As these upregulated proteins could potentially become novel biomarkers of metastasis, we have compared their abundance in primary tumor LSCC N(0) cases, primary tumor LSCC N(+) cases as well as in LSCC metastases N(+). Our results show an intense increase of cytoplasmic PPA1 abundance in the N(+) (p = 0.000042) compared to the N(0) group. In summary, we show a group of proteins deregulated in recurrences and metastases of LSCC. Moreover, we suggest the PPA1 protein as a potential new biomarker for metastasis in this cancer.

Multiplex biomarker approach for determining risk of prostate-specific antigen-defined recurrence of prostate cancer.

PubMed

Rhodes, Daniel R; Sanda, Martin G; Otte, Arie P; Chinnaiyan, Arul M; Rubin, Mark A

2003-05-07

Molecular signatures in cancer tissue may be useful for diagnosis and are associated with survival. We used results from high-density tissue microarrays (TMAs) to define combinations of candidate biomarkers associated with the rate of prostate cancer progression after radical prostatectomy that could identify patients at high risk for recurrence. Fourteen candidate biomarkers for prostate cancer for which antibodies are available included hepsin, pim-1 kinase, E-cadherin (ECAD; cell adhesion molecule), alpha-methylacyl-coenzyme A racemase, and EZH2 (enhancer of zeste homolog 2, a transcriptional repressor). TMAs containing more than 2000 tumor samples from 259 patients who underwent radical prostatectomy for localized prostate cancer were studied with these antibodies. Immunohistochemistry results were evaluated in conjunction with clinical parameters associated with prostate cancer progression, including tumor stage, Gleason score, and prostate-specific antigen (PSA) level. Recurrence was defined as a postsurgery PSA level of more than 0.2 ng/mL. All statistical tests were two-sided. Moderate or strong expression of EZH2 coupled with at most moderate expression of ECAD (i.e., a positive EZH2:ECAD status) was the biomarker combination that was most strongly associated with the recurrence of prostate cancer. EZH2:ECAD status was statistically significantly associated with prostate cancer recurrence in a training set of 103 patients (relative risk [RR] = 2.52, 95% confidence interval [CI] = 1.09 to 5.81; P =.021), in a validation set of 80 patients (RR = 3.72, 95% CI = 1.27 to 10.91; P =.009), and in the combined set of 183 patients (RR = 2.96, 95% CI = 1.56 to 5.61; P<.001). EZH2:ECAD status was statistically significantly associated with disease recurrence even after adjusting for clinical parameters, such as tumor stage, Gleason score, and PSA level (hazard ratio = 3.19, 95% CI = 1.50 to 6.77; P =.003). EZH2:ECAD status was statistically significantly associated

Biomarkers in Autism

PubMed Central

Goldani, Andre A. S.; Downs, Susan R.; Widjaja, Felicia; Lawton, Brittany; Hendren, Robert L.

2014-01-01

Autism spectrum disorders (ASDs) are complex, heterogeneous disorders caused by an interaction between genetic vulnerability and environmental factors. In an effort to better target the underlying roots of ASD for diagnosis and treatment, efforts to identify reliable biomarkers in genetics, neuroimaging, gene expression, and measures of the body’s metabolism are growing. For this article, we review the published studies of potential biomarkers in autism and conclude that while there is increasing promise of finding biomarkers that can help us target treatment, there are none with enough evidence to support routine clinical use unless medical illness is suspected. Promising biomarkers include those for mitochondrial function, oxidative stress, and immune function. Genetic clusters are also suggesting the potential for useful biomarkers. PMID:25161627

Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.

PubMed

Mallik, Saurav; Bhadra, Tapas; Maulik, Ujjwal

2017-01-01

Epigenetic Biomarker discovery is an important task in bioinformatics. In this article, we develop a new framework of identifying statistically significant epigenetic biomarkers using maximal-relevance and minimal-redundancy criterion based feature (gene) selection for multi-omics dataset. Firstly, we determine the genes that have both expression as well as methylation values, and follow normal distribution. Similarly, we identify the genes which consist of both expression and methylation values, but do not follow normal distribution. For each case, we utilize a gene-selection method that provides maximal-relevant, but variable-weighted minimum-redundant genes as top ranked genes. For statistical validation, we apply t-test on both the expression and methylation data consisting of only the normally distributed top ranked genes to determine how many of them are both differentially expressed andmethylated. Similarly, we utilize Limma package for performing non-parametric Empirical Bayes test on both expression and methylation data comprising only the non-normally distributed top ranked genes to identify how many of them are both differentially expressed and methylated. We finally report the top-ranking significant gene-markerswith biological validation. Moreover, our framework improves positive predictive rate and reduces false positive rate in marker identification. In addition, we provide a comparative analysis of our gene-selection method as well as othermethods based on classificationperformances obtained using several well-known classifiers.

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics.

PubMed

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

2015-01-01

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

Glycosylation-Based Serum Biomarkers for Cancer Diagnostics and Prognostics

PubMed Central

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

2015-01-01

Cancer is the second most common cause of death in developed countries with approximately 14 million newly diagnosed individuals and over 6 million cancer-related deaths in 2012. Many cancers are discovered at a more advanced stage but better survival rates are correlated with earlier detection. Current clinically approved cancer biomarkers are most effective when applied to patients with widespread cancer. Single biomarkers with satisfactory sensitivity and specificity have not been identified for the most common cancers and some biomarkers are ineffective for the detection of early stage cancers. Thus, novel biomarkers with better diagnostic and prognostic performance are required. Aberrant protein glycosylation is well known hallmark of cancer and represents a promising source of potential biomarkers. Glycoproteins enter circulation from tissues or blood cells through active secretion or leakage and patient serum is an attractive option as a source for biomarkers from a clinical and diagnostic perspective. A plethora of technical approaches have been developed to address the challenges of glycosylation structure detection and determination. This review summarises currently utilised glycoprotein biomarkers and novel glycosylation-based biomarkers from the serum glycoproteome under investigation as cancer diagnostics and for monitoring and prognostics and includes details of recent high throughput and other emerging glycoanalytical techniques. PMID:26509158

Biomarkers for the acute respiratory distress syndrome: how to make the diagnosis more precise

PubMed Central

García-Laorden, M. Isabel; Lorente, José A.; Flores, Carlos; Slutsky, Arthur S.

2017-01-01

The acute respiratory distress syndrome (ARDS) is an acute inflammatory process of the lung caused by a direct or indirect insult to the alveolar-capillary membrane. Currently, ARDS is diagnosed based on a combination of clinical and physiological variables. The lack of a specific biomarker for ARDS is arguably one of the most important obstacles to progress in developing novel treatments for ARDS. In this article, we will review the current understanding of some appealing biomarkers that have been measured in human blood, bronchoalveolar lavage fluid (BALF) or exhaled gas that could be used for identifying patients with ARDS, for enrolling ARDS patients into clinical trials, or for better monitoring of patient’s management. After a literature search, we identified several biomarkers that are associated with the highest sensitivity and specificity for the diagnosis or outcome prediction of ARDS: receptor for advanced glycation end-products (RAGE), angiopoietin-2 (Ang-2), surfactant protein D (SP-D), inteleukin-8, Fas and Fas ligand, procollagen peptide (PCP) I and III, octane, acetaldehyde, and 3-methylheptane. In general, these are cell-specific for epithelial or endothelial injury or involved in the inflammatory or infectious response. No biomarker or biomarkers have yet been confirmed for the diagnosis of ARDS or prediction of its prognosis. However, it is anticipated that in the near future, using biomarkers for defining ARDS, or for determining those patients who are more likely to benefit from a given therapy will have a major effect on clinical practice. PMID:28828358

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

Novel biomarkers in critical care: utility or futility?

PubMed Central

Ackland, Gareth L; Mythen, Michael G

2007-01-01

One of the holy grails of modern medicine, across a range of clinical sub-specialties, is establishing highly sensitive and specific biomarkers for various diseases. Significant success has been achieved in some of these clinical areas, most notably identifying high-sensitivity C-reactive peptide, troponin I/T and brain natriuretic peptide as significant prognosticators for both the acute outcome and the development of cardiovascular pathology. However, it is highly debatable whether this translates to complex, multi-system pathophysiological insults. Is critical care immune from the application of these novel biomarkers, given the numerous confounding factors interfering with their interpretation? PMID:18001503

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib.

PubMed

Li, Bin; Shin, Hyunjin; Gulbekyan, Georgy; Pustovalova, Olga; Nikolsky, Yuri; Hope, Andrew; Bessarabova, Marina; Schu, Matthew; Kolpakova-Hart, Elona; Merberg, David; Dorner, Andrew; Trepicchio, William L

2015-01-01

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug's known mechanism of action. Also, the models predict each drug's potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.

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.

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

PubMed Central

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

2016-01-01

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

Proteomic profiling for plasma biomarkers of tuberculosis progression.

PubMed

Liu, Qiuyue; Pan, Liping; Han, Fen; Luo, Baojian; Jia, Hongyan; Xing, Aiying; Li, Qi; Zhang, Zongde

2018-06-05

Severe pulmonary tuberculosis (STB) is a life‑threatening condition with high economic and social burden. The present study aimed to screen for distinct proteins in different stages of TB and identify biomarkers for a better understanding of TB progression and pathogenesis. Blood samples were obtained from 81 patients with STB, 80 with mild TB (MTB) and 50 healthy controls. Differentially expressed proteins were identified using liquid chromatography‑tandem mass spectrometry‑based label‑free quantitative proteomic analysis. Functional and pathway enrichment analyses were performed for the identified proteins. The expression of potential biomarkers was further validated by western blot analysis and enzyme‑linked immunosorbent assays. The accuracy, sensitivity and specificity for selected protein biomarkers in diagnosing STB were also evaluated. A total of 1,011 proteins were identified in all three groups, and 153 differentially expressed proteins were identified in patients with STB. These proteins were involved in 'cellular process', 'response to stimulus', 'apoptotic process', 'immune system process' and 'select metabolic process'. Significant differences in protein expression were detected in α‑1‑acid glycoprotein 2 (ORM2), interleukin‑36α (IL‑36α), S100 calcium binding protein A9 (S100‑A9), superoxide dismutase (SOD)1 in the STB group, compared with the MTB and control groups. The combination of plasma ORM2, IL‑36α, S100A9 and SOD1 levels achieved 90.00% sensitivity and 92.16% specificity to discriminate between patients with STB and MTB, and 89.66% sensitivity and 98.9% specificity to discriminate between patients with STB and healthy controls. ORM2, S100A9, IL‑36α and SOD1 were associated with the development of TB, and have the potential to distinguish between different stages of TB. Differential protein expression during disease progression may improve the current understanding of STB pathogenesis.

Use of a Combination Biomarker Algorithm To Identify Medical Intensive Care Unit Patients with Suspected Sepsis at Very Low Likelihood of Bacterial Infection.

PubMed

Han, Jennifer H; Nachamkin, Irving; Coffin, Susan E; Gerber, Jeffrey S; Fuchs, Barry; Garrigan, Charles; Han, Xiaoyan; Bilker, Warren B; Wise, Jacqueleen; Tolomeo, Pam; Lautenbach, Ebbing

2015-10-01

Sepsis remains a diagnostic challenge in the intensive care unit (ICU), and the use of biomarkers may help in differentiating bacterial sepsis from other causes of systemic inflammatory syndrome (SIRS). The goal of this study was to assess test characteristics of a number of biomarkers for identifying ICU patients with a very low likelihood of bacterial sepsis. A prospective cohort study was conducted in a medical ICU of a university hospital. Immunocompetent patients with presumed bacterial sepsis were consecutively enrolled from January 2012 to May 2013. Concentrations of nine biomarkers (α-2 macroglobulin, C-reactive protein [CRP], ferritin, fibrinogen, haptoglobin, procalcitonin [PCT], serum amyloid A, serum amyloid P, and tissue plasminogen activator) were determined at baseline and at 24 h, 48 h, and 72 h after enrollment. Performance characteristics were calculated for various combinations of biomarkers for discrimination of bacterial sepsis from other causes of SIRS. Seventy patients were included during the study period; 31 (44%) had bacterial sepsis, and 39 (56%) had other causes of SIRS. PCT and CRP values were significantly higher at all measured time points in patients with bacterial sepsis. A number of combinations of PCT and CRP, using various cutoff values and measurement time points, demonstrated high negative predictive values (81.1% to 85.7%) and specificities (63.2% to 79.5%) for diagnosing bacterial sepsis. Combinations of PCT and CRP demonstrated a high ability to discriminate bacterial sepsis from other causes of SIRS in medical ICU patients. Future studies should focus on the use of these algorithms to improve antibiotic use in the ICU setting. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Paleo-reconstruction: Using multiple biomarker parameters

NASA Astrophysics Data System (ADS)

Chen, Zhengzheng

Advanced technologies have played essential roles in the development of molecular organic geochemistry. In this thesis, we have developed several new techniques and explored their applications, alone and with previous techniques, to paleo-reconstruction. First, we developed a protocol to separate biomarker fractions for accurate measurement of compound-specific isotope analysis. This protocol involves combination of zeolite adduction and HPLC separation. Second, an integrated study of traditional biomarker parameters, diamondoids and compound-specific biomarker isotopes, differentiated oil groups from Saudi Arabia. Specifically, Cretaceous reservoired oils were divided into three groups and the Jurassic reservoired oils were divided into two groups. Third, biomarker acids provide an alternative way to characterize biodegradation. Oils from San Joaquin Valley, U.S.A. and oils from Mediterranean display drastically different acid profiles. These differences in biomarker acids probably reflect different processes of biodegradation. Fourth, by analyzing biomarker distributions in the organic-rich rocks recording the onset of Late Ordovician extinction, we propose that changes in salinity associated with eustatic sea-level fall, contributed at least locally to the extinction of graptolite species.

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.

Joint analysis of multiple biomarkers for identifying type 2 diabetes in middle-aged and older Chinese: a cross-sectional study

PubMed Central

Wu, Hongyu; Yu, Zhijie; Qi, Qibin; Li, Huaixing; Sun, Qi

2011-01-01

Objective Identifying individuals with high risk of type 2 diabetes is important. To evaluate discriminatory ability of multiple biomarkers for type 2 diabetes in a Chinese population. Methods Plasma adiponectin, plasminogen activator inhibitor-1, retinol-binding protein 4, resistin, C-reactive protein, interleukin 6 (IL-6), tumour necrosis factor α receptor 2 and ferritin were measured in a population-based sample of 3189 Chinese (1419 men and 1770 women) aged 50–70 years. A weighted biomarkers risk score (BRS) was developed based on the strength of associations of these biomarkers with type 2 diabetes. The discriminatory ability was tested by the area under receiver operating characteristics curve (AUC). Results Adiponectin, plasminogen activator inhibitor-1, IL-6 and ferritin were independently associated with the prevalence of type 2 diabetes, and they were used to calculate the biomarkers risk score (BRS). After adjustment for the confounding factors, the ORs for type 2 diabetes and impaired fasting glucose with each point increment of BRS were 1.28 (95% CI 1.22 to 1.34) and 1.16 (1.12 to 1.20), respectively. Compared with those in the lowest quintile of the BRS, the participants in the highest quintile have an OR (95% CI) of 6.67 (4.21 to 10.55) for type 2 diabetes. The area under the curve for the BRS and conventional risk factors alone was 0.73 and 0.76, respectively, and substantially increased to 0.81 after combining both BRS and conventional risk factors (p<0.001). Conclusions These data suggest that combining multiple biomarkers and conventional risk factors might substantially enhance the ability to identify individuals with type 2 diabetes. More prospective data are warranted to confirm this observation. PMID:22021786

Biomarkers intersect with the exposome

PubMed Central

Rappaport, Stephen M.

2016-01-01

The exposome concept promotes use of omic tools for discovering biomarkers of exposure and biomarkers of disease in studies of diseased and healthy populations. A two-stage scheme is presented for profiling omic features in serum to discover molecular biomarkers and then for applying these biomarkers in follow-up studies. The initial component, referred to as an exposome-wide-association study (EWAS), employs metabolomics and proteomics to interrogate the serum exposome and, ultimately, to identify, validate and differentiate biomarkers of exposure and biomarkers of disease. Follow-up studies employ knowledge-driven designs to explore disease causality, prevention, diagnosis, prognosis and treatment. PMID:22672124

Data-Driven Asthma Endotypes Defined from Blood Biomarker and Gene Expression Data

PubMed Central

George, Barbara Jane; Reif, David M.; Gallagher, Jane E.; Williams-DeVane, ClarLynda R.; Heidenfelder, Brooke L.; Hudgens, Edward E.; Jones, Wendell; Neas, Lucas; Hubal, Elaine A. Cohen; Edwards, Stephen W.

2015-01-01

The diagnosis and treatment of childhood asthma is complicated by its mechanistically distinct subtypes (endotypes) driven by genetic susceptibility and modulating environmental factors. Clinical biomarkers and blood gene expression were collected from a stratified, cross-sectional study of asthmatic and non-asthmatic children from Detroit, MI. This study describes four distinct asthma endotypes identified via a purely data-driven method. Our method was specifically designed to integrate blood gene expression and clinical biomarkers in a way that provides new mechanistic insights regarding the different asthma endotypes. For example, we describe metabolic syndrome-induced systemic inflammation as an associated factor in three of the four asthma endotypes. Context provided by the clinical biomarker data was essential in interpreting gene expression patterns and identifying putative endotypes, which emphasizes the importance of integrated approaches when studying complex disease etiologies. These synthesized patterns of gene expression and clinical markers from our research may lead to development of novel serum-based biomarker panels. PMID:25643280

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

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.

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

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

Fetal alcohol-spectrum disorders: identifying at-risk mothers

PubMed Central

Montag, Annika C

2016-01-01

Fetal alcohol-spectrum disorders (FASDs) are a collection of physical and neurobehavioral disabilities caused by prenatal exposure to alcohol. To prevent or mitigate the costly effects of FASD, we must identify mothers at risk for having a child with FASD, so that we may reach them with interventions. Identifying mothers at risk is beneficial at all time points, whether prior to pregnancy, during pregnancy, or following the birth of the child. In this review, three approaches to identifying mothers at risk are explored: using characteristics of the mother and her pregnancy, using laboratory biomarkers, and using self-report assessment of alcohol-consumption risk. At present, all approaches have serious limitations. Research is needed to improve the sensitivity and specificity of biomarkers and screening instruments, and to link them to outcomes as opposed to exposure. Universal self-report screening of all women of childbearing potential should ideally be incorporated into routine obstetric and gynecologic care, followed by brief interventions, including education and personalized feedback for all who consume alcohol, and referral to treatment as indicated. Effective biomarkers or combinations of biomarkers may be used during pregnancy and at birth to determine maternal and fetal alcohol exposure. The combination of self-report and biomarker screening may help identify a greater proportion of women at risk for having a child with FASD, allowing them to access information and treatment, and empowering them to make decisions that benefit their children. PMID:27499649

Blood biomarkers for brain injury: What are we measuring?

PubMed Central

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

2016-01-01

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

Classification of Genes and Putative Biomarker Identification Using Distribution Metrics on Expression Profiles

PubMed Central

Huang, Hung-Chung; Jupiter, Daniel; VanBuren, Vincent

2010-01-01

Background Identification of genes with switch-like properties will facilitate discovery of regulatory mechanisms that underlie these properties, and will provide knowledge for the appropriate application of Boolean networks in gene regulatory models. As switch-like behavior is likely associated with tissue-specific expression, these gene products are expected to be plausible candidates as tissue-specific biomarkers. Methodology/Principal Findings In a systematic classification of genes and search for biomarkers, gene expression profiles (GEPs) of more than 16,000 genes from 2,145 mouse array samples were analyzed. Four distribution metrics (mean, standard deviation, kurtosis and skewness) were used to classify GEPs into four categories: predominantly-off, predominantly-on, graded (rheostatic), and switch-like genes. The arrays under study were also grouped and examined by tissue type. For example, arrays were categorized as ‘brain group’ and ‘non-brain group’; the Kolmogorov-Smirnov distance and Pearson correlation coefficient were then used to compare GEPs between brain and non-brain for each gene. We were thus able to identify tissue-specific biomarker candidate genes. Conclusions/Significance The methodology employed here may be used to facilitate disease-specific biomarker discovery. PMID:20140228

Glycosylation Changes in Serum Proteins Identify Patients with Pancreatic Cancer.

PubMed

Drabik, Anna; Bodzon-Kulakowska, Anna; Suder, Piotr; Silberring, Jerzy; Kulig, Jan; Sierzega, Marek

2017-04-07

After more than a decade of biomarker discovery using advanced proteomic and genomic approaches, very few biomarkers have been involved in clinical diagnostics. Most candidate biomarkers are focused on the protein component. Targeting post-translational modifications (PTMs) in combination with protein sequences will provide superior diagnostic information with regards to sensitivity and specificity. Glycosylation is one of the most common and functionally important PTMs. It plays a central role in many biological processes, including protein folding, host-pathogen interactions, immune response, and inflammation. Cancer-associated aberrant glycosylation has been identified in various types of cancer. Expression of cancer-specific glycan epitopes represents an excellent opportunity for diagnostics and potentially specific detection of tumors. Here, we report four proteins (LIFR, CE350, VP13A, HPT) found in sera from pancreatic cancer patients carrying aberrant glycan structures as compared to those of controls.

Stool-based biomarkers of interstitial cystitis/bladder pain syndrome.

PubMed

Braundmeier-Fleming, A; Russell, Nathan T; Yang, Wenbin; Nas, Megan Y; Yaggie, Ryan E; Berry, Matthew; Bachrach, Laurie; Flury, Sarah C; Marko, Darlene S; Bushell, Colleen B; Welge, Michael E; White, Bryan A; Schaeffer, Anthony J; Klumpp, David J

2016-05-18

Interstitial cystitis/bladder pain syndrome (IC) is associated with significant morbidity, yet underlying mechanisms and diagnostic biomarkers remain unknown. Pelvic organs exhibit neural crosstalk by convergence of visceral sensory pathways, and rodent studies demonstrate distinct bacterial pain phenotypes, suggesting that the microbiome modulates pelvic pain in IC. Stool samples were obtained from female IC patients and healthy controls, and symptom severity was determined by questionnaire. Operational taxonomic units (OTUs) were identified by16S rDNA sequence analysis. Machine learning by Extended Random Forest (ERF) identified OTUs associated with symptom scores. Quantitative PCR of stool DNA with species-specific primer pairs demonstrated significantly reduced levels of E. sinensis, C. aerofaciens, F. prausnitzii, O. splanchnicus, and L. longoviformis in microbiota of IC patients. These species, deficient in IC pelvic pain (DIPP), were further evaluated by Receiver-operator characteristic (ROC) analyses, and DIPP species emerged as potential IC biomarkers. Stool metabolomic studies identified glyceraldehyde as significantly elevated in IC. Metabolomic pathway analysis identified lipid pathways, consistent with predicted metagenome functionality. Together, these findings suggest that DIPP species and metabolites may serve as candidates for novel IC biomarkers in stool. Functional changes in the IC microbiome may also serve as therapeutic targets for treating chronic pelvic pain.

Rapid Point-Of-Care Breath Test for Biomarkers of Breast Cancer and Abnormal Mammograms

PubMed Central

Phillips, Michael; Beatty, J. David; Cataneo, Renee N.; Huston, Jan; Kaplan, Peter D.; Lalisang, Roy I.; Lambin, Philippe; Lobbes, Marc B. I.; Mundada, Mayur; Pappas, Nadine; Patel, Urvish

2014-01-01

Background Previous studies have reported volatile organic compounds (VOCs) in breath as biomarkers of breast cancer and abnormal mammograms, apparently resulting from increased oxidative stress and cytochrome p450 induction. We evaluated a six-minute point-of-care breath test for VOC biomarkers in women screened for breast cancer at centers in the USA and the Netherlands. Methods 244 women had a screening mammogram (93/37 normal/abnormal) or a breast biopsy (cancer/no cancer 35/79). A mobile point-of-care system collected and concentrated breath and air VOCs for analysis with gas chromatography and surface acoustic wave detection. Chromatograms were segmented into a time series of alveolar gradients (breath minus room air). Segmental alveolar gradients were ranked as candidate biomarkers by C-statistic value (area under curve [AUC] of receiver operating characteristic [ROC] curve). Multivariate predictive algorithms were constructed employing significant biomarkers identified with multiple Monte Carlo simulations and cross validated with a leave-one-out (LOO) procedure. Results Performance of breath biomarker algorithms was determined in three groups: breast cancer on biopsy versus normal screening mammograms (81.8% sensitivity, 70.0% specificity, accuracy 79% (73% on LOO) [C-statistic value], negative predictive value 99.9%); normal versus abnormal screening mammograms (86.5% sensitivity, 66.7% specificity, accuracy 83%, 62% on LOO); and cancer versus no cancer on breast biopsy (75.8% sensitivity, 74.0% specificity, accuracy 78%, 67% on LOO). Conclusions A pilot study of a six-minute point-of-care breath test for volatile biomarkers accurately identified women with breast cancer and with abnormal mammograms. Breath testing could potentially reduce the number of needless mammograms without loss of diagnostic sensitivity. PMID:24599224

Paraneoplastic Antigen Ma2 Autoantibodies as Specific Blood Biomarkers for Detection of Early Recurrence of Small Intestine Neuroendocrine Tumors

PubMed Central

Cui, Tao; Hurtig, Monica; Elgue, Graciela; Li, Su-Chen; Veronesi, Giulia; Essaghir, Ahmed; Demoulin, Jean-Baptiste; Pelosi, Giuseppe; Alimohammadi, Mohammad; Öberg, Kjell; Giandomenico, Valeria

2010-01-01

Background Small intestine neuroendocrine tumors (SI-NETs) belong to a rare group of cancers. Most patients have developed metastatic disease at the time of diagnosis, for which there is currently no cure. The delay in diagnosis is a major issue in the clinical management of the patients and new markers are urgently needed. We have previously identified paraneoplastic antigen Ma2 (PNMA2) as a novel SI-NET tissue biomarker. Therefore, we evaluated whether Ma2 autoantibodies detection in the blood stream is useful for the clinical diagnosis and recurrence of SI-NETs. Methodology/Principal Findings A novel indirect ELISA was set up to detect Ma2 autoantibodies in blood samples of patients with SI-NET at different stages of disease. The analysis was extended to include typical and atypical lung carcinoids (TLC and ALC), to evaluate whether Ma2 autoantibodies in the blood stream become a general biomarker for NETs. In total, 124 blood samples of SI-NET patients at different stages of disease were included in the study. The novel Ma2 autoantibody ELISA showed high sensitivity, specificity and accuracy with ROC curve analysis underlying an area between 0.734 and 0.816. Ma2 autoantibodies in the blood from SI-NET patients were verified by western blot and sequential immunoprecipitation. Serum antibodies of patients stain Ma2 in the tumor tissue and neurons. We observed that SI-NET patients expressing Ma2 autoantibody levels below the cutoff had a longer progression and recurrence-free survival compared to those with higher titer. We also detected higher levels of Ma2 autoantibodies in blood samples from TLC and ALC patients than from healthy controls, as previously shown in small cell lung carcinoma samples. Conclusion Here we show that high Ma2 autoantibody titer in the blood of SI-NET patients is a sensitive and specific biomarker, superior to chromogranin A (CgA) for the risk of recurrence after radical operation of these tumors. PMID:21209860

Paraneoplastic antigen Ma2 autoantibodies as specific blood biomarkers for detection of early recurrence of small intestine neuroendocrine tumors.

PubMed

Cui, Tao; Hurtig, Monica; Elgue, Graciela; Li, Su-Chen; Veronesi, Giulia; Essaghir, Ahmed; Demoulin, Jean-Baptiste; Pelosi, Giuseppe; Alimohammadi, Mohammad; Öberg, Kjell; Giandomenico, Valeria

2010-12-30

Small intestine neuroendocrine tumors (SI-NETs) belong to a rare group of cancers. Most patients have developed metastatic disease at the time of diagnosis, for which there is currently no cure. The delay in diagnosis is a major issue in the clinical management of the patients and new markers are urgently needed. We have previously identified paraneoplastic antigen Ma2 (PNMA2) as a novel SI-NET tissue biomarker. Therefore, we evaluated whether Ma2 autoantibodies detection in the blood stream is useful for the clinical diagnosis and recurrence of SI-NETs. A novel indirect ELISA was set up to detect Ma2 autoantibodies in blood samples of patients with SI-NET at different stages of disease. The analysis was extended to include typical and atypical lung carcinoids (TLC and ALC), to evaluate whether Ma2 autoantibodies in the blood stream become a general biomarker for NETs. In total, 124 blood samples of SI-NET patients at different stages of disease were included in the study. The novel Ma2 autoantibody ELISA showed high sensitivity, specificity and accuracy with ROC curve analysis underlying an area between 0.734 and 0.816. Ma2 autoantibodies in the blood from SI-NET patients were verified by western blot and sequential immunoprecipitation. Serum antibodies of patients stain Ma2 in the tumor tissue and neurons. We observed that SI-NET patients expressing Ma2 autoantibody levels below the cutoff had a longer progression and recurrence-free survival compared to those with higher titer. We also detected higher levels of Ma2 autoantibodies in blood samples from TLC and ALC patients than from healthy controls, as previously shown in small cell lung carcinoma samples. Here we show that high Ma2 autoantibody titer in the blood of SI-NET patients is a sensitive and specific biomarker, superior to chromogranin A (CgA) for the risk of recurrence after radical operation of these tumors.

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.

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy.

PubMed

Karamzadeh, Nader; Amyot, Franck; Kenney, Kimbra; Anderson, Afrouz; Chowdhry, Fatima; Dashtestani, Hadis; Wassermann, Eric M; Chernomordik, Victor; Boccara, Claude; Wegman, Edward; Diaz-Arrastia, Ramon; Gandjbakhche, Amir H

2016-11-01

We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

Diagnosis of rheumatoid arthritis: multivariate analysis of biomarkers.

PubMed

Wild, Norbert; Karl, Johann; Grunert, Veit P; Schmitt, Raluca I; Garczarek, Ursula; Krause, Friedemann; Hasler, Fritz; van Riel, Piet L C M; Bayer, Peter M; Thun, Matthias; Mattey, Derek L; Sharif, Mohammed; Zolg, Werner

2008-02-01

To test if a combination of biomarkers can increase the classification power of autoantibodies to cyclic citrullinated peptides (anti-CCP) in the diagnosis of rheumatoid arthritis (RA) depending on the diagnostic situation. Biomarkers were subject to three inclusion/exclusion criteria (discrimination between RA patients and healthy blood donors, ability to identify anti-CCP-negative RA patients, specificity in a panel with major non-rheumatological diseases) before univariate ranking and multivariate analysis was carried out using a modelling panel (n = 906). To enable the evaluation of the classification power in different diagnostic settings the disease controls (n = 542) were weighted according to the admission rates in rheumatology clinics modelling a clinic panel or according to the relative prevalences of musculoskeletal disorders in the general population seen by general practitioners modelling a GP panel. Out of 131 biomarkers considered originally, we evaluated 32 biomarkers in this study, of which only seven passed the three inclusion/exclusion criteria and were combined by multivariate analysis using four different mathematical models. In the modelled clinic panel, anti-CCP was the lead marker with a sensitivity of 75.8% and a specificity of 94.0%. Due to the lack in specificity of the markers other than anti-CCP in this diagnostic setting, any gain in sensitivity by any marker combination is off-set by a corresponding loss in specificity. In the modelled GP panel, the best marker combination of anti-CCP and interleukin (IL)-6 resulted in a sensitivity gain of 7.6% (85.9% vs. 78.3%) at a minor loss in specificity of 1.6% (90.3% vs. 91.9%) compared with anti-CCP as the best single marker. Depending on the composition of the sample panel, anti-CCP alone or anti-CCP in combination with IL-6 has the highest classification power for the diagnosis of established RA.

Leveraging sequence-based faecal microbial community survey data to identify a composite biomarker for colorectal cancer.

PubMed

Shah, Manasi S; DeSantis, Todd Z; Weinmaier, Thomas; McMurdie, Paul J; Cope, Julia L; Altrichter, Adam; Yamal, Jose-Miguel; Hollister, Emily B

2018-05-01

Colorectal cancer (CRC) is the second leading cause of cancer-associated mortality in the USA. The faecal microbiome may provide non-invasive biomarkers of CRC and indicate transition in the adenoma-carcinoma sequence. Re-analysing raw sequence and metadata from several studies uniformly, we sought to identify a composite and generalisable microbial marker for CRC. Raw 16S rRNA gene sequence data sets from nine studies were processed with two pipelines, (1) QIIME closed reference (QIIME-CR) or (2) a strain-specific method herein termed SS-UP (Strain Select, UPARSE bioinformatics pipeline). A total of 509 samples (79 colorectal adenoma, 195 CRC and 235 controls) were analysed. Differential abundance, meta-analysis random effects regression and machine learning analyses were carried out to determine the consistency and diagnostic capabilities of potential microbial biomarkers. Definitive taxa, including Parvimonas micra ATCC 33270, Streptococcus anginosus and yet-to-be-cultured members of Proteobacteria, were frequently and significantly increased in stools from patients with CRC compared with controls across studies and had high discriminatory capacity in diagnostic classification. Microbiome-based CRC versus control classification produced an area under receiver operator characteristic (AUROC) curve of 76.6% in QIIME-CR and 80.3% in SS-UP. Combining clinical and microbiome markers gave a diagnostic AUROC of 83.3% for QIIME-CR and 91.3% for SS-UP. Despite technological differences across studies and methods, key microbial markers emerged as important in classifying CRC cases and such could be used in a universal diagnostic for the disease. The choice of bioinformatics pipeline influenced accuracy of classification. Strain-resolved microbial markers might prove crucial in providing a microbial diagnostic for CRC. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

NYU Lung Cancer Biomarker Center — EDRN Public Portal

Cancer.gov

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

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

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

PubMed Central

Nielson, Jessica L.; Cooper, Shelly R.; Sorani, Marco D.; Inoue, Tomoo; Yuh, Esther L.; Mukherjee, Pratik; Petrossian, Tanya C.; Lum, Pek Y.; Lingsma, Hester F.; Gordon, Wayne A.; Okonkwo, David O.; Manley, Geoffrey T.

2017-01-01

Background Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust

Cardiovascular biomarkers and sex: the case for women.

PubMed

Daniels, Lori B; Maisel, Alan S

2015-10-01

Measurement of biomarkers is a critical component of cardiovascular care. Women and men differ in their cardiac physiology and manifestations of cardiovascular disease. Although most cardiovascular biomarkers are used by clinicians without taking sex into account, sex-specific differences in biomarkers clearly exist. Baseline concentrations of many biomarkers (including cardiac troponin, natriuretic peptides, galectin-3, and soluble ST2) differ in men versus women, but these sex-specific differences do not generally translate into a need for differential sex-based cut-off points. Furthermore, most biomarkers are similarly diagnostic and prognostic, regardless of sex. Two potential exceptions are cardiac troponins measured by high-sensitivity assay, and proneurotensin. Troponin levels are lower in women than in men and, with the use of high-sensitivity assays, sex-specific cut-off points might improve the diagnosis of myocardial infarction. Proneurotensin is a novel biomarker that was found to be predictive of incident cardiovascular disease in women, but not men, and was also predictive of incident breast cancer. If confirmed, proneurotensin might be a unique biomarker of disease risk in women. With any biomarker, an understanding of sex-specific differences might improve its use and might also lead to an enhanced understanding of the physiological differences between the hearts of men and women.

Biomarker Qualification: Toward a Multiple Stakeholder Framework for Biomarker Development, Regulatory Acceptance, and Utilization.

PubMed

Amur, S; LaVange, L; Zineh, I; Buckman-Garner, S; Woodcock, J

2015-07-01

The discovery, development, and use of biomarkers for a variety of drug development purposes are areas of tremendous interest and need. Biomarkers can become accepted for use through submission of biomarker data during the drug approval process. Another emerging pathway for acceptance of biomarkers is via the biomarker qualification program developed by the Center for Drug Evaluation and Research (CDER, US Food and Drug Administration). Evidentiary standards are needed to develop and evaluate various types of biomarkers for their intended use and multiple stakeholders, including academia, industry, government, and consortia must work together to help develop this evidence. The article describes various types of biomarkers that can be useful in drug development and evidentiary considerations that are important for qualification. A path forward for coordinating efforts to identify and explore needed biomarkers is proposed for consideration. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Consensus Paper: Radiological Biomarkers of Cerebellar Diseases

PubMed Central

Baldarçara, Leonardo; Currie, Stuart; Hadjivassiliou, M.; Hoggard, Nigel; Jack, Allison; Jackowski, Andrea P.; Mascalchi, Mario; Parazzini, Cecilia; Reetz, Kathrin; Righini, Andrea; Schulz, Jörg B.; Vella, Alessandra; Webb, Sara Jane; Habas, Christophe

2016-01-01

Hereditary and sporadic cerebellar ataxias represent a vast and still growing group of diseases whose diagnosis and differentiation cannot only rely on clinical evaluation. Brain imaging including magnetic resonance (MR) and nuclear medicine techniques allows for characterization of structural and functional abnormalities underlying symptomatic ataxias. These methods thus constitute a potential source of radiological biomarkers, which could be used to identify these diseases and differentiate subgroups of them, and to assess their severity and their evolution. Such biomarkers mainly comprise qualitative and quantitative data obtained from MR including proton spectroscopy, diffusion imaging, tractography, voxel-based morphometry, functional imaging during task execution or in a resting state, and from SPETC and PET with several radiotracers. In the current article, we aim to illustrate briefly some applications of these neuroimaging tools to evaluation of cerebellar disorders such as inherited cerebellar ataxia, fetal developmental malformations, and immune-mediated cerebellar diseases and of neurodegenerative or early-developing diseases, such as dementia and autism in which cerebellar involvement is an emerging feature. Although these radiological biomarkers appear promising and helpful to better understand ataxia-related anatomical and physiological impairments, to date, very few of them have turned out to be specific for a given ataxia with atrophy of the cerebellar system being the main and the most usual alteration being observed. Consequently, much remains to be done to establish sensitivity, specificity, and reproducibility of available MR and nuclear medicine features as diagnostic, progression and surrogate biomarkers in clinical routine. PMID:25382714

Plasma microvesicle analysis identifies microRNA 129-5p as a biomarker of heart failure in univentricular heart disease.

PubMed

Ramachandran, Sweta; Lowenthal, Alexander; Ritner, Carissa; Lowenthal, Shiri; Bernstein, Harold S

2017-01-01

Biomarkers of heart failure in adults have been extensively studied. However, biomarkers to monitor the progression of heart failure in children with univentricular physiology are less well understood. We proposed that as mediators of diverse pathophysiology, miRNAs contained within circulating microvesicles could serve as biomarkers for the presence and progression of heart failure in univentricular patients. To test this, we studied the association of heart failure with elevations in specific miRNAs isolated from circulating microvesicles in a cohort of children with univentricular heart disease and heart failure. We conducted a single site cross-sectional observational study of 71 children aged 1 month-7 years with univentricular heart disease and heart failure. We demonstrated that levels of miR129-5p isolated from plasma microvesicles were inversely related to the degree of clinical heart failure as assessed by Ross score. We then showed that miR129-5p levels are downregulated in HL1 cells and human embryonic stem cell-derived cardiomyocytes exposed to oxidative stress. We demonstrated that bone morphogenetic protein receptor 2, which has been implicated in the development of pulmonary vascular disease, is a target of miR129-5p, and conversely regulated in response to oxidative stress in cell culture. Levels of miR129-5p were inversely related to the degree of clinical heart failure in patients with univentricular heart disease. This study demonstrates that miR129-5p is a sensitive and specific biomarker for heart failure in univentricular heart disease independent of ventricular morphology or stage of palliation. Further study is warranted to understand the targets affected by miR129-5p with the development of heart failure in patients with univentricular physiology.

Placenta-derived exosomes: potential biomarkers of preeclampsia.

PubMed

Pillay, Preenan; Moodley, Kogi; Moodley, Jagidesa; Mackraj, Irene

2017-01-01

Preeclampsia remains a leading cause of maternal and fetal mortality, due to ineffective treatment and diagnostic strategies, compounded by the lack of clarity on the etiology of the disorder. Although several clinical and biological markers of preeclampsia have been evaluated, they have proven to be ineffective in providing a definitive diagnosis during the various stages of the disorder. Exosomes have emerged as ideal biomarkers of pathological states, such as cancer, and have more recently gained interest in pregnancy-related complications, due to their role in cellular communication in normal and complicated pregnancies. This occurs as a result of the specific placenta-derived exosomal molecular cargo, which may be involved in normal pregnancy-associated immunological events, such as the maintenance of maternal-fetal tolerance. This review provides perspectives on placenta-derived exosomes as possible biomarkers for the diagnosis/prognosis of preeclampsia. Using keywords, online databases were searched to identify relevant publications to review the potential use of placenta-derived exosomes as biomarkers of preeclampsia.

USING ARRAY TECHNOLOGY TO IDENTIFY POTENTIAL BIOMARKERS FOR PYRETHROID INSECTICIDES.

EPA Science Inventory

Pyrethroid insecticides affect nervous system function by disruption of sodium channels in nerve membranes. FQPA requirements for assessing cumulative risk have increased the need for rapid and sensitive biomarkers of effect. This project aims to develop biochemical markers of n...

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.

Composition and dynamics of cutin and suberin biomarkers in plants and soils under agricultural use

NASA Astrophysics Data System (ADS)

María Armas-Herrera, Cecilia; Dignac, Marie-France; Rumpel, Cornelia; Arvelo, Carmen Dolores; Chabbi, Abad

2017-04-01

Cutins of plant shoots, and suberins, mostly present in roots, may act as potential biomarkers for aboveground and belowground biomass of non-woody plants. The aim of this work was to evaluate the dynamics of specific root and shoot biomarkers after land-use changes from grass to an arable land. We (i) identified and quantified specific biomarkers of cutin and suberin of three grassland species (Dactylis glomerata L., Festuca arundinacea Schreb. and Lolium perenne L.), (ii) investigated the composition of cutin and suberin in soil under different land uses (continuous and temporary grassland, arable and bare soil) of the SOERE-ACBB experimental site in Lusignan (France) and (iii) used natural 13C isotope abundances to follow the fate of cutin and suberin specific markers in soil after conversion from grassland (C3 plants) to arable land (maize, C4 plants). Our results indicated that 9-hydroxy hexadecanedioic acid and 8(9)(10),16-dihydroxy hexadecanoic acid may be used as biomarkers for aboveground biomass, whereas 1,22-docosandioic acid, 22-hydroxy docosanoic acid and 24-hydroxy tetracosanoic acid may be the most adequate belowground biomarkers for the plants investigated under the experimental conditions studied. There were marked differences in monomer composition, abundance and patterns of shoot-root allocation of these biomarkers in the plant species analysed, which demonstrates the importance to identify specific cutin and suberin biomarkers for each plant species to study the incorporation of their biomass into SOM. Cutin and suberin marker contents followed the same trends as the biomass inputs to soil: they were the highest in soils cultivated with maize and the lowest in bare soils. We found no differences in the amounts of cutin and suberin markers in soil under continuous and temporary grassland, which might indicate that the disturbance caused by conversion from grassland to cropland was transitory only. In addition, suberin marker contents decreased by

Chemical and metabolomic screens identify novel biomarkers and antidotes for cyanide exposure

PubMed Central

Nath, Anjali K.; Roberts, Lee D.; Liu, Yan; Mahon, Sari B.; Kim, Sonia; Ryu, Justine H.; Werdich, Andreas; Januzzi, James L.; Boss, Gerry R.; Rockwood, Gary A.; MacRae, Calum A.; Brenner, Matthew; Gerszten, Robert E.; Peterson, Randall T.

2013-01-01

Exposure to cyanide causes a spectrum of cardiac, neurological, and metabolic dysfunctions that can be fatal. Improved cyanide antidotes are needed, but the ideal biological pathways to target are not known. To understand better the metabolic effects of cyanide and to discover novel cyanide antidotes, we developed a zebrafish model of cyanide exposure and scaled it for high-throughput chemical screening. In a screen of 3120 small molecules, we discovered 4 novel antidotes that block cyanide toxicity. The most potent antidote was riboflavin. Metabolomic profiling of cyanide-treated zebrafish revealed changes in bile acid and purine metabolism, most notably by an increase in inosine levels. Riboflavin normalizes many of the cyanide-induced neurological and metabolic perturbations in zebrafish. The metabolic effects of cyanide observed in zebrafish were conserved in a rabbit model of cyanide toxicity. Further, humans treated with nitroprusside, a drug that releases nitric oxide and cyanide ions, display increased circulating bile acids and inosine. In summary, riboflavin may be a novel treatment for cyanide toxicity and prophylactic measure during nitroprusside treatment, inosine may serve as a biomarker of cyanide exposure, and metabolites in the bile acid and purine metabolism pathways may shed light on the pathways critical to reversing cyanide toxicity.—Nath, A. K., Roberts, L. D., Liu, Y., Mahon, S. B., Kim, S., Ryu, J. H., Werdich, A., Januzzi, J. L., Boss, G. R., Rockwood, G. A., MacRae, C. A., Brenner, M., Gerszten, R. E., Peterson, R. T. Chemical and metabolomic screens identify novel biomarkers and antidotes for cyanide exposure. PMID:23345455

The low-abundance transcriptome reveals novel biomarkers, specific intracellular pathways and targetable genes associated with advanced gastric cancer.

PubMed

Bizama, Carolina; Benavente, Felipe; Salvatierra, Edgardo; Gutiérrez-Moraga, Ana; Espinoza, Jaime A; Fernández, Elmer A; Roa, Iván; Mazzolini, Guillermo; Sagredo, Eduardo A; Gidekel, Manuel; Podhajcer, Osvaldo L

2014-02-15

Studies on the low-abundance transcriptome are of paramount importance for identifying the intimate mechanisms of tumor progression that can lead to novel therapies. The aim of the present study was to identify novel markers and targetable genes and pathways in advanced human gastric cancer through analyses of the low-abundance transcriptome. The procedure involved an initial subtractive hybridization step, followed by global gene expression analysis using microarrays. We observed profound differences, both at the single gene and gene ontology levels, between the low-abundance transcriptome and the whole transcriptome. Analysis of the low-abundance transcriptome led to the identification and validation by tissue microarrays of novel biomarkers, such as LAMA3 and TTN; moreover, we identified cancer type-specific intracellular pathways and targetable genes, such as IRS2, IL17, IFNγ, VEGF-C, WISP1, FZD5 and CTBP1 that were not detectable by whole transcriptome analyses. We also demonstrated that knocking down the expression of CTBP1 sensitized gastric cancer cells to mainstay chemotherapeutic drugs. We conclude that the analysis of the low-abundance transcriptome provides useful insights into the molecular basis and treatment of cancer. © 2013 UICC.

Biomarkers of sepsis

PubMed Central

2013-01-01

Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. A hyper-inflammatory response is followed by an immunosuppressive phase during which multiple organ dysfunction is present and the patient is susceptible to nosocomial infection. Biomarkers to diagnose sepsis may allow early intervention which, although primarily supportive, can reduce the risk of death. Although lactate is currently the most commonly used biomarker to identify sepsis, other biomarkers may help to enhance lactate’s effectiveness; these include markers of the hyper-inflammatory phase of sepsis, such as pro-inflammatory cytokines and chemokines; proteins such as C-reactive protein and procalcitonin which are synthesized in response to infection and inflammation; and markers of neutrophil and monocyte activation. Recently, markers of the immunosuppressive phase of sepsis, such as anti-inflammatory cytokines, and alterations of the cell surface markers of monocytes and lymphocytes have been examined. Combinations of pro- and anti-inflammatory biomarkers in a multi-marker panel may help identify patients who are developing severe sepsis before organ dysfunction has advanced too far. Combined with innovative approaches to treatment that target the immunosuppressive phase, these biomarkers may help to reduce the mortality rate associated with severe sepsis which, despite advances in supportive measures, remains high. PMID:23480440

Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib

PubMed Central

Li, Bin; Shin, Hyunjin; Gulbekyan, Georgy; Pustovalova, Olga; Nikolsky, Yuri; Hope, Andrew; Bessarabova, Marina; Schu, Matthew; Kolpakova-Hart, Elona; Merberg, David; Dorner, Andrew; Trepicchio, William L.

2015-01-01

Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug’s known mechanism of action. Also, the models predict each drug’s potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets. PMID:26107615

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.

Volatile organic compounds as biomarkers of bladder cancer: Sensitivity and specificity using trained sniffer dogs.

PubMed

Willis, Carolyn M; Britton, Lezlie E; Harris, Rob; Wallace, Joshua; Guest, Claire M

In a previous canine study, we demonstrated that volatile organic compounds specific to bladder cancer are present in urine headspace, subsequently showing that up to 70% of tumours can be correctly classified using an electronic nose. This study aimed to evaluate the sensitivity and specificity which can be achieved by a group of four trained dogs. In a series of 30 double-blind test runs, each consisting of one bladder cancer urine sample placed alongside six controls, the highest sensitivity achieved by the best performing dog was 73% (95% CI 55-86%), with the group as a whole correctly identifying the cancer samples 64% (95% CI 55-73%) of the time. Specificity of the dogs individually ranged from 92% (95% CI 82-97%) for urine samples obtained from healthy, young volunteers down to 56% (95% CI 42-68%) for those taken from older patients with non-cancerous urological disease. Odds ratio comparisons confirmed a significant decrease in performance as the extent of urine dipstick abnormality and/or pathology amongst the control population increased. Importantly, however, statistical analysis indicated that covariates such as smoking, gender and age, as well as blood, protein and /or leucocytes in the urine did not significantly alter the odds of response to the cancer samples. Our results provide further evidence that volatile biomarkers for bladder cancer exist in urine headspace, and that these have the potential to be exploited for diagnosis.

Identifying biomarkers of papillary renal cell carcinoma associated with pathological stage by weighted gene co-expression network analysis.

PubMed

He, Zhongshi; Sun, Min; Ke, Yuan; Lin, Rongjie; Xiao, Youde; Zhou, Shuliang; Zhao, Hong; Wang, Yan; Zhou, Fuxiang; Zhou, Yunfeng

2017-04-25

Although papillary renal cell carcinoma (PRCC) accounts for 10%-15% of renal cell carcinoma (RCC), no predictive molecular biomarker is currently applicable to guiding disease stage of PRCC patients. The mRNASeq data of PRCC and adjacent normal tissue in The Cancer Genome Atlas was analyzed to identify 1148 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 11 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = 0.45) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on nuclear division, cell cycle phase, and spindle (all P < 1e-10). All 40 hub genes in blue module can distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) PRCC (P < 0.01). A good molecular biomarker for pathological stage of RCC must be a prognostic gene in clinical practice. Survival analysis was performed to reversely validate if hub genes were associated with pathological stage. Survival analysis unveiled that all hub genes were associated with patient prognosis (P < 0.01).The validation cohort GSE2748 verified that 30 hub genes can differentiate localized from non-localized PRCC (P < 0.01), and 18 hub genes are prognosis-associated (P < 0.01).ROC curve indicated that the 17 hub genes exhibited excellent diagnostic efficiency for localized and non-localized PRCC (AUC > 0.7). These hub genes may serve as a biomarker and help to distinguish different pathological stages for PRCC patients.

NCC-AUC: an AUC optimization method to identify multi-biomarker panel for cancer prognosis from genomic and clinical data.

PubMed

Zou, Meng; Liu, Zhaoqi; Zhang, Xiang-Sun; Wang, Yong

2015-10-15

In prognosis and survival studies, an important goal is to identify multi-biomarker panels with predictive power using molecular characteristics or clinical observations. Such analysis is often challenged by censored, small-sample-size, but high-dimensional genomic profiles or clinical data. Therefore, sophisticated models and algorithms are in pressing need. In this study, we propose a novel Area Under Curve (AUC) optimization method for multi-biomarker panel identification named Nearest Centroid Classifier for AUC optimization (NCC-AUC). Our method is motived by the connection between AUC score for classification accuracy evaluation and Harrell's concordance index in survival analysis. This connection allows us to convert the survival time regression problem to a binary classification problem. Then an optimization model is formulated to directly maximize AUC and meanwhile minimize the number of selected features to construct a predictor in the nearest centroid classifier framework. NCC-AUC shows its great performance by validating both in genomic data of breast cancer and clinical data of stage IB Non-Small-Cell Lung Cancer (NSCLC). For the genomic data, NCC-AUC outperforms Support Vector Machine (SVM) and Support Vector Machine-based Recursive Feature Elimination (SVM-RFE) in classification accuracy. It tends to select a multi-biomarker panel with low average redundancy and enriched biological meanings. Also NCC-AUC is more significant in separation of low and high risk cohorts than widely used Cox model (Cox proportional-hazards regression model) and L1-Cox model (L1 penalized in Cox model). These performance gains of NCC-AUC are quite robust across 5 subtypes of breast cancer. Further in an independent clinical data, NCC-AUC outperforms SVM and SVM-RFE in predictive accuracy and is consistently better than Cox model and L1-Cox model in grouping patients into high and low risk categories. In summary, NCC-AUC provides a rigorous optimization framework to

Serum miR-206 and other muscle-specific microRNAs as non-invasive biomarkers for Duchenne muscular dystrophy.

PubMed

Hu, Jun; Kong, Min; Ye, Yuanzhen; Hong, Siqi; Cheng, Li; Jiang, Li

2014-06-01

Creatine kinase has been utilized as a diagnostic marker for Duchenne muscular dystrophy (DMD), but it correlates less well with the DMD pathological progression. In this study, we hypothesized that muscle-specific microRNAs (miR-1, -133, and -206) in serum may be useful for monitoring the DMD pathological progression, and explored the possibility of these miRNAs as potential non-invasive biomarkers for the disease. By using real-time quantitative reverse transcription-polymerase chain reaction in a randomized and controlled trial, we detected that miR-1, -133, and -206 were significantly over-expressed in the serum of 39 children with DMD (up to 3.20 ± 1.20, 2(-ΔΔCt) ): almost 2- to 4-fold enriched in comparison to samples from the healthy controls (less than 1.15 ± 0.34, 2(-ΔΔCt) ). To determine whether these miRNAs were related to the clinical features of children with DMD, we analyzed the associations compared to creatine kinase. There were very good inverse correlations between the levels of these miRNAs, especially miR-206, and functional performances: high levels corresponded to low muscle strength, muscle function, and quality of life. Moreover, by receiver operating characteristic curves analyses, we revealed that these miRNAs, especially miR-206, were able to discriminate DMD from controls. Thus, miR-206 and other muscle-specific miRNAs in serum are useful for monitoring the DMD pathological progression, and hence as potential non-invasive biomarkers for the disease. There has been a long-standing need for reliable, non-invasive biomarkers for Duchenne muscular dystrophy (DMD). We found that the levels of muscle-specific microRNAs, especially miR-206, in the serum of DMD were 2- to 4-fold higher than in the controls. High levels corresponded to low muscle strength, muscle function, and quality of life (QoL). These miRNAs were able to discriminate DMD from controls by receiver operating characteristic (ROC) curves analyses. Thus, miR-206 and other

Biomarkers of gluten sensitivity in patients with non-affective psychosis: a meta-analysis.

PubMed

Lachance, Laura R; McKenzie, Kwame

2014-02-01

Dohan first proposed that there may be an association between gluten sensitivity and schizophrenia in the 1950s. Since then, this association has been measured using several different serum biomarkers of gluten sensitivity. At this point, it is unclear which serum biomarkers of gluten sensitivity are elevated in patients with schizophrenia. However, evidence suggests that the immune response in this group is different from the immune response to gluten found in patients with Celiac disease. A systematic literature review was performed to identify all original articles that measured biomarkers of gluten sensitivity in patients with schizophrenia and non-affective psychoses compared to a control group. Three databases were used: Ovid MEDLINE, Psych INFO, and Embase, dating back to 1946. Forward tracking and backward tracking were undertaken on retrieved papers. A meta-analysis was performed of specific biomarkers and reported according to MOOSE guidelines. 17 relevant original articles were identified, and 12 met criteria for the meta-analysis. Five biomarkers of gluten sensitivity were found to be significantly elevated in patients with non-affective psychoses compared to controls. The pooled odds ratio and 95% confidence intervals were Anti-Gliadin IgG OR=2.31 [1.16, 4.58], Anti-Gliadin IgA OR=2.57 [1.13, 5.82], Anti-TTG2 IgA OR=5.86 [2.88, 11.95], Anti-Gliadin (unspecified isotype) OR=7.68 [2.07, 28.42], and Anti-Wheat OR=2.74 [1.06, 7.08]. Four biomarkers for gluten sensitivity, Anti-EMA IgA, Anti-TTG2 IgG, Anti-DGP IgG, and Anti-Gluten were not found to be associated with schizophrenia. Not all serum biomarkers of gluten sensitivity are elevated in patients with schizophrenia. However, the specific immune response to gluten in this population differs from that found in patients with Celiac disease. Copyright © 2013 Elsevier B.V. All rights reserved.

Biomarker microRNAs for prostate cancer metastasis: screened with a network vulnerability analysis model.

PubMed

Lin, Yuxin; Chen, Feifei; Shen, Li; Tang, Xiaoyu; Du, Cui; Sun, Zhandong; Ding, Huijie; Chen, Jiajia; Shen, Bairong

2018-05-21

Prostate cancer (PCa) is a fatal malignant tumor among males in the world and the metastasis is a leading cause for PCa death. Biomarkers are therefore urgently needed to detect PCa metastatic signature at the early time. MicroRNAs are small non-coding RNAs with the potential to be biomarkers for disease prediction. In addition, computer-aided biomarker discovery is now becoming an attractive paradigm for precision diagnosis and prognosis of complex diseases. In this study, we identified key microRNAs as biomarkers for predicting PCa metastasis based on network vulnerability analysis. We first extracted microRNAs and mRNAs that were differentially expressed between primary PCa and metastatic PCa (MPCa) samples. Then we constructed the MPCa-specific microRNA-mRNA network and screened microRNA biomarkers by a novel bioinformatics model. The model emphasized the characterization of systems stability changes and the network vulnerability with three measurements, i.e. the structurally single-line regulation, the functional importance of microRNA targets and the percentage of transcription factor genes in microRNA unique targets. With this model, we identified five microRNAs as putative biomarkers for PCa metastasis. Among them, miR-101-3p and miR-145-5p have been previously reported as biomarkers for PCa metastasis and the remaining three, i.e. miR-204-5p, miR-198 and miR-152, were screened as novel biomarkers for PCa metastasis. The results were further confirmed by the assessment of their predictive power and biological function analysis. Five microRNAs were identified as candidate biomarkers for predicting PCa metastasis based on our network vulnerability analysis model. The prediction performance, literature exploration and functional enrichment analysis convinced our findings. This novel bioinformatics model could be applied to biomarker discovery for other complex diseases.

Network-based approach to identify prognostic biomarkers for estrogen receptor-positive breast cancer treatment with tamoxifen.

PubMed

Liu, Rong; Guo, Cheng-Xian; Zhou, Hong-Hao

2015-01-01

This study aims to identify effective gene networks and prognostic biomarkers associated with estrogen receptor positive (ER+) breast cancer using human mRNA studies. Weighted gene coexpression network analysis was performed with a complex ER+ breast cancer transcriptome to investigate the function of networks and key genes in the prognosis of breast cancer. We found a significant correlation of an expression module with distant metastasis-free survival (HR = 2.25; 95% CI .21.03-4.88 in discovery set; HR = 1.78; 95% CI = 1.07-2.93 in validation set). This module contained genes enriched in the biological process of the M phase. From this module, we further identified and validated 5 hub genes (CDK1, DLGAP5, MELK, NUSAP1, and RRM2), the expression levels of which were strongly associated with poor survival. Highly expressed MELK indicated poor survival in luminal A and luminal B breast cancer molecular subtypes. This gene was also found to be associated with tamoxifen resistance. Results indicated that a network-based approach may facilitate the discovery of biomarkers for the prognosis of ER+ breast cancer and may also be used as a basis for establishing personalized therapies. Nevertheless, before the application of this approach in clinical settings, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed.

Fibrosis-Related Biomarkers and Risk of Total and Cause-Specific Mortality

PubMed Central

Agarwal, Isha; Glazer, Nicole L.; Barasch, Eddy; Biggs, Mary L.; Djoussé, Luc; Fitzpatrick, Annette L.; Gottdiener, John S.; Ix, Joachim H.; Kizer, Jorge R.; Rimm, Eric B.; Siscovick, David S.; Tracy, Russell P.; Zieman, Susan J.; Mukamal, Kenneth J.

2014-01-01

Fibrosis has been implicated in diverse diseases of the liver, kidney, lungs, and heart, but its importance as a risk factor for mortality remains unconfirmed. We determined the prospective associations of 2 complementary biomarkers of fibrosis, transforming growth factor-β (TGF-β) and procollagen type III N-terminal propeptide (PIIINP), with total and cause-specific mortality risks among community-living older adults in the Cardiovascular Health Study (1996–2010). We measured circulating TGF-β and PIIINP levels in plasma samples collected in 1996 and ascertained the number of deaths through 2010. Both TGF-β and PIIINP were associated with elevated risks of total and pulmonary mortality after adjustment for sociodemographic, clinical, and biochemical risk factors. For total mortality, the hazard ratios per doubling of TGF-β and PIIINP were 1.09 (95% confidence interval (CI): 1.01, 1.17; P = 0.02) and 1.14 (CI: 1.03, 1.27; P = 0.01), respectively. The corresponding hazard ratios for pulmonary mortality were 1.27 (CI: 1.01, 1.60; P = 0.04) for TGF-β and 1.52 (CI: 1.11, 2.10; P = 0.01) for PIIINP. Associations of TGF-β and PIIINP with total and pulmonary mortality were strongest among individuals with higher C-reactive protein concentrations (P for interaction < 0.05). Our findings provide some of the first large-scale prospective evidence that circulating biomarkers of fibrosis measured late in life are associated with death. PMID:24771724

Nutritional biomarkers for objective dietary assessment.

PubMed

Kuhnle, Gunter G C

2012-04-01

The accurate assessment of dietary exposure is important in investigating associations between diet and disease. Research in nutritional epidemiology, which has resulted in a large amount of information on associations between diet and chronic diseases in the last decade, relies on accurate assessment methods to identify these associations. However, most dietary assessment instruments rely to some extent on self-reporting, which is prone to systematic bias affected by factors such as age, gender, social desirability and approval. Nutritional biomarkers are not affected by these and therefore provide an additional, alternative method to estimate intake. However, there are also some limitations in their application: they are affected by inter-individual variations in metabolism and other physiological factors, and they are often limited to estimating intake of specific compounds and not entire foods. It is therefore important to validate nutritional biomarkers to determine specific strengths and limitations. In this perspective paper, criteria for the validation of nutritional markers and future developments are discussed. Copyright © 2012 Society of Chemical Industry.

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

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.

Mechanism-Based Urinary Biomarkers to Identify the Potential for Aminoglycoside-Induced Nephrotoxicity in Premature Neonates: A Proof-of-Concept Study

PubMed Central

Sabbisetti, Venkata; Turner, Mark A.; Farragher, Tracey; Bonventre, Joseph V.; Park, B. Kevin; Smyth, Rosalind L.; Pirmohamed, Munir

2012-01-01

Premature infants are frequently exposed to aminoglycoside antibiotics. Novel urinary biomarkers may provide a non-invasive means for the early identification of aminoglycoside-related proximal tubule renal toxicity, to enable adjustment of treatment and identification of infants at risk of long-term renal impairment. In this proof-of-concept study, urine samples were collected from 41 premature neonates (≤32 weeks gestation) at least once per week, and daily during courses of gentamicin, and for 3 days afterwards. Significant increases were observed in the three urinary biomarkers measured (Kidney Injury Molecule-1 (KIM-1), Neutrophil Gelatinase-associated Lipocalin (NGAL), and N-acetyl-β-D-glucosaminidase (NAG)) during treatment with multiple courses of gentamicin. When adjusted for potential confounders, the treatment effect of gentamicin remained significant only for KIM-1 (mean difference from not treated, 1.35 ng/mg urinary creatinine; 95% CI 0.05–2.65). Our study shows that (a) it is possible to collect serial urine samples from premature neonates, and that (b) proximal tubule specific urinary biomarkers can act as indicators of aminoglycoside-associated nephrotoxicity in this age group. Further studies to investigate the clinical utility of novel urinary biomarkers in comparison to serum creatinine need to be undertaken. PMID:22937100

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

Urinary biomarkers for the non-invasive diagnosis of endometriosis.

PubMed

Liu, Emily; Nisenblat, Vicki; Farquhar, Cindy; Fraser, Ian; Bossuyt, Patrick M M; Johnson, Neil; Hull, M Louise

2015-12-23

About 10% of reproductive-aged women suffer from endometriosis which is a costly chronic disease that causes pelvic pain and subfertility. Laparoscopy is the 'gold standard' diagnostic test for endometriosis, but it is expensive and carries surgical risks. Currently, there are no simple non-invasive or minimally-invasive tests available in clinical practice that accurately diagnoses endometriosis. 1. To provide summary estimates of the diagnostic accuracy of urinary biomarkers for the diagnosis of pelvic endometriosis compared to surgical diagnosis as a reference standard.2. To assess the diagnostic utility of biomarkers that could differentiate ovarian endometrioma from other ovarian masses.Urinary biomarkers were evaluated as replacement tests for surgical diagnosis and as triage tests to inform decisions to undertake surgery for endometriosis. The searches were not restricted to particular study design, language or publication dates. We searched the following databases to 20 April - 31 July 2015: CENTRAL, MEDLINE, EMBASE, CINAHL, PsycINFO, Web of Science, LILACS, OAIster, TRIP and ClinicalTrials.gov (trial register). MEDION, DARE, and PubMed were also searched to identify reviews and guidelines as reference sources of potentially relevant studies. Recently published papers not yet indexed in the major databases were also sought. The search strategy incorporated words in the title, abstract, text words across the record and the medical subject headings (MeSH) and was modified for each database. Published peer-reviewed, randomised controlled or cross-sectional studies of any size were considered, which included prospectively collected samples from any population of reproductive-aged women suspected of having one or more of the following target conditions: ovarian, peritoneal or deep infiltrating endometriosis (DIE). We included studies comparing the diagnostic test accuracy of one or more urinary biomarkers with surgical visualisation of endometriotic lesions. Two

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

PubMed Central

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

2009-01-01

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

Oncology biomarkers: discovery, validation, and clinical use.

PubMed

Heckman-Stoddard, Brandy M

2012-05-01

To discuss the discovery, validation, and clinical use of multiple types of biomarkers. Medical literature and published guidelines. Formal validation of biomarkers should include both retrospective analyses of well-characterized samples as well as a prospective clinical trial in which the biomarker is tested for its ability to predict the presence of disease or the efficacy of a cancer therapy. Biomarker development is complicated, with very few biomarker discoveries leading to clinically useful tests. Nurses should understand how a biomarker was developed, including the sensitivity and specificity before applying new biomarkers in the clinical setting. Copyright © 2012. Published by Elsevier Inc.

Biomarkers for early detection of pancreatic cancer — EDRN Public Portal

Cancer.gov

Background: The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Methods: Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Results: The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively correlated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected 1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Conclusions: Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combination offered some advantage of CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis, however further study will be needed to fully define the implications of these findings.

Discovery of urine biomarkers for bladder cancer via global metabolomics.

PubMed

Shi, Hangchuan; Li, Xiang; Zhang, Qingyang; Yang, Hongmei; Zhang, Xiaoping

2016-11-01

Bladder cancer (BC) is latent in its early stage and lethal in its late stage. Therefore, early diagnosis and intervention are essential for successful BC treatment. Considering the limitations of current diagnostic tools, noninvasive biomarkers that are both highly sensitive and specific are needed to improve the overall survival and quality of life of patients. With the advent of systems biology, "-omics" technologies have been developed over the past few decades. As a promising member, global metabolomics has increasingly been found to have clear potential for biomarker discovery. However, urinary metabolomics studies related to BC have lagged behind those of other urinary cancers, and major findings have not been systematically reported. The objective of this review is to comprehensively list the currently identified potential urinary metabolite biomarkers for BC.

The Potential Biomarkers to Identify the Development of Steatosis in Hyperuricemia

PubMed Central

He, Xiaojuan; Lu, Cheng; He, Bing; Niu, Xuyan; Xiao, Cheng; Xu, Gang; Bian, Zhaoxiang; Zu, Xianpeng; Zhang, Ge; Zhang, Weidong; Lu, Aiping

2016-01-01

Hyperuricemia (HU) often progresses to combine with non-alcoholic fatty liver disease (NAFLD) in the clinical scenario, which further exacerbates metabolic disorders; early detection of biomarkers, if obtained during the HU progression, may be beneficial for preventing its combination with NAFLD. This study aimed to decipher the biomarkers and mechanisms of the development of steatosis in HU. Four groups of subjects undergoing health screening, including healthy subjects, subjects with HU, subjects with HU combined with NAFLD (HU+NAFLD) and subjects with HU initially and then with HU+NAFLD one year later (HU→HU+NAFLD), were recruited in this study. The metabolic profiles of all subjects’ serum were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry. The metabolomic data from subjects with HU and HU+NAFLD were compared, and the biomarkers for the progression from HU to HU+NAFLD were predicted. The metabolomic data from HU→HU+NAFLD subjects were collected for further verification. The results showed that the progression was associated with disturbances of phospholipase metabolism, purine nucleotide degradation and Liver X receptor/retinoic X receptor activation as characterized by up-regulated phosphatidic acid, cholesterol ester (18:0) and down-regulated inosine. These metabolic alterations may be at least partially responsible for the development of steatosis in HU. This study provides a new paradigm for better understanding and further prevention of disease progression. PMID:26890003

CD86 expression as a surrogate cellular biomarker for pharmacological inhibition of the histone demethylase lysine-specific demethylase 1.

PubMed

Lynch, James T; Cockerill, Mark J; Hitchin, James R; Wiseman, Daniel H; Somervaille, Tim C P

2013-11-01

There is a lack of rapid cell-based assays that read out enzymatic inhibition of the histone demethylase LSD1 (lysine-specific demethylase 1). Through transcriptome analysis of human acute myeloid leukemia THP1 cells treated with a tranylcypromine-derivative inhibitor of LSD1 active in the low nanomolar range, we identified the cell surface marker CD86 as a sensitive surrogate biomarker of LSD1 inhibition. Within 24h of enzyme inhibition, there was substantial and dose-dependent up-regulation of CD86 expression, as detected by quantitative polymerase chain reaction, flow cytometry, and enzyme-linked immunosorbent assay. Thus, the use of CD86 expression may facilitate screening of compounds with putative LSD1 inhibitory activities in cellular assays. Copyright © 2013 Elsevier Inc. All rights reserved.

Imperfect Gold Standards for Kidney Injury Biomarker Evaluation

PubMed Central

Betensky, Rebecca A.; Emerson, Sarah C.; Bonventre, Joseph V.

2012-01-01

Clinicians have used serum creatinine in diagnostic testing for acute kidney injury for decades, despite its imperfect sensitivity and specificity. Novel tubular injury biomarkers may revolutionize the diagnosis of acute kidney injury; however, even if a novel tubular injury biomarker is 100% sensitive and 100% specific, it may appear inaccurate when using serum creatinine as the gold standard. Acute kidney injury, as defined by serum creatinine, may not reflect tubular injury, and the absence of changes in serum creatinine does not assure the absence of tubular injury. In general, the apparent diagnostic performance of a biomarker depends not only on its ability to detect injury, but also on disease prevalence and the sensitivity and specificity of the imperfect gold standard. Assuming that, at a certain cutoff value, serum creatinine is 80% sensitive and 90% specific and disease prevalence is 10%, a new perfect biomarker with a true 100% sensitivity may seem to have only 47% sensitivity compared with serum creatinine as the gold standard. Minimizing misclassification by using more strict criteria to diagnose acute kidney injury will reduce the error when evaluating the performance of a biomarker under investigation. Apparent diagnostic errors using a new biomarker may be a reflection of errors in the imperfect gold standard itself, rather than poor performance of the biomarker. The results of this study suggest that small changes in serum creatinine alone should not be used to define acute kidney injury in biomarker or interventional studies. PMID:22021710

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

PubMed

Yang, Xu; Lazar, Iulia M

2009-03-27

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

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

PubMed Central

2009-01-01

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

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

Metabolomics Based Dietary Biomarkers in Nutritional Epidemiology- Current Status and Future Opportunities.

PubMed

Brennan, Lorraine; Hu, Frank B

2018-04-24

The application of metabolomics in nutrition epidemiology holds great promise and there is a high expectation that it will play a leading role in deciphering the interactions between diet and health. However, while significant progress has been made in identification of putative biomarkers more work is needed to address the use of the biomarkers in dietary assessment. The aim of this review to critically evaluate progress in these areas and to identify challenges that need to be addressed going forward. The notable applications of dietary biomarkers in nutritional epidemiology include (1) Determination of food intake based on biomarkers levels and calibration equations from feeding studies (2) Classification of individuals into dietary patterns based on the urinary metabolic profile and (3) Application of metabolome-wide-association studies. Further work is needed to address some specific challenges to enable biomarkers to reach their full potential. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Analytical Pipeline for Discovery and Verification of Glycoproteins from Plasma-Derived Extracellular Vesicles as Breast Cancer Biomarkers.

PubMed

Chen, I-Hsuan; Aguilar, Hillary Andaluz; Paez Paez, J Sebastian; Wu, Xiaofeng; Pan, Li; Wendt, Michael K; Iliuk, Anton B; Zhang, Ying; Tao, W Andy

2018-05-15

Glycoproteins comprise more than half of current FDA-approved protein cancer markers, but the development of new glycoproteins as disease biomarkers has been stagnant. Here we present a pipeline to develop glycoproteins from extracellular vesicles (EVs) through integrating quantitative glycoproteomics with a novel reverse phase glycoprotein array and then apply it to identify novel biomarkers for breast cancer. EV glycoproteomics show promise in circumventing the problems plaguing current serum/plasma glycoproteomics and allowed us to identify hundreds of glycoproteins that have not been identified in blood. We identified 1,453 unique glycopeptides representing 556 glycoproteins in EVs, among which 20 were verified significantly higher in individual breast cancer patients. We further applied a novel glyco-specific reverse phase protein array to quantify a subset of the candidates. Together, this study demonstrates the great potential of this integrated pipeline for biomarker discovery.

Measuring molecular biomarkers in epidemiologic studies: laboratory techniques and biospecimen considerations.

PubMed

Erickson, Heidi S

2012-09-28

The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling. Copyright © 2012 John Wiley & Sons, Ltd.

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

PubMed

Sébédio, Jean-Louis

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

Cerebrospinal fluid biomarkers of simian immunodeficiency virus encephalitis

PubMed Central

Bissel, Stephanie J.; Kofler, Julia; Nyaundi, Julia; Murphey-Corb, Michael; Wisniewski, Stephen R.; Wiley, Clayton A.

2016-01-01

Antiretroviral therapy has led to increased survival of HIV-infected patients but also increased prevalence of HIV-associated neurocognitive disorders. We previously identified YKL40 as a potential cerebrospinal fluid (CSF) biomarker of lentiviral central nervous system (CNS) disease in HIV-infected patients and in the macaque model of HIV encephalitis. The aim of this study was to define the specificity and sensitivity along with the predictive value of YKL40 as a biomarker of encephalitis and to assess its relationship to CSF viral load. CSF YKL40 and SIV RNA concentrations were analyzed over the course of infection in 19 SIV-infected pigtailed macaques and statistical analyses were performed to evaluate the relationship to encephalitis. Using these relationships, CSF alterations of 31 neuroimmune markers were studied pre-infection, during acute and asymptomatic infection, at the onset of encephalitis, and at necropsy. YKL40 CSF concentrations above 1122 ng/ml were found to be a specific and sensitive biomarker for the presence of encephalitis and were highly correlated with CSF viral load. Macaques that developed encephalitis had evidence of chronic CNS immune activation during early, asymptomatic, and end stages of infection. At the onset of encephalitis, CSF demonstrated a rise of neuroimmune markers associated with macrophage recruitment, activation and interferon response. CSF YKL40 concentration and viral load are valuable biomarkers to define the onset of encephalitis. Chronic CNS immune activation precedes the development of encephalitis while some responses suggest protection from CNS lentiviral disease. PMID:27059917

Biomarkers of Alzheimer’s Disease Among Mexican Americans

PubMed Central

O’Bryant, Sid E.; Xiao, Guanghua; Edwards, Melissa; Devous, Michael; Gupta, Veer Bala; Martins, Ralph; Zhang, Fan; Barber, Robert

2013-01-01

Background Mexican Americans are the fastest aging segment of the U.S. population yet little scientific literature exists regarding the Alzheimer disease (AD) among this segment of the population. The extant literature suggests that biomarkers of AD will vary according to race/ethnicity though no prior work has explicitly studied this possibility. The aim of this study was to create a serum-based biomarker profile of AD among Mexican American. Methods Data were analyzed from 363 Mexican American participants (49 AD and 314 normal controls) enrolled in the Texas Alzheimer’s Research & Care Consortium (TARCC). Non-fasting serum samples were analyzed using a luminex-based multi-plex platform. A biomarker profile was generated using random forest analyses. Results The biomarker profile of AD among Mexican Americans was different from prior work from non-Hispanic populations with regards to the variable importance plots. In fact, many of the top markers were related to metabolic factors (e.g. FABP, GLP-1, CD40, pancreatic polypeptide, insulin-like-growth factor, and insulin). The biomarker profile was a significant classifier of AD status yielding an area under the receiver operating characteristic curve (AUC), sensitivity (SN) and specificity (SP) of 0.77, 0.92 and 0.64, respectively. Combining biomarkers with clinical variables yielded a better balance of SN and SP. Conclusion The biomarker profile for AD among Mexican American cases is significantly different from that previously identified among non-Hispanic cases from many large-scale studies. This is the first study to explicitly examine and provide support for blood-based biomarkers of AD among Mexican Americans. Areas for future research are highlighted. PMID:23313927

Advances in Biomarkers in Critical Ill Polytrauma Patients.

PubMed

Papurica, Marius; Rogobete, Alexandru F; Sandesc, Dorel; Dumache, Raluca; Cradigati, Carmen A; Sarandan, Mirela; Nartita, Radu; Popovici, Sonia E; Bedreag, Ovidiu H

2016-01-01

The complexity of the cases of critically ill polytrauma patients is given by both the primary, as well as the secondary, post-traumatic injuries. The severe injuries of organ systems, the major biochemical and physiological disequilibrium, and the molecular chaos lead to a high rate of morbidity and mortality in this type of patient. The 'gold goal' in the intensive therapy of such patients resides in the continuous evaluation and monitoring of their clinical status. Moreover, optimizing the therapy based on the expression of certain biomarkers with high specificity and sensitivity is extremely important because of the clinical course of the critically ill polytrauma patient. In this paper we wish to summarize the recent studies of biomarkers useful for the intensive care unit (ICU) physician. For this study the available literature on specific databases such as PubMed and Scopus was thoroughly analyzed. Each article was carefully reviewed and useful information for this study extracted. The keywords used to select the relevant articles were "sepsis biomarker", "traumatic brain injury biomarker" "spinal cord injury biomarker", "inflammation biomarker", "microRNAs biomarker", "trauma biomarker", and "critically ill patients". For this study to be carried out 556 original type articles were analyzed, as well as case reports and reviews. For this review, 89 articles with relevant topics for the present paper were selected. The critically ill polytrauma patient, because of the clinical complexity the case presents with, needs a series of evaluations and specific monitoring. Recent studies show a series of either tissue-specific or circulating biomarkers that are useful in the clinical status evaluation of these patients. The biomarkers existing today, with regard to the critically ill polytrauma patient, can bring a significant contribution to increasing the survival rate, by adapting the therapy according to their expressions. Nevertheless, the necessity remains to

Biomarkers in Japanese Encephalitis: A Review

PubMed Central

Kant Upadhyay, Ravi

2013-01-01

JE is a flavivirus generated dreadful CNS disease which causes high mortality in various pediatric groups. JE disease is currently diagnosed by measuring the level of viral antigens and virus neutralization IgM antibodies in blood serum and CSF by ELISA. However, it is not possible to measure various disease-identifying molecules, structural and molecular changes occurred in tissues, and cells by using such routine methods. However, few important biomarkers such as cerebrospinal fluid, plasma, neuro-imaging, brain mapping, immunotyping, expression of nonstructural viral proteins, systematic mRNA profiling, DNA and protein microarrays, active caspase-3 activity, reactive oxygen species and reactive nitrogen species, levels of stress-associated signaling molecules, and proinflammatory cytokines could be used to confirm the disease at an earlier stage. These biomarkers may also help to diagnose mutant based environment specific alterations in JEV genotypes causing high pathogenesis and have immense future applications in diagnostics. There is an utmost need for the development of new more authentic, appropriate, and reliable physiological, immunological, biochemical, biophysical, molecular, and therapeutic biomarkers to confirm the disease well in time to start the clinical aid to the patients. Hence, the present review aims to discuss new emerging biomarkers that could facilitate more authentic and fast diagnosis of JE disease and its related disorders in the future. PMID:24455705

PSA and beyond: alternative prostate cancer biomarkers

PubMed Central

2016-01-01

Background The use of biomarkers for prostate cancer screening, diagnosis and prognosis has the potential to improve the clinical management of the patients. Owing to inherent limitations of the biomarker prostate-specific antigen (PSA), intensive efforts are currently directed towards a search for alternative prostate cancer biomarkers, particularly those that can predict disease aggressiveness and drive better treatment decisions. Methods A literature search of Medline articles focused on recent and emerging advances in prostate cancer biomarkers was performed. The most promising biomarkers that have the potential to meet the unmet clinical needs in prostate cancer patient management and/or that are clinically implemented were selected. Conclusions With the advent of advanced genomic and proteomic technologies, we have in recent years seen an enormous spurt in prostate cancer biomarker research with several promising alternative biomarkers being discovered that show an improved sensitivity and specificity over PSA. The new generation of biomarkers can be tested via serum, urine, or tissue-based assays that have either received regulatory approval by the US Food and Drug Administration or are available as Clinical Laboratory Improvement Amendments-based laboratory developed tests. Additional emerging novel biomarkers for prostate cancer, including circulating tumor cells, microRNAs and exosomes, are still in their infancy. Together, these biomarkers provide actionable guidance for prostate cancer risk assessment, and are expected to lead to an era of personalized medicine. PMID:26790878

Considerations for biomarker-targeted intervention strategies for tuberculosis disease prevention.

PubMed

Fiore-Gartland, Andrew; Carpp, Lindsay N; Naidoo, Kogieleum; Thompson, Ethan; Zak, Daniel E; Self, Steve; Churchyard, Gavin; Walzl, Gerhard; Penn-Nicholson, Adam; Scriba, Thomas J; Hatherill, Mark

2018-03-01

Current diagnostic tests for Mycobacterium tuberculosis (MTB) infection have low prognostic specificity for identifying individuals who will develop tuberculosis (TB) disease, making mass preventive therapy strategies targeting all MTB-infected individuals impractical in high-burden TB countries. Here we discuss general considerations for a risk-targeted test-and-treat strategy based on a highly specific transcriptomic biomarker that can identify individuals who are most likely to progress to active TB disease as well as individuals with TB disease who have not yet presented for medical care. Such risk-targeted strategies may offer a rapid, ethical and cost-effective path towards decreasing the burden of TB disease and interrupting transmission and would also be critical to achieving TB elimination in countries nearing elimination. We also discuss design considerations for a Correlate of Risk Targeted Intervention Study (CORTIS), which could provide proof-of-concept for the strategy. One such study in South Africa is currently enrolling 1500 high-risk and 1700 low-risk individuals, as defined by biomarker status, and is randomizing high-risk participants to TB preventive therapy or standard of care treatment. All participants are monitored for progression to active TB with primary objectives to assess efficacy of the treatment and performance of the biomarker. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Integrated pipeline for mass spectrometry-based discovery and confirmation of biomarkers demonstrated in a mouse model of breast cancer.

PubMed

Whiteaker, Jeffrey R; Zhang, Heidi; Zhao, Lei; Wang, Pei; Kelly-Spratt, Karen S; Ivey, Richard G; Piening, Brian D; Feng, Li-Chia; Kasarda, Erik; Gurley, Kay E; Eng, Jimmy K; Chodosh, Lewis A; Kemp, Christopher J; McIntosh, Martin W; Paulovich, Amanda G

2007-10-01

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

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

Quantitative HDL Proteomics Identifies Peroxiredoxin-6 as a Biomarker of Human Abdominal Aortic Aneurysm

PubMed Central

Burillo, Elena; Jorge, Inmaculada; Martínez-López, Diego; Camafeita, Emilio; Blanco-Colio, Luis Miguel; Trevisan-Herraz, Marco; Ezkurdia, Iakes; Egido, Jesús; Michel, Jean-Baptiste; Meilhac, Olivier; Vázquez, Jesús; Martin-Ventura, Jose Luis

2016-01-01

High-density lipoproteins (HDLs) are complex protein and lipid assemblies whose composition is known to change in diverse pathological situations. Analysis of the HDL proteome can thus provide insight into the main mechanisms underlying abdominal aortic aneurysm (AAA) and potentially detect novel systemic biomarkers. We performed a multiplexed quantitative proteomics analysis of HDLs isolated from plasma of AAA patients (N = 14) and control study participants (N = 7). Validation was performed by western-blot (HDL), immunohistochemistry (tissue), and ELISA (plasma). HDL from AAA patients showed elevated expression of peroxiredoxin-6 (PRDX6), HLA class I histocompatibility antigen (HLA-I), retinol-binding protein 4, and paraoxonase/arylesterase 1 (PON1), whereas α-2 macroglobulin and C4b-binding protein were decreased. The main pathways associated with HDL alterations in AAA were oxidative stress and immune-inflammatory responses. In AAA tissue, PRDX6 colocalized with neutrophils, vascular smooth muscle cells, and lipid oxidation. Moreover, plasma PRDX6 was higher in AAA (N = 47) than in controls (N = 27), reflecting increased systemic oxidative stress. Finally, a positive correlation was recorded between PRDX6 and AAA diameter. The analysis of the HDL proteome demonstrates that redox imbalance is a major mechanism in AAA, identifying the antioxidant PRDX6 as a novel systemic biomarker of AAA. PMID:27934969

Genomic biomarkers for molecular imaging: predicting the future.

PubMed

Thakur, Mathew L

2009-07-01

Over the past few decades, great strides have been made in anatomical imaging of disease that has led to their diagnosis with minimal invasion. Despite these advances, diseases such as cancer continue to take one human life every minute in the United States. Complimentary approaches that pertain directly to the genesis of the disease might contribute to its early diagnosis and subsequent management. In cancer, an array of molecular abnormalities leading to the modulations in expression of key proteins important in the cellular signaling pathways and cell proliferation has been identified. These specific disease fingerprints, biomarkers, are overexpressed on malignant cell surfaces or within the cytoplasm, and they provide unique targets that are promising for improving cancer diagnosis and therapy. We and others have designed, synthesized, and evaluated some novel probes specific for those oncogenes and oncogene product biomarkers for PET and SPECT molecular imaging of certain types of cancers. This article briefly describes this approach and gives specific examples that depict the ability of molecular imaging to detect occult lesions not detectable by current scintigraphic approaches. The article also outlines a few examples predicting other possible applications of targeting such specific probes not yet used.

Biomarker-specific conjugated nanopolyplexes for the active coloring of stem-like cancer cells

NASA Astrophysics Data System (ADS)

Hong, Yoochan; Lee, Eugene; Choi, Jihye; Haam, Seungjoo; Suh, Jin-Suck; Yang, Jaemoon

2016-06-01

Stem-like cancer cells possess intrinsic features and their CD44 regulate redox balance in cancer cells to survive under stress conditions. Thus, we have fabricated biomarker-specific conjugated polyplexes using CD44-targetable hyaluronic acid and redox-sensible polyaniline based on a nanoemulsion method. For the most sensitive recognition of the cellular redox at a single nanoparticle scale, a nano-scattering spectrum imaging analyzer system was introduced. The conjugated polyplexes showed a specific targeting ability toward CD44-expressing cancer cells as well as a dramatic change in its color, which depended on the redox potential in the light-scattered images. Therefore, these polyaniline-based conjugated polyplexes as well as analytical processes that include light-scattering imaging and measurements of scattering spectra, clearly establish a systematic method for the detection and monitoring of cancer microenvironments.

Urinary biomarkers may provide prognostic information for subclinical acute kidney injury after cardiac surgery.

PubMed

Albert, Christian; Albert, Annemarie; Kube, Johanna; Bellomo, Rinaldo; Wettersten, Nicholas; Kuppe, Hermann; Westphal, Sabine; Haase, Michael; Haase-Fielitz, Anja

2018-06-01

This study aimed to determine the biomarker-specific outcome patterns and short-and long-term prognosis of cardiac surgery-asoociated acute kidney injury (AKI) identified by standard criteria and/or urinary kidney biomarkers. Patients enrolled (N = 200), originated a German multicenter study (NCT00672334). Standard risk injury, failure, loss, and end-stage renal disease classification (RIFLE) criteria (including serum creatinine and urine output) and urinary kidney biomarker test result (neutrophil gelatinase-associated lipocalin, midkine, interleukin 6, and proteinuria) were used for diagnosis of postoperative AKI. Primary end point was acute renal replacement therapy or in-hospital mortality. Long-term end points among others included 5-year mortality. Patients with single-biomarker-positive subclinical AKI (RIFLE negative) were identified. We controlled for systemic inflammation using C-reactive protein test. Urinary biomarkers (neutrophil gelatinase-associated lipocalin, midkine, and interleukin 6) were identified as independent predictors of the primary end point. Neutrophil gelatinase-associated lipocalin, midkine, or interleukin 6 positivity or de novo/worsening proteinuria identified 21.1%, 16.9%, 30.5%, and 48.0% more cases, respectively, with likely subclinical AKI (biomarker positive/RIFLE negative) additionally to cases with RIFLE positivity alone. Patients with likely subclinical AKI (neutrophil gelatinase-associated lipocalin or interleukin 6 positive) had increased risk of primary end point (adjusted hazard ratio, 7.18; 95% confidence interval, 1.52-33.93 [P = .013] and hazard ratio, 6.27; 95% confidence interval, 1.12-35.21 [P = .037]), respectively. Compared with biomarker-negative/RIFLE-positive patients, neutrophil gelatinase-associated lipocalin positive/RIFLE-positive or midkine-positive/RIFLE-positive patients had increased risk of primary end point (odds ratio, 9.6; 95% confidence interval, 1.4-67.3 [P = .033] and odds ratio, 14

Quantitative imaging as cancer biomarker

NASA Astrophysics Data System (ADS)

Mankoff, David A.

2015-03-01

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

Urine Metabonomics Reveals Early Biomarkers in Diabetic Cognitive Dysfunction.

PubMed

Song, Lili; Zhuang, Pengwei; Lin, Mengya; Kang, Mingqin; Liu, Hongyue; Zhang, Yuping; Yang, Zhen; Chen, Yunlong; Zhang, Yanjun

2017-09-01

Recently, increasing attention has been paid to diabetic encephalopathy, which is a frequent diabetic complication and affects nearly 30% of diabetics. Because cognitive dysfunction from diabetic encephalopathy might develop into irreversible dementia, early diagnosis and detection of this disease is of great significance for its prevention and treatment. This study is to investigate the early specific metabolites biomarkers in urine prior to the onset of diabetic cognitive dysfunction (DCD) by using metabolomics technology. An ultra-high performance liquid-chromatography-quadrupole time-of-flight-mass spectrometry (UPLC-Q/TOF-MS) platform was used to analyze the urine samples from diabetic mice that were associated with mild cognitive impairment (MCI) and nonassociated with MCI in the stage of diabetes (prior to the onset of DCD). We then screened and validated the early biomarkers using OPLS-DA model and support vector machine (SVM) method. Following multivariate statistical and integration analysis, we found that seven metabolites could be accepted as early biomarkers of DCD, and the SVM results showed that the prediction accuracy is as high as 91.66%. The identities of four biomarkers were determined by mass spectrometry. The identified biomarkers were largely involved in nicotinate and nicotinamide metabolism, glutathione metabolism, tryptophan metabolism, and sphingolipid metabolism. The present study first revealed reliable biomarkers for early diagnosis of DCD. It provides new insight and strategy for the early diagnosis and treatment of DCD.

Age and diagnostic performance of Alzheimer disease CSF biomarkers.

PubMed

Mattsson, N; Rosén, E; Hansson, O; Andreasen, N; Parnetti, L; Jonsson, M; Herukka, S-K; van der Flier, W M; Blankenstein, M A; Ewers, M; Rich, K; Kaiser, E; Verbeek, M M; Olde Rikkert, M; Tsolaki, M; Mulugeta, E; Aarsland, D; Visser, P J; Schröder, J; Marcusson, J; de Leon, M; Hampel, H; Scheltens, P; Wallin, A; Eriksdotter-Jönhagen, M; Minthon, L; Winblad, B; Blennow, K; Zetterberg, H

2012-02-14

Core CSF changes in Alzheimer disease (AD) are decreased amyloid β(1-42), increased total tau, and increased phospho-tau, probably indicating amyloid plaque accumulation, axonal degeneration, and tangle pathology, respectively. These biomarkers identify AD already at the predementia stage, but their diagnostic performance might be affected by age-dependent increase of AD-type brain pathology in cognitively unaffected elderly. We investigated effects of age on the diagnostic performance of CSF biomarkers in a uniquely large multicenter study population, including a cross-sectional cohort of 529 patients with AD dementia (median age 71, range 43-89 years) and 304 controls (67, 44-91 years), and a longitudinal cohort of 750 subjects without dementia with mild cognitive impairment (69, 43-89 years) followed for at least 2 years, or until dementia diagnosis. The specificities for subjects without AD and the areas under the receiver operating characteristics curves decreased with age. However, the positive predictive value for a combination of biomarkers remained stable, while the negative predictive value decreased only slightly in old subjects, as an effect of the high AD prevalence in older ages. Although the diagnostic accuracies for AD decreased with age, the predictive values for a combination of biomarkers remained essentially stable. The findings highlight biomarker variability across ages, but support the use of CSF biomarkers for AD even in older populations.

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

Impact of Biomarkers on Personalized Medicine.

PubMed

Carrigan, Patricia; Krahn, Thomas

2016-01-01

The field of personalized medicine that involves the use of measuring biomarkers in clinical samples is an area of high interest and one that has tremendous impact on drug development. With the emergence of more sensitive and specific technologies that are now able to be run in clinical settings and the ability to accurately measure biomarkers, there is a need to understand how biomarkers are defined, how they are used in clinical trials, and most importantly how they are used in conjunction with drug treatment. Biomarker approaches have entered into early clinical trials and are increasingly being used to develop new diagnostics that help to differentiate or stratify the likely outcomes of therapeutic intervention. Tremendous efforts have been made to date to discover novel biomarkers for use in clinical practice. Still, the number of markers that make it into clinical practice is rather low. In the next following chapters, we will explain the various classifications of biomarkers, how they are applied, measured, and used in personalized medicine specifically focusing on how they are used in de-risking the 10 plus years drug development process and lastly how they are validated and transformed into companion diagnostic assays.

Using Serological Proteome Analysis to Identify Serum Anti-Nucleophosmin 1 Autoantibody as a Potential Biomarker in European-American and African-American Patients With Prostate Cancer.

PubMed

Dai, Liping; Li, Jitian; Xing, Mengtao; Sanchez, Tino W; Casiano, Carlos A; Zhang, Jian-Ying

2016-11-01

The prostate-specific antigen (PSA) testing has been widely implemented for the early detection and management of prostate cancer (PCa). However, the lack of specificity has led to overdiagnosis, resulting in many possibly unnecessary biopsies and overtreatment. Therefore, novel serological biomarkers with high sensitivity and specificity are of vital importance needed to complement PSA testing in the early diagnosis and effective management of PCa. This is particularly critical in the context of PCa health disparities, where early detection and management could help reduce the disproportionately high PCa mortality observed in African-American men. Previous studies have demonstrated that sera from patients with PCa contain autoantibodies that react with tumor-associated antigens (TAAs). The serological proteome analysis (SERPA) approach was used to identify tumor-associated antigens (TAAs) of PCa. In evaluation study, the level of anti-NPM1 antibody was examined in sera from test cohort, validation cohort, as well as European-American (EA) and African-American (AA) men with PCa by using immunoassay. Nucleophosmin 1 (NPM1) as a 33 kDa TAA in PCa was identified and characterized by SERPA approach. Anti-NPM1 antibody level in PCa was higher than in benign prostatic hyperplasia (BPH) patients and healthy individuals. Receiver operating characteristic (ROC) curve analysis showed similar high diagnostic value for PCa in the test cohort (area under the curve (AUC):0.860) and validation cohort (AUC: 0.822) to differentiate from normal individuals and BPH. Interestingly, AUC values were significantly higher for AA PCa patients. When considering concurrent serum measurements of anti-NPM1 antibody and PSA, 97.1% PCa patients at early stage were identified correctly, while 69.2% BPH patients who had elevated PSA levels were found to be anti-NPM1 negative. Additionally, anti-NPM1 antibody levels in PCa patients at early stage significantly increased after surgery treatment

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

PubMed Central

2015-01-01

Background Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machine learning pipelines for omics data is feature selection, which is used to reduce the raw high-dimensional data into a tractable number of features. Feature selection needs to balance the objective of using as few features as possible, while maintaining high predictive power. This balance is crucial when the goal of data analysis is the identification of highly accurate but small panels of biomarkers with potential clinical utility. In this paper we propose a heuristic for the selection of very small feature subsets, via an iterative feature elimination process that is guided by rule-based machine learning, called RGIFE (Rule-guided Iterative Feature Elimination). We use this heuristic to identify putative biomarkers of osteoarthritis (OA), articular cartilage degradation and synovial inflammation, using both proteomic and transcriptomic datasets. Results and discussion Our RGIFE heuristic increased the classification accuracies achieved for all datasets when no feature selection is used, and performed well in a comparison with other feature selection methods. Using this method the datasets were reduced to a smaller number of genes or proteins, including those known to be relevant to OA, cartilage degradation and joint inflammation. The results have shown the RGIFE feature reduction method to be suitable for analysing both proteomic and transcriptomics data. Methods that generate large ‘omics’ datasets are increasingly being used in the area of rheumatology. Conclusions Feature reduction methods are advantageous for the analysis of omics data in the field of rheumatology, as the applications of such techniques are likely to result in improvements in diagnosis, treatment and drug discovery. PMID:25923811

The economics of cardiac biomarker testing in suspected myocardial infarction.

PubMed

Goodacre, Steve; Thokala, Praveen

2015-03-01

Suspected myocardial infarction (MI) is a common reason for emergency hospital attendance and admission. Cardiac biomarker measurement is an essential element of diagnostic assessment of suspected MI. Although the cost of a routinely available biomarker may be small, the large patient population and consequences in terms of hospital admission and investigation mean that the economic impact of cardiac biomarker testing is substantial. Economic evaluation involves comparing the estimated costs and effectiveness (outcomes) of two or more interventions or care alternatives. This process creates some difficulties with respect to cardiac biomarkers. Estimating the effectiveness of cardiac biomarkers involves identifying how they help to improve health and how we can measure this improvement. Comparison to an appropriate alternative is also problematic. New biomarkers may be promoted on the basis of reducing hospital admission or length of stay, but hospital admission for low risk patients may incur significant costs while providing very little benefit, making it an inappropriate comparator. Finally, economic evaluation may conclude that a more sensitive biomarker strategy is more effective but, by detecting and treating more cases, is also more expensive. In these circumstances it is unclear whether we should use the more effective or the cheaper option. This article provides an introduction to health economics and addresses the specific issues relevant to cardiac biomarkers. It describes the key concepts relevant to economic evaluation of cardiac biomarkers in suspected MI and highlights key areas of uncertainty and controversy. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Examining Autism Spectrum Disorders by Biomarkers: Example From the Oxytocin and Serotonin Systems

PubMed Central

Hammock, Elizabeth; Veenstra-VanderWeele, Jeremy; Yan, Zhongyu; Kerr, Travis M.; Morris, Marianna; Anderson, George; Carter, C. Sue; Cook, Edwin H.; Jacob, Suma

2013-01-01

Objective Autism Spectrum Disorder (ASD) is a heritable but highly heterogeneous neuropsychiatric syndrome, which poses challenges for research relying solely on behavioral symptoms or diagnosis. Examining biomarkers may give us ways to identify individuals who demonstrate specific developmental trajectories and etiological factors related to ASD. Plasma oxytocin (OT) and whole blood serotonin (5-HT) levels are consistently altered in some individuals with ASD. Reciprocal relationships have been described between brain oxytocin and serotonin systems during development. We therefore investigated the relationship between these peripheral biomarkers as well as their relationships with age. Method In our first study, we analyzed correlations between these two biomarkers in 31 children and adolescents who were diagnosed with autism and were not on medications. In our second study, we explored whether whole blood 5-HT levels are altered in mice lacking the oxytocin receptor gene, Oxtr. Results In humans, OT and 5-HT were negatively correlated with each other (p<0.05) and this relationship was most prominent in children under 11 years old. Paralleling human findings, mice lacking Oxtr showed increased whole blood 5-HT levels (p=0.05), with this effect driven exclusively by mice younger than 4 months of age (p< 0.01). Conclusions Identifying relationships between identified ASD biomarkers may be a useful approach to connect otherwise disparate findings that span multiple systems in this heterogeneous disorder. Using neurochemical biomarkers to do parallel studies in animal and human populations within a developmental context is a plausible approach to probe the root causes of ASD and identify potential interventions. PMID:22721594

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

PubMed

Kikuta, Kazutaka; Kubota, Daisuke; Yoshida, Akihiko; Qiao, Zhiwei; Morioka, Hideo; Nakamura, Masaya; Matsumoto, Morio; Chuman, Hirokazu; Kawai, Akira; Kondo, Tadashi

2017-09-01

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application. Copyright © 2017 Elsevier B.V. All rights reserved.

Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think Tank

PubMed Central

Millan, Mark J.; Bahn, Sabine; Bertolino, Alessandro; Turck, Christoph W.; Kapur, Shitij; Möller, Hans-Jürgen; Dean, Brian

2015-01-01

Background: A think tank sponsored by the Collegium Internationale Neuropsychopharmacologium (CINP) debated the status and prospects of biological markers for psychiatric disorders, focusing on schizophrenia and major depressive disorder. Methods: Discussions covered markers defining and predicting specific disorders or domains of dysfunction, as well as predicting and monitoring medication efficacy. Deliberations included clinically useful and viable biomarkers, why suitable markers are not available, and the need for tightly-controlled sample collection. Results: Different types of biomarkers, appropriate sensitivity, specificity, and broad-based exploitability were discussed. Whilst a number of candidates are in the discovery phases, all will require replication in larger, real-life cohorts. Clinical cost-effectiveness also needs to be established. Conclusions: Since a single measure is unlikely to suffice, multi-modal strategies look more promising, although they bring greater technical and implementation complexities. Identifying reproducible, robust biomarkers will probably require pre-competitive consortia to provide the resources needed to identify, validate, and develop the relevant clinical tests. PMID:25899066

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 candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics.

PubMed

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

2017-04-01

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

Phytoplankton Diversity and Geologically Relevant Carbon: Using metagenomics to determine phytoplankton biomarker production

NASA Astrophysics Data System (ADS)

Kodner, R. B.; Armbrust, E.

2008-12-01

Phytoplankton play an important role in the global carbon cycle, on short and long time scales. On long time scales, organic carbon, especially recalcitrant forms of biomass such as lipids, can be preserved and thus sequestered in sediments and rocks on geologic time scales. If the preserved lipids have some taxonomic specificity, they can be used as fossil biomarkers to characterize the community of organisms that contributed to ancient carbon sinks. Currently, it is not well understood how well the complex mixture of organic compounds preserved in geological carbon sinks represents the original community that produced those molecules or how the diversity of organism in a community is reflected in the lipid biomarkers they collectively synthesize. We have begun to investigate these questions by characterizing lipid biomarker production in modern phytoplankton communities with metagenomic data sets. Here we evaluate the information on community biomarker biosynthesis gathered from this type of data set using sterols as a case study. We have identified genes involved in sterol biosynthesis in a number of metagenomes and placed these genes in a phylogenetic context using a method designed to deal with short metagenomic sequences. The degree of taxonomic diversity of biomarker production measured with gene sequences can be more specific than lipid analysis alone.

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

PubMed

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

2017-01-01

Aside from Gleason sum, few factors accurately identify the subset of prostate cancer patients at high risk for metastatic progression. We hypothesized that epigenetic alterations could distinguish prostate tumors with life-threatening potential. Epigenome-wide DNA methylation profiling was performed in surgically resected primary tumor tissues from a population-based (n = 430) and a replication (n = 80) cohort of prostate cancer patients followed prospectively for at least 5 years. Metastasis was confirmed by positive bone scan, MRI, CT, or biopsy, and death certificates confirmed cause of death. AUC, partial AUC (pAUC, 95% specificity), and P value criteria were used to select differentially methylated CpG sites that robustly stratify patients with metastatic-lethal from nonrecurrent tumors, and which were complementary to Gleason sum. Forty-two CpG biomarkers stratified patients with metastatic-lethal versus nonrecurrent prostate cancer in the discovery cohort, and eight of these CpGs replicated in the validation cohort based on a significant (P < 0.05) AUC (range, 0.66-0.75) or pAUC (range, 0.007-0.009). The biomarkers that improved discrimination of patients with metastatic-lethal prostate cancer include CpGs in five genes (ALKBH5, ATP11A, FHAD1, KLHL8, and PI15) and three intergenic regions. In the validation dataset, the AUC for Gleason sum alone (0.82) significantly increased with the addition of four individual CpGs (range, 0.86-0.89; all P <0.05). Eight differentially methylated CpGs that distinguish patients with metastatic-lethal from nonrecurrent tumors were validated. These novel epigenetic biomarkers warrant further investigation as they may improve prognostic classification of patients with clinically localized prostate cancer and provide new insights on tumor aggressiveness. Clin Cancer Res; 23(1); 311-9. ©2016 AACR. ©2016 American Association for Cancer Research.

An in vitro metabolomics approach to identify hepatotoxicity biomarkers in human L02 liver cells treated with pekinenal, a natural compound.

PubMed

Shi, Jiexia; Zhou, Jing; Ma, Hongyue; Guo, Hongbo; Ni, Zuyao; Duan, Jin'ao; Tao, Weiwei; Qian, Dawei

2016-02-01

An in vitro cell metabolomics study was performed on human L02 liver cells to investigate the toxic biomarkers of pekinenal from the herb Euphorbia pekinensis Rupr. Pekinenal significantly induced L02 cell damage, which was characterised by necrosis and apoptosis. Metabolomics combined with data pattern recognition showed that pekinenal significantly altered the profiles of more than 1299 endogenous metabolites with variable importance in the projection (VIP) > 1. Further, screening correlation coefficients between the intensities of all metabolites and the extent of L02 cell damage (MTT) identified 12 biomarker hits: ten were downregulated and two were upregulated. Among these hits, LysoPC(18:1(9Z)/(11Z)), PC(22:0/15:0) and PC(20:1(11Z)/14:1(9Z)) were disordered, implying the initiation of inflammation and cell damage. Several fatty acids (FAs) (3-hydroxytetradecanedioic acid, pivaloylcarnitine and eicosapentaenoyl ethanolamide) decreased due to fatty acid oxidation. Dihydroceramide and Cer(d18:0/14:0) were also altered and are associated with apoptosis. Additional examination of the levels of intracellular reactive oxygen species (ROS) and two eicosanoids (PGE2, PGF2α) in the cell supernatant confirmed the fatty acid oxidation and arachidonic acid metabolism pathways, respectively. In summary, cell metabolomics is a highly efficient approach for identifying toxic biomarkers and helping understand toxicity mechanisms and predict herb-induced liver injury.

Biomarkers of cancer cachexia.

PubMed

Loumaye, Audrey; Thissen, Jean-Paul

2017-12-01

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

Systems biomarkers as acute diagnostics and chronic monitoring tools for traumatic brain injury

NASA Astrophysics Data System (ADS)

Wang, Kevin K. W.; Moghieb, Ahmed; Yang, Zhihui; Zhang, Zhiqun

2013-05-01

Traumatic brain injury (TBI) is a significant biomedical problem among military personnel and civilians. There exists an urgent need to develop and refine biological measures of acute brain injury and chronic recovery after brain injury. Such measures "biomarkers" can assist clinicians in helping to define and refine the recovery process and developing treatment paradigms for the acutely injured to reduce secondary injury processes. Recent biomarker studies in the acute phase of TBI have highlighted the importance and feasibilities of identifying clinically useful biomarkers. However, much less is known about the subacute and chronic phases of TBI. We propose here that for a complex biological problem such as TBI, multiple biomarker types might be needed to harness the wide range of pathological and systemic perturbations following injuries, including acute neuronal death, neuroinflammation, neurodegeneration and neuroregeneration to systemic responses. In terms of biomarker types, they range from brain-specific proteins, microRNA, genetic polymorphism, inflammatory cytokines and autoimmune markers and neuro-endocrine hormones. Furthermore, systems biology-driven biomarkers integration can help present a holistic approach to understanding scenarios and complexity pathways involved in brain injury.

Biomarker development targeting unmet clinical needs.

PubMed

Monaghan, Phillip J; Lord, Sarah J; St John, Andrew; Sandberg, Sverre; Cobbaert, Christa M; Lennartz, Lieselotte; Verhagen-Kamerbeek, Wilma D J; Ebert, Christoph; Bossuyt, Patrick M M; Horvath, Andrea R

2016-09-01

The introduction of new biomarkers can lead to inappropriate utilization of tests if they do not fill in existing gaps in clinical care. We aimed to define a strategy and checklist for identifying unmet needs for biomarkers. A multidisciplinary working group used a 4-step process: 1/ scoping literature review; 2/ face-to-face meetings to discuss scope, strategy and checklist items; 3/ iterative process of feedback and consensus to develop the checklist; 4/ testing and refinement of checklist items using case scenarios. We used clinical pathway mapping to identify clinical management decisions linking biomarker testing to health outcomes and developed a 14-item checklist organized into 4 domains: 1/ identifying and 2/ verifying the unmet need; 3/ validating the intended use; and 4/ assessing the feasibility of the new biomarker to influence clinical practice and health outcome. We present an outcome-focused approach that can be used by multiple stakeholders for any medical test, irrespective of the purpose and role of testing. The checklist intends to achieve more efficient biomarker development and translation into practice. We propose the checklist is field tested by stakeholders, and advocate the role of the clinical laboratory professional to foster trans-sector collaboration in this regard. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Use of biomarkers to establish potential role and function of circulating microRNAs in acute heart failure.

PubMed

Vegter, Eline L; Schmitter, Daniela; Hagemeijer, Yanick; Ovchinnikova, Ekaterina S; van der Harst, Pim; Teerlink, John R; O'Connor, Christopher M; Metra, Marco; Davison, Beth A; Bloomfield, Daniel; Cotter, Gad; Cleland, John G; Givertz, Michael M; Ponikowski, Piotr; van Veldhuisen, Dirk J; van der Meer, Peter; Berezikov, Eugene; Voors, Adriaan A; Khan, Mohsin A F

2016-12-01

Circulating microRNAs (miRNAs) emerge as potential heart failure biomarkers. We aimed to identify associations between acute heart failure (AHF)-specific circulating miRNAs and well-known heart failure biomarkers. Associations between 16 biomarkers predictive for 180day mortality and the levels of 12 AHF-specific miRNAs were determined in 100 hospitalized AHF patients, at baseline and 48hours. Patients were divided in 4 pre-defined groups, based on clinical parameters during hospitalization. Correlation analyses between miRNAs and biomarkers were performed and complemented by miRNA target prediction and pathway analysis. No significant correlations were found at hospital admission. However, after 48hours, 7 miRNAs were significantly negatively correlated to biomarkers indicative for a worse clinical outcome in the patient group with the most unfavorable in-hospital course (n=21); miR-16-5p was correlated to C-reactive protein (R=-0.66, p-value=0.0027), miR-106a-5p to creatinine (R=-0.68, p-value=0.002), miR-223-3p to growth differentiation factor 15 (R=-0.69, p-value=0.0015), miR-652-3p to soluble ST-2 (R=-0.77, p-value<0.001), miR-199a-3p to procalcitonin (R=-0.72, p-value<0.001) and galectin-3 (R=-0.73, p-value<0.001) and miR-18a-5p to procalcitonin (R=-0.68, p-value=0.002). MiRNA target prediction and pathway analysis identified several pathways related to cardiac diseases, which could be linked to some of the miRNA-biomarker correlations. The majority of correlations between circulating AHF-specific miRNAs were related to biomarkers predictive for a worse clinical outcome in a subgroup of worsening heart failure patients at 48hours of hospitalization. The selective findings suggest a time-dependent effect of circulating miRNAs and highlight the susceptibility to individual patient characteristics influencing potential relations between miRNAs and biomarkers. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Biomarkers in Diabetic Retinopathy.

PubMed

Jenkins, Alicia J; Joglekar, Mugdha V; Hardikar, Anandwardhan A; Keech, Anthony C; O'Neal, David N; Januszewski, Andrzej S

2015-01-01

diabetic retinopathy, there is need to reliably identify and triage people with diabetes. Biomarkers may facilitate a better understanding of diabetic retinopathy, and contribute to the development of novel treatments and new clinical strategies to prevent vision loss in people with diabetes. This article reviews key aspects related to biomarker research, and focuses on some specific biomarkers relevant to diabetic retinopathy.

Assessing host-specificity of Escherichia coli using a supervised learning logic-regression-based analysis of single nucleotide polymorphisms in intergenic regions.

PubMed

Zhi, Shuai; Li, Qiaozhi; Yasui, Yutaka; Edge, Thomas; Topp, Edward; Neumann, Norman F

2015-11-01

Host specificity in E. coli is widely debated. Herein, we used supervised learning logic-regression-based analysis of intergenic DNA sequence variability in E. coli in an attempt to identify single nucleotide polymorphism (SNP) biomarkers of E. coli that are associated with natural selection and evolution toward host specificity. Seven-hundred and eighty strains of E. coli were isolated from 15 different animal hosts. We utilized logic regression for analyzing DNA sequence data of three intergenic regions (flanked by the genes uspC-flhDC, csgBAC-csgDEFG, and asnS-ompF) to identify genetic biomarkers that could potentially discriminate E. coli based on host sources. Across 15 different animal hosts, logic regression successfully discriminated E. coli based on animal host source with relatively high specificity (i.e., among the samples of the non-target animal host, the proportion that correctly did not have the host-specific marker pattern) and sensitivity (i.e., among the samples from a given animal host, the proportion that correctly had the host-specific marker pattern), even after fivefold cross validation. Permutation tests confirmed that for most animals, host specific intergenic biomarkers identified by logic regression in E. coli were significantly associated with animal host source. The highest level of biomarker sensitivity was observed in deer isolates, with 82% of all deer E. coli isolates displaying a unique SNP pattern that was 98% specific to deer. Fifty-three percent of human isolates displayed a unique biomarker pattern that was 98% specific to humans. Twenty-nine percent of cattle isolates displayed a unique biomarker that was 97% specific to cattle. Interestingly, even within a related host group (i.e., Family: Canidae [domestic dogs and coyotes]), highly specific SNP biomarkers (98% and 99% specificity for dog and coyotes, respectively) were observed, with 21% of dog E. coli isolates displaying a unique dog biomarker and 61% of coyote isolates

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

Recent advances in biomarkers and therapeutic interventions for hepatic drug safety - false dawn or new horizon?

PubMed

Clarke, Joanna I; Dear, James W; Antoine, Daniel J

2016-05-01

Drug-induced liver injury (DILI) represents a serious medical challenge and a potentially fatal adverse event. Currently, DILI is a diagnosis of exclusion, and whilst the electronic evaluation of serious drug-induced hepatotoxicity (eDISH) have revolutionised the early assessment of DILI, this model is dependent upon clinical chemistry parameters that lack sensitivity and specificity. DILI management usually consists of initial withdrawal of the suspected drug and, in the case of acetaminophen, administration of specific therapy. We summarise recent advances and knowledge gaps in the development and qualification of novel DILI biomarkers and therapeutic interventions. Promising biomarkers have been identified that provide increased hepatic specificity (miR-122), mechanistic insight (Keratin-18), and prognostic information (HMGB1, KIM-1, CSF-1). Pharmacogenomics holds potential to preselect susceptible populations and tailor drug therapy. Biomarkers can uncover new mechanisms of drug-induced pathophysiology which, for HMGB1 and CSF-1, have led to promising mechanism-based therapeutic interventions. However, these biomarkers have not been formally qualified and are not in routine clinical use. With the development of inventive clinical trials and by maximising DILI data registries, these novel biomarkers could add substantial value to the current armoury, change the management of DILI in the near future and improve patient safety.

Quality specification and status of internal quality control of cardiac biomarkers in China from 2011 to 2016.

PubMed

Li, Tingting; Wang, Wei; Zhao, Haijian; He, Falin; Zhong, Kun; Yuan, Shuai; Wang, Zhiguo

2017-09-07

This study aimed to investigate the status of internal quality control (IQC) for cardiac biomarkers from 2011 to 2016 so that we can have overall knowledge of the precision level of measurements in China and set appropriate precision specifications. Internal quality control data of cardiac biomarkers, including creatinine kinase MB (CK-MB) (μg/L), CK-MB(U/L), myoglobin (Mb), cardiac troponin I (cTnI), cardiac troponin T (cTnT), and homocysteines (HCY), were collected by a web-based external quality assessment (EQA) system. Percentages of laboratories meeting five precision quality specifications for current coefficient of variations (CVs) were calculated. Then, appropriate precision specifications were chosen for these six analytes. Finally, the CVs and IQC practice were further analyzed with different grouping methods. The current CVs remained nearly constant for 6 years. cTnT had the highest pass rates every year against five specifications, whereas HCY had the lowest pass rates. Overall, most analytes had a satisfactory performance (pass rates >80%), except for HCY, if one-third TEa or the minimum specification were employed. When the optimal specification was applied, the performance of most analytes was frustrating (pass rates < 60%) except for cTnT. The appropriate precision specifications of Mb, cTnI, cTnT and HCY were set as current CVs less than 9.20%, 9.90%, 7.50%, 10.54%, 7.63%, and 6.67%, respectively. The data of IQC practices indicated wide variation and substantial progress. The precision performance of cTnT was already satisfying, while the other five analytes, especially HCY, were still frustrating; thus, ongoing investigation and continuous improvement for IQC are still needed. © 2017 Wiley Periodicals, Inc.

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.

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation

PubMed Central

2010-01-01

Background To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Methods Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Results Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Conclusions Coronin-1C could be a candidate biomarker to predict HCC invasive behavior. PMID:20181269

Coronin-1C is a novel biomarker for hepatocellular carcinoma invasive progression identified by proteomics analysis and clinical validation.

PubMed

Wu, Long; Peng, Chun-Wei; Hou, Jin-Xuan; Zhang, Yan-Hua; Chen, Chuang; Chen, Liang-Dong; Li, Yan

2010-02-24

To better search for potential markers for hepatocellular carcinoma (HCC) invasion and metastasis, proteomic approach was applied to identify potential metastasis biomarkers associated with HCC. Membrane proteins were extracted from MHCC97L and HCCLM9 cells, with a similar genetic background and remarkably different metastasis potential, and compared by SDS-PAGE and identified by ESI-MS/MS. The results were further validated by western blot analysis, immunohistochemistry (IHC) of tumor tissues from HCCLM9- and MHCC97L-nude mice, and clinical specimens. Membrane proteins were extracted from MHCC97L and HCCLM9 cell and compared by SDS-PAGE analyses. A total of 14 differentially expressed proteins were identified by ESI-MS/MS. Coronin-1C, a promising candidate, was found to be overexpressed in HCCLM9 cells as compared with MHCC97L cells, and validated by western blot and IHC from both nude mice tumor tissues and clinical specimens. Coronin-1C level showed an abrupt upsurge when pulmonary metastasis occurred. Increasing coronin-1C expression was found in liver cancer tissues of HCCLM9-nude mice with spontaneous pulmonary metastasis. IHC study on human HCC specimens revealed that more patients in the higher coronin-1C group had overt larger tumor and more advanced stage. Coronin-1C could be a candidate biomarker to predict HCC invasive behavior.

Synthesis of eukaryotic lipid biomarkers in the bacterial domain

NASA Astrophysics Data System (ADS)

Welander, P. V.; Banta, A. B.; Lee, A. K.; Wei, J. H.

2017-12-01

Lipid biomarkers are organic molecules preserved in sediments and sedimentary rocks that can function as geological proxies for certain microbial taxa or for specific environmental conditions. These molecular fossils provide a link between organisms and their environments in both modern and ancient settings and have afforded significant insight into ancient climatic events, mass extinctions, and various evolutionary transitions throughout Earth's history. However, the proper interpretation of lipid biomarkers is dependent on a broad understanding of their diagenetic precursors in modern systems. This includes understanding the taphonomic transformations that these molecules undergo, their biosynthetic pathways, and the ecological conditions that affect their cellular production. In this study, we focus on one group of lipid biomarkers - the sterols. These are polycyclic isoprenoidal lipids that have a high preservation potential and play a critical role in the physiology of most eukaryotes. However, the synthesis and function of these lipids in the bacterial domain has not been fully explored. Here we utilize a combination of bioinformatics, microbial genetics, and biochemistry to demonstrate that bacterial sterol producers are more prevalent in environmental metagenomic samples than in the genomic databases of cultured organisms and to identify novel proteins required to synthesize and modify sterols in bacteria. These proteins represent a distinct pathway for sterol synthesis exclusive to bacteria and indicate that sterol synthesis in bacteria may have evolved independently of eukaryotic sterol biosynthesis. Taken together, these results demonstrate how studies in extant bacteria can provide insight into the biological sources and the biosynthetic pathways of specific lipid biomarkers and in turn may allow for more robust interpretation of biomarker signatures.

Acute diagnostic biomarkers for spinal cord injury: review of the literature and preliminary research report.

PubMed

Yokobori, Shoji; Zhang, Zhiqun; Moghieb, Ahmed; Mondello, Stefania; Gajavelli, Shyam; Dietrich, W Dalton; Bramlett, Helen; Hayes, Ronald L; Wang, Michael; Wang, Kevin K W; Bullock, M Ross

2015-05-01

Many efforts have been made to create new diagnostic technologies for use in the diagnosis of central nervous system injury. However, there is still no consensus for the use of biomarkers in clinical acute spinal cord injury (SCI). The aims of this review are (1) to evaluate the current status of neurochemical biomarkers and (2) to discuss their potential acute diagnostic role in SCI by reviewing the literature. PubMed (http://www.ncbi.nlm.nih.gov/pubmed) was searched up to 2012 to identify publications concerning diagnostic biomarkers in SCI. To support more knowledge, we also checked secondary references in the primarily retrieved literature. Neurofilaments, cleaved-Tau, microtubule-associated protein 2, myelin basic protein, neuron-specific enolase, S100β, and glial fibrillary acidic protein were identified as structural protein biomarkers in SCI by this review process. We could not find reports relating ubiquitin C-terminal hydrolase-L1 and α-II spectrin breakdown products, which are widely researched in other central nervous system injuries. Therefore, we present our preliminary data relating to these two biomarkers. Some of biomarkers showed promising results for SCI diagnosis and outcome prediction; however, there were unresolved issues relating to accuracy and their accessibility. Currently, there still are not many reports focused on diagnostic biomarkers in SCI. This fact warranted the need for greater efforts to innovate sensitive and reliable biomarkers for SCI. Copyright © 2015 Elsevier Inc. All rights reserved.

The molecular signature of impaired diabetic wound healing identifies serpinB3 as a healing biomarker.

PubMed

Fadini, Gian Paolo; Albiero, Mattia; Millioni, Renato; Poncina, Nicol; Rigato, Mauro; Scotton, Rachele; Boscari, Federico; Brocco, Enrico; Arrigoni, Giorgio; Villano, Gianmarco; Turato, Cristian; Biasiolo, Alessandra; Pontisso, Patrizia; Avogaro, Angelo

2014-09-01

Chronic foot ulceration is a severe complication of diabetes, driving morbidity and mortality. The mechanisms underlying delaying wound healing in diabetes are incompletely understood and tools to identify such pathways are eagerly awaited. Wound biopsies were obtained from 75 patients with diabetic foot ulcers. Matched subgroups of rapidly healing (RH, n = 17) and non-healing (NH, n = 11) patients were selected. Proteomic analysis was performed by labelling with isobaric tag for relative and absolute quantification and mass spectrometry. Differentially expressed proteins were analysed in NH vs RH for identification of pathogenic pathways. Individual sample gene/protein validation and in vivo validation of candidate pathways in mouse models were carried out. Pathway analyses were conducted on 92/286 proteins that were differentially expressed in NH vs RH. The following pathways were enriched in NH vs RH patients: apoptosis, protease inhibitors, epithelial differentiation, serine endopeptidase activity, coagulation and regulation of defence response. SerpinB3 was strongly upregulated in RH vs NH wounds, validated as protein and mRNA in individual samples. To test the relevance of serpinB3 in vivo, we used a transgenic mouse model with α1-antitrypsin promoter-driven overexpression of human SERPINB3. In this model, wound healing was unaffected by SERPINB3 overexpression in non-diabetic or diabetic mice with or without hindlimb ischaemia. In an independent validation cohort of 47 patients, high serpinB3 protein content was confirmed as a biomarker of healing improvement. We provide a benchmark for the unbiased discovery of novel molecular targets and biomarkers of impaired diabetic wound healing. High serpinB3 protein content was found to be a biomarker of successful healing in diabetic patients.

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

Recommendations for Soluble Biomarker Assessments in Osteoarthritis Clinical Trials

PubMed Central

Kraus, Virginia Byers; Blanco, Francisco J; Englund, Martin; Henrotin, Yves; Lohmander, L Stefan; Losina, Elena; Önnerfjord, Patrik; Persiani, Stefano

2015-01-01

Objective To describe requirements for inclusion of soluble biomarkers in osteoarthritis (OA) clinical trials and progress toward OA-related biomarker qualification. Methods The Guidelines for Biomarkers Working Group, representing experts in the field of OA biomarker research from both academia and industry, convened to discuss issues related to soluble biomarkers and to make recommendations for their use in OA clinical trials based on current knowledge and anticipated benefits. Results This document summarizes current guidance on use of biomarkers in OA clinical trials and their utility at 5 stages, including preclinical development and phase I to phase IV trials. Conclusions Biomarkers can provide value at all stages of therapeutics development. When resources permit, we recommend collection of biospecimens in all OA clinical trials for a wide variety of reasons but in particular, to determine whether biomarkers are useful in identifying those individuals most likely to receive clinically important benefits from an intervention; and to determine whether biomarkers are useful for identifying individuals at earlier stages of OA in order to institute treatment at a time more amenable to disease modification. PMID:25952342

Biomarkers in Pediatric ARDS: Future Directions.

PubMed

Orwoll, Benjamin E; Sapru, Anil

2016-01-01

Acute respiratory distress syndrome (ARDS) is common among mechanically ventilated children and accompanies up to 30% of all pediatric intensive care unit deaths. Though ARDS diagnosis is based on clinical criteria, biological markers of acute lung damage have been extensively studied in adults and children. Biomarkers of inflammation, alveolar epithelial and capillary endothelial disruption, disordered coagulation, and associated derangements measured in the circulation and other body fluids, such as bronchoalveolar lavage, have improved our understanding of pathobiology of ARDS. The biochemical signature of ARDS has been increasingly well described in adult populations, and this has led to the identification of molecular phenotypes to augment clinical classifications. However, there is a paucity of data from pediatric ARDS (pARDS) patients. Biomarkers and molecular phenotypes have the potential to identify patients at high risk of poor outcomes, and perhaps inform the development of targeted therapies for specific groups of patients. Additionally, because of the lower incidence of and mortality from ARDS in pediatric patients relative to adults and lack of robust clinical predictors of outcome, there is an ongoing interest in biological markers as surrogate outcome measures. The recent definition of pARDS provides additional impetus for the measurement of established and novel biomarkers in future pediatric studies in order to further characterize this disease process. This chapter will review the currently available literature and discuss potential future directions for investigation into biomarkers in ARDS among children.

Biomarkers in Pediatric ARDS: Future Directions

PubMed Central

Orwoll, Benjamin E.; Sapru, Anil

2016-01-01

Acute respiratory distress syndrome (ARDS) is common among mechanically ventilated children and accompanies up to 30% of all pediatric intensive care unit deaths. Though ARDS diagnosis is based on clinical criteria, biological markers of acute lung damage have been extensively studied in adults and children. Biomarkers of inflammation, alveolar epithelial and capillary endothelial disruption, disordered coagulation, and associated derangements measured in the circulation and other body fluids, such as bronchoalveolar lavage, have improved our understanding of pathobiology of ARDS. The biochemical signature of ARDS has been increasingly well described in adult populations, and this has led to the identification of molecular phenotypes to augment clinical classifications. However, there is a paucity of data from pediatric ARDS (pARDS) patients. Biomarkers and molecular phenotypes have the potential to identify patients at high risk of poor outcomes, and perhaps inform the development of targeted therapies for specific groups of patients. Additionally, because of the lower incidence of and mortality from ARDS in pediatric patients relative to adults and lack of robust clinical predictors of outcome, there is an ongoing interest in biological markers as surrogate outcome measures. The recent definition of pARDS provides additional impetus for the measurement of established and novel biomarkers in future pediatric studies in order to further characterize this disease process. This chapter will review the currently available literature and discuss potential future directions for investigation into biomarkers in ARDS among children. PMID:27313995

The BioFIND study: Characteristics of a clinically typical Parkinson's disease biomarker cohort

PubMed Central

Goldman, Jennifer G.; Alcalay, Roy N.; Xie, Tao; Tuite, Paul; Henchcliffe, Claire; Hogarth, Penelope; Amara, Amy W.; Frank, Samuel; Rudolph, Alice; Casaceli, Cynthia; Andrews, Howard; Gwinn, Katrina; Sutherland, Margaret; Kopil, Catherine; Vincent, Lona; Frasier, Mark

2016-01-01

ABSTRACT Background Identifying PD‐specific biomarkers in biofluids will greatly aid in diagnosis, monitoring progression, and therapeutic interventions. PD biomarkers have been limited by poor discriminatory power, partly driven by heterogeneity of the disease, variability of collection protocols, and focus on de novo, unmedicated patients. Thus, a platform for biomarker discovery and validation in well‐characterized, clinically typical, moderate to advanced PD cohorts is critically needed. Methods BioFIND (Fox Investigation for New Discovery of Biomarkers in Parkinson's Disease) is a cross‐sectional, multicenter biomarker study that established a repository of clinical data, blood, DNA, RNA, CSF, saliva, and urine samples from 118 moderate to advanced PD and 88 healthy control subjects. Inclusion criteria were designed to maximize diagnostic specificity by selecting participants with clinically typical PD symptoms, and clinical data and biospecimen collection utilized standardized procedures to minimize variability across sites. Results We present the study methodology and data on the cohort's clinical characteristics. Motor scores and biospecimen samples including plasma are available for practically defined off and on states and thus enable testing the effects of PD medications on biomarkers. Other biospecimens are available from off state PD assessments and from controls. Conclusion Our cohort provides a valuable resource for biomarker discovery and validation in PD. Clinical data and biospecimens, available through The Michael J. Fox Foundation for Parkinson's Research and the National Institute of Neurological Disorders and Stroke, can serve as a platform for discovering biomarkers in clinically typical PD and comparisons across PD's broad and heterogeneous spectrum. © 2016 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society PMID:27113479

Examining Autism Spectrum Disorders by Biomarkers: Example from the Oxytocin and Serotonin Systems

ERIC Educational Resources Information Center

Hammock, Elizabeth; Veenstra-VanderWeele, Jeremy; Yan, Zhongyu; Kerr, Travis M.; Morris, Marianna; Anderson, George M.; Carter, C. Sue; Cook, Edwin H.; Jacob, Suma

2012-01-01

Objective: Autism spectrum disorder (ASD) is a heritable but highly heterogeneous neuropsychiatric syndrome, which poses challenges for research relying solely on behavioral symptoms or diagnosis. Examining biomarkers may give us ways to identify individuals who demonstrate specific developmental trajectories and etiological factors related to…

A Compendium of Urinary Biomarkers Indicative of Glomerular Podocytopathy

PubMed Central

2013-01-01

It is well known that glomerular podocyte injury and loss are present in numerous nephropathies and that the pathophysiologic consecution of disease hinges upon the fate of the podocyte. While multiple factors play a hand in glomerulopathy progression, basic logic lends that if one monitors the podocyte's status, that may reflect the status of disease. Recent investigations have focused on what one can elucidate from the noninvasive collection of urine, and have proven that certain, specific biomarkers of podocytes can be readily identified via varying techniques. This paper has brought together all described urinary biomarkers of podocyte injury and is made to provide a concise summary of their utility and testing in laboratory and clinical theatres. While promising in the potential that they hold as tools for clinicians and investigators, the described biomarkers require further comprehensive vetting in the form of larger clinical trials and studies that would give their value true weight. These urinary biomarkers are put forth as novel indicators of glomerular disease presence, disease progression, and therapeutic efficacy that in some cases may be more advantageous than the established parameters/measures currently used in practice. PMID:24327929

Age and diagnostic performance of Alzheimer disease CSF biomarkers

PubMed Central

Rosén, E.; Hansson, O.; Andreasen, N.; Parnetti, L.; Jonsson, M.; Herukka, S.-K.; van der Flier, W.M.; Blankenstein, M.A.; Ewers, M.; Rich, K.; Kaiser, E.; Verbeek, M.M.; Olde Rikkert, M.; Tsolaki, M.; Mulugeta, E.; Aarsland, D.; Visser, P.J.; Schröder, J.; Marcusson, J.; de Leon, M.; Hampel, H.; Scheltens, P.; Wallin, A.; Eriksdotter-Jönhagen, M.; Minthon, L.; Winblad, B.; Blennow, K.; Zetterberg, H.

2012-01-01

Objectives: Core CSF changes in Alzheimer disease (AD) are decreased amyloid β1–42, increased total tau, and increased phospho-tau, probably indicating amyloid plaque accumulation, axonal degeneration, and tangle pathology, respectively. These biomarkers identify AD already at the predementia stage, but their diagnostic performance might be affected by age-dependent increase of AD-type brain pathology in cognitively unaffected elderly. Methods: We investigated effects of age on the diagnostic performance of CSF biomarkers in a uniquely large multicenter study population, including a cross-sectional cohort of 529 patients with AD dementia (median age 71, range 43–89 years) and 304 controls (67, 44–91 years), and a longitudinal cohort of 750 subjects without dementia with mild cognitive impairment (69, 43–89 years) followed for at least 2 years, or until dementia diagnosis. Results: The specificities for subjects without AD and the areas under the receiver operating characteristics curves decreased with age. However, the positive predictive value for a combination of biomarkers remained stable, while the negative predictive value decreased only slightly in old subjects, as an effect of the high AD prevalence in older ages. Conclusion: Although the diagnostic accuracies for AD decreased with age, the predictive values for a combination of biomarkers remained essentially stable. The findings highlight biomarker variability across ages, but support the use of CSF biomarkers for AD even in older populations. PMID:22302554

Can interleukin-2 and interleukin-1β be specific biomarkers of negative symptoms in schizophrenia?

PubMed

González-Blanco, Leticia; García-Portilla, María P; García-Álvarez, Leticia; de la Fuente-Tomás, Lorena; Iglesias García, Celso; Sáiz, Pilar A; Rodríguez-González, Susana; Coto-Montes, Ana; Bobes, Julio

2018-04-30

Evidence suggests the existence of cytokine disturbances in patients with schizophrenia but their association with psychopathology is still unclear. The aim of the current study was to determine if pro-inflammatory cytokine levels (tumor necrosis factor-α, interleukin (IL)-6, IL-2, IL-1β, IL-1RA) are increased in stable outpatients compared with healthy subjects, and to analyze if they could be specific biomarkers of clinical dimensions in schizophrenia. We studied 73 stable outpatients with schizophrenia in their first 10 years of illness and 73 age- and sex-matched healthy controls. An accurate assessment of clinical dimensions (positive, negative, depressive, cognitive) was performed in patients. Only IL-6 levels were significantly increased in patients after controlling for body mass index, waist circumference, smoking, and psychopharmacological treatment, compared with healthy subjects. After adjusting for several confounders, multiple linear regression models identified that Positive and Negative Syndrome Scale negative symptoms, general psychopathology, and global severity are predicted by IL-1β concentrations, while motivation and pleasure domain of Clinical Assessment Interview for Negative Symptoms and Personal and Social Performance global functioning scores are predicted by IL-2 levels. Cognitive performance, positive, and depressive symptom severity did not correlate with any cytokine. Our findings suggested that IL-6 concentrations are elevated in stable patients with schizophrenia. Whereas IL-2 specifically marks severity of the motivation and pleasure domain of negative symptoms, IL-1β is not specific to this dimension as it also predicts severity of general and global symptomatology. Copyright © 2018 SEP y SEPB. Publicado por Elsevier España, S.L.U. All rights reserved.

Sorting Five Human Tumor Types Reveals Specific Biomarkers and Background Classification Genes.

PubMed

Roche, Kimberly E; Weinstein, Marvin; Dunwoodie, Leland J; Poehlman, William L; Feltus, Frank A

2018-05-25

We applied two state-of-the-art, knowledge independent data-mining methods - Dynamic Quantum Clustering (DQC) and t-Distributed Stochastic Neighbor Embedding (t-SNE) - to data from The Cancer Genome Atlas (TCGA). We showed that the RNA expression patterns for a mixture of 2,016 samples from five tumor types can sort the tumors into groups enriched for relevant annotations including tumor type, gender, tumor stage, and ethnicity. DQC feature selection analysis discovered 48 core biomarker transcripts that clustered tumors by tumor type. When these transcripts were removed, the geometry of tumor relationships changed, but it was still possible to classify the tumors using the RNA expression profiles of the remaining transcripts. We continued to remove the top biomarkers for several iterations and performed cluster analysis. Even though the most informative transcripts were removed from the cluster analysis, the sorting ability of remaining transcripts remained strong after each iteration. Further, in some iterations we detected a repeating pattern of biological function that wasn't detectable with the core biomarker transcripts present. This suggests the existence of a "background classification" potential in which the pattern of gene expression after continued removal of "biomarker" transcripts could still classify tumors in agreement with the tumor type.

Biomarkers as Common Data Elements for Symptom and Self-Management Science.

PubMed

Page, Gayle G; Corwin, Elizabeth J; Dorsey, Susan G; Redeker, Nancy S; McCloskey, Donna Jo; Austin, Joan K; Guthrie, Barbara J; Moore, Shirley M; Barton, Debra; Kim, Miyong T; Docherty, Sharron L; Waldrop-Valverde, Drenna; Bailey, Donald E; Schiffman, Rachel F; Starkweather, Angela; Ward, Teresa M; Bakken, Suzanne; Hickey, Kathleen T; Renn, Cynthia L; Grady, Patricia

2018-05-01

Biomarkers as common data elements (CDEs) are important for the characterization of biobehavioral symptoms given that once a biologic moderator or mediator is identified, biologically based strategies can be investigated for treatment efforts. Just as a symptom inventory reflects a symptom experience, a biomarker is an indicator of the symptom, though not the symptom per se. The purposes of this position paper are to (a) identify a "minimum set" of biomarkers for consideration as CDEs in symptom and self-management science, specifically biochemical biomarkers; (b) evaluate the benefits and limitations of such a limited array of biomarkers with implications for symptom science; (c) propose a strategy for the collection of the endorsed minimum set of biologic samples to be employed as CDEs for symptom science; and (d) conceptualize this minimum set of biomarkers consistent with National Institute of Nursing Research (NINR) symptoms of fatigue, depression, cognition, pain, and sleep disturbance. From May 2016 through January 2017, a working group consisting of a subset of the Directors of the NINR Centers of Excellence funded by P20 or P30 mechanisms and NINR staff met bimonthly via telephone to develop this position paper suggesting the addition of biomarkers as CDEs. The full group of Directors reviewed drafts, provided critiques and suggestions, recommended the minimum set of biomarkers, and approved the completed document. Best practices for selecting, identifying, and using biological CDEs as well as challenges to the use of biological CDEs for symptom and self-management science are described. Current platforms for sample outcome sharing are presented. Finally, biological CDEs for symptom and self-management science are proposed along with implications for future research and use of CDEs in these areas. The recommended minimum set of biomarker CDEs include pro- and anti-inflammatory cytokines, a hypothalamic-pituitary-adrenal axis marker, cortisol, the

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

PubMed

Emwas, Abdul-Hamid; Roy, Raja; McKay, Ryan T; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G A Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S

2016-02-05

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

Risk factors and biomarkers of life-threatening cancers

PubMed Central

Autier, Philippe

2015-01-01

There is growing evidence that risk factors for cancer occurrence and for cancer death are not necessarily the same. Knowledge of cancer aggressiveness risk factors (CARF) may help in identifying subjects at high risk of developing a potentially deadly cancer (and not just any cancer). The availability of CARFs may have positive consequences for health policies, medical practice, and the search for biomarkers. For instance, cancer chemoprevention and cancer screening of subjects with CARFs would probably be more ethical and cost-effective than recommending chemoprevention and screening to entire segments of the population. Also, the harmful consequences of chemoprevention and of screening would be reduced while effectiveness would be optimised. We present examples of CARF already in use (e.g. mutations of the breast cancer (BRCA) gene), of promising avenues for the discovery of biomarkers thanks to the investigation of CARFs (e.g. breast radiological density and systemic inflammation), and of biomarkers commonly used that are not real CARFs (e.g. certain mammography images, prostate-specific antigen (PSA) concentration, nevus number). PMID:26635900

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

PubMed Central

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

2013-01-01

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

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.

Discovery of putative salivary biomarkers for Sjögren's syndrome using high resolution mass spectrometry and bioinformatics.

PubMed

Zoukhri, Driss; Rawe, Ian; Singh, Mabi; Brown, Ashley; Kublin, Claire L; Dawson, Kevin; Haddon, William F; White, Earl L; Hanley, Kathleen M; Tusé, Daniel; Malyj, Wasyl; Papas, Athena

2012-03-01

The purpose of the current study was to determine if saliva contains biomarkers that can be used as diagnostic tools for Sjögren's syndrome (SjS). Twenty seven SjS patients and 27 age-matched healthy controls were recruited for these studies. Unstimulated glandular saliva was collected from the Wharton's duct using a suction device. Two µl of salvia were processed for mass spectrometry analyses on a prOTOF 2000 matrix-assisted laser desorption/ionization orthogonal time of flight (MALDI O-TOF) mass spectrometer. Raw data were analyzed using bioinformatic tools to identify biomarkers. MALDI O-TOF MS analyses of saliva samples were highly reproducible and the mass spectra generated were very rich in peptides and peptide fragments in the 750-7,500 Da range. Data analysis using bioinformatic tools resulted in several classification models being built and several biomarkers identified. One model based on 7 putative biomarkers yielded a sensitivity of 97.5%, specificity of 97.8% and an accuracy of 97.6%. One biomarker was present only in SjS samples and was identified as a proteolytic peptide originating from human basic salivary proline-rich protein 3 precursor. We conclude that salivary biomarkers detected by high-resolution mass spectrometry coupled with powerful bioinformatic tools offer the potential to serve as diagnostic/prognostic tools for SjS.

Novel proxies for reconstructing paleohydrology from ombrotrophic peatlands: biomarker and compound-specific H and C stable isotope ratios

NASA Astrophysics Data System (ADS)

Wang, J.; Nichols, J. E.; Huang, Y.

2008-12-01

Ombrotrophic peatlands are excellent archives for paleohydrologic information because they are hydrologically isolated from their surroundings. However, quantitative proxies for deciphering peatland archives are lacking. Here, we present development and application of novel organic geochemical methods for quantitative reconstruction of paleohydrology from the ombrotrophic sediments, and comparison of organic geochemical data with conventional paleoecological proxies. Application of these methods to the sediments of several North American and European peatlands has revealed significant changes in the hydroclimate throughout the Holocene. The plant assemblage living at the surface of the peatland is tightly controlled by surface moisture. Under wet conditions, Sphagnum mosses, with no active mechanism for drawing water from below the surface of the peatland, are dominant. During dry conditions, vascular plants are more productive relative to Sphagnum. A ratio of the abundance of two biomarkers representing Sphagnum and vascular plants sensitively records changes in hydrologic balance (Nichols et al., 2006, Org. Geochem. 37, 1505-1513). We have further developed stable isotope models to compute climate parameters from compound-specific H and C isotope ratios of biomarkers to create a more comprehensive climate reconstruction. Vascular plant leaf waxes carry the D/H ratio signature of precipitation that is little affected by evaporation, whereas the Sphagnum biomarker records isotopic ratios of the water at the peatland surface, which is strongly enriched by evaporation. Evaporation amount can be calculated using the differences between D/H ratios of the two types of biomarkers. C isotope ratios of Sphagnum biomarkers can also be used to quantify surface wetness. Methanotrophic bacteria live symbiotically with Sphagnum, providing isotopically light carbon for photosynthesis. These bacteria are more active when the Sphagnum is wet, thus providing more 13C-depleted CO2

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

Epigenome-Wide Association Study Identifies Cardiac Gene Patterning and a Novel Class of Biomarkers for Heart Failure.

PubMed

Meder, Benjamin; Haas, Jan; Sedaghat-Hamedani, Farbod; Kayvanpour, Elham; Frese, Karen; Lai, Alan; Nietsch, Rouven; Scheiner, Christina; Mester, Stefan; Bordalo, Diana Martins; Amr, Ali; Dietrich, Carsten; Pils, Dietmar; Siede, Dominik; Hund, Hauke; Bauer, Andrea; Holzer, Daniel Benjamin; Ruhparwar, Arjang; Mueller-Hennessen, Matthias; Weichenhan, Dieter; Plass, Christoph; Weis, Tanja; Backs, Johannes; Wuerstle, Maximilian; Keller, Andreas; Katus, Hugo A; Posch, Andreas E

2017-10-17

Biochemical DNA modification resembles a crucial regulatory layer among genetic information, environmental factors, and the transcriptome. To identify epigenetic susceptibility regions and novel biomarkers linked to myocardial dysfunction and heart failure, we performed the first multi-omics study in myocardial tissue and blood of patients with dilated cardiomyopathy and controls. Infinium human methylation 450 was used for high-density epigenome-wide mapping of DNA methylation in left-ventricular biopsies and whole peripheral blood of living probands. RNA deep sequencing was performed on the same samples in parallel. Whole-genome sequencing of all patients allowed exclusion of promiscuous genotype-induced methylation calls. In the screening stage, we detected 59 epigenetic loci that are significantly associated with dilated cardiomyopathy (false discovery corrected P ≤0.05), with 3 of them reaching epigenome-wide significance at P ≤5×10 -8 . Twenty-seven (46%) of these loci could be replicated in independent cohorts, underlining the role of epigenetic regulation of key cardiac transcription regulators. Using a staged multi-omics study design, we link a subset of 517 epigenetic loci with dilated cardiomyopathy and cardiac gene expression. Furthermore, we identified distinct epigenetic methylation patterns that are conserved across tissues, rendering these CpGs novel epigenetic biomarkers for heart failure. The present study provides to our knowledge the first epigenome-wide association study in living patients with heart failure using a multi-omics approach. © 2017 American Heart Association, Inc.

Novel Automated Blood Separations Validate Whole Cell Biomarkers

PubMed Central

Burger, Douglas E.; Wang, Limei; Ban, Liqin; Okubo, Yoshiaki; Kühtreiber, Willem M.; Leichliter, Ashley K.; Faustman, Denise L.

2011-01-01

Background Progress in clinical trials in infectious disease, autoimmunity, and cancer is stymied by a dearth of successful whole cell biomarkers for peripheral blood lymphocytes (PBLs). Successful biomarkers could help to track drug effects at early time points in clinical trials to prevent costly trial failures late in development. One major obstacle is the inaccuracy of Ficoll density centrifugation, the decades-old method of separating PBLs from the abundant red blood cells (RBCs) of fresh blood samples. Methods and Findings To replace the Ficoll method, we developed and studied a novel blood-based magnetic separation method. The magnetic method strikingly surpassed Ficoll in viability, purity and yield of PBLs. To reduce labor, we developed an automated platform and compared two magnet configurations for cell separations. These more accurate and labor-saving magnet configurations allowed the lymphocytes to be tested in bioassays for rare antigen-specific T cells. The automated method succeeded at identifying 79% of patients with the rare PBLs of interest as compared with Ficoll's uniform failure. We validated improved upfront blood processing and show accurate detection of rare antigen-specific lymphocytes. Conclusions Improving, automating and standardizing lymphocyte detections from whole blood may facilitate development of new cell-based biomarkers for human diseases. Improved upfront blood processes may lead to broad improvements in monitoring early trial outcome measurements in human clinical trials. PMID:21799852

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.

Genomic reprograming analysis of the Mesothelial to Mesenchymal Transition identifies biomarkers in peritoneal dialysis patients

PubMed Central

Ruiz-Carpio, Vicente; Sandoval, Pilar; Aguilera, Abelardo; Albar-Vizcaíno, Patricia; Perez-Lozano, María Luisa; González-Mateo, Guadalupe T.; Acuña-Ruiz, Adrián; García-Cantalejo, Jesús; Botías, Pedro; Bajo, María Auxiliadora; Selgas, Rafael; Sánchez-Tomero, José Antonio; Passlick-Deetjen, Jutta; Piecha, Dorothea; Büchel, Janine; Steppan, Sonja; López-Cabrera, Manuel

2017-01-01

Peritoneal dialysis (PD) is an effective renal replacement therapy, but a significant proportion of patients suffer PD-related complications, which limit the treatment duration. Mesothelial-to-mesenchymal transition (MMT) contributes to the PD-related peritoneal dysfunction. We analyzed the genetic reprograming of MMT to identify new biomarkers that may be tested in PD-patients. Microarray analysis revealed a partial overlapping between MMT induced in vitro and ex vivo in effluent-derived mesothelial cells, and that MMT is mainly a repression process being higher the number of genes that are down-regulated than those that are induced. Cellular morphology and number of altered genes showed that MMT ex vivo could be subdivided into two stages: early/epithelioid and advanced/non-epithelioid. RT-PCR array analysis demonstrated that a number of genes differentially expressed in effluent-derived non-epithelioid cells also showed significant differential expression when comparing standard versus low-GDP PD fluids. Thrombospondin-1 (TSP1), collagen-13 (COL13), vascular endothelial growth factor A (VEGFA), and gremlin-1 (GREM1) were measured in PD effluents, and except GREM1, showed significant differences between early and advanced stages of MMT, and their expression was associated with a high peritoneal transport status. The results establish a proof of concept about the feasibility of measuring MMT-associated secreted protein levels as potential biomarkers in PD. PMID:28327551

Analysis of the Human Prostate-Specific Proteome Defined by Transcriptomics and Antibody-Based Profiling Identifies TMEM79 and ACOXL as Two Putative, Diagnostic Markers in Prostate Cancer

PubMed Central

O'Hurley, Gillian; Busch, Christer; Fagerberg, Linn; Hallström, Björn M.; Stadler, Charlotte; Tolf, Anna; Lundberg, Emma; Schwenk, Jochen M.; Jirström, Karin; Bjartell, Anders; Gallagher, William M.; Uhlén, Mathias; Pontén, Fredrik

2015-01-01

To better understand prostate function and disease, it is important to define and explore the molecular constituents that signify the prostate gland. The aim of this study was to define the prostate specific transcriptome and proteome, in comparison to 26 other human tissues. Deep sequencing of mRNA (RNA-seq) and immunohistochemistry-based protein profiling were combined to identify prostate specific gene expression patterns and to explore tissue biomarkers for potential clinical use in prostate cancer diagnostics. We identified 203 genes with elevated expression in the prostate, 22 of which showed more than five-fold higher expression levels compared to all other tissue types. In addition to previously well-known proteins we identified two poorly characterized proteins, TMEM79 and ACOXL, with potential to differentiate between benign and cancerous prostatic glands in tissue biopsies. In conclusion, we have applied a genome-wide analysis to identify the prostate specific proteome using transcriptomics and antibody-based protein profiling to identify genes with elevated expression in the prostate. Our data provides a starting point for further functional studies to explore the molecular repertoire of normal and diseased prostate including potential prostate cancer markers such as TMEM79 and ACOXL. PMID:26237329

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

Endometrial biomarkers for the non-invasive diagnosis of endometriosis.

PubMed

Gupta, Devashana; Hull, M Louise; Fraser, Ian; Miller, Laura; Bossuyt, Patrick M M; Johnson, Neil; Nisenblat, Vicki

2016-04-20

biomarkers demonstrated significant diversity for the diagnostic estimates between the studies; however, the data were too limited to reliably determine the sources of heterogeneity. The mean sensitivities and specificities of PGP 9.5 (7 studies, 361 women) were 0.96 (95% confidence interval (CI) 0.91 to 1.00) and 0.86 (95% CI 0.70 to 1.00), after excluding one outlier study, and for CYP19 (8 studies, 444 women), they were were 0.77 (95% CI 0.70 to 0.85) and 0.74 (95% CI 0.65 to 84), respectively. We could not statistically evaluate other biomarkers in a meaningful way. An additional 31 studies evaluated 77 biomarkers that showed no evidence of differences in expression levels between the groups of women with and without endometriosis. We could not statistically evaluate most of the biomarkers assessed in this review in a meaningful way. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Although PGP 9.5 met the criteria for a replacement test, it demonstrated considerable inter study heterogeneity in diagnostic estimates, the source of which could not be determined. Several endometrial biomarkers, such as endometrial proteome, 17βHSD2, IL-1R2, caldesmon and other neural markers (VIP, CGRP, SP, NPY and combination of VIP, PGP 9.5 and SP) showed promising evidence of diagnostic accuracy, but there was insufficient or poor quality evidence for any clinical recommendations. Laparoscopy remains the gold standard for the diagnosis of endometriosis, and using any non-invasive tests should only be undertaken in a research setting. We have also identified a number of biomarkers that demonstrated no diagnostic value for endometriosis. We recommend that researchers direct future studies towards biomarkers with high diagnostic potential in good quality diagnostic studies.

Low levels of serum serotonin and amino acids identified in migraine patients.

PubMed

Ren, Caixia; Liu, Jia; Zhou, Juntuo; Liang, Hui; Wang, Yayun; Sun, Yinping; Ma, Bin; Yin, Yuxin

2018-02-05

Migraine is a highly disabling primary headache associated with a high socioeconomic burden and a generally high prevalence. The clinical management of migraine remains a challenge. This study was undertaken to identify potential serum biomarkers of migraine. Using Liquid Chromatography coupled to Mass Spectrometry (LC-MS), the metabolomic profile of migraine was compared with healthy individuals. Principal component analysis (PCA) and Orthogonal partial least squares-discriminant analysis (orthoPLS-DA) showed the metabolomic profile of migraine is distinguishable from controls. Volcano plot analysis identified 10 serum metabolites significantly decreased during migraine. One of these was serotonin, and the other 9 were amino acids. Pathway analysis and enrichment analysis showed tryptophan metabolism (serotonin metabolism), arginine and proline metabolism, and aminoacyl-tRNA biosynthesis are the three most prominently altered pathways in migraine. ROC curve analysis indicated Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine are potential sensitive and specific biomarkers for migraine. Our results show Glycyl-l-proline, N-Methyl-dl-Alanine and l-Methionine may be as specific or more specific for migraine than serotonin which is the traditional biomarker of migraine. We propose that therapeutic manipulation of these metabolites or metabolic pathways may be helpful in the prevention and treatment of migraine. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

A structured proteomic approach identifies 14-3-3Sigma as a novel and reliable protein biomarker in panel based differential diagnostics of liver tumors.

PubMed

Reis, Henning; Pütter, Carolin; Megger, Dominik A; Bracht, Thilo; Weber, Frank; Hoffmann, Andreas-C; Bertram, Stefanie; Wohlschläger, Jeremias; Hagemann, Sascha; Eisenacher, Martin; Scherag, André; Schlaak, Jörg F; Canbay, Ali; Meyer, Helmut E; Sitek, Barbara; Baba, Hideo A

2015-06-01

Hepatocellular carcinoma (HCC) is a major lethal cancer worldwide. Despite sophisticated diagnostic algorithms, the differential diagnosis of small liver nodules still is difficult. While imaging techniques have advanced, adjuvant protein-biomarkers as glypican3 (GPC3), glutamine-synthetase (GS) and heat-shock protein 70 (HSP70) have enhanced diagnostic accuracy. The aim was to further detect useful protein-biomarkers of HCC with a structured systematic approach using differential proteome techniques, bring the results to practical application and compare the diagnostic accuracy of the candidates with the established biomarkers. After label-free and gel-based proteomics (n=18 HCC/corresponding non-tumorous liver tissue (NTLT)) biomarker candidates were tested for diagnostic accuracy in immunohistochemical analyses (n=14 HCC/NTLT). Suitable candidates were further tested for consistency in comparison to known protein-biomarkers in HCC (n=78), hepatocellular adenoma (n=25; HCA), focal nodular hyperplasia (n=28; FNH) and cirrhosis (n=28). Of all protein-biomarkers, 14-3-3Sigma (14-3-3S) exhibited the most pronounced up-regulation (58.8×) in proteomics and superior diagnostic accuracy (73.0%) in the differentiation of HCC from non-tumorous hepatocytes also compared to established biomarkers as GPC3 (64.7%) and GS (45.4%). 14-3-3S was part of the best diagnostic three-biomarker panel (GPC3, HSP70, 14-3-3S) for the differentiation of HCC and HCA which is of most important significance. Exclusion of GS and inclusion of 14-3-3S in the panel (>1 marker positive) resulted in a profound increase in specificity (+44.0%) and accuracy (+11.0%) while sensitivity remained stable (96.0%). 14-3-3S is an interesting protein biomarker with the potential to further improve the accuracy of differential diagnostic process of hepatocellular tumors. This article is part of a Special Issue entitled: Medical Proteomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Biomarkers of One-Carbon Metabolism Are Associated with Biomarkers of Inflammation in Women123

PubMed Central

Abbenhardt, Clare; Miller, Joshua W.; Song, Xiaoling; Brown, Elissa C.; Cheng, Ting-Yuan David; Wener, Mark H.; Zheng, Yingye; Toriola, Adetunji T.; Neuhouser, Marian L.; Beresford, Shirley A. A.; Makar, Karen W.; Bailey, Lynn B.; Maneval, David R.; Green, Ralph; Manson, JoAnn E.; Van Horn, Linda; Ulrich, Cornelia M.

2014-01-01

Folate-mediated one-carbon metabolism is essential for DNA synthesis, repair, and methylation. Perturbations in one-carbon metabolism have been implicated in increased risk of some cancers and may also affect inflammatory processes. We investigated these interrelated pathways to understand their relation. The objective was to explore associations between inflammation and biomarkers of nutritional status and one-carbon metabolism. In a cross-sectional study in 1976 women selected from the Women’s Health Initiative Observational Study, plasma vitamin B-6 [pyridoxal-5′-phosphate (PLP)], plasma vitamin B-12, plasma folate, and RBC folate were measured as nutritional biomarkers; serum C-reactive protein (CRP) and serum amyloid A (SAA) were measured as biomarkers of inflammation; and homocysteine and cysteine were measured as integrated biomarkers of one-carbon metabolism. Student’s t, chi-square, and Spearman rank correlations, along with multiple linear regressions, were used to explore relations between biomarkers; additionally, we tested stratification by folic acid fortification period and multivitamin use. With the use of univariate analysis, plasma PLP was the only nutritional biomarker that was modestly significantly correlated with serum CRP and SAA (ρ = −0.22 and −0.12, respectively; P < 0.0001). Homocysteine (μmol/L) showed significant inverse correlations with all nutritional biomarkers (ranging from ρ = −0.30 to ρ = −0.46; all P < 0.0001). With the use of multiple linear regression, plasma PLP, RBC folate, homocysteine, and cysteine were identified as independent predictors of CRP; and PLP, vitamin B-12, RBC folate, and homocysteine were identified as predictors of SAA. When stratified by folic acid fortification period, nutrition-homocysteine correlations were generally weaker in the postfortification period, whereas associations between plasma PLP and serum CRP increased. Biomarkers of inflammation are associated with PLP, RBC folate, and

Prediagnostic Serum Biomarkers as Early Detection Tools for Pancreatic Cancer in a Large Prospective Cohort Study

PubMed Central

Nolen, Brian M.; Brand, Randall E.; Prosser, Denise; Velikokhatnaya, Liudmila; Allen, Peter J.; Zeh, Herbert J.; Grizzle, William E.; Lomakin, Aleksey; Lokshin, Anna E.

2014-01-01

Background The clinical management of pancreatic cancer is severely hampered by the absence of effective screening tools. Methods Sixty-seven biomarkers were evaluated in prediagnostic sera obtained from cases of pancreatic cancer enrolled in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Results The panel of CA 19-9, OPN, and OPG, identified in a prior retrospective study, was not effective. CA 19-9, CEA, NSE, bHCG, CEACAM1 and PRL were significantly altered in sera obtained from cases greater than 1 year prior to diagnosis. Levels of CA 19-9, CA 125, CEA, PRL, and IL-8 were negatively associated with time to diagnosis. A training/validation study using alternate halves of the PLCO set failed to identify a biomarker panel with significantly improved performance over CA 19-9 alone. When the entire PLCO set was used for training at a specificity (SP) of 95%, a panel of CA 19-9, CEA, and Cyfra 21-1 provided significantly elevated sensitivity (SN) levels of 32.4% and 29.7% in samples collected <1 and >1 year prior to diagnosis, respectively, compared to SN levels of 25.7% and 17.2% for CA 19-9 alone. Conclusions Most biomarkers identified in previously conducted case/control studies are ineffective in prediagnostic samples, however several biomarkers were identified as significantly altered up to 35 months prior to diagnosis. Two newly derived biomarker combinations offered advantage over CA 19-9 alone in terms of SN, particularly in samples collected >1 year prior to diagnosis. However, the efficacy of biomarker-based tools remains limited at present. Several biomarkers demonstrated significant velocity related to time to diagnosis, an observation which may offer considerable potential for enhancements in early detection. PMID:24747429

Uses of NHANES biomarker data for chemical risk ...

EPA Pesticide Factsheets

Background. Each year, the US NHANES measures hundreds of chemical biomarkers in samples from thousands of study participants. These biomarker measurements are meant to track trends and identify subsets of the US population with elevated exposures. There is now interest in further utilizing the NHANES data to inform chemical risk assessments. Objectives. This article highlights: 1) the extent to which NHANES chemical biomarker data have been evaluated, 2) groups of chemicals that have been studied, 3) data analysis approaches, and 4) opportunities for using these data to inform chemical risk assessments.Methods. A literature search (1999-2013) was performed to identify publications in which NHANES data were reported. Manual curation identified only the subset of publications that clearly utilized chemical biomarker data. This subset was evaluated for chemical groupings, data analysis approaches, and overall trends.Results. A small percentage of yearly NHANES-related publications reported on chemical biomarkers (8% yearly average). Of eleven chemical groups, metals/metalloids were most frequently evaluated (49%), followed by pesticides (9%) and environmental phenols (7%). Studies of multiple chemical groups were also common (8%). Publications linking chemical biomarkers to health metrics have increased dramatically in recent years. New studies are addressing challenges related to NHANES data interpretation in health risk contexts.Conclusions. This articl

Assessment of a multiple biomarker panel for diagnosis of amyotrophic lateral sclerosis.

PubMed

Chen, Xueping; Chen, Yongping; Wei, Qianqian; Ou, Ruwei; Cao, Bei; Zhao, Bi; Shang, Hui-Fang

2016-09-15

The aim of the study was to assess a panel of promising biomarkers for their ability to improve diagnosis of sporadic amyotrophic lateral sclerosis (ALS). Forty patients with sporadic ALS and 40 controls with other neurological diseases were evaluated. Levels of phosphorylated neurofilament heavy chain (pNfH), S100-β, cystatin C, and chitotriosidase (CHIT) in cerebrospinal fluid were assayed using two-site solid-phase sandwich ELISA. Patients with sporadic ALS showed higher levels of pNfH and CHIT than controls, but lower levels of cystatin C. Multivariate logistic regression that adjusted for patient age and sex identified significant associations between sporadic ALS and levels of pNfH, CHIT and cystatin C. Levels of pNfH correlated positively with rate of progression and decline based on the Amyotrophic Lateral Sclerosis Functional Rating Scale - Revised. Based on receiver operating curve analysis, a pNfH cut-off of 437 ng/L discriminated patients from controls with a sensitivity of 97.3 % and specificity of 83.8 %. A CHIT cut-off of 1593.779 ng/L discriminated patients from controls with a sensitivity of 83.8 % and specificity of 81.1 %. Combining the two biomarkers gave a sensitivity of 83.8 % and specificity of 91.9 %. Levels of pNfH in cerebrospinal fluid may be a reliable biomarker for diagnosing ALS, and combining this biomarker with levels of CHIT may improve diagnostic accuracy.

The Gingival Crevicular Fluid as a Source of Biomarkers to Enhance Efficiency of Orthodontic and Functional Treatment of Growing Patients.

PubMed

de Aguiar, Mariana Caires Sobral; Perinetti, Giuseppe; Capelli, Jonas

2017-01-01

Gingival crevicular fluid (GCF) is a biological exudate and quantification of its constituents is a current method to identify specific biomarkers with reasonable sensitivity for several biological events. Studies are being performed to evaluate whether the GCF biomarkers in growing subjects reflect both the stages of individual skeletal maturation and the local tissue remodeling triggered by orthodontic force. Present evidence is still little regarding whether and which GCF biomarkers are correlated with the growth phase (mainly pubertal growth spurt), while huge investigations have been reported on several GCF biomarkers (for inflammation, tissue damage, bone deposition and resorption, and other biological processes) in relation to the orthodontic tooth movement. In spite of these investigations, the clinical applicability of the method is still limited with further data needed to reach a full diagnostic utility of specific GCF biomarkers in orthodontics. Future studies are warranted to elucidate the role of main GCF biomarkers and how they can be used to enhance functional treatment, optimize orthodontic force intensity, or prevent major tissue damage consequent to orthodontic treatment.

The Gingival Crevicular Fluid as a Source of Biomarkers to Enhance Efficiency of Orthodontic and Functional Treatment of Growing Patients

PubMed Central

Capelli, Jonas

2017-01-01

Gingival crevicular fluid (GCF) is a biological exudate and quantification of its constituents is a current method to identify specific biomarkers with reasonable sensitivity for several biological events. Studies are being performed to evaluate whether the GCF biomarkers in growing subjects reflect both the stages of individual skeletal maturation and the local tissue remodeling triggered by orthodontic force. Present evidence is still little regarding whether and which GCF biomarkers are correlated with the growth phase (mainly pubertal growth spurt), while huge investigations have been reported on several GCF biomarkers (for inflammation, tissue damage, bone deposition and resorption, and other biological processes) in relation to the orthodontic tooth movement. In spite of these investigations, the clinical applicability of the method is still limited with further data needed to reach a full diagnostic utility of specific GCF biomarkers in orthodontics. Future studies are warranted to elucidate the role of main GCF biomarkers and how they can be used to enhance functional treatment, optimize orthodontic force intensity, or prevent major tissue damage consequent to orthodontic treatment. PMID:28232938

Evaluating Chagas disease progression and cure through blood-derived biomarkers: a systematic review.

PubMed

Requena-Méndez, Ana; López, Manuel Carlos; Angheben, Andrea; Izquierdo, Luis; Ribeiro, Isabela; Pinazo, Maria-Jesús; Gascon, Joaquim; Muñoz, José

2013-09-01

This article reviews the usefulness of various types of blood-derived biomarkers that are currently being studied to predict the progression of Chagas disease in patients with the indeterminate form, to assess the efficacy of antiparasitic drugs and to identify early cardiac and gastrointestinal damage. The authors used a search strategy based on MEDLINE, Cochrane Library Register for systematic review, EmBase, Global Health and LILACS databases. Out of 1716 screened articles, only 166 articles were eligible for final inclusion. The authors classified the biomarkers according to their biochemical structure and primary biological activity in four groups: i) markers of inflammation and cellular injury, ii) metabolic biomakers, iii) prothrombotic biomarkers and iv) markers derived from specific antigens of the parasite. Several potential biomarkers might have clinical potential for the detection of early cardiopathy. Such capacity is imperative in order to detect high-risk patients who require intensive monitoring and earlier therapy. Prospective studies with longer follow-ups are needed for the appraisal of biomarkers assessing clinical or microbiological cure after therapy. At the same time, studies evaluating more than one biomarker are useful to compare the efficacy among them given the lack of a recognized gold standard.

Biomarkers in systemic lupus erythematosus: challenges and prospects for the future

PubMed Central

Kao, Amy H.; Manzi, Susan; Ahearn, Joseph M.

2013-01-01

The search for lupus biomarkers to diagnose, monitor, stratify, and predict individual response to therapy is currently more intense than ever before. This effort is essential for several reasons. First, epidemic overdiagnosis and underdiagnosis of lupus, even by certified rheumatologists, leads to errors in therapy with concomitant side effects which may be more serious than the disease itself. Second, identification of lupus flares remains as much an art as it is a science. Third, the capacity to stratify patients so as to predict those who will develop specific patterns of organ involvement is not currently possible but would potentially lead to preventive therapeutic strategies. Fourth, only one new drug for the treatment of lupus has been approved by the US Food and Drug Administration in over 50 years. A major obstacle in this pipeline is the dearth of biomarkers available to prove a patient has responded to an experimental therapeutic intervention. This review will summarize the challenges faced in the discovery and validation of lupus biomarkers, the most promising lupus biomarkers identified to date, and the promise of future directions. PMID:23904865

Perspective on Clinical Application of Biomarkers in AKI

PubMed Central